Process Mining Café
Process Mining Café is a podcast by Fluxicon that explores the world of process mining. Each episode features conversations with experts and practitioners, discussing the latest trends, tools, and real-world applications. The show aims to make process mining accessible and engaging for both newcomers and seasoned professionals.
Afleveringen
1: Data Requirements for New IT Systems
Imagine your company introduces a new IT system and you have the opportunity to influence the data that will be collected. You want to make sure that the data is suitable for your process mining analyses in the future. Which data properties exactly will you need to ensure in the new system? We made a checklist for you, so you don't forget something essential.
2: From Research to Practice
Our conversation with Hajo Reijers, Professor for Business Process Management & Analytics at Utrecht University. We talked about how processes are made of people, his interest in empirical research methods, industry cooperations with master students, two new research papers from this year and many other things.
3: Customer Journey Analysis
In a customer journey analysis, you look at the process from the viewpoint of the customer. Daisy gives us an overview about her recent analysis of the user journey on the “Start a Business” part of the GOV.UK website, and Rudi takes us through the three main challenges that you will encounter when you analyze customer journeys with process mining.
4: Legacy Systems
Legacy systems are old, often mission-critical systems that can cause quite some headaches for their owners. Replacing these old systems is not easy, precisely because so much knowledge has been poured into them. Derek Russell and Steve Kilner joined us to talk about the different approaches to legacy system mining.
5: Healthcare
Healthcare is a very interesting but also challenging application area for process mining. For example, a data set with 1000 cases can easily have 1000 variants, because every patient follows a unique path. Together with Luise Pufahl and Fran Batchelor we discuss the specific challenges of the healthcare domain along the phases of a typical process mining project.
6: Freestyle Data Transformation
What can you do if your data — at least at first sight — does not seem suitable for process mining at all? You look for “sequences of stuff”. Léonard Studer shares three examples of how he transformed problematic data, created non-existent data from file system logs, and even manually transcribed data in different scenarios.
7: Public Administration
Introducing process mining at an organization is never easy. Together with Vincent, Lewis, and Richard we talk about the strategies that worked for UWV, and about the success factors for one concrete project. All their tips are relevant not only for public administrations but for all organizations who want to introduce process mining.
8: Strategy and Execution
There is often a divide between the strategy and the execution world in process mining. The people who are dealing with strategy are different from the people who are executing. Bogdan Ciungu joined us to discuss how organizations can bridge this divide. We talk about use cases, RFIs, and we show a concrete example for a business case.
9: Privacy, Security, and Ethics
Process miners need to be aware of their responsibility, both around the data and in how they present their analysis results. Together with Dirk Fahland and Felix Mannhardt we share many practical tips that you can start implementing today. We also discuss new research in the area of responsible data science.
10: Perspectives
When you analyze a data set with process mining, you take a process perspective on your data. This perspective is determined by what you choose as the case ID, activity name, and timestamp during the import step. Marco Montali talks with us about the various process mining perspectives and their ontology-based data extraction approach.
11: Manufacturing
Stefanie Rinderle-Ma 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 also talked about the power of domain knowledge, how process mining can leverage sensor data, and realistic expectations for automation.
12: Change Management
Organizational change is hard. As a process miner, you run into this challenge as soon as you have identified potential improvements 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? We talked with Sebastiaan van Rijsbergen and Roger Schmid about the strategies that have worked for them.
13: Lean Six Sigma
The Lean Six Sigma methodology provides a practical and customer value-focused framework for making improvements. Rudi and Anne talk about how process mining fits into Lean and Six Sigma, based on a concrete example. We also discuss where process mining changes the traditional Lean Six Sigma approach.
14: Forensics
Process mining may not be the right tool for fraud detection. However, it can help us understand what happened after an attack, for example, by visualizing the intruder's path. Lucas Vousten and Vincenzo Salden talk about how process mining can help IT security and dive into a concrete forensics example based on a ransomware attack.
15: Simulation
What if you had twice as many people? What if you didn't do that process step? Simulation allows you to test complex “what if”-scenarios without having to make the change in the real world (yet). But it's not easy! Together with Lambros Viennas and Sudhendu Rai we show how you can use process mining as a starting point for your simulation model.
16: Project vs Process
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? We speak with Fred van Middendorp about project vs. process thinking.
17: Data Quality
Garbage in, garbage out! 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. With Kanika Goel and Niels Martin, we talk about the specific data quality problems you encounter in process mining projects.
18: Process of Process Mining
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? Pnina Soffer, Barbara Weber and Francesca Zerbato share their experiences from this new sub-field in the process mining research area.
19: Auditing
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 talk about their data-driven audit approach with process mining step by step.
20: Game Analytics
Magy gives an overview of the different types of games and traditional game analytics. We look at examples, where her group has used process mining to understand the flow of games. We also talk about the ethics of using game analytics to make games more addictive and discuss the challenge of abstracting the data to the right level.
