At last year’s Process Mining Camp, Linda Jantz from BVV Pension Management told us that all-day workshops are the most effective way to drive change within an organization.

As a warm-up for this year’s Process Mining Camp, we have invited Linda to the Process Mining Café tomorrow to dive deeper into the topic: How do you organize a good workshop? Who do you invite? How do you prepare? Which tools do you use? How do you document the outcome?

Join us! The café takes place this Thursday, 12 March, at 15:00 CET (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

Join us for Process Mining Camp 2026 from 18 to 20 May in Marseille. Get your ticket here now!

At first sight, process mining seems like a magic trick: You just load some data and — boom! — a process map appears, like a rabbit from a top hat. But of course it is not quite as simple and smooth sailing from here on out.

Using a process mining tool productively requires quite a bit of skill and experience. There are lots of parameters and tools, allowing you to fine-tune your perspective, to drill down on parts of interest, or to verify your hypotheses. And, as you have surely learned, data rarely comes in the clean and ready-to-use form we use in demos. Extracting, pre-processing, and filtering that data, cleaning it of unwanted artifacts, is arguably an art form in its own right.

And then, even when you have mastered the core skills of process mining, you notice that there are plenty of further aspects to consider. How can you address the relevant problems and questions your organization faces? Who do you need to involve, and how can you adequately address their concerns? How do you go about sharing your results, demonstrating value? How can you turn insight into change and create actual, meaningful, and tangible results?

Three days of process mining

The program for this year’s Process Mining Camp is filled to the brim, so that you will take a big leap forward on all of these questions. Join us for three full days, and explore the full spectrum of process mining topics.

You will have lots of opportunity to work on your process mining skills hands-on. At the same time, you will also focus on organizational aspects, allowing you to realize more value with process mining in your company. Let’s put the rubber to the road and make sure we leave an impact!

Join us in Marseille, in the south of France. Easily reached by train or by plane, this sunny Mediterranean port city is buzzing with energy. The unique atmosphere of this place will inspire us while we focus on process mining for three intense days.

Here is what you can look forward to at this year’s camp:

Workouts. Your skills are the core of your process mining practice. Get to work in a series of hands-on exercises, challenge yourself, and broaden your repertoire.

Lightning talks. Take the stage, in front of a room full of practitioners. Tell your story, ask a question, or share an idea — no holds barred.

Workshops. Discuss how to address the right analysis goals, navigate data challenges, ensure business value, and communicate your work effectively in four interactive workshops.

Case work. Work on a process mining project from start to finish. You will join a small group of process miners, with different backgrounds, and solve the case together.

Boot camp. Learn the fundamentals of process mining and get ready for camp. This year’s boot camp takes place online, and the first session is open to everyone free of charge. Go ahead and join the boot camp here.

Join the community

Throughout three days of camp you will meet people who actually use process mining themselves, in their daily practice. We all have different backgrounds, and unique perspectives, skills, and experiences to share. You will benefit from talking with your peers, and learn how they are tackling challenges in their own environment.

It’s when you speak with others that you discover blind spots, get new ideas for how to move forward, and learn from each other. You will build lasting connections and a support network that will sustain you way beyond camp itself.

See you at camp!

This year’s camp will be more intense and hands-on than ever. At the same time, you will have lots of time to reflect, talk with your fellow campers, and make new friends in the community. You will return home fully charged, with energy and new ideas for your own process mining initiatives.

→ Sign up now to reserve your spot and lock in the lowest rate!

We are very excited about this year’s camp. We think you are going to love it, and we can’t wait to meet you all in Marseille!

Every year, process miners from around the world come together at Process Mining Camp to improve their skills and meet other process mining professionals.

Process Mining Camp 2026 will take place from 18 to 20 May in Marseille, France.

Save the days of 18-20 May in your calendar and stay tuned! We are very excited about this year’s camp and you’ll learn more about it very soon.

— Your friends from Fluxicon

In our Process Mining Café with Owen Johnson from the University of Leeds, we talked about his applications of process mining in healthcare.

Many interesting lessons emerged from this session, such as:

• Process thinking: Healthcare professionals deal with protocols and guidelines as checklists. As part of the process mining project, the process thinking needs to be developed to combat silos by bringing clinicians from different stages of the pathway together.

• Agile methodology: Owen books his time with all of the medical experts before the project starts. The process mining work then evolves in cycles until the next meeting for domain expert validation, deeper feedback, and finally the development of improvement ideas.

• Eighty-twenty-one percent rule: It makes sense to separate simple from complicated cases and to analyze them separately. Furthermore, the pathways of the last 1% of patients are really complex and you should remove them from the data. They are not appropriate for data analytics.

There are many more insights, such as why you should have a control cohort (also outside of healthcare), why it makes sense to model the process before mining it, and why it is good not to get the credit you deserve.

Watch the recording of the café here if you have missed it. A big thanks to Owen and to all of you for joining us!

Our apologies for the three audio cut-outs in the first five minutes of the session. We have added a text overlay of the questions that Anne asked Owen to the video version of the café, so that you can follow the discussion.

Links

Here are the links that we mentioned during the session:

• Williams, S., Southall, C., Haley, S., Dhafari, T.B., Kemp, S., Relton, S.D., Alty, J.E., Johnson, O., Graham, C.D. and Maguire, M. (2022), To the emergency room and back again: Circular healthcare pathways for acute functional neurological disorders. Journal of the Neurological Sciences, 437, p.120251.

• Johnson, OA, Ba Dhafari, T, Kurniati, A et al. (2019), The ClearPath Method for Care Pathway Process Mining and Simulation. In: Lecture Notes in Business Information Processing. BPM 2018: Business Process Management Workshops, 09-14 Sep 2018, Sydney, Australia. Springer, pp. 239-250. ISBN 9783030116408

• Martin, N., De Weerdt, J., Fernández-Llatas, C., Gal, A., Gatta, R., Ibáñez, G., Johnson, O., Mannhardt, F., Marco-Ruiz, L., Mertens, S. and Munoz-Gama, J., 2020. Recommendations for enhancing the usability and understandability of process mining in healthcare. Artificial Intelligence in Medicine, 109, p.101962.

• Munoz-Gama, J., Martin, N., Fernandez-Llatas, C., Johnson, O.A., Sepúlveda, M., Helm, E., Galvez-Yanjari, V., Rojas, E., Martinez-Millana, A., Aloini, D. and Amantea, I.A., 2022. Process mining for healthcare: Characteristics and challenges. Journal of Biomedical Informatics, 127, p.103994.

• Van Eck, M.L., Lu, X., Leemans, S.J. and Van Der Aalst, W.M. (2015), PM2: A process mining project methodology. In: International conference on advanced information systems engineering (pp. 297-313).

• Our 12-step process mining methodology

• Differences between ClearPath and PM2 methodology

• Process Mining Café on common preprocessing tasks with Xixi Lu

• Process Mining Café about data quality with Kanika Goel and Niels Martin

• Process Mining Café about simulation with Lambros Viennas and Sudhendu Rai

• Process Mining Café about the explorative analysis phase

• Collection of process mining applications in healthcare

• Previous Process Mining Café on healthcare with Luise Pufahl and Fran Batchelor

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions about the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

We see this frequent mistake people make when they analyze bottlenecks: They look at the average delays in the process. The problem with that is that some of the discovered process paths can be quite low-frequent. So, you run the risk of focusing on an area in the process that will not have a big impact when you improve it.

In this 3-minute video, we demonstrate how to alleviate this problem by combining the total duration with another metric, such as the mean duration, as a secondary metric in Disco.

Process mining is an exciting application area for healthcare processes. At the same time, healthcare processes often present some challenges, for example, in terms of data quality and complexity.

For the upcoming Process Mining Café this Wednesday, we have invited Owen Johnson from the University of Leeds. At a UK hospital, they employed medical students to construct an event log of Functional Neurological Syndrome (FNS) patients by following the paper trail of each patient. The discovered process map illustrated quite how often these patients were misdiagnosed and sent around.

They also developed a process mining methodology specifically for healthcare processes. We’ll discuss how this methodology differs from the classical PM2 and our 12-step process mining methodology. The session will be essential for anyone applying process mining in healthcare, but also inspiring and informative for people outside of the healthcare domain. Join us all!

The café takes place this Wednesday, 17 September, at 15:00 CEST (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

We are happy to announce the release of Disco 4.2.

Forged in the heatwaves of summer, this release is built to melt away any annoyances, and to rid us of all those nasty bugs that have been itching us out on the patio. With some topped-up security and even tighter performance and stability across the board, it’s got all the fixins and then some.

Thanks for lending a hand with all your feedback and your bug reports. Keep us posted and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• Process Map:
  • Improved performance and stability of graph layout.
  • Improved reliability of metrics generation.
• Excel Import:
  • Improved reliability and performance.
  • Security updates.
• Airlift: Improved reliability.
• Control Center: Improved hardware detection.
• Software Update:
  • Fixed a bug that could prevent manual updates in some situations.
  • Improved robustness of automatic updates.
• UI: Fixed a bug where some charts in the analysis view could not be navigated via keyboard input.
• Connectivity:
  • Improved resilience in degraded network conditions.
  • Security updates.
• Platform: Java update.

You can use anonymization to put people at ease. Process mining is not about monitoring employees but about improving the process. But when people are new to process mining, seeing their names in the data can make them uncomfortable and less likely to support you in your process mining project. Removing their names and replacing them with a generic placeholder can help you build trust.

It’s very easy to do. Watch this 4-minute video to learn how to anonymize the resource names in Disco.

In the last Process Mining Café before the summer break, we had invited Daniel Kaße from VKPB in Germany to tell us more about how he addressed the concerns from data protection, the works council, and the operational manager.

We talked about why building trust in your process mining project is necessary in the first place and how you do it. We also discussed technical steps you can take, such as removing unnecessary information, anonymization, and pseudonymization.

In the end, Daniel gave us the following checklist:

Watch the recording of the café here if you have missed it. A big thanks to Daniel and to all of you for joining us!

Quick warning: There are a few cuts in the video due to some technical issues we had on the day of recording. Our apologies for that. But you’ll be able to follow our discussion without any problem.

Links

Here are the links that we mentioned during the session:

• Sign up for the camp mailing list to be notified when Daniel’s camp presentation becomes available.

• One of the advantages of Disco is that it analyzes all your data entirely locally. For further details see our privacy policy here.

• When talking about formalizing the agreement, we mentioned the Ethical Charter that Léonard Studer from the City of Lausanne used to put his colleagues at ease. We also talked about this in the Process Mining Café with Léonard.

• Daniel went a step further and created a formal contract about the operational use of log data. He was so kind to share this document with the community, so that you can take it as a starting point for your own organization. → Download the original German ‘Vereinbarung zur betrieblichen Nutzung von Protokolldaten’ or the translated English version here.

• Daniel removed the data that he did not need, such as customer names. He did this in the data preparation phase using the ETL tool KNIME → See a screenshot of his KNIME function here.

• Daniel also pseudonomized some of the information that he wanted to keep. By replacing the original value of a sensitive data field like the employee name with a pseudonomized value, you remove the direct traceability but preserve organizational patterns. For example, you can still see if just one person handles a case, or if it is handed back and forth between multiple people (without knowing who these people are). Daniel used a hash function for his pseudonymization → See a screenshot of his hash function in KNIME here.

• If you don’t need to store a mapping between original and pseudonomized values, you can use the built-in anonymization function of Disco. During the export, you choose what to anonymize (case IDs, resource names, attributes, timestamps) and then share or re-import the data set to work with the anonymized data. As we discussed during the café, anonymization or pseudonymization can be a method of building trust, but you also lose a certain level of analyzability. We give you a detailed overview of which analysis possibilities you lose with the different types of anonymization here.

• Don’t rely too much on technical fixes, and be aware that even anonymized data might be traced back in other ways. We also discuss this in the ‘How to be a responsible process miner’ Process Mining Café with Dirk Fahland and Felix Mannhardt here.

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions about the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

One of the presenters at this year’s Process Mining Camp, Daniel Kaße from VKPB in Germany, talked about how he addressed the concerns of various people in his organization. 

These concerns are very real. Data protection teams, the works council, and process owners need to trust that you will act responsibly in your process mining project.  

Because this is such an important topic, we invited Daniel to the upcoming Process Mining Café tomorrow. We’ll discuss how to build trust in your organization and explore anonymization methods you can use to obfuscate the data. Join us!

The café takes place this Wednesday, 18 June, at 15:00 CEST (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

Process Mining Camp took place this year on May 14-16 in Eindhoven. We had a great time! The weather was lovely, and it was a joy to dive into process mining for three whole days.

It all started with the boot camp on May 14, where new campers received an in-depth introduction to how process mining works in practice. After an initial online session the week before, they spent the whole day at the campsite learning the most essential process mining concepts and applying them hands-on.

On Thursday, May 15, a number of process miners shared their experiences in the practice talks. First, Martine Truijman & Stanley Wirjadi showed us how they analyzed the usage of the MRI scanners at Maastricht UMC+ in the Netherlands. Then, Linda Jantz from BVV Pension Management in Germany convinced us that all-day workshops are the most effective way to drive change within an organization. After lunch, Lucas Vousten from Joanknecht in the Netherlands shared his approach for process mining in assurance engagements. Shinobu Saito from NTT in Japan presented a novel way to visualize processes in a 3D environment. Then, Daniel Kaße from VKPB in Germany demonstrated how he navigated the concerns of data protection, the works council, and the process owner for his process mining project. Finally, Iris Beerepoot from Utrecht University in the Netherlands reminded us that the data that is in the logs is only a part of the truth.

In the afternoon, we continued with the discussion roundtables. In small groups, everyone talked about the challenges they face in their daily process mining practice. We built on the Process Mining Challenges that were captured during last year’s camp to see which categories were most prevalent and whether we were missing any (stay tuned for an update on the challenges soon!).

We closed the day with a nice multi-course dinner, a short walk, and a last round in one of the best brewpubs in Eindhoven.

The last day, Friday, May 16, was a full day of hands-on workshops. In the first workshop, we focused on data preparation. Creating an event log can be complex, especially if you lack context about the system, its processes, and the organization. Therefore, we broke down the data preparation into smaller, intermediate goals, each with concrete results. Each sprint included analyzing the data, transforming it into the event log, and checking the results in Disco. In the second workshop, we then continued with the analysis of the process. Like in every process mining project, we performed the analysis in two stages: discovery and targeted analysis. In the discovery stage, we focused on the explorative analysis to understand how the process works. In the targeted analysis stage, we then answered concrete questions about the process. Finally, in the last workshop, we returned to the process mining challenges and collected best practices to address them.

In the end, everyone left full of new ideas and motivation for their process mining adventures. Sign up at our mailing list here to receive the video recordings when they become available and to be the first to know about next year’s camp!

Process mining is not something that you buy but something that you do. That’s why meeting other process miners and learning from each other is so important.

At Process Mining Camp, we share our experiences for multiple days. We do this at the roundtables, workshops, and the boot camp.

One of the traditions at camp are the practice talks, where a few practitioners show in detail what they have done. Because of this level of detail, you can take away something for yourself.

Lucky for those of you who could not attend last year’s camp, we have just published the videos of the practice talks from Process Mining Camp 2024.

The last speaker was Erik Scroggs from Serco in the USA. Erik shared his experience of combining process mining with automation. With an increased use of automation techniques, this is a topic that is relevant for many companies today.

Serco has supported the Center for Medicare and Medicaid Services (CMS) since 2013, when the Affordable Care Act was first implemented in the United States. Erik is a software engineer working for Serco on the CMS project since it began in 2013. He has been using process mining to help senior leadership make key decisions.

With a mix of humans and RPA bots, the goal is to assign the right task to the right user at the right time. For example, robots start processing documents to take care of simpler tasks before humans come in to make calls and handle complex issues. Erik showed how he used process mining to identify inefficiencies in the workforce assignments: Due to a missing configuration in the system, humans were taking up newly sent documents in the middle of the process, while robots should have pre-processed them first.

In addition to these improvements, Erik also used process mining to identify new opportunities for automation, calculate cost vs. benefit metrics, and accurately project future production.

Tip: You can also watch this Process Mining Café, where Erik and Lloyd talk more about the combination of process mining and automation.

Here is an overview of all the practice talk videos from Process Mining Camp 2024:

• Gerardo Rodriguez Oviedo & Rafael Herrera Carpio (BAC, Costa Rica) — Boosting data-driven culture through process mining.
• Lieven Bewaert (Atlas Copco, Belgium) — How to use process mining as an internal auditor.
• Alexandros Kakakis (Online Dialogue, The Netherlands) — Customer journeys in e-commerce.
• Ghada Zakhama & Caleb Borges (DHL Group, Germany) — Reducing the risk of medical device deliveries.
• Aljoša Jankov (OTP Bank, Serbia) — Using process mining to deliver a new credit card on time.
• Erik Scroggs (Serco, USA) — Dynamic workforce assignment with automation.

The last tickets for this year’s Process Mining Camp are being sold right now, so if you’re still on the fence, now is the time.

See you at camp next week!

We are currently publishing the practice talks from last year’s Process Mining Camp. You can already watch the talks by Gerardo and Rafael from BAC, Lieven from Atlas Copco, Alex from Online Dialogue, and Ghada and Caleb from DHL.

The fifth speaker was Aljoša Jankov from OTP Bank in Serbia. Aljoša analyzed the credit card transfer process and found that less than 40% of the cases are finished within the expected time. Watch Aljoša’s talk to see how he discovered that people filling in at different branches caused most of the delays in the process.

Get your ticket for this year’s camp here!

Process Mining Camp is already in two weeks! The full program for 14-16 May is now available here.

In addition to practicing your process mining skills hands-on, you will meet other process mining professionals to learn from them.

One of the traditions at camp are the practice talks. At this year’s camp, you will hear from the following process miners about their experiences:

Planning scarce resources based on actual usage patterns

Martine Truijman & Stanley Wirjadi (Maastricht UMC+, The Netherlands)

Martine Truijman and Stanley Wirjadi work at Maastricht UMC+. Martine is a neurologist and advisor on capacity management. Stanley is a data analyst. As an academic hospital, Maastricht UMC+ uses its MRI scanners both for research and for diagnosis and treatment purposes. The scanners are a scarce resource everyone wants to utilize in the best possible way.

At camp, Martine and Stanly show how they apply process mining to the logging of the MRI scanners. They discover the procedures and their variations for different types of scans. As a result, their more profound understanding of the actual usage allows them to create benchmarks and make optimal use of their capacity.

Creating a team of improvement advocates

Linda Jantz (BVV Pension Management GmbH, Germany)

BVV is Germany’s largest pension fund for the financial industry and a company with nearly 125 years of tradition. They run processes, and they make decisions. However, until a few years ago, data played a minimal role. What insights remained hidden? How could they be unlocked?

Linda Jantz leads a multi-disciplinary team in the customer service department that she is evolving into advocates of process improvement. Using process mining, they identify inefficiencies and transform scattered data into actionable insights. At camp, Linda shares how she fosters a culture of continuous optimization using workshops. By actively involving operational staff, she ensures that changes are shaped by those most familiar with the processes.

Using process mining for assurance engagements

Lucas Vousten (Joanknecht, The Netherlands)

Lucas Vousten started the IT audit and assurance service line at Joanknecht in 2010. Since then, he has been bridging the gap between traditional accountancy and modern technology. He applies process mining in audits, IT security & privacy, and governance risk & control.

At camp, Lucas shows how he leverages process mining to enhance the efficiency and reliability of financial audits and ISAE 3402 and SOC2 assurance engagements. His approach improves auditing processes and provides valuable insights into the performance of IT processes.

Exploring experimental approaches to processes visualization

Shinobu Saito (NTT, Japan)

NTT is a multinational corporation headquartered in Japan. One of their services, DX services, supports the advancement of customers’ businesses and business processes. Shinobu Saito is a distinguished researcher at the NTT Computer and Data Science Laboratories.

At camp, Shinobu presents ProcessCity, a three-dimensional approach to process visualization. He shows how they use Disco and ProcessCity together to move between analytic and spatial views of the process through different departments.

Building trust and overcoming stakeholder concerns

Daniel Kaße (VKPB, Germany)

VKPB provides pension benefits to pastors and church civil servants. Daniel Kaße is responsible for optimizing quality and operational processes. Data protection and the works council (the employee representatives) play a vital role in all parts of their digitalization strategy.

When Daniel wanted to use process mining in one of his projects, he realized that multiple people had concerns about his use of process mining. At camp, Daniel shares how he addressed these concerns from data protection, the works council, and the operational managers.

Unveiling hidden process behavior

Iris Beerepoot (Utrecht University, The Netherlands)

Iris Beerepoot is an Assistant Professor in the Process Science research group at Utrecht University. In her talk, she explores how process behaviors that do not typically appear in event logs can shape — and sometimes distort — process mining insights.

Drawing on various studies that leverage alternative data sources and methods beyond traditional event logs, she highlights the hidden dimensions of process behavior that often go unnoticed. She reflects on the risks of drawing conclusions from incomplete data and the potential biases this introduces.

At camp, she offers practical guidelines for interpreting process mining results in light of missing information. She also provides strategies to prevent premature termination of process mining initiatives by ensuring a more comprehensive and accurate understanding of processes.

→ See you all in Eindhoven very soon. If you have not signed up yet, you should get your ticket now!

To get ready for Process Mining Camp from 14 to 16 May, we have started to publish the practice talks from last year’s camp. You can already watch the talks by Gerardo and Rafael from BAC, Lieven Bewaert from Atlas Copco, and Alexandros Kakakis from Online Dialogue.

The fourth speakers were Ghada Zakhama & Caleb Borges from DHL, Germany. Ghada and Caleb showed how they review data quality and check compliance with Disco. Watch Ghada’s and Caleb’s talk to see how they use process mining to avoid poor service quality, contract penalties, and loss of reputation.

Get your ticket for this year’s camp here!

Process Mining Camp is only one month from now! If you are new to process mining, then we highly recommend you to join the pre-training boot camp. You will get a comprehensive crash course on what process mining is all about, so that you can get the most out of camp.

The boot camp consists of four sessions. The first session takes place online one week before camp. You will get a general introduction and some first exercises to help you get started. We continue with the remaining sessions at camp, in person, on 14 May. You will learn all the fundamental concepts you need to understand, so that you can follow the discussions and get more out of camp. This is a great opportunity to combine camp with a condensed version of our renowned process mining training.

→ To join the boot camp, choose the ‘Process Mining Camp + Boot Camp’ ticket when you get your ticket here.

To warm up for camp, we have started to publish the practice talks from last year’s camp. You can already watch the talk by Gerardo and Rafael from BAC in Costa Rica and the talk by Lieven Bewaert from Atlas Copco in Belgium.

The third speaker was Alexandros Kakakis from Online Dialogue. Alex showed us how he uses process mining for web analytics to go beyond the classical funnel view. Watch Alex’s talk to see how process mining helps you understand the real customer journey paths.

— See you at camp from 14 to 16 May!

In the practice talks at Process Mining Camp, we hear from some of our campers how they applied process mining in different contexts. We have now started to publish the practice talks from last year’s camp. You can already watch the talk from Gerardo and Rafael from BAC in Costa Rica here.

The second speaker was Lieven Bewaert from Atlas Copco in Belgium. Lieven taught us that anyone can be an auditor by applying curiosity and critical thinking. He uncovered a bug in the IT system and relieved an overloaded worker in the purchasing department. Watch Lieven’s talk to see step-by-step how he used process mining as an investigative tool.

To learn more about what Process Mining Camp is like, watch this recap video, where Lieven and Bhawana share their takeaways from last year’s camp. And if you haven’t already, get your ticket for this year’s camp here!

In last week’s Process Mining Café, we talked about comparing processes. Hanna Nesterenko from UKRSIBBANK BNP Paribas Group in Ukraine shared how she analyzed a process at her bank for three different regions.

Hanna analyzed the case durations but also rework, parallel vs. sequential flows, and long waiting times. After understanding the different characteristics of the process in each region, Hanna identified best practices for improving them.

How can you know what you should compare for your own process? Watch the recording of the café here if you have missed it. A big thanks to Hanna and to all of you for joining us!

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions about the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

The animation in process mining is very powerful because it brings the process to life. You literally see where work is queuing. And you make the process tangible for the people you want to involve in your process improvement project.

But did you know that there are two different types of animation? Watch this 3-minute video to learn the difference between Real-time animation and Synchronized animation in Disco and how they both work.

Process Mining Camp 2024 was different. We expanded the camp to two full days, including discussion roundtables, three hands-on workshops, a boot camp, and lots of time to connect with everyone.

The big benefit of Process Mining Camp is that we learn from each other. One important piece of each camp are the practice talks, where we hear from some of our campers how they applied process mining in different contexts. The practice talks in 2024 were diverse and covered use cases from auditing to customer journeys and RPA bots analysis. You can now start watching the video recordings from last year’s camp.

The first speakers were Gerardo and Rafael from BAC in Costa Rica. They showed how an initial one-man project can have a huge impact. Gerardo and Rafael created 4 million USD more demand deposits in just six months. Watch Gerardo’s and Rafael’s talk to see how they achieved this by boosting data-driven culture through process mining.

This year’s camp will push your own process mining practice to the next level. If you have not registered yet, get your ticket here.

— See you all in Eindhoven on 15 May!

For our upcoming Process Mining Café, we have invited Hanna Nesterenko from UkrSibBank BNP Paribas Group in Ukraine.

Hanna works at a bank with different processes. For example, there are multiple regions, products, or types of clients. From afar, the processes look the same, but some details make them different.

So, how can we best compare these processes? In the café, we give examples and discuss best practices. Join us!

The café takes place this Wednesday, 26 March, at 15:00 CET (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

At this year’s Process Mining Camp on 14 – 16 May you are going to meet process miners from all over the world. Sharing experiences with your peers, and getting inspired from what they are doing, is a big part of why we get together as a community.

However, hearing and talking about process mining is not enough. To truly master it, you need to apply it yourself, hands-on. Even things that you thought were simple often turn out to be more nuanced and complicated than you thought. The way to becoming an expert is by trying, failing, retrying another way, and learning from the experience.

Practice makes perfect. Therefore, on the final day of camp, you will follow a sequence of three workshops that let you apply process mining, help you to recognize road blocks, and teach you how to resolve them. Each workshop focuses on one particular aspect of process mining, and they fit together perfectly to give you the complete picture.

What makes the workshops at camp special:

• You work on concrete, realistic scenarios. We designed these workshops specifically to speed up your learning process. They are based on real-life data sets, and they present the same challenges that you encounter in your own process mining projects.

• Benefit from tight feedback loops. During the workshops, you work independently in small groups but are supported by our expert guidance at each step of the way.

• You will be challenged regardless of your current level of expertise. Our workshops are based on real-life cases. They span the gamut from the basics to advanced exercises, in such a way that learners of all stages will take away something new.

• You get direct experience with the three most important aspects of process mining. The workshops cover data, analysis, and organizational skills to help you become a better process miner all around.

→ Sign up for a process mining experience that you can get nowhere else!

Here are some more details about the three workshops on the last day of camp:

Workshop 1 · Discovery and Analysis

Before you can answer your questions about a process, you first need to fully understand it. What is the regular flow, and where are the deviations? Where does the process begin, and where does it end? Once you start analyzing, you will find that you need to refine your initial analysis questions. And eventually, you want to develop ideas for improvements and make projections about the likely effects of these process changes. How exactly do you do all this?

In this workshop, you are going to practice hands-on on a real-life data set. In a series of exercises, you will explore layers of the process in an iteration of discovery, question, and analysis cycles. For each task, we show the resolution and discuss alternative solutions in the group.

Workshop 2 · Data Skills

Data preparation is not something that you can just outsource to IT or data experts in your organization. There are various choices to be made which directly influence the types of analysis you can perform later. Therefore, you need to have a seat at the table and guide the data preparation steps, even if you don’t execute them yourself. But what exactly do you need to pay attention to?

In this workshop, you take a deep dive into the world of data extraction and preparation. You go beyond the fundamentals of case IDs, timestamps, and activities and practice your process mining data skills from all the relevant angles. Based on real-life data sets, you will create event logs for different perspectives and evaluate their data quality so that you know how reliable the data is.

Workshop 3 · Organizational Best Practices

How do you translate process mining insights into changes in your organization? How do you make sure that the improvements stick? And how do you develop your process mining projects into a routine and general practice? The challenges for process mining are not only about technical skills. You also need to take strategic and cultural factors into account.

There is no simple recipe for making process mining successful. However, many different lessons can be derived from both successes and setbacks. By now, we have all been talking about these challenges and our experiences for two days — in the discussion groups, over dinner and drinks, in the breaks, and during the workshops.

In this last workshop, we take a step back and collect what we have learned. You will leave camp with new ideas that you can apply right away.

→ Get your ticket now to join us at this year’s Process Mining Camp! We can’t wait to see you all in Eindhoven in May.

In last week’s Process Mining Café, we talked about clickstreams. Clickstreams are the digital traces that visitors leave when they navigate through a website. This data can be analyzed with a process mining tool to understand the journeys customers take on the website. As a result, the website can be made more effective or user-friendly.

Our guest was Irene Strikkers, who told us about her experience of a recent clickstream analysis project. We discussed why the funnels of traditional web analytics are not enough to understand behavior. Do you want to know what exactly process mining adds to a clickstream analysis? Watch the recording of the café here and find out — A big thanks to Irene and to all of you for joining us!

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions about the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

One powerful aspect of process mining is that you can shape the process view how you need it. For example, when you trim a process, you “cut out” just the part of the process that you want to focus on during your analysis.

But be careful, though! There are nuances in how exactly you want to place your cut. Watch this 3-minute video to learn how to trim your process in Disco.

Customer journey analyses are one of the most interesting use cases for process mining. While classical web analytics limit themselves to plain statistics such as the number of page visits, deeper insights require an analysis of the browsing behavior of the customers on the website.

But how exactly do you do this? For our upcoming Process Mining Café, we have invited Irene Strikkers to tell us about her recent clickstream analysis project. Join us!

The café takes place tomorrow, Tuesday, 25 February, at 15:00 CET (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

Get your ticket for Process Mining Camp 2025 now and join us in Eindhoven from 14 – 16 May!

When you start using process mining, you notice that it seems refreshingly simple to do: You load your data, and – boom – there you have it, a visual map of your process. Easy! You pull the sliders, you play around with some filters, and it is so easy to get to some first, actionable insight about your process. It is truly a transformative experience.

Yet, while the above is certainly true, in reality you are just scratching the surface of what process mining has to offer. Process mining is a whole practice! After discovering a process map, you need to bring in other people, create different views for different stakeholders, refine your initial analysis questions, and measure the impact of changes in your organization. Now we are not in easy country anymore.

If you do not have a lot of experience, it is easy to run into roadblocks and get stuck. And even if you have done this for a while, especially if you are working alone, or when you don’t know many other process miners, it is not always obvious how you can take the next step and get more value out of your process analysis. For this, you need to learn new skills and methodological approaches. You need fellow process miners to give you some tips, and to show you their bag of tricks. And, sometimes, you just need some inspiration: Watching how others are approaching their work can give you lots of new ideas for what to try next.

Process Mining Camp is the place to be if you want to push your process mining practice to the next level. For up to three days, you can immerse yourself in the world of process mining, get out of your comfort zone, and gain a deeper and richer level of insight. You will meet curious and driven process mining professionals from all over the globe, and from all kinds of industries and professions. You will be expanding your horizon, discussing your challenges, learning from each other, and making new friends along the way. And, with a full day of intense, expert-guided workshops, we make sure that you bring home new skills and approaches, no matter your current level of expertise.

Process Mining Camp is the conference for you, the dedicated practitioner who is serious about process mining. You will improve your craft and skills over a series of three days:

• 14 May (Wednesday): Are you still relatively new to process mining? Then, we highly recommend that you join our optional boot camp on Wednesday, just before the regular camp starts. You will learn all the fundamental concepts that you need to understand, so that you can follow the discussions and get more out of camp. This is a great opportunity to combine camp with a condensed version of our renowned process mining training.

• 15 May (Thursday): On Thursday, you will first hear from a series of professionals about their process mining experiences in the practice talks. Learning how others have approached their problems is always helpful, and it gives you inspiration for your own use cases. It also allows us to ease into camp, setting the tone and sparking conversations to come. In the afternoon, you get together in small groups for the discussion roundtables to talk about your own challenges. Finally, during the evening program you will have lots of time to connect and recharge. Get to know your fellow campers, and take the time to follow up on the discussions, questions, and ideas that you had throughout the day.

• 16 May (Friday): On Friday, the last day of camp, you are diving deep during a full day of hands-on practice. You will participate in a sequence of three workshops that each cover different aspects of process mining. We designed these workshops specifically to speed up your learning process, by working on concrete, realistic scenarios that you can normally only get from real-life experience. You will leave camp with actionable insights, new approaches, and best practices that you can apply in your work right away.

Over the years, thousands of process mining enthusiasts from more than 34 countries have joined us at camp. You are going to meet people who apply process mining in their daily practice in completely different contexts. They will help you put your own challenges into perspective. Enjoy the friendly atmosphere, and meet old and new friends from all over the world!

→ Join us at this year’s camp and sign up before 14 March to benefit from the Night Owl discount here.

Camp is our favorite thing each year. We think you are going to love it, too, and we can’t wait to see you all in Eindhoven in May!

We are happy to announce the release of Disco 4.1.

This update focuses on the core Disco user experience, from importing data from CSV and Excel files, to deriving metrics and creating process maps. We have squashed the bugs, optimized the algorithms, and changed the oil.

Thanks for all your feedback and your bug reports. Keep it up and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• Process Map: Improved reliability of metrics generation.
• CSV Import: Improved performance and stability.
• Excel Import: Fixed a rare problem with huge spreadsheets.
• Airlift: Improved performance.
• Control Center: Improved hardware detection.
• Connectivity:
  • Improved proxy detection.
  • Security updates.
• Software Update: Fixed a bug that could prevent successful automatic updates in some situations.
• Platform:
  • Fixed a rare race condition in the UI when massively multithreading.
  • Java update.

Auditors use the same process mining tools as everyone else. But their analysis questions are slightly different. For example, they often focus on compliance questions rather than performance questions. If you have not seen it yet, you should read this excellent case study from the City of Vienna and you can find many more audit examples here.

Another thing that auditors need is a way to document their findings. In Disco, we developed an audit summary that fulfills the needs of the auditor together with the Central Audit Service in the Netherlands.

In this 4-minute video, we show you how you can export the audit summary from Disco.

For the first Process Mining Cafe of the year, we invited Vinicius Stein Dani from Utrecht University to talk about the common challenges and best practices for process mining.

Vinicius, Rudi, and Anne discussed the importance and unimportance of data quality, data privacy, process mining methodologies, and domain expertise. What must you do to ensure your process mining initiative is successful? Watch the recording of the café here and find out — A big thanks to Vinicius and to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• This is the article with the 13 process mining challenges and 95 best practices, from which we picked our favorite challenges during the café.

• Vinicius Stein Dani, Henrik Leopold, Jan Martijn van der Werf, Iris Beerepoot, and Hajo Reijers. From Process Mining Insights to Process Improvement: All Talk and No Action?, CoopIS, 2023.

• Vinicius Stein Dani, Henrik Leopold, Jan Martijn van der Werf, and Hajo Reijers. Progressing from Process Mining Insights to Process Improvement: Challenges and Recommendations, EDOC, 2023.

• Vinicius Stein Dani, Henrik Leopold, Jan Martijn van der Werf, Iris Beerepoot, and Hajo Reijers. From Loss of Interest to Denial: A Study on the Terminators of Process Mining Initiatives, CAiSE, 2024.

• Use our data quality checklist to validate your data before the analysis.

• Garbage In, Garbage Out: Ensuring Data Quality for Process Mining with with Kanika Goel from Queensland University of Technology and Niels Martin from Hasselt University.

• Process Mining Preprocessing Tasks with Xixi Lu from Utrecht University.

• Case Study: Auditing With Process Mining by Jasmine Handler and Andreas Preslmayr from the City of Vienna.

• How To Be A Responsible Process Miner with Dirk Fahland and Felix Mannhardt from TU Eindhoven.

• In the Process Mining Café Sequences of Stuff, Léonard Studer from the City of Lausanne shared many practical tips about how to put people at ease when analyzing their work with process mining.

• Our Privacy, Security, and Ethics guide shares Léonard’s ethical charter and discusses anonymization options.

• Collecting Process Mining Data With Privacy In Mind with Tobias Zepter from the BVV.

• Maikel van Eck, Xixi Lu, Sander Leemans, and Wil van der Aalst. PM2: a Process Mining Project Methodology, CAiSE, 2015.

• Our 12-step project guide helps you embed your process mining project in the methodology your organization already uses.

• The Business Case for Process Mining with Miguel Angel Gómez from PROA.

• How to simplify complex process maps.

• The skills and roles needed in your process mining project team.

• How to deal with blindspots in your process through missing activities.

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions about the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

At last year’s Process Mining Camp, we collected 13 process mining challenges and 95 best practices.

We are going to talk about these process mining challenges in the next Process Mining Café together with our guest Vinicius Stein Dani from Utrecht University. Vinicius is the perfect guest for this episode because he has been working on understanding the effort, the challenges, and obstacles to progress process mining improvements in his research.

Which challenges and best practices do you see for process mining yourself? Join us! The café takes place this Wednesday, 29 January, at 15:00 CET (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

If you don’t have the time to watch the full Process Mining Café about the Explorative Analysis right now, watch this 3-minute video about how to create a baseline in Disco.

Without the right baseline you will get incorrect results. In this short video, we show you how to create a good baseline in Disco.

Yes, you should define your process mining analysis questions early in the project (even before you start extracting your data). And there are many different questions that can be answered by process mining.

However, in last week’s Process Mining Café, we did not focus on answering these analysis questions. Not yet. Because before you can go into the Targeted Analysis (Step No. 10 in the process mining project methodology below), you need to discover the process. You need to understand how the data relates to the process that you know. And you need to explore where you can best break up the data set in the right way to get ready for your analysis. This step is called Explorative Analysis (Step No. 9 in the process mining project methodology below).

The Explorative Analysis step differs for every process and data set. But there are some common steps that you can take. As a guideline, we give you seven questions that you can ask yourself:

• You start by looking around: Does the process resemble your expectations?

• Where does the process start and end?

• Do you have one or more processes?

• Is there a little or a lot of variation?

• Are the activities on the right level?

• Do the cases have the right scope?

• Have you created the right baseline?

To give you an experience of what exactly such an Explorative Analysis looks like, Rudi and Anne take on the loan application process of the BPIC 2016 dataset. You can even join our exploration by downloading the data set and following along with us!

Watch the recording here if you weren’t at the live broadcast or want to re-watch the café. Contact us anytime at cafe@fluxicon.com if you have questions or suggestions about the café!

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Before answering your analysis questions, you need to get an overview of your process. Where does it start, and where does it end? Can you recognize the expected process? Is there a little or a lot of variation? Do you see rework or other unexpected patterns?

This initial explorative analysis is more of an art than a science. To help you build up your experience, in the next Process Mining Café, Rudi and Anne will take you on a journey to discover two different processes. We show you step by step how you explore the process, make sure you understand it, and get the data ready for your analysis. Join us!

The café takes place tomorrow, Wednesday, 11 December, at 15:00 CET (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

The new dates for our Process Mining Trainings 2025 are out!

