Episodes
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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. -
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. -
Episodes manquant?
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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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. -
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. - Montre plus