21: Measures and Targets
Jan and Muthu have applied process mining to their quality management processes. On top of that, they have also extended their analyses with the so-called process capability index (Cpk). We show, based on a concrete process mining example, how this works. And you can even try the approach yourself by using their Excel template.
22: Data Preparation
Getting the data is often one of the first challenges you have at the beginning of your process mining project. Rudi and Anne answer the most frequent questions around process mining data. We also show you two common data transformations based on a practical example: One for merging two data sets and one for transposing a data set from columns to rows.
23: Public Policy Evaluation
If you are creative, you can find process mining data in unexpected places. Nuno shows 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.
24: Project Planning
Rudi and Anne talk about what it takes to make a good project plan. We first discuss the criteria for selecting a process for your process mining initiative and then go through the five ingredients of your project plan. Rather than just a big, scary document, the project plan is there for you and helps you manage the risks and communication points in the team.
25: Analysis Transformations
The data 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. Together with Scott, we look at two concrete examples to illustrate the steps in such transformations.
26: Data Collection
What do you do if you want to do process mining but you don’t have any data? Tobias found an elegant solution: He created a system that allows employees to collect data about process executions in a lightweight and system-independent way. One advantage is that this internal system has privacy considerations built-in.
27: Activity-Based Costing
In Activity-Based Costing, indirect costs such as salaries and utilities are tied back to products and services. If you combine Activity-Based Costing with with process mining, then you can allocate costs to activities in your processes and evaluate “buckets of cases” according to their costs for the organization. Willem and Anne show how this works based on a concrete example.
28: Role of the Analyst
Hugo walks 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.
29: HR Processes
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: One bottom-up approach and one top-down approach using the APQC standard process framework.
30: Urban Mobility
Andrea and Daniel 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. We discuss their project and Andrea and Daniel give you all the information that you need to reproduce their steps.
31: Business Cases
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. Rudi and Anne recommend keeping it simple, and Miguel shares how they increased revenue by 6 million Pesos (350,000 USD) without hiring additional people.
32: Analyzing Variants
Variants are sequences of activities, and they are their own dimension in process mining. They complement the process map by providing a scenario-based view of the process. Looking at the variants can give you many insights. But the crux is ensuring your variants are meaningful before you analyze them. Rudi and Anne show how to elevate them to the right level.
33: Camp 2024 Recap
We review what we learned at Process Mining Camp 2024. At camp, we immersed ourselves for two intense days of exchanging knowledge with our fellow process miners. Bhawana was a first-time attendee, and Lieven was a speaker at this year’s camp. They share their takeaways, and together, we retrace the steps of these two days.
34: Audit Research
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 talks about the benefits of using process mining as an auditor and presents two recent research works by her and her team.
35: Automation
Many companies use or plan to use automation techniques to reduce manual labor. But which parts of a process can be automated, and which parts should be better kept human? Erik and Lloyd share how they use Disco to analyze the performance of their RPA robots, identify new automation opportunities, and analyze their training processes.
36: Preprocessing
Some preprocessing tasks can be easily done in Disco. Others require the use of data transformation tools. Xixi has classified the common preprocessing tasks for process mining into six categories: Enriching, Integration, Filtering, Transformation, Reduction, and Abstraction. For each category, we discuss concrete examples from practice.
37: Explorative Analysis
When you import your data set, you first have to look around and get an overview about your process. Where does it start and where does it end? Can you recognize the expected process? Is there a lot or little variation? Do you see rework or other unexpected patterns? Join us as we discover the loan application process from the BPI 2016 dataset.
38: Challenges
Vinicius, Rudi, and Anne talk about the common challenges and best practices for process mining. They discuss 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 café to find out!
39: Clickstreams
Clickstreams are the digital traces that visitors leave when they navigate through a website. You can then analyze this data with process mining to make the website more effective or user-friendly. Irene shares her experience of a recent clickstream analysis project. We discuss why the funnels of traditional web analytics are not enough to understand behavior.
40: Comparisons
How do you determine what you should compare in a process? Hanna discovered a process at her bank for three different regions. She analyzed the case durations but also rework, parallel vs. sequential flows, and long waiting times. After understanding the different process characteristics in each region, Hanna identified best practices for improving them.
41: Building Trust
Data protection teams, the works council, and process owners need to trust that you will act responsibly in your process mining project. How do you address their concerns? We talk with Daniel about the organizational side (who to involve when and how) as well as technical steps you can take, such as removing unnecessary information, anonymization, and pseudonymization.
42: Clinical Pathways
Healthcare processes are complex due to the individuality of each patient, so process mining is particularly useful for understanding them. Process maps Owen's research group discovered at a UK hospital illustrated how often patients were misdiagnosed and sent around. Owen talks about their studies as well as their methodological framework for process mining in healthcare.
43: Workshops
When Linda took over the process improvement team, she realized that meeting with domain experts for two hours per week on a project did not lead anywhere. After she switched to full-day workshops, everyone noticed that it was significantly better. They have gained focus and obtained much better results. Linda shares step by step how she prepares and runs these workshops.