Most of you know already that process mining is not magic. It is hard work that requires a smart human analyst to interpret what they are seeing. But it surely looks like magic, and you will be able to dazzle others and have exciting new perspectives on your business processes.

At Fluxicon, we have more than 20 years of experience with process mining. We use that knowledge to build the best process mining software for professionals. We are also busy capturing the best practices in our process mining book and shaping the process mining methodology together with all of you in our annual Process Mining Camp and the monthly Process Mining Cafe.

But the most direct way to benefit from our experience is to join one of our hands-on trainings. Here is what you need to know about our process mining trainings:

• Our trainings are live. This means that the lessons are not pre-recorded. Instead, you join the teacher and the other participants in interactive web meetings.

• The groups are deliberately small. So, you can be sure to be able to bring in your own topics. You will also learn from the questions of your peers, who often have a different perspective than you.

• Our trainings are really practical. You will learn all the essential concepts of process mining in practice. This training will give you the basis to use the full potential of process mining in your work.

• No prior knowledge is required. We will start from scratch, so don’t worry if you are totally new. But even if you already have some experience with process mining you will benefit, because there is a lot to know!

• The training does not end after two weeks. We meet with the same training group after 1-2 months to discuss the first results. Afterwards, we stay in contact and keep supporting you on your process mining journey.

Dates

Each training consists of four two-hour sessions over the course of two weeks. In between the sessions, there are exercises to apply what you have learned.

The next available training dates are (click on the month below and scroll down to enroll):

• January 2025 Training: Mo 20 January, Thu 23 January, Mo 27 January, and Thu 30 January at 15:00 until 17:00 CET each day.

• March 2025 Training: Mo 17 March, Thu 20 March, Mo 24 March, and Thu 27 March at 15:00 until 17:00 CET each day.

• May 2025: There is no training in May as this is the month of our annual Process Mining Camp! Camp takes place next year on Thu 15 May and Fr 16 May in Eindhoven, the Netherlands (with an optional pre-training Boot Camp on Wed 14 May) –> Sign up at the camp mailing list to be notified about the program as soon as it is available.

• June 2025 Training: Mo 16 June, Thu 19 June, Mo 23 June, and Thu 26 June at 15:00 until 17:00 CEST each day.

• September 2025 Training: Mo 15 September, Thu 18 September, Mo 22 September, and Thu 25 September at 15:00 until 17:00 CEST each day.

• November 2025 Training: Mo 17 November, Thu 20 November, Mo 24 November, and Thu 27 November at 15:00 until 17:00 CET each day.

Make 2025 the year you get serious about bringing the magic of process mining into your organization and reserve your seat now!

I recently spoke with a customer who had built a complicated SQL query to remove certain activities from their event log. He wanted to measure the process from one step in the process to another step in the process.

When I asked him if he knew how to do this in Disco he said “No no, you don’t understand. The two steps I want to measure are in the middle of the process”. My response was “Yes exactly! Let me show you how you can easily do this”.

He was amazed and this now saves him a lot of pre-processing time. Maybe some of you also don’t know how to focus your analysis between two steps. So, we recorded a 3-minute video to show you how.

You know the saying: 80% of the time and effort is spent on data preparation and only 20% on analysis. In the latest Process Mining Café, we spoke with Xixi Lu from Utrecht University about her categorization of common preprocessing tasks in process mining.

Xixi and Anne looked at all the six categories: Enriching, Integration, Filtering, Transformation, Reduction, and Abstraction. For each of the categories, we present concrete examples. So, in this episode, you get to see a lot of different types of preprocessing (see also the extensive list of pointers in the links below).

We discussed how these six categories that they distilled from their literature review align with the practical data preparation tasks we see daily. It has been a fascinating discussion. You don’t want to miss this one, especially if you are a science and terminology nerd!

You can now watch the recording here if you weren’t at the live broadcast or want to re-watch the café. A big thanks to Xixi and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Y. Liu, V. Stein Dani, I. Beerepoot, and X. Lu. Turning Logs into Lumber: Preprocessing Tasks in Process Mining, BPM Workshops (2023)

• M.L. van Eck, X. Lu, S.J.J. Leemans, W.M.P. Van Der Aalst: PM^2: A Process Mining Project Methodology. International conference on advanced information systems engineering. pp. 297–313. Springer (2015)

• S. Suriadi, R. Andrews, A.H.M. ter Hofstede, M.T. Wynn: Event log imperfection patterns for process mining: Towards a systematic approach to cleaning event logs. Information Systems 64, 132–150 (2017)

• N. Martin. Data quality in process mining. Interactive process mining in healthcare, 53-79. (2021).

• Our data quality checklist for process mining helps you to spot and fix problems with your data.

• One of the examples for the enriching category is the unfolding of case loops by adding a sequence counter column.

• Another example is the unfolding of loops for activity repetitions.

• Integration can happen in many different forms. The simplest scenario is to combine data sets of the same shape.

• Further examples can be found in the Process Mining Café about analysis transformations.

• Guideline for when to remove outliers and when to keep them.

• A.J.M.M. Weijters, W.M.P. van der Aalst, A.K. Alves De Medeiros. Process mining with the HeuristicsMiner algorithm, BETA working paper Vol. 166 (2006)

• Removing spider activities is an example of filtering noise.

• In Disco, you transform the activity or case ID configuration simply by importing your data set from a different perspective.

• Another example of transforming is the export into another event log format.

• Our data suitability checklist helps you determine whether your data set is usable for process mining in its current form.

• Sampling is often necessary for customer journey analyses.

• Another form of reduction is splitting the log into different sub-logs.

• C.W. Günther and W.M.P. van der Aalst. Fuzzy Mining – Adaptive Process Simplification Based on Multi-perspective Metrics. BPM Conference (2007)

• S.J. van Zelst, F. Mannhardt, M. de Leoni, A. Koschmider: Event Abstraction in Process Mining: Literature Review and Taxonomy. Granular Computing 6(3), 719–736 (2021)

• Our Process Mining Café with Pnina Soffer, Barbara Weber, and Francesca Zerbato about the process of process mining.

• A combination of preprocessing tasks is relabeling activity names (integration and enriching).

• D. Fahland: Extracting and Pre-Processing Event Log. CoRR abs/2211.04338 (2022)

• H.M. Marin-Castro, E. Tello-Leal: Event Log Preprocessing for Process Mining: A Review. Applied Sciences 11(22), 10556 (2021)

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Some preprocessing tasks can be easily done in Disco. Others require the use of data transformation tools. What are the common preprocessing tasks for process mining, and how can you group them?

We have invited Xixi Lu from Utrecht University for this month’s Process Mining Café to discuss her classification, why preprocessing is separate from data quality, and how to distinguish between noise and outliers. We get practical and show you examples. Join us!

The café takes place tomorrow, Wednesday, 13 November, at 15:00 CET (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time.

Sign up for the café mailing list here to receive a reminder one hour before the session starts. Or add the time to your calendar if you don’t want to miss it.

Serco is responsible for the back office processes in the marketplace systems of the Affordable Care Act (ACA) program in the United States. In this month’s Process Mining Café, we talked with Erik Scroggs and Lloyd Dugan, who have applied process mining for various use cases.

In the café, they shared three examples.

Use case No. 1: Robot efficiency

At Serco, humans and robots work together. The robotic workers take on simple tasks and hand them over to the humans for more complex activities. Erik analyzed the flow of work between robots and humans and discovered unexpected opportunities for improving their co-working setup.

Use case No. 2: Automation opportunities

How can you identify which parts of the process can be automated? Process mining helps to identify automation opportunities by providing the numbers for calculating the business case. If you have multiple ideas, these numbers will help you to validate where you get the most out of automating next.

Use case No. 3: Training paths

As a third example, Erik showed how they analyzed their training flows. Brand-new workers start with baseline training and, over time, receive more and more training badges that make them eligible to work new product lines. Based on the discovered training paths, they can now classify their production workers and make projections for the future.

Finally, we also talked about the skepticism and bad reputation that automation sometimes has. It is a reality that if robots take over simple tasks, only the knowledge work remains. So, automation is driving existing workers more into a career path. We discussed if this is a good or a bad thing.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. A big thanks to Erik and Lloyd and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Erik gave a talk at this year’s Process Mining Camp. Sign up at the camp mailing list to be notified as soon the video recording of his presentation becomes available.

• Case study at a housing association, where process mining discovered automation opportunities.

• Privacy, Security, and Ethics guide for process mining.

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Many companies use or plan to use some form of automation technique, for example, workflow automation, programming, or Robotic Process Automation (RPA), to reduce manual labor.

But which parts of a process can be automated, and which parts should be better kept human? Process mining helps by providing an accurate and transparent picture of the underlying process needed to make such decisions.

For tomorrow’s Process Mining Café, we have invited Erik Scroggs and Lloyd Dugan from Serco to tell us more about how they are using Disco to analyze the performance of their RPA robots, identify new automation opportunities, and analyze their training processes. Join us!

Talk process mining and automation with us tomorrow, Wednesday, 9 October, at 15:00 CEST (Check your timezone here). As always, you don’t need to register. Point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 9 October 2024, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

In last week’s Process Mining Café, we talked with Mieke Jans, a professor at Hasselt University, about process mining in audit.

Auditors have different goals than process improvement teams. For example, internal auditors verify the efficiency of the process and whether it is under control. They analyze the segregation of duties, variants, and cases.

Mieke was one of the first to apply process mining in an audit setting. We talked about the benefits of using process mining as an auditor. Furthermore, we discussed two recent research works in the field.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. A big thanks to Mieke and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Mieke Jans. From Relational Database To Valuable Event Logs For Process Mining Purposes: A Procedure, 2017.

• Marzie Hosseinpour and Mieke Jans. Auditors’ Categorization of Process Deviations (Download PDF), 2024.

• Manal Laghmouch, Sebastien Lizin, Jan Mendling, Benoit Depaire, Mieke Jans. Auditors’ Risk Perception of Process Control Deficiencies: A Discrete Choice Experiment (Download PDF), 2024.

• Mieke Jans and Manal Laghmouch. Process Mining for Detailed Process Analysis, 2022.

• Example applications for process mining in audit.

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Process mining and auditing are a great combination. In next week’s Process Mining Café, we are speaking with Mieke Jans, who was at the origins of the process mining and audit research more than a decade ago.

Mieke is now a Professor at Hasselt University and Maastricht University. In the café, she will take us through the development of this line of research and share two recent works by her and her team.

Researchers and practitioners alike can learn a lot from Mieke. So, we invite you all to tune in!

Join us next week Wednesday, 18 September, at 15:00 CEST (Check your timezone here). As always, you don’t need to register. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 18 September 2024, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

We are still on summer break but don’t want to leave you without your monthly dose of process mining.

You can now watch the recording of last month’s Process Mining Café, during which we reviewed what we learned at Process Mining Camp 2024.

We invited Bhawana Bindal from Zalando and Lieven Bewaert from Atlas Copco to join us. Bhawana was a first-time attendee, and Lieven was a speaker at this year’s camp. They shared their takeaways, and together, we retraced the steps of the two days.

→ Were you at camp this year? Refresh your memory and compare your experience with our observations.

→ Have you not been at camp so far? Watch the café to hear first-hand what it was like. And sign up for the Process Mining Camp mailing list to join us next year!

Links

Here are the links that we mentioned during the session:

• This article condenses 13 Challenges and 95 Best Practices we collected at this year’s camp.

A big thanks to Bhawana and Lieven, and thanks to all of you for joining us! We will return with a new café in September. Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and our YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

A big part of this year’s Process Mining Camp was to collect and discuss the challenges we all experience when applying process mining. Some challenges are generic. Others depend on your organization or emerge from your current skill set.

Traditionally, there has been a division between data-oriented and process-oriented disciplines.

For example, data science and BI teams have a lot of data and statistics skills. But they are not responsible for the process and often don’t understand it. On the other hand, business process experts recognize things like rework when they see them, but they are not used to leveraging the data that is available. The same applies to auditors who know how to watch out for various risks in the process but might not yet be able to handle large data sets.

In fact, process mining bridges this gap by marrying process and data-driven skills. And you, the process miners, are doing this! By using data to understand processes.

However, you can also look at your own skill gaps to improve further. For example, if your background is in BI or data science, we recommend familiarizing yourself with methodologies like process analysis or lean six sigma, and picking up skills like change management. Or are you more coming from the process analysis or audit side? Then, it can be really valuable to develop some additional data skills.

Data Challenges

In the Data Skills workshop at this year’s camp we did just that. Together, we transformed and improved a data set step-by-step. We also discussed best practices for the data challenges that we collected the day before.

Overall, the most frequent data challenges that were mentioned fall into the following four groups.

DC1: No data or no access to the data

Some data is not captured. After all, most IT systems did not think about process mining when developing their data structures. Essential data fields might be missing completely (for example, instead of the history of status changes only the last status is captured) or partially (for example, there might not be a single identifier from beginning to end if multiple systems are involved).

Sometimes, getting access to the data can be difficult. For example, an external provider might manage the IT system, and data access is not included in your contract. Your own IT team might have no capacity to help you due to competing priorities. Furthermore, legacy systems and a lack of knowledge of all processes can make it difficult to know where to look for data in the first place.

Best practices

• Know the data requirements for process mining.

• To get access to the data, involve & inspire higher management by sharing process mining success stories that illustrate the benefits in monetary terms.

• Develop a good relationship with data owners.

• Involve data experts early in your process mining project and try to make them enthusiastic about what you are trying to do.

• Work together with the data science team to extract and make it suitable for process mining.

• Team up with your internal audit team as auditors can make their data extraction a priority.

• Renegociate contracts with external providers to make sure they provide you with your data.

• Make sure to include data requirements for new IT systems in the future.

DC2: Lack of data skills

Even if you have data, it might not be in the right format. Furthermore, it can be challenging to extract the data due to its volume or because of your data skills. You might need to merge data from different sources. Finally, the scope of your process determines the scope of your data, and you need to have an understanding of how the target data should look after your preparation.

Best practices

• Focus first on the core data and extend it further in a second step.

• Start with a small sample and scale up your data size later.

• Learn to translate the process questions in the right data combination.

• Avoid repeated copy and paste in Excel and develop data skills, making the data extraction and preparation repeatable.

• Keep in mind that developing an event log is an iterative process (don’t try to do it right the first time).

DC3: Data quality problems

As with any data analysis technique, data quality problems can make your analysis harder or impossible. Garbage in = garbage out. Especially manually collected data is often unreliable. Furthermore, a lack of precision in the timestamps can create wrong orderings in the events.

Best practices

• Don’t skip the data validation session.

• Use the data quality checklist to spot (and clean) common data quality problems in process mining.

• Understand how the data is collected during the process execution to foresee mismatches between data and reality.

• Use the data that you have rather than waiting for the perfect data.

• Check how much of your data remains after the cleaning step to see how representative it still is.

• Make event data quality a priority in your data architecture.

• Improve data quality if you can influence the data collection in the future.

DC4: Security and privacy concerns

If process mining is still new in your organization, you may encounter a reluctance to share data. Reasons can include security and privacy concerns and a fear of misusing the data. The rules regarding employee and customer data vary across different countries/entities.

Best practices

• Make sure you consider privacy, security, and ethics questions from the start.

• Connect to your legal team to understand which rules apply to you (e.g., GDPR).

• If you are in Germany or another country that prioritizes workers’ rights, involve the workers’ council at the beginning of the project.

• Minimize data to what you really need.

• Address privacy concerns and create an ethical charter.

• Foster a collaborative culture that helps people to speak the truth about their process.

• Data ownership and access should be a priority. Create a data access policy and a privacy guideline for process mining, and make event data part of your data governance.

• Anonymize data to hide sensitive information if needed.

• Be aware that even anonymized data may be traced back to individuals (adjust your level of protection to the type of data and the situation).

• Instead of cloud solutions, you can use a local process mining tool like Disco or ProM, where your data is not uploaded but remains in your organization.

Process Challenges

In the analysis workshop, we learned how to separate incomplete cases and how to identify the standard process and its deviations based on patterns in the data.

Overall, the most frequent process challenges that were mentioned fall into the following four groups.

PC1: Dealing with complexity

Certain processes, such as customer journeys or healthcare processes, are particular complex. For example, clickstream sequences on websites and patient pathways are very individualized. So, they contain a lot of variants. But also other processes seem quite chaotic when you first look at their complete picture in the process mining tool.

Best practices

• Remove incomplete cases, explore different perspectives, and separate data issues from process issues before you start with the analysis of your process.

• To find structure in the chaos, apply simplification techniques.

• Look at individual cases and variants to see example scenarios of the process.

• Identify events that indicate the beginning and end of the process as well as important steps in the middle. Then, use the Milestone simplification method to visualize the process just based on these milestones (hiding the rest) to get an overview.

• If you have a reference process (it can be just a whiteboard drawing from a subject matter expert), find those referenced milestones in the data.

PC2: Lack of process mining skills

Learning how to read the process map, how the sliders work, and which filtering mode does what is essential. Luckily, working with the process mining tool can be practiced, and you will gain more experience over time. If you are unsure, you can always look at the user guide or follow a training.

Best practices

• Always double-check whether your process mining results are in line with your expectations. For example, if you filter completed cases based on an endpoint and end up with just 20% of the cases from the initial data set, inverse the endpoint selection to inspect the incomplete cases to see if you have missed valid endpoints.

• To find specific activities or events, you can search them in the process map or the cases view.

• Click on paths in the process maps that seem odd to you and look at example cases.

• Use the synchronized animation to compare process behavior for different segments.

• Use TimeWarp if your SLAs are based on working time rather than calendar time.

• Make copies when you explore different analyses to preserve your current views.

• Keep your workspace organized by renaming and re-ordering data sets.

• Use the recipes to save and reuse filter combinations.

PC3: Lack of process mining methodology

In addition to learning how to use the process mining tool, you also need a plan for how to set up your project. Which process do you choose, and how big should you make it? We are currently putting together the essential ingredients in this 12-step project guide.

Best practices

• Find multiple processes to mine and eyeball the data for the low-hanging fruits.

• Take a small process to prove value fast.

• Define an objective (important for data selection and to avoid getting lost in the data).

• Look at the process with the most pain points or the largest business value.

• Embed your process mining practice into your existing way of working.

• To ask the right questions, identify the “What keeps you up at night?” and ask “If you had a magic wand and could make a wish for this process, what would it be?”.

• Keep in mind that the questions need to be made more precise once you start answering them with the data.

• If there are no targets for a process yet, you can use process mining for an initial measurement and define the ambition for, e.g., throughput times or other SLAs.

PC4: Missing domain knowledge

You can do a lot of exploration by just looking at the patterns in the process and inferring the most likely meaning from the names of the event labels. But ultimately, you will hit a wall and need domain knowledge of the process behind it. If you are not a subject matter expert yourself, you will need access to someone who can answer your questions.

Best practices

• Involve stakeholders early.

• Have a close connection with the business and select projects based on sponsorship.

• Try to understand the process yourself before consulting the expert. Keep a list of all the questions that you encounter along the way.

• Create a multi-disciplinary team (see the skills and roles that are needed for your process mining project here).

• Understand the process behind the data. For example, follow the process manager for a day (shadowing) to see a “day in life.”

• Don’t be afraid to ask “stupid” questions. Your outside perspective can be precious!

Organizational Challenges

In the third and last workshop, we examined the organizational challenges and brainstormed best practices for addressing them.

The most frequent process challenges that were mentioned fall into the following five groups.

OC1: Stakeholder management and sponsorship

Just as important as data availability is good support from the team responsible for the process. Who do you need to involve? How do you ask the right questions? And how do you manage the right stakeholders?

Best practices

• Identify a process owner, engage in dialog, and ask “Are you aware how the reality deviates from the expected process?”

• Quick workshop/demo to show, not tell, advantages.

• Discuss with auditors about the risks to look for.

• Derive “right” stakeholders from the use case.

• Use classical stakeholder map to classify stakeholders.

• Involve: Budget holder, CFO/controller, IT manager, process owner (see also skills and roles).

• Engage with stakeholders early and make them part of the project from initiation. Communication: Explain the why, how, when, and what.

• If you sense a lack of trust, have an honest dialogue and answer questions that those hesitants might have. Show how it works, and be transparent and honest!

OC2: Business case & value

If your company is not yet familiar with process mining, they might not see the benefits (yet). Finding the proper business case can be challenging and is often a chicken-and-egg problem: How do you know how much value you can realize before looking at the data?

Best practices

• Use experiences from the community to show process mining examples that are relevant to your organization.

• Tailor the business case to your use case. For example, auditors can save time on audits or avoid risks or fraud cases in the future.

• Identify company-/business issues (where KPIs are not met) and ask customers for the biggest pain.

• Choose the process where data is easily obtained to show the advantages quickly.

• Balance effort & reward when evaluating (accounting for the skill of the organization).

• Close the loop after your project: Measure the impact of the change to demonstrate the value you have delivered.

• To sustain improvement, define performance metrics and build a program to track them regularly. This helps prevent the process from falling back into old patterns.

• While privacy is not easily quantifiable in business value, you can include it in your business case as an avoided risk.

OC3: Adopt methodology (and drive change)

Having the insights from your process mining analysis does not do anything yet! You need to change the process to realize the benefits. We discussed how to manage this change and how to expand after your initial project.

Best practices

• “Start small” & be clear about the goals & impact. Have regular follow-ups & checks.

• Be open about the change and leverage the change management professionals in your organization.

• Demonstrate the value of process mining (before vs after).

• Standardize your process mining practice before expanding.

• Appoint process mining champions per business unit.

• Team up with other groups, such as the BPM group, lean six sigma experts, or the data science team to develop an integrated approach and join forces.

OC4: Connecting to strategy

Connecting your process mining initiatives with your company strategy is a good way to align them with your organization’s goals. For example, process mining can support the digital transformation journey that many companies are still making.

Best practices

• Create a clear and concrete use case that is aligned with your company’s goals.

• Thoroughly understand the company strategy as an analyst.

• Link your project to cost savings, efficiency, and operational excellence.

• Link strategy with the business case.

• Introduce and use OKR to break down company strategy (objective) into process mining tasks (key requests).

OC5: Develop a process mining capacity within the organization

How do you take the next steps after your first process mining projects? You want to skill up the organization, get new assignments, stay up to date, and build a community that shares what they have learned.

Best practices

• To build up expertise, start small and perform multiple pilot projects.

• Celebrate successes and use your successful projects to market the added value of process mining and get more people interested.

• Offer awareness training for leadership positions. Make people aware of the possibilities in all layers (bottom-up/top-down).

• Go to Process Mining Camp :)

• If you don’t have enough internal resources, hire a consultant to help you with your first projects. Make sure you can take over what they did for you after the project.

• Participate in hands-on process mining training.

• Schedule meetups with peers. Document knowledge & best practices.

• Promote process mining by nominating process mining champions.

• Start an innovation lab.

• Read and research about what is new in the field.

• Sign up for newsletter.

Process Mining Café this Wednesday

In the upcoming Process Mining Café tomorrow, this Wednesday, 10 July, at 15:00 CEST (Check your timezone here), we will review what we learned from this year’s Process Mining Camp. Come join us!

As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and share your thoughts while we are on the air, right there on the café website.

If you want to be reminded, you can:

• Add the time to your calendar
• Sign up for the café mailing list to receive an email one hour before the session starts

— See you at the café!

We had an amazing time at Process Mining Camp this year. Whether you were with us in Eindhoven or joined us via the livestream, thank you so much for being there with us!

Practice talks

First, we heard from fellow campers who shared their process mining experiences from various use cases.

Gerardo Rodriguez Oviedo & Rafael Herrera Carpio from BAC in Costa Rica showed us how an initial one-man project can have a big impact. They created 4 million USD more demand deposits in just six months. The key for them was aligning objectives across business units from the customer perspective.

Lieven Bewaert from Atlas Copco in Belgium taught us that anyone can be an auditor by applying curiosity and critical thinking. His exploration uncovered a bug in the IT system and relieved an overloaded worker in the purchasing department.

Alexandros Kakakis from Online Dialog in the Netherlands took us through a website optimization project that went beyond a classical funnel view. The client wanted to understand the real customer journey paths on their site. The process mining analysis generated improvement ideas for AB Testing.

Ghada Zakhama & Caleb Borges from DHL Group in Germany showed us how their data analytics team supports other internal auditors at DHL. Reviewing data quality is as important as checking compliance to avoid the risks of bad service quality, contract penalties, and loss of reputation.

Aljoša Jankov from OTP Bank in Serbia analyzed the credit card transfer across multiple branches. He discovered that people filling in at different branches on different days caused delays in the process. Furthermore, a change in the IT system needs to remove duplicates to lighten the workload.

Erik Scroggs from Serco in the USA showed us how 100 RPA bots and 600 humans work hand in hand. Using process mining, Erik could improve the handover of work between robots and humans and quantify the benefit of automating further parts of the process.

→ Sign up for the camp mailing list here by the end of today to receive the public slides from the presentations tomorrow.

Discussion roundtables

Next, we sat together in small discussion roundtables to discuss our challenges with process mining.

For an easier start, we had curated the groups along themes such as healthcare, lean six sigma, and customer journeys based on the campers’ interests and backgrounds. However, the discussions quickly broadened and covered all kinds of challenges any process miner encounters.

Each group then dug deeper to uncover the underlying issues and causes. We organized them into data, process, and other challenges.

Finally, each group reported back by sharing their main takeaways from the discussion with all of us.

Evening

It was time to get some food and relax. We had the whole evening together to continue our discussions and learn from each other.

After dinner, we rolled out the bingo cards. We thought we had made answering some of the questions difficult or even impossible. I still can’t believe that Erik knew the first ten digits of Pi by heart. And who was it who had done process mining in secret? (Let us know where and how 😃)

With the motivation and combined smarts of our community from all over the globe, solutions were found very quickly. Thank you all for playing!

Hands-on workshops

The next day, we started fresh and got to work. In two hands-on workshops, we practiced creating a suitable data set and learned what to watch out for before analyzing the data in the process mining tool.

Hopefully, everyone learned something new. Some of you have taken their first process mining steps. Others have sharpened their skills and learned from each other.

Your training licenses are still valid until the end of August. So, you have all summer to revisit the exercises at your own pace.

Organizational best practices

In the third and final workshop, we revisited the remaining challenges from the first day and collectively captured best practices to address them.

There were a lot of useful and creative ideas. We also closed the loop by locating where they fit in the project cycle of the process mining methodology.

All together, we have been capturing use cases for process mining for well over a decade. This year’s talks, roundtables, and workshops make for some great additions to the community’s knowledge.

It was really fun to spend these two days with you all. Thank you!

What is next

In the upcoming Process Mining Café on Wednesday, 10 July, at 15:00 CEST (Check your timezone here) we will review the learnings from this year’s Process Mining Camp. Come join us!

As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and share your thoughts while we are on the air, right there on the café website.

If you want to be reminded, you can:

• Add the time to your calendar
• Sign up for the café mailing list to receive an email one hour before the session starts

— See you at the café!

Process Mining Camp starts tomorrow — We can’t wait to see you all in Eindhoven!

For those of you who are going to join us here, you are in luck: We believe that this will be our best camp ever, with two full days of process mining practice talks, roundtable discussions, intensive workshops, and lots of time with your fellow process mining campers!

For those of you who can’t join us in person, here is the next best thing: Join us around the globe for a livestream of this year’s practice talks on Thursday, June 13! Take a peek through the cracked doors of our campsite, and learn about what our speakers have experienced.

Note that we can’t take questions¹, and while we try to give you a great experience, we cannot guarantee a perfect view — After all, camping is a contact sport, and we usually have our hands full with making sure that everything’s perfect for the people in the room. But we hope that you’ll join us here in spirit, that you have a good time, and of course that you can make it next year!

To watch our livestream, simply go to processminingcamp.com tomorrow, June 13th, at 13:00 CEST (check your own timezone here). No registration is needed. You will be able to watch the livestream right there.

— See you all tomorrow!

You can now watch the video recordings from last year’s camp. If you have missed them, here is the first talk by Eric N. Kildea from Radwell in the United States, the second talk by Stefan Wick from the Universitätshospital Zürich in Switzerland, the third talk by Xhentilo Karaj from Euroclear in Belgium, and the fourth talk by Franck Diafouka, Ruth Zonanashvili, and Mithra Gruber from the European Medicines Agency in the Netherlands.

Our fifth and last speaker was Vanessa Schindler from T4media in Germany. Vanessa showed us what process mining adds to her toolbox as a customer journey analyst. Of course, she still uses web analytics tools like Google Analytics, but process mining helps her focus on the user’s actual behavior. Technically, the data is available without any problems: The Case ID is the user on the website, the Activity is the website’s page name, and the Timestamp is the time of the visit. What is difficult is the complexity of the user journeys: The data needs to be simplified to answer targeted questions. Watch Vanessa’s talk to see how you can better understand the customer journey based on process mining.

For this year’s camp, this is your last chance to get your ticket here.

— See you all in Eindhoven this Thursday!

You can now watch the video recordings from last year’s camp. If you have missed them, here is the first talk by Eric N. Kildea from Radwell in the United States, the second talk by Stefan Wick from the Universitätshospital Zürich in Switzerland, and the third talk by Xhentilo Karaj from Euroclear in Belgium.

Our fourth speakers were Franck Diafouka, Ruth Zonanashvili, and Mithra Gruber from the European Medicines Agency in the Netherlands. Franck shared their experience from establishing a working group on process mining across different EU organizations. Ruth explored process mining for risk assessments. Mithra then connected the various stakeholders of process mining to challenges beyond technical aspects. For example, ethical considerations are essential to avoid staff discrimination by colleagues or management. Furthermore, data protection and privacy must be ensured to comply with EU DPR and other legislation. Watch Franck’s, Ruth’s, and Mithra’s talk to see what it looks like to work on process mining at the European Union.

For this year’s camp, you can get your ticket here.

— See you all in Eindhoven on 13 June!

You can now watch the video recordings from last year’s camp. If you have missed them, here is the first talk by Eric N. Kildea from Radwell in the United States and the second talk by Stefan Wick from the Universitätshospital Zürich in Switzerland.

Our third speaker was Xhentilo Karaj from Euroclear in Belgium. Xhentilo walked us through the phases of an internal audit with process mining. In each phase, Xhentilo examines the challenges and opportunities that process mining brings compared to the classical audit approach. For example, traditionally, the analysis in the Fieldwork phase is based on samples and interviews. In contrast, auditors can use process mining to test the entire data population. In the Clearance phase, process mining changes the relationship with the auditee due to fact-based observations. Watch Xhentilo’s talk to see how a process mining project in audit looks like step by step.

For this year’s camp, you can get your ticket here.

— See you all in Eindhoven on 13 June!

We are happy to announce the release of Disco 4.0.

This update touches almost every part of the Disco experience, bringing expanded functionality, improved stability, and better performance all around. We have also comprehensively modernized Disco’s foundations and dependencies, and we improved the update framework to ensure an even smoother migration going forward.

Thank you all for your ideas, your feedback, and of course your bug reports. Keep ’em coming and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• Process Map:
  • Label start and end edges in case coverage perspective.
  • Improved performance and stability of graph layout.
  • Improved PDF export.
• Statistics: Extended case statistics export with active / passive time and case attributes.
• Charts: Higher-resolution image export.
• Cases: Fixed active time calculation for TimeWarp.
• Audit report: More useful export for unfiltered data sets.
• Excel Import: Improved stability and performance.
• Software Update: Added the option to run assisted manual update.
• Airlift: Improved reliability and performance.
• UI: More complete retina / hiDPI support.
• Octane: Support for very long case IDs.
• Control Center: Improved hardware detection.
• Connectivity:
  • Novel high-performance HTTP client.
  • Proxy settings auto-detection improved.
  • Improved performance and reliability.
  • Ensure functionality for legacy runtimes.
  • Security update.
• Security: Addressed potential vulnerability in Excel import.
• Platform: Java update.

You can now start watching the video recordings from last year’s camp. If you have missed it, here is the first talk by Eric N. Kildea in the United States.

Our second speaker was Stefan Wick from the Universitätshospital Zürich in Switzerland. The hospital wanted to restructure nine business units into three new divisions. The goal was to group existing departments that work closely together in the same division, where possible. Stefan used process mining to analyze the relationship between clinics based on their interactions to ensure the correct placement. Watch Stefan’s talk to see how he had to massage the data to get the views that he needed for his analysis.

For this year’s camp, you can get your ticket here.

— See you all in Eindhoven on 13 June!

Process mining camp is where we learn from other process miners. One important part is the practice talks, where we hear from some of our campers how they applied process mining in different contexts.

At Process Mining Camp 2023, our speakers showed how they analyze logistics processes and patient journeys, how process mining fits into audit projects and risk assessments, and what process mining adds to classical customer journey analyses. You can now start watching the video recordings from last year’s camp.

Our first speaker was Eric N. Kildea from Radwell in the United States. Eric showed us two different cases. For one process, he identified over 16,000 items that Radwell could ship directly to specific branches to avoid unnecessary back-and-forth shipments. The other case resulted in hiring staff in an understaffed department, given the increase in incoming items. Watch Eric’s talk to see how he could analyze very complex physical processes.

For this year’s camp, the last tickets are on sale now. If you have not yet signed up, you can get your ticket here.

— See you all in Eindhoven on 13 June!

We are busy with the last preparations for this year’s Process Mining Camp, and we can’t wait to see you all on June 13 and 14!

Today, we have two exciting updates for you: We now have finished the full program including the practice talks. And we have found the perfect location for camp (see more at the bottom of this post).

Practice talks

Practice talks have been a tradition at Process Mining Camp since 2012. At this year’s camp, there will be six practice talks about a wide variety of use cases:

• Ghada Zakhama & Caleb Borges (DHL Group, Germany) — Reducing the risk of medical device deliveries.

  Ghada and Caleb will share how their data analytics team supports business audit teams with innovative and automated approaches across various stages of the audit process. Using a medical devices management process as a case study, they will show how process mining helps reduce the risk of issues and anomalies within business processes.

• Alexandros Kakakis (Online Dialog, The Netherlands) — Customer journeys in e-commerce.

  Alex is an expert in data insights with a background in data science. He analyzes e-commerce websites using tools such as BigQuery and Python. At camp, Alex will demonstrate how he uses process mining to understand the customer journey. He will show how he translates complex behavior maps into actionable results relevant to his clients.

• Gerardo Rodriguez Oviedo & Rafael Herrera Carpio (BAC, Costa Rica) — Boosting data-driven culture through process mining.

  BAC is the biggest bank in Central America. Gerardo and Rafael have been using process mining at BAC with great success, significantly reducing throughput times and increasing closing rates for their processes. At camp, they will share how they use the opportunities identified through process mining to lead organizational improvement initiatives. They will focus on how process mining helps them to establish a data-driven culture across the different business areas.

• Aljoša Jankov (OTP Bank, Serbia) — Using process mining to deliver a new credit card on time.

  At OTP Bank Serbia, Disco revealed improvement opportunities for the credit and debit card application process. Following a client’s request, the credit and debit cards were sent between different branches. After Aljoša had overcome the data preparation challenges, he could investigate workarounds and bottlenecks. His analysis helped to explain behaviors that cause the conformance violations against procedural rules.

• Lieven Bewaert (Atlas Copco, Belgium) — How to use process mining as an internal auditor.

  Lieven is a Safety Health Environmental Quality Analyst at Atlas Copco. Based on the purchasing process he analyzed, he will share his experiences, the approach he took for process mining in an internal audit setting, and the challenges he encountered along the way.

• Erik Scroggs (Serco, USA) — Dynamic workforce assignment with automation.

  Serco has supported the Center for Medicare and Medicaid Services since 2013, when the Affordable Care Act was first implemented in the United States. Erik is a software engineer, and he has been using process mining to help senior leadership make key decisions. The insights gained from analyzing various processes has helped identify opportunities for automation, calculate cost vs. benefit metrics, and accurately project future production.

New campsite: Fifth Eindhoven

This year’s camp is different because, in addition to the practice talks, there will be discussion roundtables, three workshops on the second day, a boot camp, and lots of time to connect with everyone.

For this new format, we have found the perfect place with the Fifth in downtown Eindhoven. Located in the city’s former gasworks building, the Fifth is a concert venue, jazz club, restaurant and bar, and a focal point of the annual Dutch Design Week.

While the Fifth is located a stone’s throw from the city center, it is tucked away in a post-industrial yard. This gives us the intimacy, peace, and quiet to fully focus on process mining for two full days. With a state of the art projector and audio system, and the Fifth’s excellent restaurant and bar, we have all that we need, right there on site.

We will have several comfortable rooms at our disposal, so whether we’re listening to talks, having roundtable discussions, workshops, or we’re just hanging out for lunch or dinner — we’ll be right at home.

For those of you who have already booked your hotels, you are still in the right place. The Fifth is also located in the Eindhoven city center: It can be reached from Eindhoven Central train station by a 15 minute’s walk. See all the details regarding the camp’s location here.

If you have not yet signed up, you should get your ticket now!

— See you all in Eindhoven on 13 June.

Last week’s Process Mining Café was dedicated to a hands-on session about variants. Variants are their own dimension of looking at a process and they complement the process map. They look at sequences of activities from the beginning until the end of the process. Therefore, they provide a simplified, scenario-based view of the process. But the crux is that you need to make sure that your variants are on the right level before you analyze them.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Article about how to understand the variants in your process

• Muthu’s approach to determining process capability based on variants

• Simplification strategies such as the milestone method, the trimming of the process, and the removal of spider activities help to bring the variants to the right level

• Keep in mind that you are not limited to the literal variants, but semantic variants can group behavior on any level that is meaningful for your process

• When you consider variants in your process, you may end up asking yourself in which situations outliers should be included or excluded

• Manfred had asked about simulation in the chat, and we promised to link the Process Mining Café about process mining and simulation here

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and our YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Process Mining Camp will take place just over a month from now! We are excited to see you all and will reveal the last details about this year’s camp very soon. Stay tuned and sign up at our camp mailing list to be notified once the full program is published.

With our three workshops on the second day, hands-on practice will be a big part of this year’s camp. In this spirit, we dedicate today’s Process Mining Café to a hands-on session on variants.

Rudi and Anne will take you on a journey to think about variants, explain possible traps if you rely on variants as an indicator too early, and show how to use variants productively.

What insights have you gained from analyzing the variants in your process? We invite you to share your experiences with us today, Wednesday, 15 May, at 15:00 CEST (Check your timezone here). No registration is required. Simply join us at fluxicon.com/cafe and be part of the live discussion as we explore this fascinating topic.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this Wednesday, 15 May 2024, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

In last week’s Process Mining Café, we talked with Miguel Angel Gómez from PROA about his process mining project at Chopo Laboratories in Mexico. We discussed the results of their analysis and the benefits they got from the improvement. Interestingly, they did not focus on cost-cutting but increased revenue by 6 million Pesos (350,000 USD) without hiring additional people.

