Process Mining Café 6: Freestyle Data Transformation

Process Mining Café 6

Léonard Studer is an internal consultant for business process management at the City of Lausanne and a true process mining veteran. After having him as a speaker at our very first Process Mining Camp in 2012, we brought him back in 2015 with an honest and in-depth talk about their analysis of the construction permit process.

Along his journey in process mining, Léonard has developed a habit for finding data in rather unusual and unexpected places. We have asked him to join our next Process Mining Café to share his experiences of what else you can do if your data — at least at first sight — does not seem suitable for process mining at all. So, if you need some inspiration, or just want to hear his process mining war stories from the City of Lausanne, don’t miss our Process Mining Café next week!

Join us on Wednesday 28 April, at 16:00 CET! (Check your own timezone here).

As always, there is no registration required. Simply point your browser to 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 next week Wednesday 28 April, at 16:00 CET!

Project Guide – Part 1: Process Selection

We have discussed a lot of practical process mining topics here on the blog over the past years, but one thing that is still missing is a step-by-step project guide. This is what this new series is all about.

  • Step 1: Process selection (this article)
  • Step 2 - 12: Coming soon

Today, we start with the first step in any process mining project: The selection of the process that should be analyzed (see below). The other steps will be added in future editions and linked from here.

Process Selection

When you start out with process mining, it is often not so easy to know where to start. Which process should you pick first? And which process might be less suitable for your process mining project?

In a previous article, we identified data availability and process awareness as two key ingredients to judge the suitability of a process for process mining. Read it here to see the detailed break-down and recommendations.

In addition, consider the following tips as well:

  • Agree on the scope. Make sure that everyone has the same understanding of where the process starts and where it ends. Often, people have a different process scope in mind while they are using the same process name (for example, “Is invoicing still part of the purchasing process?” or “Will the pre-operative care be included in the analysis of the surgery process at the hospital?"). All stakeholders should agree on the same process scope.

  • Ensure champion support. Just as important as the data availability is a good support from the team that is responsible for the process. You will need access to a domain expert who knows the process well and can answer questions during your analysis. Without the support of a good champion, you will hit a wall of questions very quickly. Process mining does not happen in a vacuum and an unavailable project sponsor who wants a “surprise me” analysis is a red flag. You also need the support of the process manager in defining the main analysis goals for the process mining project.

  • Keep an eye on improvement potential. If you need to choose a process among multiple good candidates, pick the process that is most relevant and has the most improvement potential. Unless you just want to play around for learning purposes, there must be an interest from the business in the results of your process mining analysis. You can either assess the improvement potential with a classical business case analysis or base the decision on the gut feeling and anecdotal evidence from the process experts. If you still have a tie between multiple processes, go for the one with the highest volume (for example, based on the number of cases that are processed).

Have you picked your process? Then you can move to the next step: Making your project plan.

Process Mining in Healthcare

In last week’s Process Mining Café, we talked about process mining in healthcare with Luise Pufahl, a postdoctoral researcher at TU Berlin in Germany, and Fran Batchelor, a nursing informatics specialist at UW Health in the United States. You can now watch the recording here.

When you apply process mining to a healthcare process then at first 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. However, there are many challenges that make things more difficult in practice.

We discussed the specific challenges of process mining in healthcare along the phases of a typical process mining project.

1. Scoping

First, you need to answer the question where does the process start and where does it end? Simply taking the patient ID as the case ID means that the scope spans the lifetime of the patient. Usually, this is too big and you want to limit the analysis to a smaller scope like a surgery. Another way to focus the analysis is to select a subset of activities, for example, based on the medical guidelines for a specific diagnosis and treatment pathway.

2. Extracting and preparing the data

During the data preparation, often different data sources need to be merged to get all the information that is needed. In this phase, understanding the data and dealing with data quality issues are the biggest problems. For example, there can often be data quality problems if the data is manually recorded. As more data is collected automatically (also by medical devices), the availability and quality of the data improves while data privacy concerns become more important as well.

3. Dealing with complexity

Once you import your data set into Disco, you need to deal with the complexity of the process even more than you would for most other processes. For example, it can easily happen that a data set with 1000 cases has 1000 variants, because every patient follows a unique path. The grouping of cases, leaving out details, activity aggregation, but also unfolding can help to get the data set to the right level for the analysis.

4. Analyzing and communicating the results

To interpret the analysis results correctly, domain knowledge is very important. The process visualizations that can be produced with process mining are more complicated than the manual Visio models that are often traditionally created, because they show all the unexpected flows, exceptions, and inefficiencies. However, in contrast to the manual models they show the actual flow of the process and help a lot in the communication with the medical staff.

Thanks again to Luise and Fran, and to all of you, for joining us!

Here are the links that we mentioned during the session:

Disco 2.12

Software Update

We are happy to announce that we have just released Disco 2.12.

We recommend that you update at your earliest convenience. Like every release of Disco, this update fixes a number of bugs and improves the general performance and stability. It especially increases performance for Airlift connections, and improves robustness when connecting to legacy endpoints.

Thank you all for sending us your feedback and bug reports, and thanks for using Disco!

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


  • Improved support for new Airlift endpoints.
  • Handle legacy Airlift endpoints more gracefully.
  • Bug Fixes and Performance Enhancements
Process Mining Café 5: Healthcare

Process Mining Café 5

It has been great fun to catch up with all of you in our Process Mining Café every month. We will be back in the café next Tuesday, and our topic for this session is process mining in healthcare. Healthcare is such an interesting area for process mining, because although you can expect many challenges, there are also so many opportunities.

Join us on Tuesday 23 March, at 16:00 CET! (Check your own timezone here)

We have invited Fran Batchelor from UW Health, a nursing informatics specialist who has been analyzing the flow of surgical processes for several years. We will also be joined by Luise Pufahl, a postdoctoral researcher at TU Berlin who is specializing on healthcare processes and logistics in her research. Together, we will discuss what is difficult, but also why it is so worthwhile to apply process mining in healthcare.

As always, there is no registration required. Simply point your browser to 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 next week Tuesday 23 March, at 16:00 CET!