Finding your way to your business case as a process miner is a bit of a chicken-and-egg problem: You first have to do the analysis to determine the improvement potential. So, it can be a good idea to perform a small pilot project. But even afterward, you need to decide how much of the opportunity you can realistically expect to realize. We discussed all this with Miguel and recommend to keep it simple.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks to Efe, Axel, Markus, and Jori for the discussion, and a big thanks to Miguel and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• How to make a business case for process mining (including the ROI template shown during the café)

• Process mining is agnostic to the methodology used around it, such as Lean Six Sigma

• The auditing case study by Jasmine and Andreas and the companion Process Mining Café compare the time and effort people spend in each phase of a traditional process mining project vs. an audit with process mining

• Instead of only focusing on cost-cutting, also watch out for additional revenue opportunities such as in this housing association WoonFriesland, where vacant properties could be re-rented on average seven days faster

• Quantifying qualitative improvements such as improved usability is often harder but also important

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

This year’s Process Mining Camp on 13 & 14 June is made for experts. But that does not mean that those of you who are new to process mining should not attend.

In fact, as beginners we learn best when we see, first-hand, more advanced practitioners at work. We all learn the fastest by observing experts at the top of their game. Nevertheless, it can be useful for you to have a solid grip on the basics, so that you are better able to follow the discussions.

This is why, this year, we offer an optional boot camp training just before camp for those of you who are new to process mining. When you sign up for camp, choose the Process Mining Camp + Boot Camp ticket (the second ticket on the list) to reserve your seat for this pre-training.

The boot camp is going to cover a big part of the lessons from our regular trainings. In this crash course, we will teach you the most important process mining concepts. By immediately immersing yourself in the real-life use cases at camp, you will solidify your understanding and bring it to life. The boot camp also gets you ready to start practicing, and to participate in the workshops on the second day of camp.

Boot Camp program

The boot camp consists of two sessions. The first session takes place online one week before camp, on 6 June. The precise time will be determined based on the availability and the time zones of the participants. Afterward, you will get a homework exercise to work on between the first and the second session. Then, on Thursday morning, 13 June, just before camp starts, the second session takes place in person at the campsite.

You will learn:

• Introduction and positioning: We will keep the introduction short and focus on how process mining fits into existing process improvement methodologies. We will also look at how process mining differs from other methods and what it is not, so you can clearly place it in your head.

• Guided hands-on session: Then, we will dive into the first hands-on session. Together, we will go through a typical process mining scenario, step by step. You will learn how to import data and perform your first process mining analysis.

• Simplification strategies for complex processes: One of the first challenges you will encounter in your process mining projects is that the discovered process maps can become very complicated. Based on concrete examples, you will learn ten strategies for dealing with this complexity.

• Hands-on exercises: You will start practicing with two exercises, where you will work on real data sets by yourself. We will discuss your solutions in the group and talk about the different use cases for process mining.

During the boot camp, you will learn everything to become prepared for camp, even if you are still a greenhorn. With this foundation, you will be able to step over some of the more obvious challenges, so that you can have a deeper discussion and challenge others.

We recommend the boot camp to newcomers as it allows you to focus more on what is relevant for you instead of just listening in. You will have a broader perspective and more effectively place what you hear at camp in the right context.

You will also receive a Disco training license for 60 days, so that you can hit the ground running at the boot camp and continue to learn at your own pace.

Furthermore, you will join a follow-up meeting online with the same training group after 1-2 months to discuss the first results. Afterwards, we stay in contact and keep supporting you on your process mining journey.

The only catch is that we have a very limited number of seats available for the boot camp. → Sign up now, and make sure you don’t miss this opportunity!

Certificate of attendance

Both boot campers and regular campers will receive a certificate of attendance to document their education activities.

We have also created an overview of the educational and training components at this year’s camp, to help you better plan and justify attending camp. Do you still need to request permission to come to camp this year? Send us an email at camp@fluxicon.com, and we will send you some information on how you can fit process mining camp into your own training program and budget.

Sign up for a process mining practice that you can get nowhere else. If you buy your ticket before midnight this Friday, 19 April, you help us plan, and you can still benefit from the morning person rate before prices go up.

We can’t wait to see you all at camp!

In the next Process Mining Café this Wednesday, we have invited Miguel Gómez from PROA in Mexico. PROA is a healthcare services provider that collects samples and takes images to produce medical interpretations that help people make decisions related to their medical treatments.

Miguel has done several process mining projects that have had a big impact at the company. In the café, we will talk about these projects in more detail. One of his challenges was that after the improvement he was asked to quantify the benefits. Together, we will discuss how to make a business case for process mining.

What has been your experience with business cases for process mining? Join us this Wednesday, 17 April, at 15:00 CEST, and let us know! (Check your timezone here). As always, no registration is required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 17 April 2024, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

Most organizations have complex processes that are hard to manage and control. Moving out of a fire-fighting mode and stepping back to understand the existing business processes is the necessary starting point for process improvement.

A lot of data is available in IT systems (e.g., CRM, ERP, Workflow, PDM, ITSM, homemade or legacy systems, data warehouses, or even Excel) that contain detailed information about which activities are performed, when, and by whom. What is needed are quick methods to gain insight in this data to understand the underlying processes and take actions.

Process mining can be used to quickly and objectively get a complete picture of a process by automatically analyzing the IT data and visualizing the real process flows that took place.

Many of you already know this and are convinced about the benefits of process mining. But you may still be asked to make a business case before you can start. So, how exactly can you quantify the added value of process mining?

You will need to look at the precise use case and business context in which you want to apply process mining. This article provides several example scenarios in which process mining helps internal process improvement departments. Many of these advantages also apply to other process mining use cases, such as auditing. At the end of the article, we provide you with an ROI template that you can use as a starting point for your own process mining business case.

1. Challenges for Process Improvement departments

A Lean Six Sigma or Process Improvement department, a Change Management team, a Process Excellence function, or a Process Performance or BPM group employs process experts and internal consultants who help different departments in the organization to re-structure and optimize their business processes. In cooperation with the process owners, these teams deliver process improvements that aim to provide long-lasting cost savings and increased revenue for the company.

The starting point for any process improvement project is the so-called ‘As-is’ process analysis, in which the current state and all the deficiencies of the process are mapped out, and improvement opportunities are identified. The traditional way of process discovery is carried out manually through workshops and interviews.

The advantages of process mining are the objective and quick diagnosis of process issues. If you use a traditional method of manual process discovery, you typically have the following problems:

1. It takes lots of time for the people who do the interviews and process mapping. This is about the time that is spent by the internal consultants. If they could do their work faster, they could do more projects and therefore deliver more value for their organization.

2. It binds people (interviewees) from productive work into discussions about how things are currently done just to understand the ‘as-is’ process. This is about the time other people (outside the process improvement department) must spend on ‘As-is’ process discovery. For example, suppose there is a one-week workshop with one consultant and ten employees from the operations department. In that case, this costs the company the consultant’s time plus 50 FTE days for the participating operations manager and other stakeholders.

3. The results are subjective, based on what people think about the processes, not necessarily on how the processes really are. If these subjective insights are used as the basis for the improvement project, there is the risk that the applied improvement measures will not be effective (because they do not address the real problems).

4. Different opinions may not be resolved (political deadlock). In situations where the participating people cannot agree on a unified view of the ‘As-is’ process and its problems, the risk is high that the project will fail, and no process improvement will be carried out at all.

5. You get only a sample view, not the complete picture. The manual picture will never be complete if you ask people to spell out the process. Like with the risk of a subjective bias, an incomplete picture carries the risk of missing important parts in the process analysis and therefore the risk of implementing the wrong (ineffective or even counterproductive) improvement measures.

6. Manual tracking and measurement is costly and biased and provides only sample data. This is about the practice of measuring process steps with a stopwatch to collect objective evidence: (1) Doing this manual work is very time-consuming, (2) People who are observed behave differently than normally, and (3) Only a limited sample can be obtained (e.g., tracing 30 cases over a few weeks).

7. Because the cost of process diagnosis and information collection is so high, it cannot be easily repeated. Therefore, the impact of process improvements is often hard to estimate (“Did we really achieve what we wanted to achieve?”). Without a way to measure the effect of the improvement initiative, the actual value that the project delivered to the organization cannot be measured. There is also the risk that people fall back into old behavioral patterns after some time.

In the next section, we review how process mining can help to address these seven challenges.

2. Benefits of using process mining in process improvement projects

Process mining significantly lowers the cost of understanding the current process by bypassing interviews and extracting the necessary information out of the existing data from the IT systems. This way, you can focus your discussions on ‘why’ the processes are performed the way they are. Furthermore, iterative improvements with continuous assessment of the impact of changes become possible because you can repeat the analysis at any point in time at little cost.

The benefits of process mining with respect to the challenges discussed in the previous section are described in the following table:

3. Ingredients of your business case

While the benefits of process mining are often obvious and it is clear that using process mining will “pay for itself,” you will most likely find yourself in the position of having to justify the investment. How do you do that? You create a business case for your management to approve the purchase.

Ultimately, each business case is unique, but you can follow a number of guidelines to put it together. In this section, we give you a starting point for how you can create a business case for your own process mining projects (see also the ROI template in the next section).

First, you can assemble the investments that you need to make. Think of the following components for a process mining project:

• Software license cost - The use of the process mining software

• Training cost - Educating the people who will use process mining about the approach and the software

• Employee cost - Time investment of the people involved in the project (analysts but also additional stakeholders)

• Data extraction cost - You may need to pay the IT department (or your external IT provider) to extract or transfer the data

• Professional services - If you are getting help from an external consultancy to help you with the project, their services need to be incorporated as well

To quantify the return, you can think in two dimensions:

1. Saving costs: Where will you reduce your current expenses?

   There are two categories of cost savings that you can consider for process mining projects:

   1.1. Cost savings through more efficient As-Is Process Analysis

   Revisit the section ‘Benefits of using process mining in process improvement projects’ above to think through this category of cost savings. Doing at least one small pilot project in your organization (that you can compare with past projects that you had done in “the old way”) will help you get some hard numbers you can use for your business case.

   For example:

   • Time reduction for process analyst: How much faster was the process discovery for the analyst? How much effort did it take before to understand the current processes and collect and analyze data manually?

   • Less time for subject matter experts in the As-Is workshops: How much time have you saved for these stakeholders in the workshops by focusing on the ‘Why’ rather than the ‘What’?

   • Avoided risk of focusing improvement activities in the wrong area: It is easy to waste process improvement resources by focusing on the wrong places or processes. If you have seen project failures in the past, can you quantify their loss in proportion to the risk and include this component in your business case?

   1.2. Expected cost savings through the process improvements themselves

   If you make your business case for the overall process improvement project (not just the use of process mining in your current process improvement activities), include the potential cost savings from the improved processes. This is usually difficult to quantify beforehand because you do not yet know how much improvement potential you will find.

   Also, here, it can help to first do a quick scan of your process to get some hard numbers, if possible. Alternatively, you may be able to draw upon your experience from past process improvement projects or your domain expertise about the process and the potential value of improving it just a little bit (especially for high-volume or high-value processes, small improvements can have a big impact).

   The expected savings will then be quantified in a unit that makes sense for your particular process.

   For example:

   • Fewer steps: How many steps are needed to complete one case in your process? Your process mining analysis can often determine an ideal range of steps. Cases that take more steps indicate rework. Your improvement project will focus on finding the root causes and avoiding this rework in the future.

     You can then determine the improvement potential based on the process’s volume. For example, for the incident management process at a bank, the cost of one step was estimated to be around 20 Euros. If you can save 200,000 steps within one year, this cost reduction is 4 million Euros.

   • Reducing total activity time: In processes where the time of activities incurs significant costs, reducing their duration can amount to cost savings. For example, in call centers, one minute of an agent being on the phone with a customer is often quantified with 1 Euro in costs.

   • Avoided penalties: In some processes, missing specified Service Level Agreements (SLAs), for example for how fast the service is delivered, leads to penalties that need to be paid. If improving the process leads to a speed-up that helps to meet the contract SLA for more cases, then these penalty payments can be reduced.

   • Improved quality: If poor quality of the delivered product or service leads to the rejection by the customer, then all the steps that were taken to deliver this service or product were essentially wasted. Clear processes with quality assurance measures on the way, and the adherence to these process guidelines (i.e., compliant processes), can ensure that services are delivered more consistently. If your process mining analysis helps to reduce the variation in the process and improves compliance, then the reduced rejection rates can be quantified in terms of less waste (i.e., cost savings).

   • Fewer people: If, by improving the process’s efficiency, fewer people can handle the same amount of work, then their salaries can be used to quantify the cost savings.

2. Increasing revenue: What will you gain that you did not have before?

   If you can tie your process improvements to additional revenue, your business case should state these expected gains and put them in perspective with the investment.

   For example:

   • More orders processed: In a telecom process, almost half of the customer orders were lost because the ordering process did not work well. Solving these process problems increases the revenue in the value of these otherwise lost orders.

   • Happier customers leading to more business: In customer service processes, often the focus is not so much on saving costs but on making the customers happy and, therefore, keeping them as a customer and having them recommend the company to their friends and colleagues. Their process improvement initiatives target the increase of customer satisfaction measures, such as the Net Promotor Score (NPS), which are then used as a proxy to estimate the resulting increase in revenue.

   • More payments: In processes that deliver services to their customers based on contract SLAs, it can be the case that the customer only pays for the service if it was delivered on time. If the process efficiency can be improved in such a way that more cases meet the SLA, then this leads to an increase in revenue.

   • Sustaining improvements: One of the challenges discussed above was that traditional process improvement projects have trouble maintaining the effects of their process improvements over time. If people slide back into old patterns, then the gains from these process improvement initiatives are lost. Process mining can help to verify and monitor the effectiveness of past process improvements to sustain the improvements.

Finally, even if they are harder to quantify, make sure to mention “softer” benefits such as being in control, being proactive, etc., and also think about whether you can tie your proposal to your company’s strategic goals. For example, many organizations place importance on digital transformation in their strategic agendas for the next five years.

4. ROI template

You can create an excel sheet, where you list the investment on the one side, and the expected cost savings and revenue increase on the other side, to show how long it would take to recoup the investment over time.

For example, if a total investment of 100,000 Euros will lead to an expected revenue increase of 20,000 Euros per month, your business case shows that the investment has paid for itself within five months. After that, every month will continue to deliver an additional 20,000 Euros for the business.

To make this calculation easier, we have created an ROI template that you can use as a starting point:

→ Directly download ROI Business Case Template in PDF format (contact us for the Excel and Numbers versions)

When you look at the template, you will see that it follows the same structure as this article. However, it is more detailed and provides examples for process improvement roles, auditors and controllers, IT departments, and process owners. Furthermore, it includes examples of soft benefits and further references.

We are curious if you get to use the ROI template and if you have any additions or feedback about it. Let us know, and if you find it useful, share it with your colleagues!

5. Process Mining Café

Business cases can be tricky. What do you include in your calculation, and what do you leave out? What is a realistic assessment, and what is just wishful thinking?

In this month’s Process Mining Café next week on 17 April, we will look at a concrete process mining project and discuss its business case in more detail. We would love for you to join us and share your own process mining business cases.

Keep an eye on this blog or sign up at our café mailing list to be notified about this Process Mining Café and all future café editions.

In last week’s Process Mining Café, Andrea Delgado and Daniel Calegari from the Universidad de la República, Uruguay, showed us how they used process mining on open data for an urban mobility project.

Before the session, they had already shared a detailed description along with all the scripts to reproduce their approach. We had a lively discussion in the café and you are invited to continue the conversation, whether per email, on LinkedIn, or with Andrea and Daniel directly.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks to Puttwaldo, Scott, and Miguel for the discussion, and a big thanks to Andrea, Daniel, and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Case study about the process mining analysis of bus lines in Montevideo in Montevideo by Andrea Delgado, Daniel Calegari, and Nicolás Carignani

• Open data definition on Wikipedia

• Exporting the Disco process maps as XML files

• Another creative use of open data to analyze football matches by Hadi Sotudeh

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Hands-on practice is at the very heart of this year’s Process Mining Camp on 13 and 14 June. Above, you can watch a short video we recorded to tell you more about the workshops on the second day of camp.

To help you advance your process mining skills, you will get to work on real-life data sets. You will be exposed to the same challenges that you typically also encounter in your own process mining projects, supported by our expert guidance. You will participate in three workshops that fit together perfectly, with each of them focusing on different skills that you need to be successful.

→ Sign up for a process mining practice that you can get nowhere else. If you buy your ticket before the end of Friday, you can still benefit from the early bird rate!

Here are some further details about the three workshops on the second day of camp:

Workshop 1 · Discovery and Analysis

There is a certain magic in watching an experienced process miner approach a new data set. While they apply standard practices like identifying incomplete cases, they also follow their intuition and explore layers of the process in an iteration of discovery, questions, and analysis cycles.

Sure, it takes domain knowledge to identify the standard process and its deviations. But it is also a question of experience to know what to look out for, which questions to ask, and how to break up the “spaghetti processes” — even if you are not familiar with the process at all.

In this workshop, you are going to practice on a real-life data set. Together, we will discover and analyze this data set in multiple phases. We show you standard practices and discuss the results in each phase before going further. There will be time to apply the same approach to multiple data sets, and you can even bring your own data, if you like!

Workshop 2 · Data Skills

It is important to accept that your process mining data will not be perfect when you start analyzing it. After all, the vast majority of IT systems were not created with process mining in mind. Recognizing these limitations should not discourage you. Instead, embrace it as an opportunity for getting creative! Learn to navigate the available data and its possibilities.

In this workshop, you are going beyond the fundamentals of process mining, typically centered around case IDs, timestamps, and activity logs. More than just talking about these concepts, you are going to experience them together to gain a better understanding of the associated challenges and explore potential remedies.

To achieve this, you will immerse yourself in a practical case. In multiple steps, you will identify and address issues like faulty and missing data. You will explore techniques for combining event logs from different systems. And you will be stretching the boundaries of the data beyond their original design. We’ll also be discussing what the logs of the future might look like, and what steps you can take today to achieve that vision.

Workshop 3 · Organizational Best Practices

How do you translate process mining insights into changes in your organization? How do you make sure that the improvements stick? And how do you develop your process mining projects into a routine and general practice? The challenges for process mining are not only about technical skills. You also need to take strategic and cultural factors into account.

There is no simple recipe for what makes process mining successful. But there are a lot of different lessons that can be derived from both successes and from setbacks. By now, we have all been talking about these challenges and our experiences for two days — in the discussion groups, over dinner and drinks, in the breaks, during the workshops. In this last workshop, we take a step back and collect what we have learned.

Together, we are going to make this really practical. We will list what works, what doesn’t work and in which situation — and we put it into perspective. You will leave camp with new approaches and patterns that you can apply right away in your future process mining projects.

— We can’t wait to see you all in Eindhoven!

In the next Process Mining Café tomorrow, we have invited Andrea Delgado and Daniel Calegari from the Universidad de la República, Uruguay, to talk about their process mining case study for urban mobility.

They discover process flows for the bus lines in Montevideo using open data from the city. They then export the XML process maps from Disco to display the discovered processes in the spatial city map. Andrea and Daniel share their scripts and will give you all the information that you need to reproduce their steps.

How could you do a similar analysis for your own city? Join us tomorrow, Wednesday, 20 March, at 15:00 CET to find out! (Check your timezone here). As always, no registration is required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 20 March 2024, at 15:00 CET! Add the time to your calendar if you don’t want to miss it.

This is a guest article by Andrea Delgado, Daniel Calegari, and Nicolás Carignani from the Computer Science Institute, School of Engineering, Universidad de la República, Uruguay. They have used open data to discover the process flows from bus lines in Montevideo. They then exported the XML process maps from Disco to display the discovered processes in the spatial city map. In this article, they explain their approach and give you all their scripts and the information that you need to reproduce the approach for your own city.

If you have a guest article or process mining case study that you would like to share, please get in touch with us via anne@fluxicon.com.

Urban mobility allows us to access housing, jobs, and urban services, and its planning, control, and analysis are of utmost importance to city governments. Transport modeling and planning must address several challenges, such as traffic congestion, public transport crowding, pedestrian difficulties, and atmospheric pollution. Smart cities use technology to improve urban services, e.g., Intelligent Transportation Systems that incorporate technologies generating real-time data that can be processed to extract valuable information.

In 2010, the Municipality of Montevideo, Uruguay, defined a Mobility Plan, which included the creation of the Metropolitan Transportation System (Sistema de Transporte Metropolitano, STM), serving a population of 1.4 million. The STM defines several city public transportation elements, adding an ITS with on-board GPS unit control systems on each bus and smart cards for citizens, as illustrated in Figure 1. The Mobility Management Center manages and controls traffic and transportation in the city using the real-time data provided by the STM.

Fig. 1: STM system elements: smart cards for citizens, buses with GPS, and smart card readers that register data for each trip.

We address a set of questions defined by the Municipality of Montevideo in the context of a joint research project concerning their transportation system (STM) data from buses and smart card trips by applying process mining techniques. For this, we use open data provided by the STM within the governmental open data catalog¹. We provided another view on public transportation data to business experts to help them make decisions on the city’s urban mobility, considering different perspectives, including the behavior of bus lines according to the planned routes [1].

People working in the urban mobility domain are used to analyze data in traditional formats (tables, graphics, etc.) and locate geospatial data in the city map. In our first attempt, we analyzed the reference process model corresponding to the bus routes and the data from the actual trips made by passengers within the buses using a traditional process mining approach. However, we realized that the results could be deployed over Montevideo´s city map to improve visualization and understanding of the outcomes.

In what follows, we present an extract of the behavior of bus lines analysis presented in [1], focusing on deploying the bus lines process models provided by Disco over Montevideo´s city map using the open-source geospatial software QGis².

Open Data from the STM system

Below, we present some definitions of the Metropolitan Transport System (STM) that are needed to understand the data we used for the analysis:

• A line is a public name by which a set of routes of a transportation company is known, e.g., 2, 103, 148, 306, 405, 526, D11.
• Sub-lines are each one of the routes that a line has (difference in the streets traveled), with a direction.
• A variant is each instance of the route of a sub-line, with a specific origin, destination, and direction (maximal, partial, circular)
• Every variant (line, sub-line, direction, origin, destination) has a set of frequencies that defines a departure time on a given day (working days, Saturdays, Sundays, and holidays).
• Stops in the route of each variant are known, as well as the stop of origin and destination, all identified by a unique code.

The theoretical schedule by which a bus travels through each stop is also known for each frequency. Apart from the bus data, the information on passengers’ STM card payments is also known. There are different types of passengers, e.g., ordinary users, retirees, and students. Every time a payment is recorded, there is a registry with the kind of passenger, the stop at which it boards, the variant and frequency to which the bus belongs, and the time of departure, among other information. Below, we present the primary datasets we used for the reference process models of the bus line routes and the process model of actual passengers’ trips we show in the map of Montevideo, extracted from [1].

[UBS] Urban bus schedules, by stop³. It contains the bus schedules for urban transportation. These are estimated theoretical schedules in which a bus line will pass through a particular stop along its route. These data are obtained by estimating each stop’s passing times according to the transport units’ average speed, predefined schedule, and distance between stops.

• type of day: 1 - working days (Monday to Friday), 2- Saturdays, 3 - Sundays and holidays.
• cod variant: identifies the variant of the line.
• frequency: identifies the frequency for the variant for the type of day, i.e., the specific hours.
• cod loc stop: shows the code of each stop
• ordinal: shows the number of stops within the bus line route, i.e., first (1), second (2), etc.
• hour: shows the estimated hour for the bus to arrive at the stop
• day before: indicates if the frequency started the day before (for late-night lines)

The UBS file contains data from more than 100 bus lines with more than 800 variants and 1000 corresponding frequencies. Four companies provide the service and cover the metropolitan area with more than 4700 stops.

[TSB] Trips made on STM buses⁴. It contains all the trips made on the urban collective transport lines in Montevideo by each operating company, line, variant, day and time, tickets sold at all stops in the system, by type of user, payment method, and sections of each trip. The information comes from all the records processed by the STM trip validation machines.

• id trip: identifies the trip within the system; in combined tickets, the id trip is repeated in all
• buses the user rides while the ticket is valid.
• line code: shows the code of the bus line
• cod variant: identifies the variant of the line
• frequency: identifies the frequency for the variant
• with card: shows if the STM card was used in the payment of the trip
• date event: timestamp of date and hour of the trip
• trip type: combined (1 hour, 2 hours), student, retired, standard user.
• origin stop code: shows the code of the stop at which the user got on the bus

The TSB file we used to analyze the STM trips corresponds to May 2022, which contains 25 million records, including all trips from the STM system registered within the 136 bus lines of Montevideo. For experimentation, we selected different bus lines from these to maximize the city coverage [1].

[BLOD]⁵ Bus lines, origin, and destination. It contains geographic information that, among other data, includes the lines’ description, origin, and destination. This dataset contains the shapefile⁶ that provides geospatial data for the bus line destinations for each bus line, sub-line, and variant.

[CTSC]⁷ Buses: stops and checkpoints. It contains geographic information on stops and control points. This dataset contains the shapefile with geospatial data for the stops defined within the city, referenced in the bus lines routes.

Process mining applied to urban mobility

From the perspective of the behavior of bus lines according to the planned routes, we analyzed the data to answer some of the business experts’ questions, in particular, the ones related to bus lines and their use by passengers:

1. What is the route of a bus line?
2. How is the mobility of people within the STM?

Regarding the reference model of the bus lines (question 1), we can obtain it from the UBS file that contains the theoretical schedules. We select variants for each line, setting the variant and frequency codes and day as {case ID}, the stop code as {activity ID}, the hour of the stop as {timestamp}, and the rest of the data fields as {attributes} of the activity. Since variants have different directions corresponding to the sub-line, we obtain two sequential sections in each direction. The reference model must contain the same stops in the same order as the ones defined by the variant in the STM system, which is accessible from the website for a scheduled consultation.

Regarding users’ data on authentic trips of the bus lines (question 2), we can discover a travel model for a bus line from the TSB file. We filter by line and selected the variant, frequency, and day of the trip as {case ID}, the stop code as {activity ID}, the hour of each trip of each stop as {timestamp}, and the rest of the data fields as {attributes} of the activity. The number of events at each stop is the number of passengers boarding. Thus, loops represent multiple passenger boardings at the same stop. Unlike the reference model, the process is not linear since, in some frequencies, there are stops in which nobody boards. We can filter data by days (business days, Saturdays, Sundays, and holidays), day hours, seasons, type of user, company, etc.

Figure 2 (extracted from [1]) depicts examples of these two process models discovered in Disco for bus line 125, variant 667, which is the maximal variant in one direction. This bus line goes in one direction from the old city to the West, ending in Cerro Beach and returning in the other direction.

In this Figure, we can see: a) the bus line in the map taken from the STM schedules site⁸, b) an excerpt of the reference model (i.e., bus stops included in the line), and c) an excerpt of the STM trips within its frequencies.

Fig. 2: Bus line 125 route from [1] with stops for the 667 variant: a) in the STM website bus schedule, b) excerpt of the reference model, and c) excerpt of the STM trips within its frequencies

From users’ data on actual trips of the bus lines (question 2), it could be possible to analyze load metrics after filtering and discovering the model. For example, it is possible to answer: At which stops do people not get on? At which stops do more people get on? At what times does the bus have more and fewer passengers? What happens to those lines in a particular area? Moreover, it is possible to answer performance questions such as: What is the total duration of the frequencies (on average, maximum, minimum)? Are there frequencies with delays? As an example, we present in Figure 3 the performance model for bus line 300 (one of its variants), which goes from the bottom of the city near the city center to the city’s north periphery, showing the delays in the transitions between stops of the bus line route, calculated with the actual trips data.

Fig. 3: Bus line 300 route with stops for one of its variants: a) in the STM website bus schedule, b) and c) excerpt of performance models with delays in the transitions from the STM trips data.

Exporting from Disco and visualizing the models over Montevideo´s city map

As mentioned before, people working in the urban mobility domain are used to seeing locations on the city map, analyzing data, and considering geospatial data. Although the process models provided valuable information, they should be compared manually to the bus line route provided over the STM site’s city map to identify where some behaviors arise. To improve visualization for business experts, we developed a prototype to deploy process models over Montevideo’s city map.

Disco allows the export of XML files of the resulting process models, both the process map and the performance view. As we selected the bus line stops as activities of the process, which have a corresponding geospatial location over Montevideo city, we can locate each stop in the map and, correspondingly, the Disco process model we exported. Also, the dataset containing the data for each bus line route destination is used to locate the reference bus line route over the map. These data correspond to BLOD and CTSC files with shapefiles geospatial data of the bus line routes and stops in Montevideo.

We used the open-source geospatial software QGIS, which supports loading city maps with corresponding coordinates worldwide, creating/adding layers with geospatial data in the shapefiles to be seen over the map, and developing scripts with Python to work with them. In Figure 4, we present the process flow for deploying the process models exported from Disco over the city map loaded in QGis with the help of the scripts we developed.

Fig. 4: Process for deploying process models exported from Disco over the city map in QGis.

The first step is to load the event log into Disco, in our case, the data corresponding to the passengers’ actual trips over a bus line, to discover the corresponding process model of the bus line route, which can be filtered by variant as shown above. Then, the resulting process model can be exported in XML format, which will be one of the inputs to QGis to show over the city map. We want to show both the process map with the flow of the actual trips over the bus line and the performance map with the delays of the buses on the actual trips, as depicted in Figures 2 and 3. In Fig. 5 a screenshot of the export model XML we used in Disco is shown.

Fig. 5: Disco export model in XML format

In QGis, we first load the shapefile data of the stops and the origin and destination of buses over the city map as vector layers and then the city map layer as the XYZ layer. These layers should be in the same coordinate format and time zone to match locations. We load the Python scripts we developed in the project options. Figure 6 shows a QGis screenshot with the three layers in the bottom left panel and the Python scripts in the right panel.

Fig. 6: QGis software with Montevideo city map layer (XYZ), bus stops over the city (from CTSC shapefile), and bus lines origin and destination over stops (from BLOD shapefile)

The Python scripts we developed transform the Disco process models into a QGis layer that can be deployed over the city map, using as reference the stops and the bus line origin and destination geospatial data we first loaded over the city map. The QGis scripts are as follows:

• layer_from_disco_model_flow.py: transforms a Disco process model flow (XML) into a QGIS layer, which allows visualization over the map.
• legs_for_variant.py: divides a bus line into sections (consecutive stops), which is then used as input for the performance process model calculations.
• layer_from_disco_model_performance.py: transforms a Disco performance process model (XML) into a QGIS layer using the legs_for_variant output layer as input.

To illustrate the process in QGis and its results, we use the bus line 21 route that we show in Figure 7 for the 7488 variant: a) the bus line in the map taken from the STM schedules site, and b) an excerpt of the STM trips within its frequencies, which is the one we import in QGis. This bus line goes in one direction from Independence Square (the entrance of the old city) to the east, parallel to the coast, and ends in the Portones Shopping Center in the Punta Gorda neighborhood. It has extensions of the route to the old city (left) and to the entrance of the Canelones Department (right).

Fig. 7: Bus line 21 route with stops for the 7488 variant: a) in the STM website Bus schedule, b) excerpt of the reference model, and c) excerpt of the STM trips within its frequencies

The process model exported from Disco corresponding to Figure 7 c), and transformed into a QGis layer can be seen over the Montevideo city map shown in Figure 8, with zoom over the first sections (left). It can be seen that differently to the ones presented in Figure 7, a) and b), it has arcs that traverse over non-consecutive stops, which reflects, as we mentioned, the actual trips over the bus line route, where in some frequencies, no passengers are getting into the bus in some stops.

Fig. 8: Process model flow view exported from Disco discovered from the STM trips actual data for the 21 bus line route and variant 7488 deployed over Montevideo city map

Zooming again on the upper-right corner flow, we can see the details of the process model flow in Disco and the corresponding process model deployed over the city map, as shown in Figure 9: a) the process model in the city map, and b) the process model flow in Disco. It can be seen that stop 2126 goes over the left in the map, stop 2131 goes over the right, and stop 2128 goes in the middle, with the flow to the right. If the two views of the model are compared in Figure 9 a) and b), the difference is noticeable. The map gives a much greater context, allowing one to quickly know the exact location of the activities (stops in this case), the corresponding area, and the neighborhood, allowing one to relate the generated model to information not included.

Fig. 9: Zoom of the process model of the bus line 21 route upper-right corner flow and correspondence with the Disco process map

In this case, we could further investigate why, on several occasions, no passengers are getting on the bus at stop 2128. Some causes could be the following: the stop infrastructure is worse than other nearby stops, there are security issues in the area, and it is mainly used by specific groups of users (e.g., students) within input and output hours of the school.

The performance process model exported from Disco corresponding to Figure 7 c), and transformed into a QGis layer can be seen over the Montevideo city map shown in Figure 10: a) the model exported from Disco with delays in transitions between the stops, and b) deployed in the map showing sections delays using the semaphore metaphor: green, yellow and red for more significant delays.

Fig. 10: Performance process model for the bus line 21 route from the bus actual trips data: a) the model exported from Disco with delays in transitions, and b) deployed in the map showing sections delays

Again, as in Figure 8, being able to visualize the specific sections of the bus line that present the worst times over the bus line route in the map, provides a much greater context, allowing to identify the zone at which the sections belong quickly. In this case, it can be seen that the section to the left that goes from the Centenario stadium (round green space marked in the middle below the bus line) to the old city presents the worst delays. This is consistent with that zone being bustling over Avenue Av. Italia, passing through the Three Crosses bus terminal and traversing from start to end the main center avenue Av. 18 de Julio towards the old city entrance (Independence Square).

Conclusions and reproducibility for other cities

We have presented a case study on the application of process mining to analyze urban mobility open data from the STM transport system in Montevideo, Uruguay. We showed how, using Disco, we can discover the reference process model of bus lines using the stops defined for each one and the actual STM trips process model that shows the actual behavior of bus lines regarding passengers’ use within the different frequencies (actual trips) of the buses.

Due to the interest of business people in this specific domain who normally visualize and analyze data over the city map, we developed a prototype that, using the process model export feature of Disco in XML format, allows us to import them into the open-source geospatial software QGis, deploying them over the city map of Montevideo. This provides much greater context to users, as discussed in the previous section.

Regarding reproducibility for other cities, exporting the process models to Disco, importing the layers for the stops and bus lines routes over the city map, and generating the QGis layers for the process models can be applied straightforwardly. For the scripts to work, the process models to be exported from Disco should use as activities the stops of the bus lines, and the files containing the shapefiles with geospatial data of the stops and bus lines routes should be available. The city map layer is loaded as an XYZ layer directly in QGis, available for all cities. The data and format are available from the bus actual trips system of the desired city (i.e., the records of the passengers’ trips) and should probably have to be manipulated to provide the same fields that we used (e.g., bus line, variant, stops to relate to the shapefiles, etc.), or the scripts can be adapted to the data provided by the system under analysis.

The scripts and data are publicly available⁹ for further experimentation and analysis.

References

[1] Delgado, A., Calegari, D., Process Mining for Improving Urban Mobility in Smart Cities: Challenges and Application with Open Data, 56th Hawaii International Conference on System Sciences (HICSS-56), Maui, Hawaii, USA, Scholarspace, 2023. https://hdl.handle.net/10125/102846

[2] Rodao, B., Carignani, N., Ferreira, S., Minería de Procesos para el análisis de movilidad urbana. Tesis de grado. Universidad de la República (Uruguay). Facultad de Ingeniería, 2023. (In Spanish) https://hdl.handle.net/20.500.12008/42549

Authors

Andrea Delgado - adelgado@fing.edu.uy - https://www.fing.edu.uy/~adelgado

Daniel Calegari - dcalegar@fing.edu.uy - https://www.fing.edu.uy/~dcalegar

Nicolás Carignani - nicolas.carignani@fing.edu.uy

This year’s Process Mining Camp will run for two full days — Fire up your calendar and block 13 and 14 June 2024 right away!

Since the beginning, we have always been making changes and improvements to the way we run camp. This year, however, we took a big step back and thought about what we can do so that you can get even more out of camp.

You are a dedicated practitioner who is serious about process mining. You want to improve your craft and skills, and level up in your mastery of process mining. At the same time, you want to have deep, meaningful interactions and connect with the global process mining community. This year’s camp is tailor-made for you, the process mining expert!

More time to connect

When you are all on your own, it is easy to walk in circles. You run the risk of getting stuck or drawing the wrong conclusions. Talking to others can snap you out of an impasse and save you a lot of time that you would have spent figuring everything out by yourself.

Meeting other process miners has always been the main feature at each year’s camp. But having just a few minutes over coffee between talks is not enough to get to know each other.

At this year’s camp, you will have two complete days and an entire evening to connect with your process mining peers. At the end of camp, you will have talked to, and know, everyone!

Workshops take center stage

Process mining looks like magic. However, it is, in fact, a craft that you need to develop in your organization. For this, learning and practice are essential.

Our previous workshops at camp were relatively short, and you had to pick one of them. At this year’s camp, we will have a full day of workshops that cover all the important angles of applying process mining.

You will participate in a program of three hands-on workshops that fit together perfectly. These workshops are designed to supercharge your learning by working on concrete, realistic scenarios that you can normally only get from real-life experience.

Discussion roundtables

We all have different perspectives, and we benefit by considering these different angles. At this year’s camp, you will be part of the discussion and contribute your own experience.

We start by collecting challenges and ideas in small groups of up to eight people. The results of these discussion roundtables are then shared with the whole community. They will set the theme for the rest of camp: Throughout these two days, we will sharpen these challenges and their solutions together.

Boot Camp

We want this year’s camp to be a great experience for you, especially if you already consider yourself an advanced process miner. Of course, we also made sure that, if you are still on your way there, process mining camp will help you fill your gaps.

However, what do you do if you are a process mining greenhorn?

For the first time, we offer an optional boot camp training for those who are just starting out with process mining. In two sessions, one week before camp and at the beginning of the first camp day, you will learn all the basics that you need to follow the discussions and start practicing yourself.

Keeping It 100

We are revamping camp in a major way. At the same time, we also want to hold on to the things that have always made process mining camp so special.

No-nonsense practice talks. Process mining professionals from a variety of industries tell us about their projects in honest practice talks. The camp speakers do not only tell success stories but really show what they did. They will also share what did not work for them and what they have learned. If you have never been to camp, you can watch the videos from previous camps here.

Process mining for professionals. Camp is from practitioners for practitioners. No academic weeds, no sales show, and zero hype. Technology is fascinating, but we are not using technology for technology’s sake. We are all singularly focused on creating value for our organizations. Process mining camp, in its essence, is thoroughly pragmatic.

Our annual family meeting. Over the years, thousands of process mining enthusiasts from more than 34 countries have joined camp. You are going to meet people who apply process mining in their daily practice in completely different contexts. They will help you put your own challenges into perspective. Enjoy the friendly atmosphere, and meet old and new friends from all over the world!

See you at camp!

So, this year’s camp will run for two full days. It will go deeper, and it will be more practical than ever. In addition to the camp talks as you know them, we are adding discussion round tables to inform and guide camp. And we have a complete second day with an integrated program of three workshops, so that you can be sure to advance your process mining skills.

Clearly, we are asking more of you. The price tag is higher simply because it costs more to put this type of camp together. And you are committing two days of your time. But you are going to get so much more out of it!

You will get:

• A hands-on process mining practice that you can get only here
• New skills and knowledge that you can apply right away
• Feedback on your own challenges and data sets
• A perspective on where you stand and where to turn to next
• Face time with process mining experts
• Deep and extended exchange with your peers
• Personal connections that will help you way beyond camp
• A very comfy t-shirt

→ Sign up now to reserve your spot and lock in your early bird discount!

We are very excited about this year’s camp. We think you are going to love it, and we can’t wait to meet you all in Eindhoven!

In last week’s Process Mining Café, we talked about Human Resources (HR) processes. Alex Cheremukhin, who used to be the Global HR Transformation Programme Manager at a British multinational, shared his experience.

There is a lot of variability in Human Resources (HR) processes. This is only natural as people are different! And there is different legislation in different countries, different types of benefits, etc.

We show two approaches for dealing with this complexity: (1) One approach starts with the raw data from SAP HR, and we map the data to the process level in a bottom-up way. (2) The second approach is broader and takes a top-down view using the APQC standard process framework, making it possible to look at interactions and flows across different processes. Alex shows this based on a Workday example.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. A big thanks to Alex and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• The Police in the Netherlands have used process mining in HR to make better decisions

• APQC Standard Process Framework

• Ulrich model

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

In the next Process Mining Café tomorrow, Rudi and Anne will talk with Alex Cheremukhin about Human Resources (HR) processes.

Alex used to be a process owner in HR for a big multinational. We discuss why there is so much more variability in HR compared with, for example, finance processes. As you can imagine, people are different! And there is different legislation in different countries, different types of benefits, etc.

So, how do you deal with this complexity when you analyze HR processes with process mining? We will show two approaches: One bottom-up and one top-down approach. Do you want to see how you can analyze your own HR processes?

Join us tomorrow, Wednesday, 21 February, at 15:00 CET! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 21 February 2024, at 15:00 CET! Add the time to your calendar if you don’t want to miss it.

In last week’s Process Mining Café, Hugo Verver walked us through the analysis of the complaints process at the Dutch health insurance provider VGZ.

As the data analyst, Hugo could use process mining to bring a fact-based view of the process to the subject matter experts. But he also needed to protect them from jumping to conclusions too early when the data was not good enough yet. He takes us through his process of assessing the data quality and the steps to make it fully usable.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. A big thanks to Markus, Eric, Alex, Niek, Willem, and Tina for their excellent questions. And thanks again to Hugo and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Previously, Roel and Wesley combined process mining with Lean methods at VGZ

• Léonard Studer talks about analyzing the building permit process at the City of Lausanne

• Tina asked about the process for discovering data quality. We recommend this data quality checklist as a starting point

• Process Mining Café about customer journeys

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

A new year has started. And with it, our new training season! Perhaps you want to make 2024 the year you get serious about bringing the magic of process mining into your organization?

Of course, process mining is not actually magic. It is hard work that requires a smart human analyst to interpret what they are seeing. But it surely just looks like magic, and you will be able to dazzle others and have exciting new perspectives on your business processes.

At Fluxicon, we have more than 20 years of experience with process mining. We use that knowledge to build the best process mining software for professionals. We are also busy capturing the best practices in our process mining book and shaping the process mining methodology together with all of you in our annual Process Mining Camps and the monthly Process Mining Cafés.

But the most direct way to benefit from our experience is to join one of our hands-on trainings. Here is what you need to know about our process mining trainings:

• Our trainings are live. This means that the lessons are not pre-recorded. Instead, you join the teacher and the other participants in interactive web meetings.

• The groups are deliberately small. So, you can be sure to be able to bring in your own topics. You will also learn from the questions of your peers, who often have a different perspective than you.

• Our trainings are really practical. You will learn all the essential concepts of process mining in practice. This training will give you the basis to use the full potential of process mining in your work.

• No prior knowledge is required. We will start from scratch, so don’t worry if you are totally new. But even if you already have some experience with process mining you will benefit, because there is a lot to know!

• The training does not end after two weeks. We meet with the same training group after 1-2 months to discuss the first results. Afterwards, we stay in contact and keep supporting you on your process mining journey.

Dates

Each training consists of four two-hour sessions over the course of two weeks. In between the sessions, there are exercises to apply what you have learned.

The next available training dates are (click on the link and scroll down to enroll):

• March 2024 Training: Mo 11 March, Thu 14 March, Mo 18 March, and Thu 21 March from 15:00 until 17:00 CET each day.

• May 2024 Training: Tue 21 May, Thu 23 May, Mo 27 May, and Thu 30 May from 15:00 until 17:00 CEST each day.

• July 2024 Training: Mo 15 July, Thu 18 July, Mo 22 July, and Thu 25 July from 15:00 until 17:00 CEST each day.

• September 2024 Training: Mo 16 September, Thu 19 September, Mo 23 September, and Thu 26 September from 15:00 until 17:00 CEST each day.

• November 2024 Training: Mo 18 November, Thu 21 November, Mo 25 November, and Thu 28 November from 15:00 until 17:00 CET each day.

We hope you have had a great start to the new year! As for us, we are excited to continue our Process Mining Café series. In its laid-back format, the café allows us to take the time to talk through a broad range of process mining topics. And we love doing it together with all of you.

The next café takes place already this week on Wednesday. Rudi and Anne talk with Hugo Verver from the health insurance provider VGZ. We will talk about his analysis of the complaints process and specifically focus on his perspective as a data analyst. In which phases was it crucial for him to interact with the subject matter experts and change managers? How did he embed process mining in his day-to-day work, and what did he learn from it? Stay tuned for some impressive before and after pictures!

Join us on Wednesday, 24 January, at 15:00 CET! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 24 January 2024, at 15:00 CET! Add the time to your calendar if you don’t want to miss it.

In this year’s last Process Mining Café, we discussed Activity-based Costing (ABC) with Willem Glasbergen.

In ABC, indirect costs are tied back to products and services. For example, if you have a maintenance expense of 500 Euros after 1000 hours for a machine in a production process, you can allocate 50 Cents (500 / 1000) extra costs per machine hour.

If you combine ABC with process mining, you can allocate costs to activities in your processes and evaluate “buckets of cases” according to their costs for the organization. For example, in service processes, indirect costs are often the salaries of the employees working in the process. Considering these costs for your process mining analysis can help improve your process in the right direction. Willem and Anne showed how this works based on a concrete example.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks again to Willem and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Lucy Brand-Wesselink’s presentation at Process Mining Camp 2016

• Activity Cost Driver in ABC: https://www.investopedia.com/terms/a/activity-cost-driver.asp

• “Buckets of cases” can be segmented explicitly or based on the behavior in the process

• The 2017 BPI Challenge Loan Application Data Set was used as an example in the demo

• Willem’s Cheat Sheet with the steps that he follows in his approach when combining ABC with process mining. Let him know if you have questions or feedback!

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

In this week’s café, we are taking a closer look at Activity-based Costing (ABC).

Already in 2016 at ALFAM, our guest Willem Glasbergen combined process mining with Activity-based Costing. In the café, he tells us what you need to pay attention to when you apply process mining with ABC. We will also discuss a concrete example together based on Willem’s approach. Join us!

The café takes place this Wednesday, 13 December, at 15:00 CET! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 13 December 2023, at 15:00 CET! Add the time to your calendar if you don’t want to miss it.

In the latest Process Mining Café, we talked with Tobias Zepter from the BVV. At BVV, they did not have any data available for process mining. Therefore, Tobias created a system that allows employees to collect data about process executions in a lightweight and iterative way.

Privacy was essential for them from the beginning. Tobias discussed how the privacy of the employees and customers is protected and showed us the system he has built. You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks again to Tobias and all of you for joining us!

Contact us anytime at cafe@fluxicon.com if you have questions or suggestions for the café.

Have you seen that the Process Mining Café is also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up for our café mailing list and the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

This is the 2nd article in our project guide series. You can find an overview of all the articles in the series here.

Today, we bring you the second step in any process mining project: Creating your project plan (see below).

It all starts with inspiring others

One of the challenges is that process mining and its potential are often unknown. To find a suitable project, you usually must make some noise to get the right people on board.

Showing the potential and discussing the opportunities and challenges of applying process mining is, therefore, an excellent first step. You can show an introduction, a live demo (see video), a case study, or a video recording (a shorter, 15-minute version is here). What would be the biggest potential for process mining within your organization? For inspiration, you can also look at the typical use cases for process mining here.

Once you have selected your process and have an idea for a project, you can create your project plan. For experienced project managers this is easy. However, if running a project is new for you, you might be tempted to skip this step and dive right into the analysis. Don’t do this.

If you don’t know how to make a good project plan and it seems like a daunting task, read the following article. Fortunately, rather than a big, scary document, the project plan can be quite practical. It is there for you and it helps you to communicate the objectives, the investments and the risks to your stakeholders. To get started, you can answer the following five questions.

[As a companion to this step, you can watch the video recording of our Process Mining Café about Project Planning here.]

1. The Objective: Understand the problem and why do we need to do something about this now?

Create a one-page overview for your project by writing the following three paragraphs.

Describe the situation in a maximum of 100 - 150 words.

This is a statement of the current state of affairs. It should be fact-based (e.g., “Since its founding 15 years ago, the company has grown from a startup with no revenue and one employee to a robust enterprise with $15 million in revenue and 60 employees”). Because it is fact-based, this situation description should be something with which no one can reasonably disagree. We often use this section to highlight positives. If possible, give the person to whom you are presenting credit for their accomplishments.

Describe the problem in a maximum of 100 - 150 words.

This is a statement of the problem – the issue you are addressing (e.g., “Over the past three years, revenue growth has stalled”). It lays out why the company should act. Without this problem, the company wouldn’t need to do anything; There would be no reason for a change. People who are resisting the change you are suggesting may try to take issue with the problem. After all, if it isn’t valid, there is no need to change. Therefore, you, as the presenter, should base this section on objective facts that are irrefutable (“Sales three years ago were $15.1 million, while sales last year were $14.9 million”). People may not like hearing this, but they can’t argue that it isn’t true.

Describe the goal in a maximum of 100 – 150 words.

This is your recommendation; it resolves the problem. The goal brings focus to your process mining analysis. For example, are you improving customer experience, reducing cost, or mitigating risks? What would be the primary questions that you need to answer to understand the problem fully? If you can’t boil your recommendation down to a single goal, you should have more than one project.

2. The Approach: How does process mining fit the methodology and approaches we adopted?

Process mining is agnostic to which methodology you use, but it needs a surrounding approach to be effective. Most organizations already use a methodology, for example, for their improvement projects or audits. We advise applying process mining in combination with the methodology that your organization has adopted.

Find out which approach is used and align your process mining project plan with this existing approach. Describe why process mining is beneficial in this context.

Lean Six Sigma: DMAIC

For example, many companies use the Define Measure Analyze Improve Control (DMAIC) approach of Lean Six Sigma. You can see how the twelve process mining steps align with DMAIC in the image above. To see an example of the benefits of using process mining with Lean Six Sigma, read our series on combining Lean Six Sigma and Process Mining and watch this Process Mining Café about Lean Six Sigma and Process Mining.

Auditing

Another example is the use of process mining in an audit project. Each audit department already has an approach that structures the audit into several phases. The following picture shows how the twelve steps of the process mining project fit into the audit process described by Wilco Brouwers and Dave Jansen from CZ. To see a detailed example of how process mining was used in a concrete audit, read this case study about Auditing with Process Mining by Jasmine Handler and Andreas Preslmayr from the City of Vienna and watch this Process Mining Café about how process mining changes the traditional audit approach.

Plan Do Check Act (PDCA)

You can map any approach on the twelve steps of your process mining project. For example, the last image above shows how they align with the Plan Do Check Act (PDCA) improvement cycle.

3. Sponsorship and Project Team: Who needs to be involved?

No one knows everything. A variety of skills and roles are required for your process mining project team. Sometimes, a single person can combine multiple roles at once. In other situations, you need to involve different people for each role.

Determine who you need on your team and who provides vital input. For example, make sure you have someone on board who helps you to get and prepare the data. Furthermore, in addition to the sponsor, you will need access to domain experts who help you validate the data and can answer questions about the process during the analysis.

4. Key Risks: What are the key risks, and how should we mitigate them?

Unexpected things will happen during your project. Some of them you can’t plan for upfront, but for the things that are likely to happen, you can already discuss what to do.

For example, what do you do if you have difficulties accessing the data or have significant data quality problems? In our Process Mining Café about project planning, we recommend building in a deliberate breaking point early in your project, where you determine whether the data is suitable to continue.

Discussing these key risks with your sponsor and agreeing on how to handle these situations will help you find the proper support throughout your project.

5. Deliverables: What will be delivered when?

Set a realistic plan to manage expectations. Most process mining projects will take from 4 weeks up to 6 months. Projects that take longer are either scoped down or broken up into multiple stages.

Think about the deliverables that you will produce in each of the process mining project phases. Note that there can be multiple deliverables per step. For example, rather than going into the complete data extraction right away, it is a good idea to request a small sample of data first. This will help ensure that process mining fits the purpose without wasting too much time on other things.

Think through your whole project, but keep it simple. Your main goal with the project plan is to help you manage the risks and communication points in the team.

Planning is often seen as a burden, but it doesn’t have to be. If you create your plan by answering the five questions above, you are good to go.

Have you written your project plan? Great! Then, you can move to the next step: Defining your analysis questions.

To read the following articles in this project guide series, keep an eye on this blog or receive email notifications for new blog articles by signing up here.

What do you do if you want to do process mining but you don’t have any data?

Tobias Zepter, Lead Enterprise Architect at BVV, found an elegant solution: He created a system that allows employees to collect data about process executions themselves in a lightweight and system-independent way. One advantage is that this internal system has privacy considerations built-in.

In the following Process Mining Café on Monday, Tobias will show us their system and discuss their design considerations. Have you ever wondered how to collect process mining data in your organization? Or are you just curious to see what Tobias has built? Join us!

The café takes place next Monday, 13 November, at 15:00 CET! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Monday, 13 November, at 15:00 CET! Add the time to your calendar if you don’t want to miss it.

In the latest Process Mining Café, Rudi and I spoke with Scott Leslie from Evidant about analysis transformations.

The data that you find in information systems was not created for process mining purposes. So, often, you need to shape the data to make it suitable. Furthermore, different analysis questions may require particular views on the data. We look at two concrete examples to illustrate the steps in such transformations.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks again to Scott and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Previous Process Mining Café about common data preparation questions for process mining

• Our Process Mining Transformations series shows common data transformations, such as unfolding loops for activity repetitions

• Process mining examples for customer journey analyses

• If you have a start and complete timestamp for each activity, you can distinguish active time and waiting time between activities

• Another example of mapping activity names to bridge the business-IT gap in the data

• Keep in mind that attributes are not static but may change over time. If you enhance your data with such attributes today, you may be missing their historical values

• Leonard from the City of Lausanne shows in his Process Mining Camp talk how he tried to group free-text activities

• Enhancing your data set can enable you to take different views, like hand-over of work between different departments

• We showed how to focus on steps between activities, and Marcus asked what to do about missing activities

• Example of analysis transformation driven by domain knowledge: Fran from the UW Health Nursing Informatics Department shares one of her data transformations

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Have you already seen that the Process Mining Café is now also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up to our café mailing list, the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

One thing we discussed in our Process Mining Café on Data Preparation is that you work with the data that you have. The next Process Mining Café this Wednesday will be about the fact that you can further shape the data to look at the process as you want it. These specific types of data transformations are called analysis transformations: Data transformations that you make with the specific goal to better analyze your process.

Rudi and I are joined by Scott Leslie from Evidant, who will tell us about the analysis transformations that he frequently makes. Based on two concrete examples, we show how the modifications improve the analysis possibilities step by step. Come join us, too!

The café takes place tomorrow, Wednesday, 11 October, at 15:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe on Wednesday, 11 October, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

In the latest Process Mining Café, Rudi and I talked about project planning. First, we discussed how you can select a suitable process for your process mining project. Then, we went through the five main ingredients for making a good project plan:

1. Be clear about the objective

2. Understand the methodology around process mining

3. Assemble the right project team

4. Mitigate the key risks

5. Identify deliverables and make project plan

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks again to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Which process mining project should you start with?

• Example of a fully automated process, where process mining was still useful: Boris from Vanderlande used process mining to solve a problem of recirculating parcels

• Combining Lean Six Sigma and process mining

• Process mining camp talk by Wilco and Dave from CZ about process mining in internal audit

• Case study: Auditing with process mining

• Skills and roles needed in your process mining project

• Previous Process Mining Café about common data preparation questions for process mining

• Process mining does not discover project plans (like Gantt charts) but you can analyze project processes. In our Process Mining Café about ‘Project vs. Process Thinking’ we talked about how project management processes often contain a lot of parallelism

• Marc from KLM looked at the characteristics of the different agile teams

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Have you already seen that the Process Mining Café is now also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up to our café mailing list, the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

We are happy to announce the release of Disco 3.6.

This update makes loading your log data into Disco even faster and more reliable, especially if you are importing from CSV or Excel documents. We have also thoroughly updated Disco’s foundation, so you should expect better performance, less bugs, and improved security all around.

Thanks for all your feedback, you are really doing the Lord’s work here. Keep it up and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• CSV Import: Improved stability and performance.
• Excel Import: Improved stability and performance.
• XES Export: Fixed validation issues.
• macOS: Fix graph layout for some Apple silicon users stuck on Big Sur.
• Connection: Improved stability.
• Control Center: Improved hardware detection.
• Platform:
  • Java update.
  • Streamlined dependencies.

In our next Process Mining Café this Wednesday, Rudi and I will discuss what it takes to create a good project plan for your process mining project. Join us!

The café takes place this week, Wednesday, 20 September, at 15:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 20 September, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

In this last Process Mining Café before our summer break, we spoke with Nuno Serra from Food4Sustainability CoLAB in Portugal.

If you are creative, you can find process mining data in unexpected places. Nuno showed us how he turned static data from an agricultural government funding program into a process view. After creating timestamps and activities from implicit information, he could analyze how farmers requested more or less aid over the years in the context of the development of their farms.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks again to Nuno and to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Information and brochure about the project (both in Portuguese)

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Have you already seen that the Process Mining Café is now also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up to our café mailing list, the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Food4Sustainability CoLAB is a non-profit association dedicated to innovation in sustainable food production. Nuno Serra is the director at Food4Sustainability and has used process mining to evaluate the effect of public policy on farmers.

In our next Process Mining Café this Wednesday, Nuno will show us how he tweaked the data to be able to use it for process mining and what kind of analyses he could then do with it. Join us!

Discuss public policy and data magic with us this week, Wednesday, 19 July, at 15:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 19 July, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

In the latest Process Mining Café, Rudi and I went through the most frequent questions around data. An event log is something that you make, and getting the data is often one of the first challenges you have at the beginning of your process mining project.

We also show you two common data transformations based on a practical example. Building the data on a logical level is a crucial step in understanding the choices you make preparing the data. Even a small sample data set can serve as the blueprint to explain how you need the data to be.

You can now watch the recording here if you missed the live broadcast or want to re-watch the café. Thanks again to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Data extraction checklist

• Marc Tollens from KLM shows how he analyzed Jira data at Process Mining Camp 2018

• Mark Pijnenburg and Carmen Bratosin analyzed data from the MRI machines at Philips Healthcare during Process Mining Camp 2019

• Skills and roles needed in your process mining team

• Manual activities need to be taken into account when you interpret your process map

• Which process mining project should you start with?

• Data suitability checklist

• Data requirements for new IT systems

• Jasmine Handler and Andreas Preslmayr did their own data preparation in this audit project, which enabled them to fully understand the data and the choices that needed to be made

• Combining data sets in Excel, in an ETL tool, and with SQL

• Column-formatted data often has missing timestamps for activity repetitions

• Transposing the data in Excel and with an ETL tool

• Put additional information in separate columns to preserve the flexibility to unfold individual activities

• You can get creative and find data for process mining everywhere. See also the Process Mining Café with Léonard Studer from the City of Lausanne in Switzerland, where we look at different examples of “Sequences of Stuff”

• Privacy, Security, and Ethics are becoming more and more important. See also the Process Mining Café with Dirk Fahland and Felix Mannhardt from TU Eindhoven, where we talk about how to be a responsible process miner

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Have you already seen that the Process Mining Café is now also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up to our café mailing list, the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

Last week’s Process Mining Camp was wonderful! It felt like a family reunion, in a good way. We had a full program and plenty of time to interact with the community.

Keynote

We started by welcoming the campers and telling them that the Process Mining Café is now also available as a podcast. The café is an extension of the discussions in our camp community and has covered a broad range of topics, from process mining research, over specific use cases, up to various aspects of the process mining methodology.¹

As a continuation of the previous Process Mining Café, we then talked a bit more about data preparation. There are various phases of data preparation, some inside and some outside of Disco. We showed examples from different phases and gave tips for preparing the data to keep maximum flexibility in your analysis.

We also recommended that the campers think about their own strengths and knowledge gaps. Process analysts might consider adding some data preparation skills (like learning an ETL tool) because this will empower them to be even more independent. In turn, data specialists can benefit from familiarizing themselves with process analysis methodologies and picking up some change management skills.

Eric N. Kildea — Radwell International, USA

Eric Kildea from Radwell in the United States was the first speaker. Radwell buys, sells, and repairs industrial automation and electrical control equipment and Eric vividly showed us the complexity behind these physical processes. Previously, they had already tried mapping their processes manually, but this was very difficult. At the same time, they had terabytes of data, which he thought they should be able to use more constructively.

Eric worked closely with the process managers and experts for all his process mining projects. They know their processes very well. From their years of experience, they have developed a gut feeling about what is happening. Using process mining, they could then compare their gut feeling with the process reality. Eric showed two different cases. One identified over 16,000 items that should be shipped to specific branches. The other one resulted in hiring staff in a department that was just understaffed, given the increase in incoming items.

Stefan Wick — Universitätshospital Zürich, Switzerland

Stefan Wick from USZ in Switzerland presented two examples from the hospital setting. One case was a re-organization case: Nine hospital business units had to be reorganized into three new divisions. The goal was to group existing departments that work closely together in the same division, where possible. Stefan used process mining to analyze the relationship between clinics based on the sum of their interactions to ensure the correct placement.

At camp, Stefan showed in detail both the massaging of the data he had to do and the resulting views he could create in Disco. Overall, he had to split the data, duplicate records, sort events, split cases, and aggregate unit descriptions to the right granularity. He also encouraged the campers to use the recipe functionality to keep good track of their analyses.

Xhentilo Karaj — Euroclear, Belgium

Xhentilo Karaj from Euroclear in Belgium showed us step-by-step what the usage of process mining in an internal audit project looks like. He started with a checklist for the applicability of process mining in the Business Understanding phase. He then went through the Fieldwork, Clearance, and Reporting phases based on a concrete example.

In each phase, he looked at the challenges but also the opportunities that process mining brings compared to the classical audit approach. For example, traditionally, the analysis in the Fieldwork phase is based on samples and interviews. In contrast, process mining can be used to test the full population of data. In the Clearance phase, process mining changes the relationship with the auditee due to the fact-based observations.

Franck Diafouka, Ruth Zonanashvili & Mithra Gruber — European Medicines Agency

Franck Diafouka from the European Medicines Agency talked about capacity building as the process of strengthening organizations’ and people’s skills, abilities, and knowledge. Over time, they have moved from a centralized Centre of Excellence to a decentralized model, where process owners, internal auditors, and internal controllers all build up their own expertise and collaborate in an inter-group knowledge-sharing setting.

Franck also shared their experience from establishing a Working Group on Process Mining across different EU organizations and how they explore process mining for risk assessments. Mithra Gruber then connected the various stakeholders of process mining to challenges beyond technical aspects. For example, ethical considerations are essential to avoid staff discrimination by colleagues or management. Furthermore, data protection and privacy must be ensured to comply with EU DPR and other legislation.

Vanessa Schindler — T4media GmbH, Germany

Vanessa Schindler from T4media in Germany gave the last practice talk of the day. Vanessa’s job is to optimize and personalize websites for their customers, and she showed us what process mining adds to the toolbox of a customer journey analyst. Of course, she still uses web analytics tools like Google Analytics, but process mining helps her focus on the user’s actual behavior.

Technically, the data is available without any problems: The Case ID is the user on the website, the Activity is the pagename of the website, the Timestamp is the time of the visit of the site. What is difficult is the complexity of the user journeys: The data needs to be simplified to answer targeted questions. Vanessa demonstrated to us, based on several examples, how this works.

Discussion Workshop

In the afternoon, we dove into three parallel workshops. The first workshop was a discussion workshop, in which the participants talked about various challenges that emerge when process mining is applied in an audit. It was an extension of the discussion about the challenges that Mithra presented from the working group before.

Problem-solving Workshop

The second workshop put the campers in action to develop their own project plan. Based on a framework of identifying a process, the goals of the project, the stakeholders, and risks, a planning with deliverables for each phase was established.

Analysis Workshop

In the third workshop, we worked hands-on on several process mining analysis questions in Disco. We saw that even seemingly simple questions could become quite complicated once you try to make them concrete enough to answer with the process mining tool.

Meeting the Community

In addition to all the learning, practicing, and knowledge exchange, it was just lovely to see everyone again. Some of us could finally meet each other in person after interacting virtually for a long time. So, there were a lot of lively conversations in the breaks between the sessions.

At the end of the day, we could enjoy the beautiful summer weather in a relaxing atmosphere over our BBQ and drinks. Everyone was talking about process mining and everything else. It was the cherry on top of a really nice day before finally saying goodbye.

You can sign up at our camp mailing list here to receive the video recordings and slides of this year’s presentations.

We already look forward to next year’s camp. See you then!

So you can’t join us for Process Mining Camp tomorrow? That’s a shame, you are going to miss out on a great atmosphere, friendly conversation, collaborative workshops, and the famous campfire BBQ.

Lucky for you, though, we are going to try and provide a livestream¹, so you can at least watch the talks right from your home!

Tune in live for Process Mining Camp by visiting https://processminingcamp.com tomorrow, Wednesday, 21 June, around 10:00 CEST. The program will run until 18:00.

There is no registration required. Simply point your browser to https://processminingcamp.com when it is time.

See you tomorrow, in Eindhoven and all around the world!

The week of this year’s Process Mining Camp has come! On Wednesday, we will all get together in Eindhoven for the twelfth time. We started sharing the recordings from last year’s camp with you. Watch the talks of Machteld and Marianne from the Dutch Police, Sjoerd from AGCO Finance, Beth from CorVel, and Robin from VolkerWessels Telecom if you have not seen them yet.

The last speakers at Process Mining Camp 2022 were Maxime Parres-Albert and Maxime Brochier from GSK Biologicals in Belgium. Watch Maxime’s and Maxime’s talk to see how they improved the speed of the HBSM process for clinical trials of new vaccines using process mining.

Analyzing the Human Biological Sample Management process for clinical trials

In the clinical trial phase of a new medicine or vaccine, blood samples and other samples are collected from the people participating in the clinical trial. Overall, GSK manages millions of samples that go through hundreds of process steps in its Human Biological Sample Management (HBSM) process. It is vital to complete the HBSM process as quickly as possible while maintaining quality requirements.

Maxime Parres-Albert is a senior tech engineer, and Maxime Brochier is a business innovation lead at GSK. Using process mining on clinical operations data, they were able to improve the HBSM process and identify bottlenecks and best practices. For example, clinical test results can now be released faster. They also showed the complex data transformations that they had to perform to get the data in the right shape and shared their change management approach.

Process Mining Camp 2023 takes place on 21 June in Eindhoven and we have a fantastic program for you. This is your last chance if you have not signed up yet to get your ticket here!

We are happy to announce the release of Disco 3.5.

With the warm season turning into high gear here in Europe, we made sure that Disco is all water-proof, so that you can do all your process mining from the comfort of your favorite beach.

We gave Disco’s graph layout engine a proper update for a serious performance boost and lots of bug fixes, and we streamlined our Airlift client even more. In the Excel import, there were some bugs we didn’t care for, so we got rid of them.

If you are using Disco on macOS, this release greatly improves the way you can increase system memory, so you can mine even larger data sets without breaking a sweat. Plus, Disco will now alert you if you are running our Intel build on your brand new Apple silicon rig. Which is fine and all but, you know, this one goes up to eleven.

Thanks for all your ideas and bug reports, they keep the good times rolling. Keep it up and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• Process Map: Increased performance and stability of graph layout.
• Airlift:
  • Improved import reliability.
  • Improved performance and responsiveness.
• Excel Import: Improved handling of malformed cells during import.
• Control Center: Improved hardware detection.
• Connection:
  • Proxy settings auto-detection improved.
  • Improved stability and performance.
• macOS:
  • Setting the memory limit no longer breaks the installation.
  • Notify users running in Rosetta emulation.
• Platform: Java update

To get ready for Process Mining Camp on 21 June this year, we are sharing the recordings from last year’s camp with you. Watch the talks of Machteld and Marianne from the Dutch Police, Sjoerd from AGCO Finance, and Beth from CorVel if you have not seen them yet.

The fourth speaker at Process Mining Camp 2022 was Robin Schouten from VolkerWessels Telecom in the Netherlands. Watch Robin’s talk to see how he calculates the First Time Yield (FTY) for his quality measurement.

Making the business case with process mining and Lean Six Sigma

VolkerWessels Telecom designs, builds and maintains telecommunication networks. Quality and timeliness are essential when delivering these network services to their customers.

Robin is a Lean Six Sigma green belt. In his talk, Robin shows how Lean Six Sigma professionals can benefit from including process mining into their toolbox. He examines classical Lean Six Sigma tools next to their corresponding process mining analyses and shows how they supplement and complement each other.

He demonstrates how he calculates the First Time Yield (FTY) and uses the statistical tools of Lean Six Sigma to determine the statistical significance of the discovered bottlenecks. With the combination of both approaches, process mining and Lean Six Sigma, you can create a detailed business case for your improvement opportunities.

Process Mining Camp 2023 takes place on 21 June in Eindhoven and we have a fantastic program for you. Get your ticket here!

To prepare for Process Mining Camp on 21 June this year, we are sharing the recordings from last year’s camp with you. Watch the talks of Machteld and Marianne from the Dutch Police and Sjoerd from AGCO Finance if you have not seen them yet.

The third speaker at Process Mining Camp 2022 was Beth Borman from CorVel in the United States. Watch Beth’s talk to see how she adapted her analysis approach to the type of process.

Every process requires a tailor-made analysis approach

CorVel is a US provider of risk management solutions for the workers’ compensation, auto, health, and disability management industries. As a project manager, Beth identifies optimization opportunities based on the Theory of Constraints data analysis and process mining. While analyzing several processes, she noticed she could not take the same approach for every process.

For structured processes, the entire process can be analyzed at once. The analysis focuses on identifying bottlenecks, exceptions, and areas of automation. Unstructured processes, like their claims management process, must be analyzed from various angles. You need to be creative and explore smaller pieces or segments. The focus is on finding patterns and standardization opportunities.

Process Mining Camp 2023 takes place on 21 June in Eindhoven and we have a fantastic program for you. Get your ticket here!

To get ready for Process Mining Camp on 21 June this year, we are sharing the recordings from last year’s camp with you.

Sjoerd van der Zee from AGCO Finance was the second speaker at Process Mining Camp 2022. Watch his talk to see how answering one question tends to create new, additional questions.

Peeling the onion: How to move through multiple discovery and analysis cycles

AGCO Finance is a joint venture between the global financial solutions partner DLL and AGCO, an agricultural equipment manufacturer. Sjoerd is working in AGCO Finance’s operations function. He focuses on improving efficiency and service levels.

At first, Sjoerd was reluctant to do the process mining analysis himself. He is grateful that he did so because learning the process mining part is easy if you have the process and domain knowledge.

Process mining has given him a fresh perspective on the different paths and steps in his processes. However, he needed to apply his domain knowledge to iterate through discovery, questions, and analysis cycles. With every new iteration, you will get more of the necessary insights that enable you to take steps to improve your business.

Process Mining Camp 2023 takes place on 21 June in Eindhoven and we have a fantastic program for you. Get your ticket here!

While we are all waiting impatiently for the 12th Process Mining Camp on 21 June this year, we are starting to share the recordings from last year’s camp with you. Time to revisit those stories, refresh your memories, and savor the nice moments. We can’t wait to see you all again this year!

Machteld Oosterhof and Marianne Ravelli from the Politie were the first to take the stage at Process Mining Camp 2022. Watch their talk to see their journey of changing the organizational mindset from making decisions based on guesswork towards being guided by facts.

Making better decisions with process mining

The Police in the Netherlands are composed of ten regional operating units. The human resource (HR) department makes good police work possible by onboarding and supporting all officers and staff to fulfill their daily duty.

Machteld is a business operations specialist, and Marianne is a business controller at the HR shared services center. Traditionally, knowledge workers have been driving process improvements based on their personal expertise and gut feeling. However, most processes in the HR administration are now digitized. Therefore, the ambition is to move towards process improvements that are based on data. Machteld and Marianne share their experiences from three projects, where they showed facts and figures that sometimes confirmed and sometimes refuted assumptions.

Process Mining Camp 2023 takes place on 21 June in Eindhoven and we have a fantastic program for you. Get your ticket by 17 May to benefit from the Early Bird rate and secure your very own camp t-shirt!

In our next Process Mining Café this Wednesday, Rudi and I will go through the most common data challenges and what you can (or cannot) do about them. Join us!

Discuss data requirements and data preparation with us this week, Wednesday, 17 May, at 15:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 17 May, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

For every summer camp, there comes a time when you pull up your sleeves, grab a shovel, and do your part.

At Process Mining Camp, you won’t have to do the dishes, but you can become actively involved and contribute your own experience and perspective. One perfect place to do just that is in one of our three very distinct afternoon workshops:

• Our first workshop is a discussion workshop that continues after Franck, Ruth, and Mithra’s talk. You can share your experiences and discuss all aspects of process mining in audits and beyond, including ethics and professional standards.

• In our second workshop, you go into problem-solving mode. Based on our 12-step process mining project framework, you will work in small teams on developing the right project plan for different cases.

• Our third analysis workshop lets you dive into typical process mining analysis questions with hands-on practice. Bring your laptop! You will receive a training license from us if you don’t have a Disco license yet.

The workshops are running in parallel, so you can only join one. Choose the workshop you want to attend when selecting your camp ticket here.

Here are the full descriptions of the workshops at Process Mining Camp 2023.

Workshop 1: How can you use process mining for audits?

Process mining does not replace the traditional audit approach. However, it requires some changes and a conscious effort to fit process mining into the existing way of working. In some places, more work is needed. In other places, things get easier.

The goal of this discussion-based workshop is to share openly and learn from each other. You will talk about process mining in auditing and internal control. Discuss your approach, challenges, and questions with other auditors, compliance officers, and risk managers, and exchange your experiences to improve the efficiency and effectiveness of your internal control systems.

Franck Diafouka, Ruth Zonanashvili and Mithra Sophie Gruber enthusiastically work for the Internal Audit function at the European Medicines Agency and have established a Working Group on Process Mining across several EU bodies.

Workshop 2: How do you make a proper project plan for process mining?

Achieving your process mining goals requires a solid approach to getting things done. However, there is no one single cookbook for every process mining analysis. Each project could require a different approach to solve certain challenges or eliminate risks of failure.

In this workshop you will learn what the key deliverables are for a process mining project. Work out the best approach given particular technical or organizational conditions, and discuss what you could or should do when these conditions change. A practical and fun way to share experiences and learn the best practices.

Rudi Niks has been one of the first process mining practitioners. He has over ten years of experience in creating value with process mining. At Fluxicon, he ensures that Disco miners are the best process miners in the world.

Workshop 3: What questions can you answer with process mining?

When you start out with process mining, you often wind up in some kind of chicken-and-egg dilemma: You are supposed to start with questions about your process, but which kinds of questions can you actually answer with process mining?

We will give you 20 typical process mining questions as a starting point, and we will show you how to answer them. In this workshop, you will work hands-on with multiple data sets to understand the different approaches for measuring your process performance, analyzing compliance, and answering other process mining questions.

Anne Rozinat is the co-founder of Fluxicon and working with process mining every day. She has obtained her PhD Cum Laude in the process mining group at Eindhoven University of Technology, and she has given countless process mining trainings over the years.

Which one are you going to pick?

All three workshops are an excellent way to process what you have learned, and to set the next steps for your own process mining practice. You will come away with new insights and actionable knowledge that you can use immediately.

Don’t miss this year’s camp and register now — We look forward to having you!

The heart and soul of every Process Mining Camp are our practice talks. You will hear from other process miners like yourself, who share what they have been doing. Hear their stories, pick up some of their tricks, and avoid their mistakes in your own process mining projects.

At this year’s camp, on 21 June, you will hear inspiring practice talks from professionals who apply process mining for use cases from process improvement, over auditing, to customer journey analysis.

Get to know the speakers of Process Mining Camp 2023!

Eric N. Kildea, Radwell International (USA)

The processes at Radwell are not purely pieces of information. Instead, physical machines and spare parts are being sent from one place to another as Radwell stocks, sells, and repairs industrial automation, electronic, and electrical control equipment for plant floor and facility maintenance machinery. Eric analyzes these processes to help managers put data to their intuition for making the right decisions.

Eric Kildea is an International Project Manager at Radwell International. He is well-versed in Agile strategies and has successfully managed projects ranging from office relocations, corporate policy development, company rebranding, data mining, process optimization, mergers, and acquisitions to ERP (Enterprise Resource Planning) changeovers. Each project is unique and can be organized using the proper project management techniques.

Stefan Wick, Universitätshospital Zürich (Switzerland)

The University Hospital Zurich (USZ) is one of the biggest hospitals in Switzerland, and Stefan is a process manager in the business development team. He has used process mining for different projects, including a re-organization and optimizing admission and discharge times. The proper data wrangling was a crucial success factor for applying process mining to these healthcare processes. At camp, he will show concrete examples of some of the data transformations he had to do.

Stefan Wick has been a process manager at USZ for over 14 years. After his Master’s degree in Pharmacy almost 30 years ago, he worked at USZ in various areas, from the laboratory to the IT department and quality management. He now uses his experience and analytical skills to support customers and business units in their process improvement projects.

Xhentilo Karaj, Euroclear (Belgium)

Xhentilo will share the approach he has used for process mining in the internal audit at Euroclear. It starts with the identification of which processes are suitable for process mining. Xhentilo then takes us through the different phases of the audit. He shows the concrete challenges he has encountered in the data collection, the data pre-processing, and the data analysis phases of his audits in the past.

Xhentilo Karaj is Senior Data Analyst at Euroclear. As a data professional with 6+ years of experience working in the Information Technology and Financial Services industries, he enjoys working with information systems and data. Recently, he has been building data products focused on audit process automation and continuous auditing, in the quest of making the internal audit of Euroclear more data-driven.

Franck Diafouka, Ruth Zonanashvili & Mithra Gruber, European Medicines Agency (Netherlands)

Franck, Ruth, and Mithra enthusiastically work for the Internal Audit function at the European Medicines Agency based in Amsterdam since 2019. Beyond the use of process mining tools and techniques to support their auditing and risk assessment practices, they will present an interesting case on building process mining capacity within an EU Agency and across several EU bodies through the establishment of a Working Group on Process Mining.

Franck Diafouka is Head of Audit (ad interim) at the European Medicines Agency, which he joined in 2006. Franck is a certified lead auditor with a keen interest in data analytics and innovative thinking. He is one of the co-founders and current chair of the Working Group of Process Mining.

Ruth Zonanashvili is an Internal Audit Officer and Project Manager at the European Medicines Agency, which she joined in 2020. A key part of her role is to develop innovative approaches to implement data analytics in the Internal Audit Function’s core work, including process mining in audit and risk assessment. Ruth is one of the co-founders and current secretary of the Working Group on Process Mining.

Mithra Sophie Gruber is a trainee in the Internal Audit function at the European Medicines Agency, which she joined in 2022. Mithra has a background in molecular and microbiology, as well as quality management. She loves to experiment with creative and alternative approaches to find new solutions. She joined the Working Group for Process Mining earlier this year.

Vanessa Schindler, T4media GmbH (Germany)

Vanessa advises companies on designing, planning, and implementing digital analytics, conversion optimization, and data management. Process mining has become a great asset on top of classical web analytics to get a deeper understanding of the customer journey. At camp, she will show the advantages that process mining has over traditional website analysis tools based on concrete examples.

Vanessa Schindler currently serves as a Digital Analytics Consultant at T4media. In this role, she is responsible for the project management of website personalizations from business requirements to the go-live using A/B tests to validate success. Before this task, she was the project manager for a global tracking concept and rollout in +70 markets, including reporting, ad hoc analysis, and onsite and remote training.

Learn from your fellow process miners!

Whether you are new to process mining or you are a seasoned expert — it is essential to see concrete examples of what others have been doing. It is insightful, inspiring, and it might just give you the idea for your next project!

For any open questions that come up, you can clarify them in the Q&A. Even better, the speakers are here for camp like the rest of us, and they will be there for the whole day. So, you will have plenty of opportunities to talk to them, and to continue the discussion over coffee, lunch, or dinner.

Don’t miss the chance to connect with your peers and learn from their stories – Register for Process Mining Camp here now!

Process Mining Camp 2023 is coming to the TU/e campus in Eindhoven on Wednesday, 21 June — and you can reserve your seat now!

Come for a day full of inspiring practice talks from professionals who apply process mining for all kinds of use cases — from process improvement, over auditing, to customer journey analysis. After a refreshing lunch, join one of our workshops. Here you can dive into a process mining topic of your choice, in depth, together with a small group of fellow campers.

We are finally ready to share the detailed program for this year’s camp here, and we think you’re going to love it!

A lot of people who have come to their first camp tell me afterward: “That was really nice!” And I reply: “I know!” So, if you have been on the fence, wondering whether camp is the right place for you, or whether you’ll fit in – the answer is, most likely: Yes!

Process Mining Camp has always had a very special atmosphere, a certain vibe. Here is what, for me, sets camp apart – what makes it different from other events and conferences:

• Camp talks go deep. In their practice talks, our speakers show you what they have been doing, including tips and tricks, but also stumbles and mistakes. They are not peddling corporate success stories, but they want to share their personal, professional development. And, more often than not, you will find a lot to take home into your own practice.

• The speakers are one of us. They use process mining just as you do. They have often attended camp themselves in the past, and they are eager to share their story with all of you. And of course they’re here for camp like the rest of us, to learn from people like you.

• The attendees are all process mining professionals themselves. You can talk to anyone, and you can be sure to learn something. A discipline like process mining thrives on the lively, open, and friendly exchange between professionals. This is what camp is all about!

• You are in the arena. Join one of our workshops in the afternoon, and expand your practice hands-on. But also in the Q&A after talks, in the hallway, and in the lunch, dinner, and coffee breaks – you will find that camp is, most of all, the community meetup for process miners like you. It is all about sharing your ideas, questions, and experiences with other process miners.

Early bird tickets are available until 17 May, but don’t wait and secure your ticket right away! We have limited seats because we want people to have the chance to really get to know each other.

Food and drinks are included. With the return of last year’s popular BBQ at the end of the day, we will even have our own little campfire. You will leave, maybe a little tired, but certainly inspired, and with new friends in the community.

Don’t miss Process Mining Camp 2023 and sign up now. Whether you are a beginner, or you have been working with process mining for many years – I am sure you will go home with lots of relevant insights for your own work.

If you have any questions, don’t hesitate to let us know by email to camp@fluxicon.com, or however you prefer to get in touch.

We can’t wait to see you all in Eindhoven on 21 June!

In the latest Process Mining Café, Rudi and I got together with Jan van Moll and Muthuvelan Varadharajulu from Philips Healthcare for a very special episode.

We talked about their application of process mining to quality management processes. But on top of that, we also showed a concrete approach, in which Muthu and Jan have extended their process mining analyses with the so-called process capability index (Cpk).

The Cpk is a statistical measure that captures the ability of an engineering process to produce an output within specification limits. By doing that, it says something about the likelihood of meeting a target in the future based on the consistency of past values.

In the cafe, we showed based on a concrete process mining example how this works. And you can even try the approach yourself by using Muthu’s template (see links below) for your own analyses. Let us know how this works out for you via cafe@fluxicon.com or contact Muthu and Jan directly via LinkedIn or per email.

If you missed the live broadcast or want to re-watch the café, you can now watch the recording here. Thanks again to Jan and Muthu and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Download Muthu’s Excel template and the PPT documentation

• Explanation of the process capability index (Cpk) on Wikipedia

• Joris Keizers shows how Veco could improve further with process mining after they had reached a plateau with their Lean Six Sigma activities

• Our series on combining Lean Six Sigma and process mining (see also our Process Mining Café on the topic here)

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Have you already seen that the Process Mining Café is now also available as a podcast? So, if you prefer to listen to our episodes in your favorite podcast player, you can get them all here.

Sign up to our café mailing list, the YouTube playlist, follow Fluxicon on LinkedIn, or add the café calendar to never miss a Process Mining Café in the future.

It has been almost three years ago now that our Process Mining Café first went on air. Back then, it was our daily meetup during Process Mining Camp 2020, where we had the previous day’s speakers back on for a Q&A – it was a place to relax, kick back, and catch up with all the campers.

We decided to keep going with the café after camp, because it just worked so well. Compared to an annual event like camp, the café is much more lightweight for everybody involved, and it is free to explore the boundaries that would probably be too off-topic for camp. In short, it’s quality process mining time with interesting people, but you don’t need to put your life on hold to participate.

Today, by popular demand, we bring you an even more light-weight way to check into our café sessions. You can subscribe to the café audio feed, wherever you like to get your podcasts:

• Apple Podcasts
• Overcast
• Spotify
• Google Podcasts
• or directly from our RSS feed.

Podcasts are perfect for when you have some time, but you need your eyes elsewhere. So whether you want to spice up your workout or your commute, or you need a friendly companion for walking the dog or tending to your garden: The café podcast feed has you covered.

Thank you for checking back with us and being a regular in our little café – Good to have you, and see you again soon!

This is the 11th and last article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

Within this case study, we followed the 9-step model from Figure 3 to apply process mining in our audit. Throughout our journey, we experienced that the nine steps were not in a strict sequence. We frequently could use the things we learned in later phases of the project to improve deliverables from earlier steps. For example, we reworked our analysis questions multiple times as we gained new information regarding data availability and quality in later phases of the project.

Thus, the model has to be seen as an iterative approach where a rolling review contains validation steps on multiple levels. The image at the top shows the most important validation steps (click here to see a larger version).

First, we evaluated whether the data sets used as the input for the process mining analysis matched the raw data and the data from the productive system. Within this validation step, we ensured that we based our data analysis on a reliable data source.

Then, we validated the process itself by checking if the discovered model represents the process model defined in an earlier phase of the project. Within this step, we examined if we used the correct data or if there was any need to adapt the data model.

Next, we checked whether the analysis answers covered all the analysis questions. This way, we could check for any analysis question we had not answered yet, whether that was due to a lack of data or simply forgetting it.

Finally, we validated the results of the data analysis by checking if they met the requirements of the data analysis concept and if we had considered the primary audit objective sufficiently. With this evaluation, we could determine if the final analysis covered what we planned to audit.

All these validation steps helped us to get reliable results on a certain level of assurance and quality and improve the deliverables made throughout the process mining project.

Challenges and Limitations

Figure 17: Challenges and limitations

We encountered a number of challenges during our process mining project (see Figure 17).

Data preparation was one of the main challenges. As previously discussed, only for some process steps we wanted to consider was data available. Thus, we could not answer all the analysis questions we had in mind in the first place.

The available data was spread over different tables, which had to be linked to each other. 1:n and n:m relationships made data preparation more complicated, and we had to implement multiple versions of the data transformation workflow before it provided reliable and validated data we were confident in.

The lack of direct access to the productive systems made data validation even more time-consuming because there was a dependency on the audited party to provide the data for cross-checking. Furthermore, as we performed the audit during the covid-19-pandemic, only limited on-site visits were possible due to contact restrictions.

The high complexity of the analyzed process and the vast number of events in the data sets made the explorative analysis quite challenging. As a result, analysis questions No. 1 (“Do the real processes fit the should-process?“) and No. 12 („Are there any bottlenecks within the process?”) were hard to analyze. We had to simplify the data to reduce complexity to a level that made the process analyzable. Ultimately, it was impossible to state a definite percentage of how many cases did or did not fit the should-be process.

The 1:n and n:m relationships made it necessary to work with different data sets for different analysis questions. As a result, we made our process mining analyses from the order perspective as well as from the invoice perspective.

Despite the challenges and limitations listed above, the process mining analysis gave us an excellent insight into how the purchase-to-pay process was performed in reality. Thus, the benefits of using process mining in the audit (see Figure 18) did exceed the challenges we needed to overcome.

Benefits of using process mining in an audit

Figure 18: Benefits of using process mining in our audit

Within our audit work, we are often confronted with massive amounts of data and a high number of cases. As our resources are limited and we need to finish our audits within a specific timeframe, traditionally, we choose a sample of cases from the relevant process data and look at those cases in more detail.

Using process mining, we do not need to pick a sample anymore. Instead, we can analyze all cases regardless of the total number. For example, in the audit of this study, we could perform a complete examination of all 2,550 cases and give statements about order and invoice releases for all purchase orders from the year 2019.

We still used sampling techniques for a targeted investigation of those cases where we detected irregularities. This way, we allocate our resources more efficiently. From our experience, this led to a higher quality of the audit results and a higher assurance of detecting potential weaknesses in the internal control systems.

Furthermore, working with enormous amounts of data, it is often also hard to present the analysis results in a way everyone can follow. The graphical interface of the process mining software is very beneficial regarding this aspect. We could easily perform the analysis steps in attendance of the audited party to make transparent what we had done to come to the specific result. Of course, this benefit is even bigger when the audited party also has experience with process mining. In this case, they can retrace the analysis and measure if the changes they made due to the auditors’ recommendations have the expected impact.

Finally, using process mining to evaluate the effect of changes made to the process can also be very beneficial from the auditor’s perspective. If a follow-up audit is performed, process mining can be used once again to fully examine all cases and verify whether the implemented changes have improved the quality of the process.

As shown in this article, using process mining in an audit can be very beneficial and allows a deeper insight into the process of interest. Getting started with process mining in audit work is undoubtedly challenging, but it gets easier with more experience. We started using process mining in our audits in 2016 and have worked on improving our practice ever since. Every process mining project has been a new chance to improve our approach and make the audit trail more transparent.

With this article, we want to encourage other auditors to learn more about process mining and incorporate it into their audit method. We value exchanges with our peers and invite you to contact us to discuss your experiences with us via the contact details below.

Authors

Jasmine Handler, MA MSc - jasmine.handler@wien.gv.at (corresponding author)


Ing. Dipl.Ing.(FH) Andreas Preslmayr, MSc - andreas.preslmayr@wien.gv.at

You can also download the whole article as a PDF here for easier printing or sharing with others.

This is the 10th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

The data analysis results summarized the answers to the analysis questions and were the basis for our audit report, including the findings and recommendations.

Figure 16 shows that we could answer all our questions. Only questions No. 1 and No. 12 could not completely be answered because on the one hand we had some blind spots in the process due to a lack of data and on the other hand we had to simplify the process considerably to deal with its complexity. Therefore, we set their status to yellow.

Figure 16: All our analysis questions could be answered

Within the explorative analysis, we discovered that in 2019 approximately 1% of all orders were canceled. In addition, for 1.4% of all cases, an order was placed in the information system, but no further activities were recorded. These cases appeared to be canceled as well, but the cancellation was not documented in the information system. While the total percentage of canceled orders was in a normal range, we identified a potential for improvement regarding the documentation of canceled cases.

Furthermore, we found that ca. 7% of all cases started with an invoice recording (the corresponding order was only placed later). These cases indicated that the formal procurement process was not always observed. Instead, some employees made purchases without prior authorization, an undesirable behavior called ‘Maverick Buying.’

Within the targeted analysis, we had realized that 17% of all invoiced orders were not released. However, this irregularity was tolerable because they all belonged to the product group office supplies, which did not require an order release activity.

The procurement guidelines of the audited party also required that all orders with an order value of more than 20,000 EUR had to be released following the four-eyes-principle. Our analysis showed that, except for one case, the four-eyes-principle was observed whenever the order value of 20,000 EUR was exceeded. In this one case, a two-staged release was documented in the information system, but one person was not entitled to release an order of this value. This deviation from the defined release process indicated that there might be a weakness in the internal control system. Therefore, we recommended that the release permissions should be evaluated on a regular basis.

Regarding invoice processing, the procurement guidelines demanded that all invoices be checked before payment. Our process mining analysis showed that these checks were not consistently documented in the information system. Thus, it was not transparent if the necessary checks were performed before payment.

In addition, a four-eyes-principle was mandatory during invoice release whenever the invoiced sum deviated more than 10% or 1,000 EUR from the order value. In individual cases, this four-eyes-principle was not followed. Therefore, we recommended that further control measures needed to be implemented to ensure that all invoices were checked properly before they were released for the final payment.

Furthermore, our process mining analysis showed that approximately half of all invoices were immediately due for payment, although the general payment target was set to 30 days after receiving an invoice. Thus, there was potential improvement regarding the documentation of payment targets.

Finally, the payment target was not observed in approximately 6% of all cases. The audited party reasoned that, in some cases, there was still a need for clarification regarding the incoming goods or the conformance of performance when an invoice was due for payment. Further investigations also showed that when the payment targets were not met, there often had been a delay in releasing the invoice for the final payment. We recommended monitoring the observance of payment targets and implementing measures to reduce waiting times if needed.

Read the next article here.

We are happy to announce the release of Disco 3.4.

This release has an all-new PDF export, so your process maps will not only look a bit nicer, but they will also export faster. We also fixed a number of bugs and annoyances, and sanded the edges all around, particularly in the Excel import and Airlift client.

Thanks for sending us your ideas and bug reports. Keep it up and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• Process Map: Improved quality and stability of PDF export.
• Excel Import:
  • Improved XSLX import.
  • Fixed a bug with empty sheets.
• Airlift: Improved import reliability and performance.
• Control Center: Improved hardware detection.
• Connection:
  • Proxy settings auto-detection improved.
  • Improved stability and performance.
• Platform: Java update

This is the 9th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

To answer our analysis questions from Table 1, we used both an explorative and targeted analysis.

During the explorative analysis, we investigated the discovered models looking for unexpected or strange process paths, long waiting times, and other abnormalities in a broader way. With this type of analysis, we were able to address questions No. 1 (“Do the real processes fit the should-process?”) and No. 12 (“Are there any bottlenecks within the process?”).

Questions No. 2 to 11 were answered through a targeted analysis. We translated each analysis question into a customized set of filters based on the definitions we had created in the ‘Analysis questions’ step. Although we had already defined the analysis questions in some detail, we further refined these specifications to ensure we only detected cases that violated the process requirements.

For example, the goal of question No. 2 (“Are all orders released?”) was to find out whether there were cases with a missing order release. The target value for this analysis was 100%. However, there could be legitimate reasons why an order release could be missing. We concluded that only orders that were executed needed a release activity. Furthermore, there might be orders that were never carried out. Thus, we decided to exclude canceled cases from the data basis for this question.

So, we used a combination of three different filters to answer question No. 2 (“Are all orders released?”). First, we excluded all orders that were canceled, which in our data set meant removing cases with the attribute value L or X in the attribute “Löschkennzeichen” (see Figure 13).

Figure 13: Excluding canceled orders

Second, finding out whether an order was really executed was not easy. We had no data that indicated when an order form was sent to the supplier. There was also no data that showed when the contract was locked or when the incoming goods were checked. Therefore, we chose the invoice as a means to measure if an order was actually performed. Figure 14 shows the second filter that includes only orders with an invoice (“Eingangsrechnung erfassen” in German).

Figure 14: Including only orders with an invoice

Third, because we wanted to find violations of question No. 2, we excluded all orders with an order release activity. So, we searched for the opposite of the required behavior in the process. Figure 15 shows this third filter that excludes all cases that contain any of the selected order release activities (“PO - Dokument freigegeben. Stufe 001” - “… 003”).

Figure 15: Excluding orders with an order release activity

As a result of applying these three filters, we found that 17% of all non-canceled cases lacked an order release, although an invoice was recorded. Looking at those cases in more detail, we discovered that all orders referred to the goods group of office supply. The audited party explained that office supplies did not need to go through the regular order release workflow and could be ordered without a prior order release. Thus, these orders also complied with the procurement guidelines despite the irregularities we discovered.

Similar to the example above, we answered each of the remaining analysis questions by translating them into customized filter settings. In addition, we discussed all the discovered irregularities with the audited party to determine whether there was a genuine reason for the deviation or whether we had found a compliance violation within the process.

Read the next article here.

Rudi and I look forward to welcoming Muthuvelan Varadharajulu and Jan van Moll from Philips Healthcare to the upcoming Process Mining Café this Wednesday. Join us!

Every large company has a quality management system (QMS) that helps coordinate the processes to meet customer and regulatory requirements. Jan is the Head of Quality Assurance, and Muthu is a Master Black Belt and Senior Quality Manager. Together, they use process mining to gain more visibility into the actual processes than they would have with traditional KPIs.

In addition, Muthu and Jan leverage their statistical background to extend their process mining results with a statistical analysis of the capability of the process to meet a specific target. In the café, we will demonstrate their approach based on a concrete example.

Discuss measures and targets with us this week, Wednesday, 29 March, at 15:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 29 March, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it.

Process Mining Camp takes place again for the 12th time on Wednesday, 21 June, on the TU/e campus in Eindhoven!

Process Mining Camp is not your run-of-the-mill commercial conference but a community meet-up with a unique flair. It’s the one time of the year when you can meet other process miners from all over the world, working in all kind of industries.

Get down and compare notes with your fellow process miners and learn how they do their job, and what they have come up with. Exchange your experiences, share best practices, get new inspiration and fresh ideas, and make new friends along the way.

Process Mining Camp is a day full of inspiring practice talks from companies who use process mining for various use cases — from auditing, over process improvement, to customer journey analyses.

In the afternoon, join one of our hands-on workshops. Here you can dive into a process mining topic of your choice, in depth, together with a small group of fellow campers.

Just like the previous eleven editions, this year’s camp is all about you, the professionals who are using process mining. Having a process mining tool is not enough on its own. You also need the knowledge and experience to apply process mining efficiently, interpret the results, and act on the insights. Learning from your fellow process miners is the best way to build those skills. Plus, it’s just great fun!

So, block 21 June 2023 in your agenda and start making your plans.

Do you need a visa to visit the Netherlands? We can provide you with an invitation letter for the embassy. Do you want to combine the trip with some sightseeing? Most international flights arrive via Amsterdam’s Schiphol airport, a direct 80-minute train connection from Eindhoven¹. If you have any questions, don’t hesitate to get in touch with us via camp@fluxicon.com.

Click here to sign up for the camp mailing list, and we will let you know when tickets go on sale. And, even if you cannot make it to camp this year, you should still sign up, so we can send you the presentations and video recordings later.

We can’t wait to meet you all again in Eindhoven! See you on 21 June, everyone!

This is the 8th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

Once we had access to our transformed data sets, we loaded the data into the process mining software Disco and got a first impression of the complexity of the process.

Although we had worked with simplification methods from the beginning and focused on the activities from the high-level reference process to identify relevant data tables, the process map was still very complex. Figure 10 shows the discovered process model from an order perspective.

Figure 10: Discovered process model

Due to the high complexity, we applied further simplification strategies to enable an explorative analysis and a should-be comparison of the real process paths and the reference process.

Firstly, by including most of the timestamp fields that we could find, we had derived a high number of activities from the raw data files. Among these activities were administrative process steps that were outside our reference process. We reduced the number of activities by only keeping those process steps that we could directly map to the high-level reference process (Milestone simplification method). This reduced the number of activities from more than 100 to approximately 50. Note that the data in the IT system was still more detailed than the high-level process. For example, a purchase order could be checked, rejected, and released on different levels (see Figure 11).

Figure 11: Mapping data to the high-level process

Secondly, there was still a high variation regarding the process paths. Therefore, we decided to cluster the data into four groups (Semantic variant simplification method). These four groups were:

1. canceled cases,

2. cases without an invoice,

3. cases with one invoice, and

4. cases with multiple invoices.

By looking at each data segment separately, the number of process variants was further reduced.

Finally, we also decided to focus on the most common process paths to get an overview of the mainstream behavior (Variant simplification method). Figure 12 shows the discovered model based on only the ten most frequent process variants. This helped us to get an overview of the main process before going into detail and analyzing the less frequent paths and how they deviate from mainstream behavior.

Figure 12: Discovered model after simplification

Due to the complexity reduction, we could now perform an explorative analysis, searching for inconsistencies and analyzing unexpected process paths in more detail.

Read the next article here.

In the latest Process Mining Café, we invited prof. Magy Seif El-Nasr to talk about data analytics for games.

Magy gave an overview of the different types of games and traditional game analytics. Recently, her research group at the department of Computational Media at UC Santa Cruz has used process mining to understand the usage flows of educational games, the strategies people use to solve puzzle games, and sentiment flows in teamwork games. We talked about the ethics of using game analytics to make games more addictive and discussed the challenges of abstracting the data to the right level.

If you missed the live broadcast or want to re-watch the café, you can now watch the recording here. Thanks again to Magy and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Magy’s first book is a collection of edited papers focusing on the data collected and analyzed by video game vendors to improve the game player experience: Game Analytics. Maximizing the Value of Player Data, Editors: Magy Seif El-Nasr, Anders Drachen, Alessandro Canossa. Springer, 2013.

• Magy’s second book is a textbook on game analytics. Game Data Science by Magy Seif El-Nasr, Truong-Huy D. Nguyen, Alessandro Canossa, and Anders Drachen. Oxford University Press, 2021.

• Video of the parallel game

• A Data-Driven Design of AR Alternate Reality Games to Measure Resilience is the paper written by Reza Habibi et. al about their analysis of the alternate reality game LUX (see Example No. 3 in the café)

• Finding the right level of abstraction in soccer and robot soccer

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

This is the 7th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

The data transformation workflow generated a data set we could use for our process mining analysis. According to the data, between 01 January 2019 and 31 December 2019, a total of 2,550 orders with an order value of approximately 21 Mio. EUR were processed.

Initially, we had chosen the order number as our case ID. Therefore, all cases were analyzed from an order perspective (see Figure 8).

Figure 8: Order perspective (data set left, process view right)

However, during the analysis, it became clear that due to the 1:n relationship between orders and invoices, we could not answer all our analysis questions regarding invoice processing with this data set. For example, in Figure 8, one can see that two invoices (invoice 1230007 and invoice 1230008) are associated with order 1030071289-10. There are two events for activity “Check invoice” and “Make payment” (one for each invoice). This complicates answering questions such as analysis question No. 7 (“Have all invoices been checked before payment?”).

Therefore, we decided to generate a second data set focused on the invoice perspective. This was achieved by combining the order and invoice numbers into a new case ID. The scope of this second data set is smaller (invoicing and payment only). The benefit is that the activities related to invoice 1230007 and the activities related to invoice 1230008 now appear in their own case and can be analyzed separately (see Figure 9).

Figure 9: Invoice perspective (data set left, process view right)

Based on these two data sets – one from an order perspective and one from an invoicing perspective – we could now start answering our analysis questions.

Read the next article here.

This is the 6th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

The goal of the next step was to bring the raw data in a format that we could load into the process mining software. We filtered the relevant information from the raw data files and linked the data tables based on the prior defined connections. The output data was formatted as an event log, with a unique ID as case ID, activity names, timestamps, resources, and attributes for each event.

We performed the data transformation using the open-source software KNIME. To validate the transformed data, we performed crosschecking with the productive system whenever we implemented changes in the data transformation workflow. These validation steps showed quite some potential for improvement, and we adapted the workflow several times until the output data finally represented the data from the productive system (see Figure 7 below).

Figure 7: The first (left) and last (right) data transformation workflow version

The data transformation was the most time-consuming step within the process mining project. One of the factors was that we had no direct access to the productive system. Therefore, the audited party had to support the data validation process and help with crosschecking. This led to waiting times and delays within the project.

Another factor was that we initially had not appropriately considered the 1:n and n:m relationships when tracing the case IDs. For example, one order can lead to several invoices and payments. Furthermore, one invoice can address multiple orders. One payment can cover more than one invoice, and so on. These many-to-many relationships had to be adequately handled during data transformation.

After several adaptions to the transformation workflow, we passed all the validation steps and generated a data set we were confident working with.

Read the next article here.

In a new research spotlight, we have invited Magy Seif El-Nasr, professor and department chair of Computational Media at UC Santa Cruz, to tell us how they use process mining for game analytics.

Games are a broad field that includes entertainment, serious games, and esports (electronic sports). We will talk about different types of games and the current trends in data analytics in the upcoming Process Mining Café this Wednesday. Join us!

The café takes place this week, Wednesday, 1 March, at 16:00 CET (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 1 March, at 16:00 CET! Add the time to your calendar if you don’t want to miss it.

This is the 5th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

The data for our process mining analysis was stored in two different systems: SAP and the WMD xSuite feeder. We had identified the data tables that needed to be extracted from these systems when we specified the data model. We had no direct access to the Wiener Stadtwerke’s information systems. Thus, the audited party extracted the data tables for us and provided the raw data in CSV files.

From the data model, we already knew in which tables the timestamps for each activity were located. For example, we knew that the timestamp for ‘Create purchase request’ could be found in the EBAN table. The timestamp for the ‘Release purchase request’ activity could be found in the WMD table, and so on. However, because the raw data was distributed across multiple CSV files, we also needed to find the connections between the individual data tables so that we could merge the files into one (see Figure 6 for the connections between the tables - click on the image to see a larger version).

Figure 6: Raw data with connections between the tables

For each table, we identified which information could be used as a timestamp for an activity, resources, and other activity- or case-related attributes.

Based on the knowledge of the relevant data fields for the activity timestamps, attributes, and resources, and with this understanding of the connections between the raw data tables, we now had the basis for building our event log.

Read the next article here.

This is the 4th article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

Looking at the purchase-to-pay process in more detail, it was clear that it was pretty complex. We had received a detailed process description from the audited party and decided to simplify the process and look at it from an aggregated perspective to handle the complexity. The high-level reference process we defined included only those steps that were essential to finding answers to the analysis questions described in the previous step.

We expected considerable amounts of data to be generated for this process in the information system. Based on the high-level reference process, we tried to identify the essential data fields populated while performing the process.

The purchase-to-pay process was mainly executed using SAP. For each process step, we looked for the corresponding database table and enriched the process model with this information. For example, the data for ‘Create purchase request’ could be located in the EBAN table in SAP (see Figure 5).

Figure 5: Process and data model

While creating the process and data model, we realized that not all the steps from the high-level reference process were done in SAP. For example, we detected that the approval and release workflows were performed with an SAP add-on called WMD xSuite feeder. As the approval and release steps were essential for the compliance audit, we included these data tables in the data model and the later data extraction.

Other steps like getting an offer, locking a contract, sending the order form to the supplier, and checking the incoming goods were neither performed in SAP nor with the WMD xSuite feeder. These steps (colored in grey in Figure 5) were performed manually or via E-Mail. Due to a lack of data availability, we excluded these steps from our process mining analysis.

After defining the process and data model, we had quite a good overview of the available data and where we could find the data. Thus in the next step, we extracted the raw data for further processing.

Read the next article here.

As a companion to our new series on process mining in audit, we invited the authors of the article, Jasmine Handler and Andreas Preslmayr from the City of Vienna, to our latest Process Mining Café.

Jasmine and Andreas walked us through the different phases of a typical audit project. In this deep-dive, they explained how process mining changes the traditional approach for each stage: Does this step get easier? Will it require more work? And is this step only there because of process mining, or would they have done it anyway?

If you missed the live broadcast or want to re-watch the café, you can now watch the recording here. Thanks again to Jasmine, Andreas, and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Article Auditing with Process Mining

• Assessing whether your data is suitable for process mining

• How difficult is it to get data for process mining?

• Mieke Jans’ Process Mining Camp 2015 presentation about extracting process mining data from SAP

• Process Mining Café about auditing at Process Mining Camp 2021 with Mieke, Jasmine, and Andreas

• Process Mining Camp 2013 presentation by Youri Soons from the Central Auditing Service in the Netherlands

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

This is the 3rd article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

We defined the following 12 analysis questions (see Table 1). As shown in Table 1, most of the questions are related to compliance issues (our primary audit objective), only two are related to performance questions, and none are about user experience.

Table 1: Analysis questions

Besides formulating the general analysis questions, we also tried to define them as precisely as possible and make them measurable. Thus, we specified the metric, target value, process scope of interest, and influencing factors for each analysis question. Table 2 shows how we made analysis question No. 2 more concrete by defining these aspects.

Table 2: Analysis question No. 2 in more detail

When we want to answer the question “Are all orders released?” it seems straightforward initially, but it is a good idea to think further about how exactly we can measure the answer to this question. We expected that order releases would be registered within the information system. So, we chose the presence of the release activity as a metric. In addition, we assumed that all orders must be released without exception. So, we set the target value to 100%, which means that a release activity needs to be documented for each order.

Then, we defined the process scope to show which part of the purchase-to-pay process is relevant to find the information needed to answer the analysis question. For question No. 2, the process scope comprised all activities related to the release step in the information system.

Finally, we also collected the influencing factors we needed to consider while performing the data analysis and interpreting the results. Regarding the order release, we assumed that a four-eye principle might be relevant above a specific value limit. Thus we defined the value limit as an influencing factor that needed to be kept in mind for later analysis.

We specified detailed definitions for all analysis questions in a similar manner as shown for question No. 2 above.

Because we defined the analysis questions at a very early stage of the process mining project, we needed to make certain assumptions, especially regarding the metric and the influencing factors. We adapted these analysis questions multiple times in later phases of the project because we kept gaining more insight into the process and the data.

Nevertheless, defining the analysis questions at this early stage of the project was very useful. It helped us to get a good overview of the data we needed. As a result, we could reduce the risk of forgetting certain aspects or data fields during data extraction.

Read the next article here.

This is the 2nd article in our case study series on auditing with process mining. The series is written by Jasmine Handler and Andreas Preslmayr from the City of Vienna. You can find an overview of all the articles in the series here.

The City of Vienna Court of Audit follows a risk-based audit selection procedure. Therefore, the audit was already defined within the annual audit planning. The ‘Data analysis concept’ determines the audit scope in further detail. It gives an overview of the audited party, the process of interest, the IT framework, and the main audit objective.

The audited party - Wiener Stadtwerke - is one of Austria’s most significant infrastructure groups with about 15.000 employees. Its business activities can be categorized as follows:

• Energy (electricity, gas, heating, cooling)
  • Generation
  • Distribution
  • Grid operation
• Public transport (subway, tram, bus)
  • Traffic management and planning
  • Operation
  • Marketing
  • Distribution
• Funeral
  • Cemeteries
  • Cemetery nursery
  • Stonemasonry
• Car Parks

The total assets of Wiener Stadtwerke amounted to approximately Euro 13,900 million on 31 December 2020. The Wiener Stadtwerke Group was 100% owned by the City of Vienna.

We defined the process of interest in more detail by describing the general process scope. As we planned to audit the purchase-to-pay process, we delimited this process as depicted in Figure 4. The audited process scope comprised procurement and invoice processing, beginning with the demand report and ending with the payment of the corresponding invoice.

Figure 4: Purchase-to-pay process

This general process scope was used later as a reference point for further investigations and gave a first impression of the start and the end points of the process of interest.

The timeframe for the audit was determined to be the year 2019. More precisely, we considered all orders that were sent between 01 January 2019 and 31 December 2019.

We investigated the IT infrastructure of the City of Vienna Court of Audit and the audited party to get an idea about which type of data and which tools would be available to process and analyze this data.

From our preliminary research, we knew that the audited party used SAP to administrate the purchase-to-pay process. We expected that we would need to transform the data after we exported it from SAP. As an ETL tool to do these transformations, we chose the KNIME Analytics Platform because we already used this software for data transformations in earlier process mining projects and achieved good results.

The primary audit objective was to perform a compliance audit. We wanted to analyze the Wiener Stadtwerke’s purchase-to-pay process concerning its regularity and compliance with organization-specific framework conditions.

Due to this main audit objective, we planned to address aspects like the completeness of the process, segregation of duties, adherence to the four-eyes-principle, and the effectiveness of the internal control system. In addition, we wanted to consider the lead time and the occurrence of bottlenecks from a performance perspective. User experience questions were outside the scope of this audit.

After defining the general framework and the primary audit objective, it was time to specify the focus areas of the audit in more detail. So, in the next step, we identified the concrete analysis questions we wanted to answer within our process mining analysis.

Read the next article here.

To kick off our new series on process mining in audit, we have invited the authors of the article, Jasmine Handler and Andreas Preslmayr from the City of Vienna to the upcoming Process Mining Café this Wednesday. Join us!

Process mining does not replace the traditional audit approach. However, it requires some changes and a conscious effort to fit process mining into the existing way of working. In some places, more work is needed. In other places, things get easier. Together with Jasmine and Andreas, we will talk about their data-driven audit approach with process mining step by step.

Discuss with us about the changes to the regular audit process and the benefits and challenges this week, Wednesday, 1 February, at 15:00 CET! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Sign up for the café mailing list here to receive a reminder and the PDF version of the full article one hour before the session starts.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 1 February, at 15:00 CET! Add the time to your calendar if you don’t want to miss it.

This is a guest article by Jasmine Handler and Andreas Preslmayr from the City of Vienna. They previously presented their case study at the Process Mining Camp here. Now, they have written up their experience to help others learn from it even more. If you have a guest article or process mining case study that you would like to share, please get in touch with us via anne@fluxicon.com.

Auditors have a clearly defined process in which they carry out an audit. Process mining does not replace this traditional audit approach. However, it requires some changes and a conscious effort to fit process mining into the existing way of working. In some places, more work is needed. In other places, things get easier. In this article, we describe in detail how process mining fits into the different phases of the audit cycle based on a concrete project. We describe the changes that needed to be made to the audit process and the benefits and challenges.

City of Vienna Court of Audit

The City of Vienna Court of Audit is an autonomous and independent public audit institution. It audits the institutions and entities in the City of Vienna concerning their financial management and safety. And it supports those in positions of responsibility in politics and administration with audit reports and recommendations.

In the framework of its audit work, the City of Vienna Court of Audit reviews the use of Vienna’s public funds. It also monitors compliance with safety regulations to protect the citizens of Vienna and its visitors.

However, the resources to perform these tasks are limited. To set audit priorities, the City of Vienna Court of Audit follows a selection procedure for audits in the form of a risk analysis.

For the selected audits, the City of Vienna Court of Audit team then uses different audit procedures depending on the audit. Process mining has been used as an audit method in several audits since 2016. In 2020, the purchase-to-pay process of the Wiener Stadtwerke, one of Austria’s largest infrastructure groups, was analyzed.

Using the example of the Wiener Stadtwerke, this article shows in detail how process mining was applied to perform a data-driven audit. The results of this audit are publicly available in the audit report here. The following article focuses on the method of process mining in the context of an audit. It describes in detail how process mining was leveraged in the different audit phases and the challenges and benefits we experienced.

Data driven audit approach with process mining

Internationally accepted audit standards guide the audit work of the City of Vienna Court of Audit. At the same time, it is the goal to further improve the existing standards in cooperation with national and international audit institutions while engaging in the exchange of experiences. Audits are carried out according to the standardized audit process (see Figure 1).

Figure 1: Overall audit process

Each step of the process depicted above contains several tasks. Figure 2 shows the tasks related to the step ‘Conducting the audit’: First, an audit concept is created. Then, the data is collected. This data is then used to perform a situational and deviation analysis, from which the audit results and recommendations are derived. In addition, the audit trail and evidence are documented, and the audit file is generated.

Figure 2: Conducting the audit

We must adapt our working method when we use process mining in our general audit approach. Especially the way of collecting and analyzing data changes within the audit process compared to other audit methods.

To include process mining into the ’Collection of data’ and ‘Situational and deviation analysis’ phases, we followed the nine steps shown in Figure 3.

Figure 3: Data driven audit approach with process mining

Following this model helped us a lot to standardize our approach when using process mining in an audit. It summarizes the essential deliverables for collecting the data and performing the situational and deviation analysis.

In the following sections, we explain each step and each deliverable of the model depicted in Figure 3 in more detail.

• Step 1 - Data analysis concept
• Step 2 - Analysis questions
• Step 3 - Process and data model
• Step 4 - Raw data
• Step 5 - Data transformation
• Step 6 - Data sets
• Step 7 - Discovered model
• Step 8 - Analysis answers
• Step 9 - Data analysis results
• Challenges and benefits

You like this case study and are enthusiastic about process mining? Share the article with your friends and colleagues! You can point them to this page for the web version or download the whole article as a PDF here.

We also recommend to watch this companion Process Mining Café, where Jasmine and Andreas walk us through the nine steps and explain how process mining changes the traditional audit approach in each phase.

How exactly do people analyze their data during the explorative and targeted analysis phases of a process mining project? This is the topic of a whole sub field in the process mining research area.

In our latest Process Mining Café, we spoke with Pnina Soffer from Haifa University and Barbara Weber and Francesca Zerbato from the University of St. Gallen about the process of process mining.

Researchers approach the topic from two different angles: (1) A top-down approach guided by cognitive psychology and (2) a bottom-up approach based on behavioral discovery (process mining!). For both approaches, the researchers collect detailed data sets in user test labs that capture the analysts’ behavior in multiple dimensions: Think aloud data, application logs, screen recordings, interview data, and even eye tracking data. In the café, we looked at two of these data sets to see what you can learn from them.

If you missed the live broadcast or want to re-watch the café, you can now watch the recording here. Thanks again to Pnina, Francesca, Barbara, and all of you for joining us!

Links

Here are the links to the papers that we mentioned during the session¹:

• Zerbato, F., Soffer, P., Weber, B. (2021). Initial Insights into Exploratory Process Mining Practices. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds) Business Process Management Forum. BPM 2021. LNBIP, vol 427. Springer, Cham.

• Zimmermann, L., Zerbato, F., Weber, B. (2022). Process Mining Challenges Perceived by Analysts: An Interview Study. In: Augusto, A., Gill, A., Bork, D., Nurcan, S., Reinhartz-Berger, I., Schmidt, R. (eds) Enterprise, Business-Process and Information Systems Modeling. BPMDS EMMSAD 2022 2022. LNBIP, vol 450. Springer, Cham.

• Zerbato, F., Soffer, P., Weber, B. (2022). Process Mining Practices: Evidence from Interviews. In: Di Ciccio, C., Dijkman, R., del Río Ortega, A., Rinderle-Ma, S. (eds) Business Process Management. BPM 2022. LNCS, vol 13420. Springer, Cham.

• Zerbato, F., Koorn, J.J., Beerepot, I., Reijers, H., Weber, B. (2022). On the Origins of Questions in Process Mining Projects. In: Almeida, J.P.A., Karastoyanova, D., Guizzardi, G., Montali, M., Maggi, F.M., Fonseca, C.M. (eds) Enterprise Design, Operations, and Computing. EDOC 2022. Lecture Notes in Computer Science, vol 13585. Springer, Cham.

• ProMiSE project: Process Mining Support for End-users (Grant number: 197032).

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

We are happy to announce the release of Disco 3.3.

This update fixes a number of issues and annoyances that we have discovered, and that you have reported, since the last 3.2 release. If you are affected by any of these isolated issues, you probably already know.

While we were at it, we put on the winter tires and topped up the oil, to get us ready for the cold season. So you get the latest security fixes and performance improvements all around. And of course we thoroughly dusted the corners and polished the UI some, so this baby’s ready to drive!

All this comes fuelled, as per usual, by your ideas and bug reports. Keep us posted and, as always, thank you for using Disco!

How to update

We recommend that you update to the latest version of Disco at your earliest convenience. Disco will automatically download and install this update the next time you run it, if you are connected to the internet¹.

If you prefer to install this update of Disco manually, you can download and run the latest installer packages from fluxicon.com/disco/download

Changes

• CSV Import:
  • Fixed an issue where import errors could point to one-off line numbers.
  • Prioritize high-severity issues in import problem feedback.
  • Improved description of import problems.
• Excel Import:
  • Improved XLSX import.
  • Improved performance and stability.
• Process Map:
  • Fixed an isolated issue with graph layout on the Apple M1/2 platform.
  • Improved performance and stability of graph layout.
• Airlift: Improved import performance and stability.
• Control Center: Fixed an issue where disk benchmark could fail.
• UI: Improved interface fidelity for fractional HiDPI displays on Windows.
• Connection: Improved stability and performance.
• Platform: Java update

Join us for an all-new Process Mining Café this week Thursday!

Each process mining project consists of many different steps, from project selection over data preparation to the analysis and control phases. But if we just look at the analysis phase: How exactly are people performing their analyses? Are they first exploring or immediately answering questions? And how do they deal with new questions that come up in the process?

Together with Pnina Soffer from Haifa University and Barbara Weber and Francesca Zerbato from the University of St. Gallen, we will look deeper into the analysis phase of a process mining project than usual.

Discuss with us the process of process mining this week, Thursday, 20 October, at 15:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Thursday, 20 October, at 15:00 CEST! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you like us to remind you one hour before the session.

As Niels pointed out, analyzing faulty data cannot only have unpleasant effects like losing the trust of the process manager. In application areas like healthcare, it can have serious consequences that put people at risk.

In our latest Process Mining Café, we spoke with Kanika Goel from Queensland University of Technology and Niels Martin from Hasselt University about data quality. If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

First, we discussed why general data quality frameworks like the DAMA dimensions are insufficient when we talk about data quality in process mining: Process mining data has temporal relations as multiple events are linked to a case and ordered in time. This is why there are specific categorizations of data quality problems for process mining in the literature (see links below).

We then discussed several practical data quality examples and current research approaches along the four phases of dealing with data quality problems:

1. Detection. Checklists like our data quality checklist (click on the image below to see the complete checklist) help to detect problems in your data set.

   

   Furthermore, Kanika and Niels discussed research approaches that support automated and domain knowledge-assisted data quality checks.

2. Cleaning. After finding and investigating the data quality problems, the data needs to be corrected. You can often do this cleaning step with the process mining tool (see the checklist above for examples). But sometimes, you must go back to the source data to fix it.

   Kanika told us about a research project that repairs activity labels with a gamification and crowdsourcing approach.

3. Analyzing the cleaned data. Before you analyze the cleaned data, make sure to check whether the data is still representative! For example, if you had to remove 90% of the cases due to data quality problems, you cannot assume that the remaining 10% represent the entire process. It is also a good idea to create a new baseline for the cleaned data as the basis for your analysis (see Step 2 in this article for an example).

   Kanika and Niels see that people often forget that the data has been cleaned and analyze the cleaned data as they would the initial data. They developed an approach that enhances the original data with annotations to maintain awareness about the performed data cleaning and transformation steps.

4. Root causes and prevention. We discussed that process mining newcomers should not expect their data to be perfect. You work with the data that you have. And often, detecting data quality issues is a valuable insight in itself! Strive for data that is “fit for use” use improve your data quality along the way.

   To get at the root causes of data quality problems, you sometimes have to go outside the technical systems and include social and organizational dimensions like peer pressure and performance incentives. We discussed a research framework that captures the root causes of data quality problems in a holistic manner (see all the links to the discussed papers below).

Finally, we took a step back and looked at the broader field of data governance, where data quality is just one aspect. Niels and Kanika shared an example from ongoing research that reveals that process mining-specific approaches are needed in other data governance areas as well. ¹

Thanks again to Kanika and Niels and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• The Six Primary Dimensions for Data Quality Assessment by the DAMA UK Working group on ‘Data Quality Dimensions’ describe the general data quality dimensions of completeness, consistency, uniqueness, validity, accuracy, and timeliness.

• Wanna improve process mining results? by J.C. Bose and W.M.P. van der Aalst was the first process mining-specific data quality problem categorization.

• The Event Log Imperfection Patterns for Process Mining by S. Suriadi, R. Andrews, M.T. Wynn and A.H.M. ter Hofstede build on this categorization and identify common data quality patterns based on practical experience.

• Our data quality checklist for process mining helps you find and clean problems that are common in event log data.

• The paper Enhancing event log quality: Detecting and quantifying timestamp imperfections by D. Fischer, K. Goel, R. Andrews, C. van Dun, M.T. Wynn and M. Roglinger presents an automated approach for detecting and quantifying timestamp-related issues.

• The article DaQAPO: Supporting flexible and fine-grained event log quality assessment by N. Martin, G. Van Houdt and G. Janssenswillen introduces an R-package that supports event log quality assessments.

• The paper Collaborative and Interactive Detection and Repair of Activity Labels in Process Event Logs by S. Sadeghianasl, A.H.M. ter Hofstede, S. Suriadi and S. Turkay shows how gamification and crowdsourcing can be leveraged for repairing activity labels.

• The article Quality-Informed Process Mining: A Case for Standardised Data Quality Annotations by K. Goel, S.J.J. Leemans, N. Martin and M.T. Wynn proposes data quality annotations for event logs.

• The paper An expert lens on data quality in process mining by R. Andrews, F. Emamjome, A.H.M. ter Hofstede and H. Reijers investigates root causes for data quality problems (see also our Process Mining Café with Hajo Reijers about this topic).

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Join us for the first Process Mining Café after the summer break this Wednesday!

Data quality is essential for any data analysis technique. If you base your analysis on data, you must ensure that the data is correct. Otherwise, your results will be wrong. Together with our guests Kanika Goel from QUT and Niels Martin from Hasselt University, we will talk about data quality for process mining both from a research and practitioner perspective.

Discuss with us this week, Wednesday, 7 September, at 16:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday, 7 September, at 16:00 CEST! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session.

One of the underlying assumptions of process mining is that a certain process awareness is already present in the organization. This means that people understand the importance of processes and their impact on the desired outcomes. How could you otherwise run any improvement projects?

In the latest Process Mining Café, Rudi and I spoke with Fred van Middendorp from Heijmans about how to apply process mining in an organization where this process awareness is not yet there. If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Using process mining in a project-based company is not just about how you do it. Instead, you need to pay special attention to how you talk about it.

We discussed the following tips for process miners who still need to increase process awareness in their organization:

1. Build up a shared understanding of phases. Even project- or contract-based processes have activities that repeat. Collect the activities and sort them into “buckets” of rough phases to create a shared process view on a high level. This is also the start of your data collection.

2. Challenge the idea of uniqueness. People often think that every project is unique. This is only partly true because there are common parts that they are not aware of. Process mining can help you to reveal which parts of the process are truly unique.

3. Be aware that knowledge is connected to a person. Making processes explicit makes the knowledge of the person explicit. This provides the opportunity to discover best practices. At the same time, it might lead to resistance because — for that person — it also means giving up power.

4. People will compare themselves. It is natural to check how you are doing compared to others. This can give ideas (“Oh, you are doing it that way!”). However, sometimes different projects are not comparable, and you must protect them from drawing wrong conclusions.

5. Looking over the boundary of the own work area. People in later phases of a process tend to resolve problems without letting the people in earlier phases know about them. Viewing the entire process with process mining helps spot problems in the handover of work.

6. Discuss what quality means. Be clear about what “good work” means and how you can analyze it with process mining. Do you want to reduce rework or improve speed? For example, a project may not need to be as fast as possible but on time. Goals differ based on customer expectations.

7. Getting the new way of working to stick. Agreeing on a defined process ensures that the work is done better in a consistent manner. However, it is easy to fall back into old patterns. Process mining can be motivating by showing progress, and it helps discover backslides.

Thanks again to Fred and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Process awareness is one dimension in the categorization of which processes are suitable for process mining

• Keep in mind that the variants are not only determined by the “uniqueness” but also by the level of detail in your data. Abstracting to a higher level (for example, with the Milestone Method) will give you a process view with less variation and more common ground. See also this demo of simplification strategies in our customer journey café

• Expect parallelism in your process map if you analyze project-based processes. Here are some strategies to simplify the parallel views if you are getting confused

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

It was exciting to meet each other in person again at this year’s Process Mining Camp. To make the camp as safe and relaxed as possible, we had arranged all the breaks, lunch, and the BBQ dinner outdoors.

We were a bit nervous about the weather. But luckily, the sun was shining, and we got a hot summer day without rain.

We had limited the number of participants for this year’s camp to a smaller group. The auditorium at the Technical University Eindhoven had good ventilation. And we were all wearing masks. So, we were good to go!

Keynote

In the keynote, we celebrated the 10th anniversary of Process Mining Camp. It was nice to be back to where it started and where most of the camps since took place each year.

We also celebrated the 10th anniversary of Disco and discussed what it means to use process mining as an analysis tool.

Police

Then, we started with the practice talks. Machteld Oosterhof and Marianne Ravelli from the Police in the Netherlands talked about what it takes to change the decision-making mindset from being driven by knowledge to being guided by facts.

They shared three projects in which the initial assumption was quite different from the analysis results and ultimate resolutions. They warned the campers not always to trust their gut and to be aware that bias can be all around you.

AGCO Finance

At first, Sjoerd van der Zee from AGCO Finance was reluctant to do the process mining analysis himself. But now, he is grateful that he did because learning the process mining part is easy if you have the process and domain knowledge around you.

In his presentation, Sjoerd showed us how answering one question generated new, additional questions. And how you need to keep on asking the “why” question until there are no further questions left.

CorVel

After lunch, Beth Borman from CorVel in the United States looked at two types of processes: Structured and unstructured processes. For structured processes, the entire process could be analyzed at once. The analysis focused on identifying bottlenecks, exceptions, and areas of automation.

She also explained how she analyzed a very unstructured claims management process from various angles. You need to be creative and explore smaller pieces or segments. The focus is on finding patterns and standardization.

VolkerWessels

Robin Schouten from VolkerWessels shared his experience combining process mining with Lean Six Sigma.

He showed us in detail how he calculates the First Time Yield (FTY) for his quality measurement. And he demonstrated how he uses the statistical tools of Lean Six Sigma to determine the statistical significance of the discovered bottlenecks.

Discussion roundtables

After the coffee break, we all remained outside for the discussion roundtables. We split into twelve groups, each formed around topics from process mining in financial services, manufacturing, or healthcare, to use cases like customer journeys and auditing. Other groups discussed responsible process mining and the opportunities and challenges of new and old IT systems.

We had some initial questions prepared for the group members to get to know each other. But most of the question cards were empty and filled by the roundtable participants.

This way, the discussion was driven by the statements and questions of the group rather than by some pre-determined schedule. The groups talked for more than one and a half hours, and many wished they had even more time!

Each group had appointed one person to share a one-minute summary of their discussion with all of us. In a lightning round of summaries, we got a glimpse of the full range of discussions that were going on in all the groups.

GSK

Maxime Parres-Albert and Maxime Brochier from GSK in Belgium closed the day with the last practice talk. They improved the speed of the Human Biological Sample Management process for clinical trials of new vaccines using process mining. For example, clinical test results can now be released faster.

They also showed the complex data transformations that they had to perform to get the data in the right shape. And they shared their change management approach.

Thank you!

Throughout the day, we had great questions and lively discussions after each presentation. A big thanks to the speakers and to all of you for coming and being such an active part of the camp!

We also would like to thank the viewers who joined the livestream. Many of you told us that you could follow along and join the camp from afar.

If you would have liked a closer look at the slides, or you just want to revisit the experience, you should sign up to our camp mailing list today: We will send out the slides from the presentations tomorrow.

We hope to see all of you at next year’s camp! Until then, join the camp mailing list to receive the video recordings and notifications about our monthly café livestreams. We’ll meet again, back in the café or at the next camp!

No dice getting a ticket for Process Mining Camp tomorrow? You are in luck — We are going to provide a livestream¹, so you can watch the talks from the comfort of your home!

Tune in live for Process Mining Camp by visiting https://processminingcamp.com tomorrow, Thursday, 23 June, at 10:00 CEST. The program will run until 18:00. Check your timezone here and add the time to your calendar if you don’t want to miss it.

There is no registration required. Simply point your browser to https://processminingcamp.com when it is time. You can watch the camp talks and add your questions for the Q&A while we are on the air, right there on the camp website.

See you tomorrow, in Eindhoven and all around the world!

Process Mining Camp is just one week away. There are less than a handful of tickets left, so get yours now and sign up here if you want to come!

To get ready for camp, you can watch the recordings of Process Mining Camp 2021. If you have missed them before, watch the kick-off of last year’s camp, the audit day, the manufacturing day, and our camp day focused on process owners. Today, we bring you the recordings of the fifth and last day. The Friday was all about robots.

It started with the closing keynote by Wil van der Aalst, where he argued for a hybrid automation approach with the human in the loop. Together with Wil, we then talked about robots, ethics, and the future of machine learning with Manuela Veloso, Head of AI Research at JPMorgan Chase.

Man or Machine: Hybrid Intelligence

Process mining is not a magic wand. It is a discipline that requires a smart human being who can make the connection between the data and the underlying business process — with the help of the process mining tool. You have to apply your domain knowledge to interpret the results and develop improvement ideas.

Pundits love to tell us which professions will be replaced by robots any day now. All the while, the smart devices in our pockets and at home are not as smart as we would like them to be. Where exactly lies the boundary between what machines can do, and what will humans continue to do well into the future? In his closing keynote, Wil explored the questions of where technology outperforms humans, where human intelligence is needed, and where both blend together to combine the best of both worlds.

Process Mining Café: Robot Ethics

Human-AI interaction has many challenges. For example, organizations are reluctant to deploy learned policies if they do not trust them because they don’t understand them. Explainability research tries to address this by creating explanations for otherwise black-boxed models. Furthermore, ethical considerations and data privacy play a role.

Together with Manuela and Wil, we discuss misconceptions about artificial intelligence and how realistic expectations can lead to more productive learning systems.

Process Mining Camp takes place on Thursday, 23 June 2022. Add the time to your calendar and register now for this year’s camp!

This year’s Process Mining Camp is just around the corner. See the program here and sign up now!

To get ready for camp, you can watch the recordings of Process Mining Camp 2021. If you have missed them before, watch the kick-off of last year’s camp, the audit day, and the manufacturing day. Today, we bring you the recordings of the fourth day. The Thursday was all about process mining in telecommunications.

It started with the presentation by Gary Bonneau from Cox Communications, who showed how he got from disparate data sources to end-to-end process visibility. Gary and I then talked about data autonomy and skills with the Process Mining Camp speaker and process miners of the year Carmen Lasa Gómez from Telefónica and Javier García Algarra from U-tad University.

End to End Process Analysis

Cox Communications is an American company that provides digital cable television, telecommunications, and home automation services in the United States. Gary is a senior manager for product operations at Cox Business (the business side of Cox Communications).

Gary has been working in the telecommunications industry for over two decades and — after following the topic for many years — is a bit of a process mining veteran as well. Now, he is using process mining to visualize his fulfillment processes. The business life cycles are very complex. Multiple data sources must be connected to get the complete picture of the end-to-end process. At camp, Gary showed how process mining allows him to analyze his process by himself, independently from the IT department.

Process Mining Café: Make Your Data Work

Process mining provides a new autonomy to process owners who can finally analyze their own process without long IT projects or consultant teams.

Together with Carmen, Javier, and Gary, we discuss who owns the process mining data, how to get access to data to analyze on your own, and what kind of skill profile an independent process miner has.

Stay tuned for the videos from the last day of camp.

Process Mining Camp takes place on Thursday, 23 June 2022. Add the time to your calendar and register now for this year’s camp!

We are happy to announce the release of Disco 3.2.

This update is all about making what’s good about Disco even better, most notably importing data. Disco will now support an even wider array of timestamp formats, in both CSV and XES imports. And you can now directly import Excel spreadsheets of unlimited size.

We have updated the graph layout and runtime for Disco, to make sure you get the best performance and the latest security fixes ¹. This update also improves the general performance and stability of Disco, and we have fixed a number of bugs and annoyances.

Thanks for all your ideas, and your bug reports. Keep them coming and, as always, thank you for using Disco!

How to update

As with every update, this release also contains a number of smaller enhancements and fixes. We recommend that you update to the latest version of Disco at your earliest convenience.

Disco will automatically download and install this update the next time you run it, if you are connected to the internet.

If you prefer to install this update of Disco manually, you can download and run the updated installer packages from fluxicon.com/disco/download

Changes

• CSV Import:
  • Improved parsing timestamps with sub-millisecond precision and time zones.
  • Give more specific feedback on import problems.
• Excel Import: Load event logs from XLSX files of arbitrary size.
• XES Import: Parse timestamps with sub-millisecond precision.
• MXML Import: Parse timestamps with sub-millisecond precision.
• Process Map: Improved performance and stability of graph layout.
• Connection: Improved proxy configuration.
• Platform: Java update.

The Early Bird deadline for this year’s Process Mining Camp passes tomorrow at 12:00 CEST. Join us if you can and sign up now!

To get ready for camp, you can watch the recordings of Process Mining Camp 2021. If you have missed them before, watch the kick-off of last year’s camp and the audit day. Today, we bring you the recordings of the third day. The Wednesday was all about process mining in manufacturing.

It started with the report of two impressive improvement projects by Minh Chau Nguyen and Klaus Kühnel from Wacker. Minh Chau, Klaus, and I then dove into Lean manufacturing with the process mining veteran Joris Keizers, who achieved a 50% cycle time reduction for Veco’s core production process.

Process Mining at Wacker

Wacker is a German chemical company that produces silicone rubbers, polymer products, biotech solutions, and polysilicon and wafers for the semiconductor industry. Minh Chau is a digitalization manager and Klaus is a project and program management practitioner at Wacker.

Minh Chau and Klaus have seen how process mining complements existing analysis tools in the toolbox of a productivity manager in the era of digitized industries. They showed two concrete cases from analyzing the polysilicon production process at Wacker. One of the projects has resulted in saving the company 17 million Euros per year and the other one lead to a cost reduction of 400 thousand Euros per year.

Process Mining Café: Shop Floor Talk

A core aspect of Lean Manufacturing is that you “walk the GEMBA”: Managers physically visit the production lines to look for waste and opportunities in the process. With process mining you analyze the process based on data, at a remove from the actual manufacturing process.

Together with Joris, Minh Chau, and Klaus, we discuss whether this is a problem and — if so — how it can be overcome.

Stay tuned for the videos from the following days of camp.

Process Mining Camp takes place on Thursday, 23 June 2022. Add the time to your calendar and register now for this year’s camp!

To get ready for this year’s Process Mining Camp (see the program and sign up here!), you can now watch the recordings of Process Mining Camp 2021.

Watch the kick-off of last year’s camp if you have not seen it yet. Today, we bring you the recordings of the second day. The Tuesday was all about process mining in audit.

It started with an excellent talk by Jasmine Handler and Andreas Preslmayr from the City of Vienna Court of Audit. Janine, Andreas, and I then picked up the discussion from a broader audit perspective in the process mining café with our special guest Mieke Jans. Mieke is an Associate Professor at Hasselt University in Belgium and has been working on process mining in audit for more than 15 years.

Challenges of Audit with Process Mining

The City of Vienna Court of Audit is an autonomous and independent public audit institution for the municipality City of Vienna. Jasmine and Andreas are both auditors at the City of Vienna Court of Audit and audit financial operations, security, and safety regulations of the public entities of the city.

Last year, they audited one of Austria’s largest infrastructure groups: The Wiener Stadtwerke. In this audit, they used process mining to evaluate the correctness, compliance, efficiency, and expediency of the control system. At camp, Jasmine and Andreas shared their approach and best practices. They show how they got from the raw data to concrete insights and recommendations from an audit perspective.

Process Mining Café: Compliance for the Win

When you apply process mining for audits, some special requirements emerge that are less relevant in a process improvement context. What are these requirements, which type of auditor uses process mining, and is it a problem if there are too many exceptions when looking at the entire dataset?

Together with Mieke, Jasmine, and Andreas, we discuss how process mining impacts the traditional audit methodology, audit standards, new definitions of materiality, and research on how auditors assign risk to deviations.

Stay tuned for the videos from the following days of camp.

Process Mining Camp takes place on Thursday, 23 June 2022. Add the time to your calendar and register now for this year’s camp!

Pack your bags, get your provisions, and plan your trip — Just a few more weeks until we get together at this year’s Process Mining Camp on Thursday, 23 June in Eindhoven, the Netherlands.

You can find the camp website with the detailed program here. And of course you should register now to get one of our limited early bird tickets!

While we are in the final stretches of preparing this year’s camp, here is what you can expect.

Practice talks: Listen and learn

Our honest and relatable practice talks are the heart and soul of Process Mining Camp. Here are the speakers who will share their experiences at this this year’s camp.

Politie (Netherlands)

The Police in the Netherlands are composed of ten regional operating units. The human resource (HR) department makes good police work possible by onboarding and supporting all officers and staff to fulfill their daily duty.

Machteld Oosterhof is a business operations specialist, and Marianne Ravelli is a business controller at the HR shared services center. Traditionally, knowledge workers drive process improvements by their expertise and gut feeling. However, most processes in the HR administration are digitalized. Therefore, the ambition is to implement improvements based on data. Machteld and Marianne share their experiences when showing facts and figures and the effect of confirming or refuting assumptions.

AGCO Finance (Netherlands)

AGCO Finance is a joint venture between the global financial solutions partner DLL and AGCO, an agricultural equipment manufacturer. AGCO Finance offers a one-stop shop for financing agricultural machinery for farmers.

Sjoerd van der Zee is working in AGCO Finance’s Operations function. He focuses on improving efficiency and service levels. Process mining has given him a fresh perspective on the different paths and steps in his processes. At camp, he will show how you can apply your domain knowledge to iterate through discovery, questions, and analysis cycles. Multiple cycles are required to obtain the necessary insights that enable you to take steps to improve your business.

CorVel (United States)

CorVel is a US provider of risk management solutions for the workers’ compensation, auto, health, and disability management industries. They provide their clients with the information and insights to make smart decisions.

As a project manager, Beth Borman identifies optimization opportunities based on the Theory of Constraints data analysis and process mining. While analyzing several processes, she noticed that she could not take the same approach for every single process. Some processes seem to be more straightforward, while others are real brain teasers. Beth will show you how you can adapt your analysis approach to your process.

VolkerWessels Telekom (Netherlands)

VolkerWessels Telecom designs, builds and maintains telecommunication networks. Quality and timeliness are essential when delivering these network services to their customers.

Robin Schouten is a Lean Six Sigma green belt. At camp, Robin will show how Lean Six Sigma professionals can benefit from including process mining into their toolbox. He examines classical Lean Six Sigma tools next to their corresponding process mining analyses and shows how they supplement and complement each other. With the combination of both approaches, you can create a detailed business case for your improvement opportunities.

GSK Biologicals (Belgium)

In the clinical trial phase of a new medicine or vaccine, blood samples and other samples are collected from the people participating in the clinical trial. Overall, GSK manages millions of samples that go through hundreds of process steps in its Human Biological Sample Management (HBSM) process. It is vital to complete the HBSM process as quickly as possible while maintaining quality requirements.

Maxime Parres-Albert is a senior tech engineer, and Maxime Brochier is a business innovation lead at GSK. Using process mining on clinical operations data, they were able to map the HBSM process and identify bottlenecks and best practices. At camp, they will share the data transformations they had to make and give tips for organizing change management.

Get to know your fellow process miners

In the afternoon, we get interactive — Join us for a discussion roundtable and connect to the community on a deeper level.

In small groups of up to eight people, you will talk about process mining topics such as customer journeys, auditing, Lean Six Sigma, the business case for process mining, data transformations, and security, privacy and ethics.

The goal is not to solve all the world’s problems but to share openly and learn from each other. In the interaction with other process miners who have similar backgrounds as you, you can discuss challenges and ideas that deserve further attention.

At the end of the roundtable, each group will share their main insights with the rest of the community, so that we can all benefit.

Talk to us

For the very first time at camp, Rudi and Anne will run a process mining clinic. Do you have a data set that defies all your efforts? Questions that you always wanted to get answered? Process mining problems that leave you scratching your head?

Bring your laptop and show them to us! We will unpack the issue together and dig into our experiences to give you expert advice.

The clinic will be available during all the breaks as well as in parallel to the discussion roundtables.

Join the community and sign up now!

Dive into process mining for a whole day, and find out what others in the community are up to. We take care of food and drinks during camp. And if you sign up before Friday 3 June 12:00 CEST, not only can you benefit from our early bird rate — you’ll also get your very own camp t-shirt!

All the breaks, lunch, dinner, and coffee will be outside. Other parts of the camp program will also take place outdoors (learn more about our Corona measures here). We expect this year to be the most summer-campy camp ever. We will even have a sort-of campfire in the form of a BBQ at the end of the day.

Don’t miss Process Mining Camp 2022, and sign up now!

We can’t wait to see you in Eindhoven on 23 June.

— Your friends from Fluxicon

To get ready for this year’s Process Mining Camp (sign up here to be notified once the registration opens very soon!), you can now watch the recordings of Process Mining Camp 2021.

While this year’s camp takes place in Eindhoven again, we were still gathering online last year. For one week, we spent two relaxed hours of process mining per day on the internet together, with a mix of practice talks, lab sessions, and Process Mining Cafés.

Here are the recordings of the opening keynote, Daan’s practice talk, and the process mining café from the first day.

Welcome & Opening Keynote

We looked back at the talks from the past nine years of Process Mining Camp, and we categorized them into industries and use cases. Categorizations into industries are helpful if you want to see examples of how other companies in your line of business have used process mining. Another way, however, to look at these same case studies and camp talks is to group them into use cases. A use case is less concerned about the industry where you apply process mining. Instead, it focuses on who is using process mining and why.

It is helpful to look at process mining examples from this perspective because it helps you understand how process mining fits into the methodologies you already use (and how it will change your current way of working). For example, process improvement teams often work with the DMAIC approach from Lean Six Sigma, or the PDCA cycle. Auditors have their own procedures. Based on three examples, we show how you can integrate process mining into these existing methodologies.

Analysts and Domain Experts are Complements

The first practice talk was given by Daan Jabroer from Volksbank in the Netherlands. Volksbank is a Dutch bank that includes brands such as SNS, ASN Bank, RegioBank, and BLG Wonen. Daan is a business improvement consultant at Volksbank.

For more than eleven years, Daan has worked on architecting, (re)designing, modeling, and improving the business processes at various banks. The processes are constantly changing, and process mining is a great tool to explore the impact of these changes over time. However, for Daan, the real value lies in the collaboration between the process mining analyst and the domain expert. During the first quarter of 2020, the mortgage provisioning lead time was above the stated limit. Daan shows how only the process analyst and the domain expert together can solve the problem.

Process Mining Café: Mind the Gap

For the daily Process Mining Café, our speakers of the day were joined by old friends from previous process mining camps. On Monday, Daan and Anne got together with Sudhendu Rai, from AIG in the United States. Sudhendu is Head of Data-Driven Process Optimization in AIG’s Investments organization and combined process mining with discrete-event simulation in the past.

Does it make a difference which improvement methodology is used with process mining? How do you best explain process mining to others? And how do you ensure that the right actions are taken after the analysis?

Together with Sudhendu and Daan, we discuss the typical questions and the daily challenges of a process improvement practitioner working with process mining.

Stay tuned for the videos from the following days of camp.

Process Mining Camp takes place on Thursday, 23 June 2022. Add the time to your calendar and sign up for the camp mailing list here not to miss anything about this year’s camp!

Join us for our last Process Mining Café before Process Mining Camp and the following summer break this Wednesday!

Together with our guest Fred van Middendorp from Heijmans, Rudi, and I will talk about project vs. process thinking. Project-driven organizations like construction companies approach everything from a project perspective. However, process improvement initiatives require process awareness. How do you deal with this as a process mining practitioner?

Discuss with us this week, Wednesday 18 May, at 16:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday 18 May, at 16:00 CEST! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session.

We are always excited to learn about new research from our academic partners. Today, we would like to highlight an interesting paper about the design and implementation of video-based process mining that Wolfgang Kratsch, Fabian König, and Maximilian Röglinger have published in the Decision Support Systems journal.

Manual activities often leave blind spots in the process analysis because you cannot see them in the data. Especially for manufacturing processes, there is an opportunity to use video data to fill these blind spots. The video data contains valuable process-related information, but there is no standardized approach to creating event logs from unstructured video data yet.

The authors developed a reference architecture that bridges the gap between computer vision and process mining. The computer vision capabilities that are the basis for extracting the process-related information from video data are shown in Figure 1 below (click on the image to see a larger version). The extracted low-level events are then aggregated to the level of detail required for the process mining use case.

Figure 1. Illustration of computer vision capabilities

You can read their paper here. Thanks to Wolfgang, Fabian, and Maximilian for allowing us to share their research!

What if you had twice as many people? What if you didn’t do that process step? Simulation is such an exciting topic because it allows you to test complex “what if”-scenarios without having to make the change in the real world (yet).

In the latest Process Mining Café, we talked with Lambros Viennas from Bridgnorth Aluminium and Sudhendu Rai from AIG about combining process mining with simulation. Based on an example in Disco and AnyLogic, we show how you can use process mining as a starting point for your simulation model. If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Thanks again to Sudhendu and Lambros and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• How process mining compares to simulation

• Example of how the process structure and process parameters can be extracted from the process mining tool for the simulation

• Sudhendu’s presentation at Process Mining Camp 2019 shows how AIG could reduce the cycle time from 12 days to 5 days (increasing the throughput by over 30%) by combining process mining with simulation

• In his follow-up talk at Process Mining Camp 2020, Sudhendu talks more about how they used real-world data and discrete-event simulation optimization for improving insurance business processes within AIG

• Sudhendu’s “Process Wind Tunnel for Improving Business Process” talk at the Winter Simulation Conference 2021 (slides)

• Bruce Silver’s articles on making simulation useful and why simulation in most BPM tools is a fake feature

• Modeling, and thus simulating, human behavior is challenging. You can take a look at Chapter 9 in my Ph.D. thesis, this paper, and Wil’s Business Process Simulation Survival Guide as a starting point

• Lambros recommends this whole list of references to dive deeper into the literature

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Summer is on the horizon, and that means one thing: It is time to dust off the old tent and get ready for this year’s Process Mining Camp on 23 June!

As any camper will tell you, process mining is not something you just own or buy — process mining is something we are doing. It is not just a tool but a discipline.

Some things you have to learn on your own, other things you can learn from books. But we learn best when we share experiences with our peers. When we get together and talk about how exactly we do process mining.

This one goes up to eleven

Ten years ago, we got together for the first Process Mining Camp, and it has been the highlight of our year ever since. At Process Mining Camp, you meet people who face the same challenges as you. You exchange experiences and learn from each other. And you might just make some new friends along the way.

After two years of online camps, we will hold this year’s Process Mining Camp in person again. While our talks are the backbone of the event, the whole camp experience is interactive, spontaneous, and personal. Plus, clearing your schedule and being away for camp allows you to be present in a very different way.

Thanks to our friends from the TU/e Process Analytics group, we will pitch our tents once again at the auditorium of the Technical University in Eindhoven, back where it all started.

We know that traveling to a conference requires more time and effort than tuning in to an online event. So, we will make sure that this trip is worth your while. To maximize your time with other process miners, we will have discussion roundtables in smaller groups and plenty of social time.

What’s on the menu

Here is what you can expect from this year’s camp:

• We are already working with some great speakers on their practice talks. So, the program will be top-notch. And of course, you can meet the speakers over coffee later in the day.

• You can join one of our discussion roundtables and go deeper on various process mining topics. The discussion groups will be small so that you meet and get to know everyone in your group.

• We will have a process mining clinic. Bring your most tricky process mining problems and get expert advice.

• There will be plenty of time for socializing so that you get the chance to catch up with everyone.

• By moving much of the camp outdoors, this will be the most summer-campy camp ever! We will even have a sort-of campfire in the form of a BBQ at the end of the day.

Join us for the tenth anniversary of the Process Mining Camp community!

Pull out your calendar now and mark Thursday, 23 June, as Process Mining Camp day! (add it to your calendar here)

Safe and sound

Of course, Corona is still in the air, and we do not have our heads in the sand. So, this is how we are going to make camp a safe experience for all of us.

The practice talks will be presented in a large, well-ventilated room with lots of space. We will provide masks, and we will all be wearing them indoors.

All the breaks, lunch, dinner, and coffee will be outside. Many parts of the camp program will also take place outdoors. So, you can breathe fresh air while conversing with your fellow process miners.

We want everybody to feel safe and comfortable at camp. If you have any questions or concerns, please do not hesitate to let us know at camp@fluxicon.com.

Making the camp safe also means keeping the number of attendees lower than usual, which means that tickets will be even more limited this year. Be sure to sign up for our waiting list here, and we will give you a heads up right before we open registration very soon.

We can’t wait to see you in Eindhoven on 23 June!

— Your friends from Fluxicon

Simulation allows you to analyze “what if”-scenarios without making the change in the real-world process. The problem is that you first need a good model representing the current reality before you can start modeling the “what if”.

This is where process mining can help: It provides a picture of the current process that you can use as a starting point for your simulation.

Together with our guests Lambros Viennas (Bridgnorth Aluminium) and Sudhendu Rai (AIG), we will talk about how you can combine process mining with simulation in our upcoming Process Mining Café. Join us!

The café takes place this week, Thursday 28 April, at 16:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Thursday 28 April, at 16:00 CEST! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session.

This is the 4th article in our series on combining Lean Six Sigma and process mining. It focuses on how process mining can be applied in the Analyze phase of the DMAIC improvement cycle. You can find an overview of all articles in the series here.

In your baseline measurement, you have already determined that the targets for the process - both CTQ 1 in the contact center and CTQ 2 in the credit application department - are not met. The next question is ‘What could be the potential causes?’.

You know that the customer contact center recently completed a lengthy digitalization project. That project had consumed a lot of resources from the contact center. Therefore, you decide that this is not the best time to dive into the first CTQ with yet another project. However, the credit manager is very interested in a deeper analysis of the underwriting process. A project team is hand-picked, and a first meeting is scheduled.

In this meeting, you share your measurements and observations with the team and ask them what could be the potential causes of the delays. You capture three different hypotheses from the group and start to test them. The analysis is done based on the baseline from the Measure phase, in which you had already removed incomplete cases and adjusted the time from calendar days to business days.

Hypothesis 1: More underwriters are needed (Debunked)

One hypothesis was that more work was coming in than the underwriting team could handle. This, of course, would result in a backlog that a growing work in progress would build up over time.

However, when looking at the Active cases over time graph in Disco, you cannot find any evidence of growth in the work in progress (see Figure 22).

Figure 22: Work in progress does not show a trend of growth over time

In the ‘Active cases over time’ chart, you will always see a “warm-up” period at the beginning and a “cool-down” period in the end. The number of active cases is 0 at the beginning and end of the timeframe. Of course, in reality, there are not 0 cases in the process, but the previously active cases are not visible in the data because you are only looking at a specific time frame.

Therefore, you look for a trend between the end of the warm-up and the start of the cool-down (see red arrow in Figure 22). There is no significant increase in work in progress for the credit application process.

Hypothesis 2: Applications above 50k take more time (Debunked)

The team also expected that applications for a credit of a higher amount were more complex to handle. They require a sign-off from a senior underwriter, which could cause delays when the underwriter is unavailable.

You test this hypothesis by first segmenting the applications into two populations (A) with an amount up to €50k and (B) with an amount above €50k by filtering cases based on the ‘Amount’ attribute in Disco. The average and median case durations for applications in population B appear to be slightly higher than those in population A. But are these differences statistically significant?

You export the case durations for each population via the Cases Export in Disco. Based on these two populations, you then perform a hypothesis test in Minitab¹ to determine if the mean of the lead time for populations A and B are really different. You transform the case durations from both populations into hours (corresponding to the net time for working days in hours) and copy them into separate columns in one file (see Figure 23).

Figure 23: Mann-Whitney test in Minitab

Different hypothesis tests are suitable for different situations. One crucial point to consider is that the case durations distribution of the credit application process is not normally distributed. This is true for most service processes, where people rather than predictable machines play the central role. As a result, hypothesis tests that assume a normal distribution (for example, the ANOVA test) are unsuitable. Instead, you use a non-parametric test such as the Mann-Whitney test². Figure 23 shows the configuration of the Mann-Whitney test that determines whether the hypothesis that applications with an amount of up to €50k take less time than applications above €50k is true.

Figure 24: The results of the hypothesis test in Minitab show that credit applications above €50k do not take significantly more time

Figure 24 shows the outcome of the Mann-Whitney hypothesis test in Minitab. If there were a significant difference in the two populations, there would be a p-Value that is smaller than 0.05. Based on the results in Figure 24, you can see that with 0.113, the p-Value is higher than 0.05 and, therefore, conclude that the processing of credit applications for amounts above €50k does not take significantly more time.

Hypothesis 3: Incomplete cases require more time

In the Measure phase, you noticed that some applications were set to the ‘Incomplete’ status to deliberately delay the payment upon the customer’s request. You then removed these cases from the baseline data set because, in reality, they do not reflect incomplete applications. However, even after correcting this data quality problem, there are still 2339 cases for which the credit application was incomplete at least once (53% of all the cases in the baseline data set), some of them even multiple times.

The third hypothesis of the project meeting was that such incomplete applications take more time. After all, the missing information needs to be requested per email and received back from the customer. So, this may be one of the reasons why the promise to give the customer certainty about their loan within three business days cannot be realized.

To test this hypothesis, you again segment the data set into two populations: (A) applications that were complete right away (never incomplete) and (B) applications that have at least one ‘Incomplete’ step. In Disco, you can easily segment the data by clicking on the ‘Incomplete’ activity in the process map and using the Filter this activity… shortcut to add a pre-configured Attribute filter in ‘Mandatory’ mode (Population B). The applications that were never incomplete can then be filtered by simply changing the Attribute filter mode to ‘Forbidden’ (Population A). These two modes filter the data based on the presence or absence of the ‘Incomplete’ activity.

The process maps for the cases in populations A (left) and B (right) are shown in Figure 25 below (click on the image to see a larger version). 


Figure 25: Process map for applications that were complete the first time (A, on the left) and for applications that were incomplete at least once (B, on the right); with median durations as primary metric and absolute frequency as secondary metric

The process maps show that an additional 26.2 + 20.2 hours of median time accumulate every time the company requests the missing information from the customer. Overall, the complete applications in population A have a median lead time of 1.9 business days, and incomplete applications in population B have a median lead time of 3.2 business days. Now, the question is again whether this difference is statistically significant.

Figure 26: Case durations for ‘Complete’ applications (population A) and ‘Incomplete’ applications (population B) in net hours on business days in Minitab

You export the case durations for each data segment from Disco and copy them below each other into Minitab, with the category label ‘Complete’ for population A and ‘Incomplete’ for population B (see Figure 26). You then run the Graphical Summary analysis in Minitab to obtain statistical overview information about the data. Figure 27 shows the resulting summary, and, as before, you confirm that the data is not normally distributed (see red highlight in the lower right corner).

Figure 27: Graphical Summary analysis in Minitab for ‘Complete’ applications (population A) and ‘Incomplete’ applications (population B); both populations are shown not to be normally distributed

You again apply the Mann-Whitney hypothesis test as you did for Hypothesis 2. However, this time, the result shows that the case durations are significantly different for both groups (see Figure 28). The p-value is 0 and, therefore, smaller than 0.05. So, Hypothesis 3 can be confirmed. The results show that with 95% confidence, incomplete applications take between 44.7 and 47.4 net hours longer than applications that were complete the first time.

Figure 28: The results of the hypothesis test in Minitab show that incomplete applications do take significantly more time compared to applications that are complete the first time

Deep dive into the root cause

The process map shows how often applications are incomplete, but you cannot see how often the ‘Incomplete’ loop is repeated within the same case. This information is available in the data and can be brought out in various ways (see our Rework Analysis Guide for an overview). However, it can also be helpful to unfold loops by enumerating each iteration as a separate activity in the process map.

Figure 29 shows the process for both complete and incomplete applications with unfolded loops. The number behind the activity name indicates whether an application goes through the ‘Incomplete’ loop for the 1st, 2nd, 3rd, 4th, 5th, or 6th time. By unfolding the repetitions, you can see that most cases require just one additional request before the underwriting team makes the final decision. However, one application required six iterations before the final approval. You also notice that no applications were rejected after the 5th request for additional information.

Figure 29: The process flow of the credit application process with unfolded loops

This unfolded process perspective already gives a deeper insight into what is going on, but it still does not answer the question “Why are these cases incomplete?”. You cannot answer this question based on the initial dataset because the reason why an application was incomplete is not in the data. After consulting the underwriters, you understand that the required documents vary from customer to customer. It looked simple at first, but especially in cases where they need to evaluate several income sources (employment, entrepreneurship, and pension), the document requirements can become very complex very quickly. Cases that fall into a grey area of the underwriting policy even leave room for interpretation by the underwriter.

Fortunately, the ‘Incomplete’ reasons are available in a functional email box. Because the email data is unstructured, it requires a manual review of the email communication to enrich the existing dataset. Getting the ‘Incomplete’ reason for all applications in the whole dataset would require considerable effort. Therefore, you decide to take a sample to understand what is most frequently missing in these incomplete documents. The sample data describes 939 incomplete documents for a total of 177 applications. You create a Pareto analysis with Minitab to show the frequency of these missing documents (see Figure 30).

Figure 30: A Pareto view of the ‘Incomplete’ reasons

Note that Disco can also create a Pareto view of the attribute distribution. Furthermore, attaching the ‘Incomplete reason’ attribute to the corresponding ‘Incomplete’ activity in the original data gives you additional analysis possibilities. For example, you can filter based on different ‘Incomplete’ reason attribute combinations to view the process map for these subsets in more detail. You can even bring the new attribute as an additional dimension into your process view.

From the Pareto view of the ‘Incomplete’ reasons in Figure 30, you can see that the bank statements are the most frequent problem. Together with the salary statements, issues with the contract (e.g., a missing signature), and the employment statements, they cause 81.4% of all incomplete documents. Focusing on resolving these ‘Incomplete’ causes would be a good start.

Finding the root cause for these ‘Incomplete’ reasons requires a more detailed analysis. For example, it could be that a document was completely missing. But it is also possible that documents were not readable (bad photograph or scan), in the wrong format, or not legally valid. This underlying reason lies at the heart of understanding what went wrong and how it can be prevented in the future. Classical Lean Six Sigma tools such as a Fishbone diagram or 5-Times-Why work great when you reach the limits of what the data can tell you.

Stay tuned to learn how process mining can be applied in the following phases of the DMAIC improvement cycle! If you don’t want to miss anything, use this RSS feed, or subscribe to get an email when we post new articles.

GDPR has increased the awareness about data privacy but also security questions. Companies have started to do data risk assessments, look at where their data is stored, who has access to the data, etc.

Within IT Security, there are preventive measures like risk analyses and security assessments. Investigations of what has happened after a fraud, hack, or other incident are called ‘forensics’ (after the scientific methods of solving crimes).

In the latest Process Mining Café, we talked with Lucas Vousten and Vincenzo Salden about process mining in a security audit and forensics context. They discussed the most common errors that companies make, and, step by step, we went through their analysis of a ransomware attack with process mining. If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Thanks again to Lucas and Vincenzo and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Process mining café on Privacy, Security, and Ethics

• Earlier paper on the exploitation of process mining for security audits shows how process mining can be used for more standard applications such as finding control-flow deviations, testing authorization constraints, testing Binding of Duties and Segregation of Duties constraints, testing data constraints, and testing time constraints

• Lucas recommends this article about IT security’s importance in protecting against ransomware and his interview about pen testing

After the café, Lucas also put the following seven fundamental principles together for you:

1. Identification of Crown jewels. Identify all critical assets (information and systems) in your organization.
2. Identify vulnerabilities. Scan all your IT components for known vulnerabilities and make a risk analysis based on availability, integrity, and confidentiality.
3. Use safe settings. Check the settings of equipment, software, and network and Internet connections. Adjust default settings and look critically at features and services that are automatically ‘on’.
4. Perform periodic updates. Ensure devices and software are up to date. Install security updates immediately. Turn on automatic updates so that your devices and software always run on the latest version.
5. Restrict access. Define for each user which systems and data access are required to work. Make sure that access rights are adjusted in a timely manner if someone gets a new position or leaves the company.
6. Prevent viruses and other malware. There are a few ways to prevent malware: Encourage safe employee behavior, use antivirus/anti-malware programs, download apps safely, and limit software installation.
7. Incident Response Plan. Be sure to have a well-prepared contingency plan if anything goes wrong (including disaster recovery, insurance, communication, etc.).

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

Last year’s Process Mining Camp was the 10th edition of our annual community meeting. In the opening keynote, we took a look at the industries and the use cases that categorize the talks from the past nine years.

When you start with process mining, it is always helpful to see examples from people who were in a similar situation as you are now. Understanding what did not work for them can help you to avoid mistakes. And you can pick up their recommendations about what they did right.

INDUSTRIES

One way to look at all the process mining stories is to categorize them per industry. Newcomers in the process mining world often want to hear about the experiences of similar companies. For example, a process analyst at a bank might want to see examples of how other banks have used process mining.

So, we thought it could be helpful to compile an overview of all the camp talks and case studies for you. And we grouped them into industries (click on a category below to jump to the examples in that section):

• Financial Services
• Insurance and Pension Funds
• Healthcare
• Government and Municipalities
• Production
• Logistics and Transportation
• Telco and Utilities
• Software & Services

USE CASES

Another way, however, to look at these same case studies and camp talks is to group them into use cases. A use case is less concerned about the industry where you apply process mining. Instead, it focuses on who is using process mining and why. It is helpful to look at process mining examples from this perspective because it helps you understand how process mining fits into the methodologies you already use (and how it will change your current way of working).

So, we have also grouped the cases into the following use cases (click on a category below to jump to the examples in that section):

• Process Improvement Teams
• Auditors
• Process Owners
• Customer Journeys
• IT Use Cases

Of course, some of the cases fall into multiple categories. Nevertheless, we picked one industry and one use case for each. We hope you find the collection valuable as a reference and inspiration ground.

All these examples remind us that process mining can be applied anywhere where processes are found! If you have a guest article or process mining case study that you would like to share, please get in touch with us via anne@fluxicon.com.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

Banks and other financial services organizations have been among the earliest process mining users and we can see why: Most of their processes are invisible. Like all complex processes, they have hidden waste and thus improvement potential. And they have invested in resources that are trained in process thinking. So, these people are perfectly suited to pick up a new instrument like process mining and use it to their advantage.

Here are examples from the financial services sector, in no particular order.

• Jozef Gruzman and Claus Mitterlehner from Raiffeisen Bank International share how they use a black-box discovery approach before they explore and review the processes with the subject matter experts in the different countries.

• John Müller analyzed the customer journeys at ING DIRECT Australia and realized that process mining changed the way questions were asked, because the process mining tool allowed the business users to explore their own process.

• Tijn van der Heijden developed a framework for conducting process mining projects at the Rabobank and also wrote a case study about the invoicing process analysis.

• Sudhendu Rai shared his experiences of using process mining with simulation at AIG. He shows how they could reduce the cycle time from 12 days to 5 days, increasing the throughput by over 30%.

• Niyi Ogunbiyi from Deutsche Bank talked about being clear about what process mining can and can’t do and about finding the right balance between targeted vs. untargeted exploration.

• Frank van Geffen from the Rabobank was one of the speakers at the first Process Mining Camp in 2012 and came back in 2014 to share how they reduced the waiting time in their IT service desk process by 72,000 hours in six months.

• Mieke Jans and her colleagues wrote this case study about applying process mining during an audit at a bank after the regular internal audit had already taken place. They found many things that the internal audit team had not found.

• This HR process case study analyzed how a bank reacts to requests and questions from employees. They discovered that there were significant delays if a case had to be sent to external specialists.

• Lucy Brand-Wesselink from Alfam, an ABN AMRO subsidiary, expected a straight-through process. However, she found a lot of variation and only 45% of the cases were processed completely automatically. Using process mining, she found where the rework in the process was.

• Olga Gazina and Daniel Cathala from Euroclear applied process mining to the release process at the Component and Data Management IT division. What made the analysis particularly complex were the configurations and versions that are developed, tested and released in parallel.

• Harm Hoebergen and Redmar Draaisma from Freo showed how their operational management approach incorporates process mining to maintain and improve performance of the loan and credit processes.

• Daan Jabroer from the Volksbank talked about the importance of the collaboration between the process mining analyst and the domain expert at Process Mining Camp 2021 and we discussed process improvement practices with Sudhendu Rai from AIG in the Process Mining Café afterwards.

• Stefan Michel investigated the data quality of a payment process at the Swiss National Bank (SNB). The results of the analysis show that the data that is available via the core banking platform, the Avaloq Banking System (ABS), is appropriate for process mining.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

Insurance companies have been among the early adopters of process mining. The data from their claim handling systems is often very suitable and accessible for process mining.

• The Suncorp commercial insurance branch reduced claims processing times by distinguishing simple and complex claims. Donna Stewart talks about the project in this interview.

• Sebastiaan van Rijsbergen from Nationale Nederlanden talked about the journey of change and how process mining had brought peace into a discussion that was heated by opinions and conflict before. He also joined our change management cafe.

• Mitchell Cunningham from the Suncorp personal insurance branch integrated process mining into their process management methodology. They also explored connecting process mining results to service process outcome measures, like customer satisfaction.

• PGGM applies process mining with a multi-disciplinary team of data scientists and Lean Six Sigma experts. This case study highlights one of their applications in audit, which makes the audit more efficient.

• Roel Blankers from VGZ improved the lead time of the dental care claims process by almost 40%. They are operational visual management to track process performance every day. Lean has been adopted as the problem-solving methodology.

• Dave Jansen and Wilco Brouwers from CZ developed a new approach for auditing their digital processes of the future. They show where they see differences compared to the traditional audit approach in the preparation, fieldwork, reporting, and follow-up steps in their audits.

• Nelleke Smits from a.s.r. worked together with different business units for her process mining projects in the Medical Report, Complaints, and Life Product Expiration areas. During these projects, she realized that different organizational approaches are needed for different situations.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

When you apply process mining to a healthcare process then everything seems to be very clear: The patient ID should be the case ID, the steps are the diagnosis, treatment, or scheduling activities that took place, and the timestamps are the date and time when the activity happened.

In practice, there are quite some challenges that make things more difficult (like the process complexity that you encounter). At the same time, process mining provides many opportunities for healthcare processes, which explains why there are so many application examples from this space.

• David Baltar Boilève from the Hospital Universitario Lucus Augusti analyzed bottlenecks in the cancer diagnosis process. They presented their case here and you can find a PDF version here.

• Fran Batchelor from UW Health explains how surgical services can be analyzed with process mining. She also shared how she had to unfold data for one of her analyses to get a detailed enough view.

• Hilda B. Klasky from Oak Ridge National Laboratory analyzed healthcare data from the Veterans Affairs Corporate Data Warehouse to discover and visualize clinical order processes like the radiology process.

• Luise Pufahl from the TU Berlin and Fran Batchelor from UW Health joined our Process Mining Café about healthcare processes.

• Dennis Arrindell from Social Insurance Bank of Curaçao shared a case study about Process Mining Obstetrical Care Claims Data.

• Miguel Gómez from the healthcare services provider PROA shows in detail how he made the business case for his process mining projects.

• Stefan Wick from Universitätshospital Zürich analyzed hospital business units for a reorganization.

• Muthuvelan Varadharajulu and Jan van Moll from Philips Healthcare have applied process mining to their quality management processes and extended their analyses with the so-called process capability index (Cpk).

• Matthew H. Loxton from WBB contributed a case study that shows how process mining can be used for Quality Improvement. They found opportunities for improvement related to data governance risks, functionality of EHR, and inconsistent use of EHR status and disposition.

• Maxime Parres-Albert and Maxime Brochier from GSK Biologicals analyzed the Human Biological Sample Management (HBSM) process for clinical trials with Disco.

• Bart van Acker from RadboudUMC saw how process mining helped to bridge the gap between process improvement professionals and the medical staff based on the example of the Intensive care unit and the Head and Neck Care chain.

• Earlier case studies show applications at the AMC in Amsterdam, the hospital of So Sebastio in Santa Maria da Feira, Portugal, and the General hospital of Chania in Greece.

• There is also a MOOC and a book about process mining in healthcare. And take a look at our overview about typical data challenges in this area here.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

Government organizations have used process mining to analyze and streamline their administrative processes in many different areas.

• Henrique Pais da Costa from the Brazilian government applied process mining in the Brazilian executive branch. They looked at the production of administrative acts from conception until submission to the legislative branch, represented by the National Congress, or until publication.

• Vincent Veraart, Lewis Ho, and Richard Verheijen from UWV, the Dutch employee insurance agency, shared how they used process mining during the introduction of the temporary (Corona) emergency bridging measure NOW in our process mining café about public administration.

• Youri Soons from the Central Auditing Service in the Netherlands used process mining to make their audit work more efficient. It helps them to find abnormalities in a process (e.g., skipped steps or broken segregation of duties). The auditors can then focus on these exceptions.

• Daisy Wain analyzed the ‘Start a Business’ journey on the GOV.UK website. Rather than just looking at individual parts of the process, they discovered the end to end journeys through both content and services. Daisy also joined our process mining café about customer journeys.

• Wim Leeuwenkamp from the Dutch Tax Office was also at the first process mining camp and shared his experiences from a pilot project in the audit department of the Ministry of Finance. Gathering the data was not easy due to the legacy systems in the IT environment.

• Johan Lammers from Statistics Netherlands (CBS) produces statistics about processes and processes are needed to produce statistics. As a government-funded office, the efficiency and the effectiveness of their processes is important to spend that public money well.

• Zsolt Varga from the European Court of Auditors shows the results from four different process mining projects at different agencies. In some of these projects they could use their own data. In other projects they had to rely on external data from standard and non-standard systems.

• Edmar Kok talked about a project at DUO, the study financing arm of the Dutch Ministry of Education, where a new IT sytem was introduced. Process mining helped to uncover technical errors in the pilot phase. They also defined business KPIs for the new process based on the pilot usage.

• The Social Insurance Bank of Curaçao (SVB) reimburses healthcare providers for delivering obstetrical care (childbirth). In this study, they investigate the claim that there is undue retention amongst gynecologists for clients that initially started their process at the midwife clinic.

Also municipalities have many application possibilities for process mining.

• Wim Kouwenhoven from the City of Amsterdam is responsible for improving and controlling the financial function at the City of Amsterdam. He shares the five-step approach that they used for introducing process mining.

• Léonard Studer from the City of Lausanne was among the speakers of the very first process mining camp in 2012. Three years later, he came back to show a detailed study of the construction permit process. In his process mining café, we talked about being creative in finding data and ethics.

• Arturo Martínez Escobar analyzed the complaints process at the Granada city council. The results of this project changed the point of view of the managers in the department, who initially thought that the negligence of employees was the main cause of the delay.

• Jasmine Handler & Andreas Preslmayr from the City of Vienna audited one of Austria’s largest infrastructure groups: The Wiener Stadtwerke. They used process mining to evaluate the correctness, compliance, efficiency, and expediency of the control system. In the following Process Mining Café with Mieke Jans, we discussed audit standards, new definitions of materiality, and research on how auditors assign risk to deviations.

• David Truffet worked with a local government authority in Australia, where they had to replace an in-house legacy system with a new workflow system. He was asked to document 4 out of 16 processes and their interactions with the back office systems. With process mining they documented all 16 processes in half of the estimated time for documenting 4 of the processes.

• Ellen van Molle and Bram Vanschoenwinkel showed the analysis of an interim sector company (only available in Dutch) at an industry association association event. They investigated the sign-up process of the website for the municipal organization.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

There have been many case studies and experience reports from mining manufacturing processes over the years. It’s always an exciting area because you can see things being made or moved.

• Joris Keizers from Veco achieved a 50% cycle time reduction for their core production process. See also this case study and his interviews.

• Klaus Kühnel and Minh Chau Nguyen analyzed the polysilicon production process at Wacker Chemie AG. One of the projects has resulted in saving the company 17 million Euros per year and another lead to a cost reduction of 400 thousand Euros per year. In the following Process Mining Café with Joris Keizers from Veco, we discussed how you can keep a connection to the physical process when you analyze the data.

• Kevin Joinson GlaxoSmithKline (GSK) developed a new approach for cost deployment. Cost deployment is a method from World Class Manufacturing, where an industrial engineering approach is taken to understand the cost of losses based on 100% of the cost (PDF version).

• Freerk Jilderda from ASML increased the system availability by analyzing and improving lithography system start and calibration sequences. See also this earlier case study of analyzing failure recoveries in ASML’s testing process.

• Giancarlo Lepore from Zimmer Biomet analyzed the material flow in their production process. He compares process mining to the traditional process analysis methods and shows how they were able to resolve data quality problems in their master data management in the ERP system.

• Mick Langeberg from Veco discovered an entire new process ‘From Engineering to Order’ that was not managed before. They could radically accelerate the New Product Development cycle and convert this to an opportunity for faster growth.

• Mark Pijnenburg from Philips Healthcare applied process mining to understand how Philips’ MRI machines are actually used by physicians in the field. The discovered usage patterns increase the test coverage based on real-life behavior for these machines.

• Frank van Geffen and Rudi Niks analyze the IT service management process of Volvo IT. The apply the DMAIC improvement framework.

• Philipp Horn analyzed the world’s largest purchasing process at Volkswagen with Process Mining. He emphasizes the responsibility of the analyst to take all the context information into account.

• Capgemini analyzed the Procure-to-Pay process for AkzoNobel Decorative Paints. 16 local processes could be analyzed in a very short time frame without the need to hold local workshops and process mapping sessions in all these countries.

• This case study shows the first-use consumer test, a version of a usability test, by a television manufacturer. It is one of the earliest applications of process mining to analyze customer journeys (Dutch article).

• See also this example analysis and our process mining café about manufacturing here.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

Logistics and transportation examples often focus on the efficiency but also fluidity of their processes.

• Boris Nikolov from Vanderlande applied process mining in the area of logistic process automation. He validated and optimized test scenarios during some of the most critical phases of a project — acceptance testing and operational trials.

• Christian Pohle from Lufthansa Technik AG used process mining in combination with the Theory of Constraints (TOC) to identify and address bottlenecks in the parts repair process.

• Remco Bunder and Jacco Vogelsang from the Dutch Railway applied process mining on every dataset they could put their hands on. They analyzed the bike rental service, how the lockers at the stations were used, and the resolution of broken windows, escalators, and elevators.

• Marc Gittler and Patrick Greifzu from DHL analyzed the parcel delivery process based on hundreds of millions of events. They also reduced their audit time by 25% in comparison to classical data analytics by using process mining to analyze the quality of their own audit process.

• Marc Tollens from KLM analyzed data from Jira, a project management software for (agile) software development, to see if he can help the teams learn from each other. He compared the flows of three teams to identify key differences in behavior and the resulting effects.

• Zbigniew Paszkiewicz applied process mining to the Inventory Processes Dendro, a mattress production company in Poland. The mining was performed on data coming from the WMS as it is, without any modifications of the system or special preparations.

• Bram Vanschoenwinkel from AE worked with a package delivery company in Belgium, which processes around 300,000 packages on a daily basis. See also their case study here.

• The refund process of an electronics manufacturer in Germany required the coordination of many external entities: repair centers, callcenters, dealers, and logistics companies. Process mining allowed to analyze the end-to-end process across all of these companies (PDF version).

• John Hansen and Claudia Billing analyzed the baggage handling process at Copenhagen Airports A/S. They found that the process bottlenecks were not related to the baggage factory belt performance.

• Walter Vanherle analyzed the operational process at a security services company. Service delivery is managed via contractual obligations based on target performance. One of the challenges was that the data came from multiple devices with different clocks (PDF version).

• Ana Aeroportos is responsible for managing the entire airport infrastructure in Portugal. They analyzed their ITIL “Change Order” process with process mining.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

Telecom and utilities companies have many application possibilities for process mining, both in their administrative as well as work order processes.

• Carmen Lasa Gómez first analyzed the work order process Telefónica. As a result, the percentage of work orders that are performed outside the scheduled window could be decreased from 62% to 5% within just one year. They also discovered a hidden cultural drift in their incident management process (PDF version).

• Gary Bonneau from Cox Communications uses process mining to visualize his own fulfillment processes. The business life cycles are very complex and multiple data sources need to be connected to get the full picture. In the following Process Mining Café with Javier García and Carmen Lasa Gómez from Telefónica, we discussed who owns the process mining data and what kind of skill profile an independent process miner has.

• Gijs Jansen from Essent analyzed the credit insurance process. It was a simple process that was expected to be automated for most cases. However, the process mining results showed the contrary: Gijs found that disputes on contracts required a manual intervention for many cases.

• Abs Amiri from SPARQ Solutions applied process mining to a dispatching process. He identified the factors that were causing bottlenecks and was able to create significant benefits for the call dispatching processes.

• Carmen Vermeer and Noortje Groenendaal from Total Gas & Power looked at the customer journey process at Total. The customer service, billing, sales, and marketing departments are all involved in this customer lifecycle. Instead of looking at these individual departments one by one, Carmen and Noortje analyzed successful and unsuccessful customer journeys from a customer’s point of view.

This article is part of a collection of process mining examples organized by industry. You can find the full overview here.

There are all kinds of software and services companies that can benefit from process mining as well.

• Paul Kooij from Zig Websoftware helped their customer WoonFriesland to improve the housing allocation process by analyzing the data from Zig’s automation platform. He uncovered hidden opportunities to reduce the vacancy time by 4,000 days within just the first six months.

• Jan Vermeulen from Dimension Data showed several applications of process mining for the IT outsourcing services that they provide for multinationals. In one of the use cases, Dimension Data was able to compete in a RfP process for a new customer by providing a customized offer after analyzing the customer’s data with process mining.

• Mieke Jans was among the speakers at the very first process mining camp when she was still at Deloitte. She came back three years later and shared her approach of extracting process mining data from any ERP system.

• Dinesh Das from Microsoft mined the global trade process. He then showed how the discovered business rules can be operationalized as continuous measure fulfillment and create triggers to act using machine learning and AI.

• Erik Davelaar from KPMG demonstrates the added value of process mining for external auditors (and the auditees) this based on three different case studies.

• Internet companies like LOEN Entertainment in Korea are holding voluminous log data that records users’ service usage behavior. LOEN adopted process mining to analyze the user journeys during the day when they signed up with a KakaoTalk account.

• Willy van der Schoot from Atos has worked on the analysis of the incident and change management processes in their Managed Services sector. She shares some tips that have worked for her to keep track of her own analysis and deliverables.

• Vladimir Rubin shares his experience from applying process mining to software processes for a tourism company. He shows how process mining can help to derive the view of the software processes from a technical perspective by analyzing the performance and frequency of calls.

• Legacy systems are old, often mission-critical systems that can cause quite some headaches for their owners. Process mining can help to understand how these systems are used and replace them. We did a whole process mining café about legacy systems here.

• Process mining has many advantages over classical web analytics. What makes it difficult is the complexity of the user journeys: The data needs to be simplified to answer targeted questions. Vanessa Schindler from T4media demonstrates how this works.

• Generating improvement ideas for a website requires that you understand the real customer journey paths. Alexandros Kakakis from Online Dialogue showed how he uses process mining to go beyond a classical funnel view. His colleague Irene Strikkers takes us through their approach based on a concrete project in the process mining café on clickstreams.

• Zvi Topol from MuyVentive analyzed chatbot interactions as an example of how conversational interfaces can be improved.

• In our process mining café about forensics, Lucas Vousten and Vincenzo Salden analyzed a ransomware attack flow with process mining.

• And, just for fun, Hadi Sotudeh from JADS analyzed the 2018 Soccer World Cup data with process mining.

This article is part of a collection of process mining examples organized by use case. You can find the full overview here.

The most common use case for process mining is process improvement. These improvement projects are carried out in the context of existing improvement methodologies, such as Lean, Six Sigma, BPM, PDCA, etc. Process improvement specialists, or centralized process improvement teams, perform the process mining analyses and work together with the business units that are responsible for the process and have the domain knowledge.

• Example project at a loan application process by combining process mining and Lean Six Sigma (see also our Lean Six Sigma café here).

• Christian Pohle from Lufthansa Technik AG used process mining in combination with the Theory of Constraints (TOC) to identify and address bottlenecks in the parts repair process.

• Frank van Geffen and Rudi Niks analyze the IT service management process of Volvo IT. The apply the DMAIC improvement framework.

• Roel Blankers from VGZ improved the lead time of the dental care claims process by almost 40%. They are operational visual management to track process performance every day. Lean has been adopted as the problem-solving methodology.

• Joris Keizers from Veco achieved a 50% cycle time reduction for their core production process. See also his case study that shows how process mining is more accessible than statistical analyses from the classical Six Sigma toolbox.

• Sudhendu Rai shared his experiences of using process mining with simulation at AIG. He shows how they could reduce the cycle time from 12 days to 5 days, increasing the throughput by over 30%.

• Klaus Kühnel and Minh Chau Nguyen analyzed the polysilicon production process at Wacker Chemie AG. One of the projects has resulted in saving the company 17 million Euros per year and another lead to a cost reduction of 400 thousand Euros per year. In the following Process Mining Café with Joris Keizers from Veco, we discussed how you can keep a connection to the physical process when you analyze the data.

• Jozef Gruzman and Claus Mitterlehner from Raiffeisen Bank International share how they use a black-box discovery approach before they explore and review the processes with the subject matter experts in the different countries.

• Léonard Studer from the City of Lausanne was among the speakers of the very first process mining camp in 2012. Three years later, he came back to show a detailed study of the construction permit process. In his process mining café, we talked about being creative in finding data and ethics.

• Bart van Acker from RadboudUMC saw how process mining helped to bridge the gap between process improvement professionals and the medical staff based on the example of the Intensive care unit and the Head and Neck Care chain.

• Sebastiaan van Rijsbergen from Nationale Nederlanden talked about the journey of change and how process mining had brought peace into a discussion that was heated by opinions and conflict before. He also joined our change management cafe.

• David Baltar Boilève from the Hospital Universitario Lucus Augusti analyzed bottlenecks in the cancer diagnosis process. They presented their case here and you can find a PDF version here.

• Carmen Lasa Gómez first analyzed the work order process Telefónica. As a result, the percentage of work orders that are performed outside the scheduled window could be decreased from 62% to 5% within just one year. They also discovered a hidden cultural drift in their incident management process (PDF version).

• Matthew H. Loxton from WBB contributed a case study that shows how process mining can be used for Quality Improvement. They found opportunities for improvement related to data governance risks, functionality of EHR, and inconsistent use of EHR status and disposition.

• Sebastiaan van Rijsbergen from Nationale Nederlanden talked about the journey of change and how process mining had brought peace into a discussion that was heated by opinions and conflict before. He also joined our change management cafe.

• Mitchell Cunningham from the Suncorp personal insurance branch integrated process mining into their process management methodology. They also explored connecting process mining results to service process outcome measures, like customer satisfaction.

• Hilda B. Klasky from Oak Ridge National Laboratory analyzed healthcare data from the Veterans Affairs Corporate Data Warehouse to discover and visualize clinical order processes like the radiology process.

• Earlier health care studies show applications at the AMC in Amsterdam, the hospital of So Sebastio in Santa Maria da Feira, Portugal, and the General hospital of Chania in Greece.

• Niyi Ogunbiyi from Deutsche Bank talked about being clear about what process mining can and can’t do and about finding the right balance between targeted vs. untargeted exploration.

• Nelleke Smits from a.s.r. worked together with different business units for her process mining projects in the Medical Report, Complaints, and Life Product Expiration areas. During these projects, she realized that different organizational approaches are needed for different situations.

• Kevin Joinson GlaxoSmithKline (GSK) developed a new approach for cost deployment. Cost deployment is a method from World Class Manufacturing, where an industrial engineering approach is taken to understand the cost of losses based on 100% of the cost (PDF version).

• Daan Jabroer from the Volksbank talked about the importance of the collaboration between the process mining analyst and the domain expert at Process Mining Camp 2021 and we discussed process improvement practices with Sudhendu Rai from AIG in the Process Mining Café afterwards.

• Henrique Pais da Costa from the Brazilian government applied process mining in the Brazilian executive branch. They looked at the production of administrative acts from conception until submission to the legislative branch, represented by the National Congress, or until publication.

• Capgemini analyzed the Procure-to-Pay process for AkzoNobel Decorative Paints. 16 local processes could be analyzed in a very short time frame without the need to hold local workshops and process mapping sessions in all these countries.

This article is part of a collection of process mining examples organized by use case. You can find the full overview here.

A common use case is the auditing use case. Here, an internal or external audit team analyzes the process with the goal to verify the compliance of the process with existing rules. Efficiency-related findings such as discovered bottlenecks may be shared with the audited business unit as added value but are not central for the audit team. Process mining can, however, also be used to make the audit team’s own auditing process more efficient and increase the level of assurance by basing their assessment on 100% of the data rather than samples.

• Case study series about auditing with process mining. We also recommend to watch this companion Process Mining Café, where the authors of the series walk us through the nine steps and explain how process mining changes the traditional audit approach in each phase.

• Jasmine Handler & Andreas Preslmayr from the City of Vienna audited one of Austria’s largest infrastructure groups: The Wiener Stadtwerke. They used process mining to evaluate the correctness, compliance, efficiency, and expediency of the control system. In the following Process Mining Café with Mieke Jans, we discussed audit standards, new definitions of materiality, and research on how auditors assign risk to deviations.

• Zsolt Varga from the European Court of Auditors shows the results from four different process mining projects at different agencies. See also his summary article on page 68 in this journal or its online version here.

• Mieke Jans and her colleagues wrote this case study about applying process mining during an audit at a bank after the regular internal audit had already taken place. They found many things that the internal audit team had not found.

• Dave Jansen and Wilco Brouwers from CZ developed a new approach for auditing their digital processes of the future. They show where they see differences compared to the traditional audit approach in the preparation, fieldwork, reporting, and follow-up steps in their audits. See also their IIA review here (only available in Dutch).

• Marc Gittler and Patrick Greifzu from DHL analyzed the parcel delivery process based on hundreds of millions of events. They also reduced their audit time by 25% in comparison to classical data analytics by using process mining to analyze the quality of their own audit process.

• Youri Soons from the Central Auditing Service in the Netherlands used process mining to make their audit work more efficient. It helps them to find abnormalities in a process (e.g., skipped steps or broken segregation of duties). The auditors can then focus on these exceptions.

• Erik Davelaar from KPMG demonstrates the added value of process mining for external auditors (and the auditees) this based on three different case studies.

• PGGM applies process mining with a multi-disciplinary team. This case study highlights one of their applications in audit, which makes the audit more efficient.

• Wim Leeuwenkamp from the Dutch Tax Office was at the first process mining camp and shared his experiences from a pilot project in the audit department of the Ministry of Finance. Gathering the data was not easy due to the legacy systems in the IT environment.

• Mieke Jans was also among the speakers at the very first process mining camp when she was still at Deloitte. She came back three years later and shared her approach of extracting process mining data from any ERP system.

• Audit Manager Stefan Michel investigated the data quality of a payment process at the Swiss National Bank (SNB). The results of the analysis show that the data that is available via the core banking platform, the Avaloq Banking System (ABS), is appropriate for process mining.

• Xhentilo Karaj from Euroclear discusses the challenges he has encountered in the data collection, data pre-processing, and data analysis phases of his audits.

• Franck Diafouka, Ruth Zonanashvili, and Mithra Gruber from the European Medicines Agency have established a working group in process mining across several EU bodies.

This article is part of a collection of process mining examples organized by use case. You can find the full overview here.

Process owners are individuals or process teams who analyze their own processes. Their advantage is that they have intimate domain knowledge and know the processes very well. Process owners who become independent from IT and internal consulting groups by getting access to a data export of their own process data can benefit enormously from process mining, because they can act much faster and don’t need to know all of their questions in advance.

• Fran Batchelor from UW Health explains how surgical services can be analyzed with process mining. She also shared how she had to unfold data for one of her analyses to get a detailed enough view and joined our process mining café about healthcare.

• Johan Lammers from Statistics Netherlands (CBS) produces statistics about processes and processes are needed to produce statistics. As a government-funded office, the efficiency and the effectiveness of their processes is important to spend that public money well.

• Gary Bonneau from Cox Communications uses process mining to visualize his own fulfillment processes. The business life cycles are very complex and multiple data sources need to be connected to get the full picture. In the following Process Mining Café with Javier García and Carmen Lasa Gómez from Telefónica, we discussed who owns the process mining data and what kind of skill profile an independent process miner has.

• Lucy Brand-Wesselink from Alfam, an ABN AMRO subsidiary, expected a straight-through process. However, she found a lot of variation and only 45% of the cases were processed completely automatically. Using process mining, she found where the rework in the process was.

• Wim Kouwenhoven from the City of Amsterdam is responsible for improving and controlling the financial function at the City of Amsterdam. He shares the five-step approach that they used for introducing process mining.

• Freerk Jilderda from ASML increased the system availability by analyzing and improving lithography system start and calibration sequences. See also this earlier case study of analyzing failure recoveries in ASML’s testing process.

• Olga Gazina and Daniel Cathala from Euroclear applied process mining to the release process at the Component and Data Management IT division. What made the analysis particularly complex were the configurations and versions that are developed, tested and released in parallel.

• The Social Insurance Bank of Curaçao (SVB) reimburses healthcare providers for delivering obstetrical care (childbirth). In this study, they investigate the claim that there is undue retention amongst gynecologists for clients that initially started their process at the midwife clinic.

• Philipp Horn analyzed the world’s largest purchasing process at Volkswagen with Process Mining. He emphasizes the responsibility of the analyst to take all the context information into account.

• The Suncorp commercial insurance branch reduced claims processing times by distinguishing simple and complex claims. Donna Stewart talks about the project in this interview.

• Giancarlo Lepore from Zimmer Biomet analyzed the material flow in their production process. He compares process mining to the traditional process analysis methods and shows how they were able to resolve data quality problems in their master data management in the ERP system.

• Harm Hoebergen and Redmar Draaisma from Freo showed how their operational management approach incorporates process mining to maintain and improve performance of the loan and credit processes.

• Abs Amiri from SPARQ Solutions applied process mining to a dispatching process. He identified the factors that were causing bottlenecks and was able to create significant benefits for the call dispatching processes.

• Remco Bunder and Jacco Vogelsang from the Dutch Railway applied process mining on every dataset they could put their hands on. They analyzed the bike rental service, how the lockers at the stations were used, and the resolution of broken windows, escalators, and elevators.

• Jan Vermeulen from Dimension Data showed several applications of process mining for the IT outsourcing services that they provide for multinationals. In one of the use cases, Dimension Data was able to compete in a RfP process for a new customer by providing a customized offer after analyzing the customer’s data with process mining.

• This HR process case study analyzed how a bank reacts to requests and questions from employees. They discovered that there were significant delays if a case had to be sent to external specialists.

• Tijn van der Heijden developed a framework for conducting process mining projects and worked with the finance department of the Rabobank to improve their invoicing process analysis.

• Vincent Veraart, Lewis Ho, and Richard Verheijen from UWV, the Dutch employee insurance agency, shared how they used process mining during the introduction of the temporary (Corona) emergency bridging measure NOW in our process mining café about public administration.

• Arturo Martínez Escobar analyzed the complaints process at the Granada city council. The results of this project changed the point of view of the managers in the department, who initially thought that the negligence of employees was the main cause of the delay.

• Bram Vanschoenwinkel from AE worked with a package delivery company in Belgium, which processes around 300,000 packages on a daily basis. See also their case study here.

• Walter Vanherle analyzed the operational process at a security services company. Service delivery is managed via contractual obligations based on target performance. One of the challenges was that the data came from multiple devices with different clocks (PDF version).

• Ana Aeroportos is responsible for managing the entire airport infrastructure in Portugal. They analyzed their ITIL “Change Order” process with process mining.

• Zbigniew Paszkiewicz applied process mining to the Inventory Processes Dendro, a mattress production company in Poland. The mining was performed on data coming from the WMS as it is, without any modifications of the system or special preparations.

• See also this production process analysis and our process mining café about manufacturing here.

This article is part of a collection of process mining examples organized by use case. You can find the full overview here.

A customer journey analysis means that you are taking the perspective of the customer and analyze how they are interacting with your organization (rather than looking at how the internal processes work). Goals of the analysis are typically more qualitative, such as increasing the user experience. Technically, this may involve analyzing click-stream data from the website. But customer journey analysts often analyze the processes across multiple channels as well.

• This case study shows the first-use consumer test, a version of a usability test, by a television manufacturer. It is one of the earliest applications of process mining to analyze customer journeys (Dutch article).

• Daisy Wain analyzed the ‘Start a Business’ journey on the GOV.UK website. Rather than just looking at individual parts of the process, they discovered the end to end journeys through both content and services. Daisy also joined our process mining café about customer journeys.

• Process mining has many advantages over classical web analytics. What makes it difficult is the complexity of the user journeys: The data needs to be simplified to answer targeted questions. Vanessa Schindler from T4media demonstrates how this works.

• Generating improvement ideas for a website requires that you understand the real customer journey paths. Alexandros Kakakis from Online Dialogue showed how he uses process mining to go beyond a classical funnel view. His colleague Irene Strikkers takes us through their approach based on a concrete project in the process mining café on clickstreams.

• John Müller analyzed the customer journeys at ING DIRECT Australia and realized that process mining changed the way questions were asked, because the process mining tool allowed the business users to explore their own process.

• Mark Pijnenburg from Philips Healthcare applied process mining to understand how Philips’ MRI machines are actually used by physicians in the field. The discovered usage patterns increase the test coverage based on real-life behavior for these machines.

• Internet companies like LOEN Entertainment in Korea are holding voluminous log data that records users’ service usage behavior. LOEN adopted process mining to analyze the user journeys during the day when they signed up with a KakaoTalk account.

• Carmen Vermeer and Noortje Groenendaal from Total Gas & Power looked at the customer journey process at Total. The customer service, billing, sales, and marketing departments are all involved in this customer lifecycle. Instead of looking at these individual departments one by one, Carmen and Noortje analyzed successful and unsuccessful customer journeys from a customer’s point of view.

• Boris Nikolov from Vanderlande applied process mining in the area of logistic process automation. He validated and optimized test scenarios during some of the most critical phases of a project — acceptance testing and operational trials.

• Ellen van Molle and Bram Vanschoenwinkel showed the analysis of an interim sector company (only available in Dutch) at an industry association association event. They investigated the sign-up process of the website for the municipal organization.

• Gijs Jansen from Essent analyzed how customer requests were handled, which departments were involved, and how often each request was touched by which employee. This resulted into a new set of KPIs that were discussed monthly to reduce the lead time and to limit the number of touches.

• Frank van Geffen from the Rabobank was one of the speakers at the first Process Mining Camp in 2012 and came back in 2014, where he shared a customer journey use case in which they looked at how customers were using their new mortgage self-assessment tool on the website.

• The refund process of an electronics manufacturer in Germany required the coordination of many external entities: repair centers, callcenters, dealers, and logistics companies. Process mining allowed to analyze the end-to-end process across all of these companies (PDF version).

• John Hansen and Claudia Billing analyzed the baggage handling process at Copenhagen Airports A/S. They found that the process bottlenecks were not related to the baggage factory belt performance.

This article is part of a collection of process mining examples organized by use case. You can find the full overview here.

There are all kinds of IT use cases, from improving software development to replacing legacy systems.

• Edmar Kok talked about a project at DUO, the study financing arm of the Dutch Ministry of Education, where a new IT sytem was introduced. Process mining helped to uncover technical errors in the pilot phase. They also defined business KPIs for the new process based on the pilot usage.

• Marc Tollens from KLM analyzed data from Jira, a project management software for (agile) software development, to see if he can help the teams learn from each other. He compared the flows of three teams to identify key differences in behavior and the resulting effects.

• Vladimir Rubin shares his experience from applying process mining to software processes for a tourism company. He shows how process mining can help to derive the view of the software processes from a technical perspective by analyzing the performance and frequency of calls.

• Paul Kooij from Zig Websoftware helped their customer WoonFriesland to improve the housing allocation process by analyzing the data from Zig’s automation platform. He uncovered hidden opportunities to reduce the vacancy time by 4,000 days within just the first six months.

• Dinesh Das from Microsoft mined the global trade process. He then showed how the discovered business rules can be operationalized as continuous measure fulfillment and create triggers to act using machine learning and AI.

• Willy van der Schoot from Atos has worked on the analysis of the incident and change management processes in their Managed Services sector. She shares some tips that have worked for her to keep track of her own analysis and deliverables.

• Legacy systems are old, often mission-critical systems that can cause quite some headaches for their owners. Process mining can help to understand how these systems are used and replace them. We did a whole process mining café about legacy systems here.

• David Truffet worked with a local government authority in Australia, where they had to replace an in-house legacy system with a new workflow system. He was asked to document 4 out of 16 processes and their interactions with the back office systems. With process mining they documented all 16 processes in half of the estimated time for documenting 4 of the processes.

• Zvi Topol from MuyVentive analyzed chatbot interactions as an example of how conversational interfaces can be improved.

• In our process mining café about forensics, Lucas Vousten and Vincenzo Salden analyzed a ransomware attack flow with process mining.

• And, just for fun, Hadi Sotudeh from JADS analyzed the 2018 Soccer World Cup data with process mining.

Banks and credit card organizations automatically detect fraudulent patterns and block accounts, often before the owners of these accounts notice that anything has been up. Process mining is not the right tool for such fraud detections. However, it can help to understand what happened, for example, by visualizing the intruder’s path.

For our upcoming Process Mining Café about forensics, we have invited Lucas Vousten and Vincenzo Salden from the IT Security team at Joanknecht. We will first talk about how process mining can help in a general IT security context but then dive into a concrete forensics example based on a ransomware attack. Join us!

The café takes place this week, Wednesday 30 March, at 16:00 CEST! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday 30 March, at 16:00 CEST! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session.

This is the 8th article in our series on typical process mining data preparation tasks. You can find an overview of all articles in the series here.

I picked up two little tricks from our customers that I thought could be useful for some of you as well. So, I am sharing them here. They are both related to the Windows command shell.

The first trick is from David. He showed me that you could open the command prompt in the path of the desired folder if you simply type cmd at the top of the folder window.

The second trick is from Maxime, who found out that you can join multiple data sets of the same shape by using the copy command in the following way:

copy /Y *.csv out\combinedfile.csv

You can watch the video above to see how I used both tricks to combine four separate data sets from January to April into one combined file. The combined file can then be imported into Disco.

As a companion to our Combining Lean Six Sigma and Process Mining series, Rudi and I discussed how process mining fits into Lean Six Sigma in the last Process Mining Café. If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Lean Six Sigma is the composition of two methodologies: Lean and Six Sigma. Lean has the goal to create flow and focuses on eliminating waste. Six Sigma focuses on defects and has a more statistical approach. With Lean Six Sigma, both methods are merged and often used with other tools like the fishbone diagram, asking 5x why, hypothesis tests, etc. In the café, we showed how process mining fits both into Lean and Six Sigma based on a concrete example.

We also discussed where process mining changes the traditional approach. For example, data does not need to be manually collected anymore because it is already there. Furthermore, you don’t need statistical measuring if you have the complete data. And finally, most statistical hypothesis tests are not applicable for processes with a large variation because they assume that the data is normally distributed, which is often not the case.

At the same time, data is not everything. Often, the actual root causes are not in the data at all. Furthermore, looking only at data is like searching a needle in the haystack. You need domain knowledge and an understanding of the goals of the process to know where to focus your analysis.

Lean is often used for processes driven by knowledge workers, where there are still a lot of opportunities to improve. When obvious waste is eliminated, one needs to move to a more sophisticated data-driven approach such as Six Sigma. Process mining can be combined with both methodologies and sits somehow in the middle. For organizations who have picked the low-hanging fruits with Lean and for whom Six Sigma with their rigid statistical approach is a bridge too far, process mining provides a way to dig deeper and unlock the next level of improvements. Watch the Process Mining Café session now to learn how.

This session is helpful for Lean Six Sigma professionals who want to understand how process mining fits into their daily practice. But we also encourage all process miners who are new to Lean Six Sigma to educate themselves in these methodologies because they provide a practical and customer value-focused framework for making improvements.

Links

Here are the links that we mentioned during the session:

• Article on how to reduce waste with process mining

• Accelerating DMAIC using process mining

• Christian Pohle from Lufthansa Technik shares how they use process mining with the Theory of Constraints (TOC)

• Roel Blankers shows how they use the A3 approach to keep track of their improvement journey at VGZ

• From the community: In response to our Lean Six Sigma series, Brooks Olphin shared a link to one of his articles that discusses how Measure is already part of the Define phase now

• Our Process Mining Café episode on Change Management

• In the discussion of the Control phase of the DMAIC cycle, we mentioned the presentation by Gijs Jansen from Essent, who held weekly meetings to keep their improvement efforts in check

• Case study and presentation by Joris Keizers from Veco that shows how process mining is more accessible than statistical analyses

• Ian asked about finding failures, and we mentioned the example of how ASML analyzes failure recoveries in their testing process

• Article about the differences between Lean Six Sigma and Data Science (only available in Dutch at the moment)

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

This is the 3rd article in our series on combining Lean Six Sigma and process mining. It focuses on how process mining can be applied in the Measure phase of the DMAIC improvement cycle. You can find an overview of all articles in the series here.

So far, you have established the common expectation that a loan should be provided to the customer within one week (see ‘a’ in Figure 5). Furthermore, you have translated this ambition into two Critical to Qualities (CTQs):

CTQ 1: 90% of the offers should be provided within eight hours after the first customer contact (see ‘b’ in Figure 5).

CTQ 2: 80% of the customers should have certainty about their loan application within three business days after receiving the signed contract (see ‘c’ in Figure 5).

Figure 5: Ambition and CTQs on process map with only approved and rejected applications (mean durations)

As a next step, you want to measure the baseline performance for the overall ambition and each CTQ.

The ambition to provide a loan within one week

To establish the baseline performance for the ambition, you first need to find all the completed cases. To select the 14,761 loans that were either approved or rejected, you can use the Endpoints filter in Disco (see Figure 6). After choosing the ‘Approved’ and the ‘Rejected’ activity as one of the required end activities, you can select the ‘Apply filters permanently’ option to reset the outcome of this filter as “the new 100%” of your data set.

Figure 6: Filtering approved and rejected loan applications to establish the baseline for the ambition

You can now measure the baseline performance for these loan applications to see how many are completed within seven days. To do this, you add a Performance filter and lower the upper case duration boundary to 7 days (see Figure 7). While configuring the filter, you already get an estimate of the number of cases covered by the current selection. After applying the filter, you can see in the final result that 9,782 cases (or 66% of the loan applications - see Figure 8) were actually completed within seven days.

Figure 7: Measuring the baseline for the ambition of completing loan applications within seven days

Note that if you had not reset the Endpoint filter result as your new base dataset using the ‘Apply filters permanently’ option, you would have measured your baseline performance for the initial data set of 20,732 cases. This initial data set would have included cases that were just started or are currently waiting for a reaction from the customer, etc., and not just the 14,761 cases that were either rejected or approved. The outcome would have been the same 9,782 cases, but the percentage would have been different because 9,782 cases are 47% of 20,732 cases. So, the baseline measurement % would not have been correct.

Figure 8: The resulting process map of all loan applications that were completed within seven days

Besides filtering the cases completed within seven days, you can also filter the cases that took longer than seven days (by inverting the selection of the Performance filter in Figure 7). While looking at these applications that took longer than seven days, you notice that the channel caused a big chunk of the delay. Sending the offer package by post and receiving it back from the customer per post adds two to four days to the lead time. Could this be one of the causes of the low conversion at this point in the process?

This finding triggered an interesting discussion. Moving the offline part of the application process to an online channel could significantly speed up the completion time. However, this would require a significant IT investment for the loan provider because they would need to extend the online platform to digitally sign the contract and securely provide the necessary documents for underwriting. And we are not in the improvement stage yet. Let’s keep focusing on measuring the baseline first.

CTQ 1: Offer provided within 8 hours

Establishing personal contact with the customer is an essential step in the process that is also highly valued by the customer. After the online application, the loan provider calls each customer to qualify their needs and provide them with the correct information.

Speed is considered one factor that influences the customer’s decision for a loan provider. Therefore, the management team had agreed that the offer should be provided within eight business hours after the first customer contact (CTQ 1).

CTQ 1 can be measured from the first activity of the process until the ‘Offered’ step. To create the baseline for this CTQ, you start from the entire data set again (not just the completed cases). You want to include the measurement for those cases that have not yet reached the end of the process, but an offer has already been made.

Figure 9: Cutting out the first part of the process (until the ‘Offered’ step) to measure the baseline for CTQ 1

To focus on this first part of the process, you can use the ‘Trim first’ option of the Endpoints filter (see Figure 9), again with the ‘Apply filters permanently’ option enabled to create the new baseline. The resulting process scope is now limited to just the first phase, which provides the correct basis for measuring the baseline for CTQ 1 (see Figure 10).

Figure 10: The resulting process scope for the baseline measurement of CTQ 1

Like measuring the ambition to provide a loan within one week, you can now use the Performance filter to measure how many offers the loan provider delivered within eight hours. The result is that for 3,175 of the 8,038 applications (39% of the cases), the customer service agent made an offer within eight hours.

However, in fact, this CTQ is defined in business hours. The customer contact center does not operate around the clock but six days a week. During weekdays they work from 8 am until 8 pm and from 8 am until 3 pm on Saturday. The non-working hours need to be excluded from the measurement. Otherwise, offers made for applications that came in shortly before the closing of the previous workday and completed immediately after the start of the next workday would (falsely) be measured as not meeting the CTQ.

To measure the baseline in business time as intended, you need to take one extra step: Using the TimeWarp functionality in Disco, you can define the call center team’s working hours. In addition to specifying the working times per day of the week, the holidays (which are whole non-working days) can be eliminated automatically (see middle in Figure 11).

The result is that you only count the “net” time in all the performance metrics. For example, the median time between the ‘Lead’ step (when the application reaches the call center) and the ‘Offer’ step (when the loan provider sends the offer out) changes from 18.6 (calendar) hours to 5.6 (working) hours. The time outside the team’s working time is not counted (see left and right in Figure 11).

Figure 11: The median performance measurements of the baseline process before and after adding the business hours and holidays using the TimeWarp functionality in Disco

The “net” time is also used for the performance statistics. For example, the case durations are now shown in pure working time as well. You could export these corrected business time durations from Disco (see Figure 12) and analyze the capability of the process by evaluating CTQ 1 in Minitab¹ (see Figure 13). It shows that a whole 56% (and not just 39% as was previously measured in calendar time) of the applications resulted in an offer within eight business hours. For 76% of the applications, the call center team could provide an offer within 16 business hours.

Figure 12: The case durations are also shown in business time after specifying the working hours with TimeWarp

Figure 13: The case durations can be exported from the process mining tool to be analyzed in Minitab

You can get the same results when you apply the Performance filter for up to eight hours case duration to the data set that has been corrected for the business time via TimeWarp in Disco itself (see Figure 14). So, it is unnecessary to go to Minitab for the measurement step. We can measure the CTQ directly in the process mining tool.

Figure 14: 56% of the cases meet the CTQ 1 of providing an offer within eight business hours

In addition to the actual measurement of the baseline, a further advantage of using the process mining tool is that you can analyze the process flows, variants, bottlenecks within the process, example cases, etc., in great detail. We will come back to using Minitab and Disco together in a complementary manner in the next phase of the DMAIC cycle.

CTQ 2: Decision within 3 business days

Finding the baseline for the underwriting process is a little bit more complicated. Especially defining the meaning of when exactly there is certainty about the loan is not so easy. After some deliberation, you decide to measure from the moment the applicants returned the signed contracts until the applications were either approved or rejected. To create this baseline, the Endpoints filter in ‘Trim’ mode can be used again as before (see Figure 15).

Figure 15: Creating the baseline for CTQ 2

When you measure the performance based on this baseline, you find that only 41% of the applications were approved or rejected within three days.

When you look further at the process, you find that something strange is happening: It should not be possible that incomplete applications are approved (see the highlighted path on the left side in Figure 16).
 Furthermore, you notice that the Work in Progress graph (via the ‘Active Cases over Time’ statistics) shows a significant drop every 22nd of the month (see highlighted drops on the right side in Figure 16). This means that a large number of cases are completed at the same time (in “bulk mode”).

Figure 16: Incomplete applications are approved (left), and sharp drops in the Work in Progress can be observed each 22nd of the month (right)

You are looking at some examples with the credit manager, and they can explain what happened: Besides the loan product, they also offer a credit product, for which some customers request to receive the payment on the 22nd of the month. In the IT system, the payout is connected to the activation of the loan. Therefore, these applications are (artificially) set into the ‘Incomplete’ mode to delay the payment. On the 22nd of the month, they are then all set to ‘Approved’ to trigger the payment.

This workaround revealed a double use of the ‘Incomplete’ status, which is meant to be used to indicate that a loan application was incomplete. However, the delayed payouts were not incomplete applications at all. This misuse of the system is a data quality problem that needs to be considered for the process mining analysis (and for the reporting). The credit manager nodded and said that she knew something was not right with the current reporting.

Figure 17: Removing the cases that go from ‘Incomplete’ to ‘Approved’

Next to the fact that not all the applications that went through the ‘Incomplete’ step were incomplete, these delayed payouts should also not be measured in our CTQ 2 baseline because the customer already had clarity about their credit loan.

To clean the data, you click on the path from ‘Incomplete’ to ‘Approved’ in the process map and add a filter via the shortcut ‘Filter this path’ (see Figure 17). You can then change the filter settings from ‘directly followed’ to ‘never directly followed’ to remove (rather than focus on) these cases. Again, you check the ‘Apply filters permanently’ option to set the cleaned dataset as the new, corrected baseline (see Figure 18).

Figure 18: After changing the filter setting to ‘never directly followed’, the new (corrected) baseline for CTQ 2 can be created

The corrected data set does not contain any of the “parked” cases in the ‘Incomplete’ status, and the sharp drops around the 22nd of the month have disappeared (see Figure 19). This is now the correct basis to repeat the baseline measurement using the Performance filter.

Figure 19: The corrected dataset for the CTQ 2 baseline measurement

After the correction, the baseline performance measurement of the CTQ 2 went from 41% to 45% of applications that were processed within three days.

However, there is still one more correction to make. Just as with CTQ 1, the definition of CTQ 2 is not actually in calendar days but in business days. Therefore, the weekends and holidays should be excluded from the measurement. As before, this correction can be made by specifying the working days via the corresponding TimeWarp definition.

The credit application team works five days a week from Monday through Friday. Because the SLA is defined in days, you do not need to specify the working hours for these days. Just indicating the working days and excluding the weekends and holidays will give the correct result (see Figure 20).

Figure 20: Specifying the TimeWarp settings to be able to measure CTQ 2 in business days

After this second correction, the baseline measurement for CTQ 2 is established at 62% (see Figure 21).

Figure 21: 62% of the cases meet the CTQ 2 of deciding about the loan within three business days

You notice how the CTQ 2 measurement has gone up from the initial 41% to 62%, which is a big difference! Process mining has helped to accurately measure the CTQ by detecting and cleaning a data quality problem and correcting for non-working time. Furthermore, it has helped build trust with the credit manager, who, by helping you validate the data, gained confidence that the numbers you are measuring reflect the reality and truth of the process.

Stay tuned to learn how process mining can be applied in the following phases of the DMAIC improvement cycle! If you don’t want to miss anything, use this RSS feed, or subscribe to get an email when we post new articles.

As a companion to our ongoing Lean Six Sigma series, Rudi and I will discuss process mining and Lean Six Sigma in our following Process Mining Café this Wednesday.

We will talk about the differences between Lean and Six Sigma, how process mining fits into these existing methodologies, the boundaries, and which developments and misconceptions there are. Join us!

The café takes place this week, Wednesday 2 March, at 16:00 CET! (Check your timezone here). As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe this week, Wednesday 2 March, at 16:00 CET! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session starts.

This is the 2nd article in our series on combining Lean Six Sigma and process mining. It focuses on how process mining can be applied in the Define phase of the DMAIC improvement cycle. You can find an overview of all articles in the series here.

Imagine you are working with the director of a loan provider to address the impact of digitalization on the loan process. Due to falling interest rates, the margins of the loan products are under pressure. Therefore, the yield of these loans cannot be guaranteed in the long term, leading to limitations in funding from the shareholders. The director’s strategy is to grow the portfolio by at least 10% to achieve the same return on investment with a lower interest rate. In addition, the costs have to be reduced by 30% within two years to remain competitive in the short term.

You meet with both the customer contact and credit manager. You immediately sense that they are under pressure as they are knee-deep in a big IT change program. They argue whether this would be the right time to take on yet another project. You know that without their commitment, the project would not even lift off. You need to take an approach that gets their attention without putting even more pressure on the workforce.

Therefore, you request access to the data from the primary loan application system, which processes each loan. A couple of days later, you get your hands on a dataset with all the transactions of the loan applications of the past year (see Figure 1).

Figure 1: Data sample from the transactions in the primary loan application system

The data contains the following information:

• Application ID: The unique identification number for each application

• Status: The name of the step in the process that was completed

• Timestamp: The moment at which the step has been completed

• Resource: The anonymized¹ name of the user who completed the step in the process

• Department: The department of the user who completed the process step

• Amount: The amount of the loan application

• Product: The type of product (application for either a credit or a personal loan)

To start making sense of this data, you quickly get some high-level statistics. For example, using Excel and Minitab², you can find out that:

• On average, 5,099 applications are coming in every month. 22% of them are converted to a loan.
• You can see the frequency of each of the activities.
• The average lead time from online application to payout is 15 days.

However, you are still missing some context to understand what is going on. It would help if you had a deeper insight into the process itself.

Understanding the process

Value Stream Mapping seems like a good next step to better understand the process. However, this would require involvement from domain experts from operational teams. You would need at least a half-day workshop to map the process and another half-day to identify the waste. Therefore, you take a different approach and use process mining to visualize and understand the process.

The transactional data from the loan application system fulfills the minimum requirements for process mining. So, you can simply import the data set into the process mining software Disco.

During the import step, the ‘Application ID’ column is configured as the Case ID, the ‘Status’ column as the Activity name, the ‘Timestamp’ column is configured as a Timestamp, and all the other fields are included as Resource and Other attributes (see Figure 2).

Figure 2: Importing the transactional data from the loan application system into the process mining tool Disco

After pressing the Start import button, the process mining tool now automatically discovers a process map that shows how the process happened based on the data (see Figure 3 - Click on the image below to see a larger version).

Figure 3: The resulting process map (has been automatically discovered by the process mining tool)

From the discovered process map, you can see that 16,846 customers apply for a loan online (see 1a in Figure 3), while 3,886 customers prefer to apply by calling the call center directly (see 1b in Figure 3). You can also see that the automated pre-approval credit check rejected 7,036 customers online (see 2 in Figure 3).

For each application that is not automatically rejected, the customer is called back to establish a personal relationship. On the phone, they check whether the requested loan fits their income. An offer package is sent by post to the customer (see 3 in Figure 3). The customer must then provide the required information, such as bank statements, income statements, etc., and return a signed copy of the contract using the return envelope (see 4 in Figure 3).

The underwriter checks if the application is complete and approves or rejects the application (see 5a and 5b in Figure 3). If needed, additional information is requested (see 6 and 7 in Figure 3). If the customer has not accepted the offer, the application is canceled (see 8 in Figure 3).

Don’t forget to take a step back

One advantage of process mining compared to the traditional Value Stream Mapping approach is that you don’t need to create the process map manually. It is automatically created by the process mining tool based on the data you import. But before you can draw any conclusions from these visualizations, you need to make sure that you fully understand the process to explain your observations.

You feel that you are missing some domain expertise and decide to meet with the managers to share your findings so far. You show them an animation of the process map (see Figure 4). The animation brings the process to life by visually moving each case (here, each loan application) as a yellow token through the process based on the actual timestamps in the data.

The managers immediately start to raise questions about the conversion rates at certain stages and the number of incomplete cases circulating in the underwriting stage. You are happy to have their attention, but you realize that it is too early to discuss the internal process. First, you need to focus on the essentials from a customer perspective.

Luckily, there is an extensive customer satisfaction report, including the CES and NPS scores. This report identifies the price (i.e., the interest) and the speed and ease of the application process as the most important factors for the customer. The latter point has been translated into the ambition to provide a loan within a week.

Together, you plot this ambition on the process and translate it into the following Critical to Qualities (CTQs):

1. 90% of the offers should be provided within 8 hours after the first customer contact.
2. 80% of the customers should have certainty about their loan application within three business days after receiving the signed contract.

Stay tuned to learn how process mining can be applied in the following phases of the DMAIC improvement cycle! If you don’t want to miss anything, use this RSS feed, or subscribe to get an email when we post new articles.

Organizational change is hard. It’s already hard for a single person to change their habits. It’s even harder for a whole organization to change its way of working. There are reasons why things have grown the way they are. But there are also reasons to want to do better.

As a process miner, you run into this challenge as soon as you have identified potential improvements for your organization and need to implement them. How do you get people on board? And how do you get them to stick with you in the new way?

Change management¹ is a methodology for managing an organizational change and guiding people through the necessary transition. We process miners can learn a lot from change management professionals to be more successful. At the same time, process mining can help to support change management in several places as well.

In the last Process Mining Café, Sebastiaan van Rijsbergen (Project & Change Manager at Nationale-Nederlanden) and Roger Schmid (Business Transformation Manager at Stryker) shared their experiences with us. If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Change management is all about people. So, it’s a little bit of a “soft” topic. I encourage especially the hard-core nerds of you out there to tune in and listen to their advice. You need to hear these things more often to build up awareness. And this might just be the missing piece that makes your next process mining project a real success.

Thanks again to Sebastiaan and Roger and all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Good insights alone do not guarantee that the changes will be made. This article by Alexander Van Caeneghem and Jean-Marie Bequevort describes three cases, where their clients did not take any action despite their clear recommendations

• Hand-out with pointers shared by Sebastiaan on Change management approaches (Planned Change vs. Organizational Dynamics, and Kotter as best of both worlds)

• Roger recommends starting with a project charter

• Stakeholder analysis

• Resistance, restraining forces, and force field analysis

• Ethical charter discussion and Process Mining Café about privacy, security, and ethics

• Building the right team: Roles in a process mining project

• Data validation is essential to build trust

Contact us via cafe@fluxicon.com if you have questions or suggestions for the café anytime.

The digital transformation does not only impact the expectation of the customer. It also affects the techniques and methods that companies use to delight customers every day. The Lean Six Sigma methodology has proven itself as a solid approach to continuously improve the quality of products, and how they are produced and brought to the customer. It has its background in the production industry, where it was initially used by manufacturing companies like Toyota, Motorola, and General Electric. It has also been adopted by many service organizations today.

The DMAIC (Define, Measure, Analyze, Improve, and Control) improvement cycle lies at the heart of Six Sigma. It breaks up the improvement cycle into several stages: First understanding the problem, measuring it, then identifying the root cause from the potential causes, and ultimately developing a solution that can be implemented under a control plan. This overarching DMAIC approach remains in place also in the digital era. However, as more and more data is being collected within organizations, new Data Science techniques enter the Lean Six Sigma domain to speed up the DMAIC improvement cycle. This gives the Lean Six Sigma practitioner new perspectives and tools to find root causes quickly.

Process mining is one of these innovations that is an excellent addition for various stages in the DMAIC to analyze the real complexity of value streams. Value Stream Mapping is a great Lean tool to understand a process and identify opportunities to improve. The drawback of this approach is that it can be time-consuming. It requires a lot of effort from the facilitator and experts to elicit all the required information to understand the current situation. It typically takes at least half a day to create a value stream that is aligned with the stakeholders. Another problem is that it is a subjective exercise, which heavily relies on the knowledge of the people involved in the mapping exercise. The participants often have their own view of the processes and represent their own agendas. It is also not possible to capture all the complexity and variations, so you could argue how close it actually represents the reality.

This article series will show you how process mining can be applied as part of a Lean Six Sigma project following the DMAIC methodology based on a concrete example from a loan provider. We show the advantages of using process mining and highlight the limitations from a Lean Six Sigma practitioner’s point of view.

Process mining itself is agnostic with respect to the methodology that is used around it. For example, you can apply process mining in the context of a BPM project, with a Theory of Constraints approach, in a Plan/Do/Check/Act cycle, or, as an auditor, within the audit methodology of an audit practice. However, you do need some methodology around it to interpret the results that your process mining analysis is giving you. 


So, while this guide is written from the perspective of a Lean Six Sigma practitioner, it is also useful for process miners who want to know how they can embed their process mining activities into a framework that helps them to translate their insights into actions that make an impact for the organization, which is, of course, where the ultimate value is for most process mining projects.

Stay tuned! If you don’t want to miss anything, use this RSS feed, or subscribe to get an email when we post new articles.

• Part 1: Define phase
• Part 2: Measure phase
• Part 3: Analyze phase
• Part 4: Improve phase (coming soon)
• …

Process mining as a tool does nothing by itself. The process mining analyst (you!) needs to interpret what they see and do something with these insights. Even if you can identify clear improvement ideas, getting your organization to actually change and implement them is a whole different story.

We process miners can learn a lot from change management and improvement professionals. It is their job to put themselves into the shoes of the people who work in the process. Making sure that everyone is heard helps to build support for the improvement journey.

For the upcoming Process Mining Café, we have invited two change management veterans, Sebastiaan van Rijsbergen from Nationale-Nederlanden and Roger Schmid from Stryker, to talk about the strategies that have worked for them.

Join us on Monday 31 January, at 16:00 CET! (Check your timezone here). We will each share our Top / Flop 5 learning points in this area. And we are curious about yours as well!

As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and join the discussion while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe next week, Monday 31 January, at 16:00 CET! Add the time to your calendar if you don’t want to miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session starts.

We are happy to announce the release of Disco 3.1.

This update brings a new case coverage perspective for analyzing process maps, and makes exporting process map metrics even more straightforward. We have also improved the general performance and stability of Disco, and we fixed a number of bugs and annoyances.

Thanks for your continued feedback, ideas, and bug reports. Keep them coming and, as always, thank you for using Disco!

Case Coverage

Visualizing process maps by frequency is very popular for a reason. It allows you to focus your attention on the mainstream behavior, and fix those problems which occur the most often.

With Disco 3.1, the absolute frequency and case frequency perspectives are joined by a new case coverage perspective. Closely related to case frequency, this metric shows the percentage of cases where an activity or path in the process map has been observed.

Sometimes it is more intuitive to think in terms of percentages, rather than look at total frequency — especially when you are comparing multiple large numbers. Try pairing the new case coverage metric with case frequency as secondary metric for the best of both worlds.

Export Process Map Metrics

Disco is well-known for its clear and beautiful process maps, but did you know that you can also export the raw metrics behind those images?

Every metric that can be chosen as a visualization perspective is included in a separate CSV file, bundled in a ZIP-compressed archive. This is a great, open, and efficient format, which is perfect if you want to use those metrics in other analysis tools.

However, many people have a favorite place for table-based data, and that place is Excel. So, with Disco 3.1 we have included the option to write those same metrics directly to one single Excel workbook, batteries included. Now all you spreadsheet afficionados can dive in straight where you left off in Disco.

How to update

As with every update, this release also contains a number of smaller enhancements and fixes. We recommend that you update to the latest version of Disco at your earliest convenience.

Disco will automatically download and install this update the next time you run it, if you are connected to the internet.

If you prefer to install this update of Disco manually, you can download and run the updated installer packages from fluxicon.com/disco/download

Changes

• Process Map:
  • Introducing case coverage perspective.
  • Increased performance and stability of graph layout¹.
  • Improved compatibility of layout with some legacy versions of macOS¹.
• Process Map Export:
  • Export metrics to Excel workbook.
  • Include case coverage in XML and metrics export.
• CSV Import: Improved performance and stability.
• Filter: Fixed a UI problem when trying to restore invalid recipes.
• TimeWarp: Fixed a regression with bank holidays.

In last week’s Process Mining Café, Stefanie Rinderle-Ma from the Technical University of Munich showed us how their open source process engine steers production processes. A nice side-effect of their system is that it collects data that can be used for process mining again!

We realized that many standard process mining terms could be misleading in manufacturing. We also talked about the power of domain knowledge, how process mining can leverage sensor data, and realistic expectations for automation.

If you missed the live broadcast or want to re-watch the café, you can now watch the recording here.

Thanks again to Steffi and to all of you for joining us!

Links

Here are the links that we mentioned during the session:

• Open-source process engine CPEE
• Case study at Veco shows 50% cycle time reduction for their production process (see also Joris’ presentation at Process Mining Camp 2015)
• Process mining at Wacker has yielded 17 Million Euros savings per year by reducing 1 hour of process time
• Lufthansa has combined process mining with the Theory of Constraints to optimize their parts repair process
• Open PhD positions in Steffi’s group (apply by January 9th, 2022)

Our running list of potentially ambiguous words ended up at:

• Spaghetti diagrams (it’s the name of a different technique)
• Process (be careful, people might talk about chemical or other non-discrete processes!)
• Instance vs. batch
• Process automation (better use orchestration)
• Robotic process automation (which kinds of robots?)
• …

Contact us via cafe@fluxicon.com if you can think of other examples for misleading terminology, or if you have questions or suggestions for the café, anytime.

We are happy to tell you that we have just released Disco 3.0.

Disco 3.0 updates the Disco platform across the board, and it also brings our first fully native release for Apple Silicon Macs – so, especially if you own one of these machines, we recommend that you update at your earliest convenience. This update improves the general performance and stability of Disco, and it fixes a number of bugs and annoyances.

Keep sending us your feedback, ideas, and bug reports, and as always, a big thanks for using Disco!

Performance

This version of Disco improves performance across the board. There is almost no part of Disco that we could not make just a little bit faster, if you can believe it.

And even those parts left untouched work better now, thanks to a comprehensive update of our platform. Most notably, this version of Disco marks our transition to Java 17, which fixes a number of problems and greatly improves performance and responsiveness.

To make sure you can take full advantage of these platform improvements, we recommend that you download and install this update manually.

Apple Silicon

This is the first release of Disco to provide fully native support for the Apple Silicon platform.

When Apple announced their switch to a proprietary, arm64-based processor architecture, they provided the Rosetta 2 translation layer. This allowed applications built for their (now-legacy) Intel platform to keep working well, but of course even a great translation cannot fully match native performance.

With this release, all components of Disco can now be used without Rosetta, which allows Disco 3.0 to use the full native performance provided by the M1 processors. If you have a newer Mac with an M1 processor (or later), you should download and install Disco 3.0 for Apple Silicon manually to get the best performance and user experience.

→ Get Disco 3.0 for Apple Silicon here!

Security

We would like to thank all of you who approached us following the recent disclosure of security vulnerabilities in the log4 library (cf. CVE-2021-44228 and CVE-2021-45046). Fortunately, no version of Disco has been affected by this vulnerability.

We monitor relevant security announcements and check our software stack for known vulnerabilities regularly, and we could confirm that Disco is not affected shortly after publication. However, if you think there is some important news that has not crossed our radar, or you have found a vulnerability in our software, please let us know at security@fluxicon.com anytime.

Like most software, Disco is built on top of many open source libraries we depend on. We regularly update these dependencies along with Disco itself, and these updates frequently contain security fixes. If you are concerned about software security, you should make sure to install updates as soon as you can.

How to update

Disco will automatically download and install this update the next time you run it, if you are connected to the internet.

If you prefer to install this update of Disco manually, you can download and run the updated installer packages from fluxicon.com/disco/download

Changes

• Process Map:
  • Adjust user interface more gracefully for very small screens.
  • Mining very large and complex data sets is now more responsive.
  • Increased performance and stability of graph layout.
• Animation: Better support partial exporting of very large animations.
• CSV Import: Improved performance and stability.
• Excel Import:
  • Improved general reliability.
  • Fixed a problem with reading XLSX documents.
  • Gracefully handle even more unconventional documents.
• Airlift:
  • Smoother user experience when browsing and downloading large and complex data sets.
  • Improved import performance and stability.
• Log Export: Exporting very large data sets is now faster and more responsive.
• TimeWarp: Updated bank holidays calendars.
• Control Center: Extended support for Apple Silicon platform.
• Connection: Increased security and reliability.
• Platform:
  • Native support for Apple Silicon platform (Requires manual installation).
  • Java update (Requires manual installation).

There have been many case studies and experience reports from manufacturing and logistics over the years. It’s always an exciting area because you can see things being made or moved.

In next week’s Process Mining Café, we will talk about process mining research in the manufacturing industry with our guest Stefanie Rinderle-Ma from the Technical University of Munich. She will also take us through their projects with the open-source process engine CPEE.

Join us on Thursday 16 December, at 16:00 CET! (Check your timezone here). Discuss with us about sensor data, automation, and spaghetti diagrams.

As always, there is no registration required. Simply point your browser to fluxicon.com/cafe when it is time. You can watch the café and share your thoughts and questions while we are on the air, right there on the café website.

Tune in live for Process Mining Café by visiting fluxicon.com/cafe next week, Thursday 16 December, at 16:00 CET! Add the time to your calendar to make sure you don’t miss it. Or sign up for the café mailing list here if you want us to remind you one hour before the session starts.

This is a guest article by the Social Insurance Bank of Curaçao (SVB). If you have a guest article or process mining case study that you would like to share, please get in touch with us via anne@fluxicon.com.

The Social Insurance Bank of Curaçao (SVB) reimburses healthcare providers for delivering obstetrical care (childbirth). These reimbursements are processed as claims data and meet all the requirements of an event log for process mining. This case study provides the findings of a process mining initiative applied to obstetrical care claims data in Curaçao, covering three years from 2018 until 2020.

Background

Obstetrical care in Curaçao is provided by two types of healthcare providers: (1) midwives and (2) gynecologists.

In theory, healthy pregnant women should receive obstetrical care from midwives, while at-risk pregnant women should be directed to a gynecologist. In practice, the volume of deliveries at the gynecologist is much higher compared to the midwives.

One particular claim by the midwife clinic is that whenever a midwife sends her client to a gynecologist for a single check-up in the form of a pregnancy ultrasound, the chance is great that this client never returns to the midwife clinic. The claim perpetuated by the midwife clinic is that there is a high level of undue retention of pregnant women amongst gynecologists, especially of clients that initially started their process at the midwife clinic.

Another relevant consideration is that some women may prefer to be treated by a gynecologist rather than a midwife. In case of an emergency during labor, the woman needs to be transported to the gynecologist at the hospital in a rushed fashion. The midwife clinic is at least a ten-minute ambulance drive from the hospital, not including response time.

These claims and considerations merit deeper analysis to understand the patient journey of pregnant women. Because the obstetrical process has a clear beginning and end, process mining is perfect for analyzing this case.

Research questions

We formulated the following research questions to guide the process mining project.

1. What does the overall obstetrical process look like?
2. How is the interaction of women flowing between the gynecologist and the midwife clinic?

Remember that the SVB is not an active player in this process but merely a passive purchaser of the services. The focus of this process mining project is not to improve operations. Instead, we want to test the validity of the claim that gynecologists “steal away” patients from the midwife clinic.

Data pre-processing of gynecologist claims data

The activities in the event log of the gynecologist are based on ‘fee-for-service’ claims. As a result, each activity is recorded on a fairly detailed level with its corresponding timestamp. The timestamp contains the date but no hours or minutes.

Our analysis of the gynecologist claims dataset required us to understand what distinguishes a gynecological process from an obstetrical process. All gynecologists in Curaçao are OB-GYN doctors, which means that they deliver both obstetrical (childbirth, or OB) and gynecological (female reproductive system, or GYN) care.

Most care delivered by OB-GYN doctors in Curaçao is GYN-related, not OB. Including all GYN-related cases in the analysis results in a process map that downplays the OB process because the associated frequencies of OB care are smaller. However, without any medical domain knowledge, it can be challenging to discern which activities are OB and which are GYN.