An introduction to Process Mining

When you ask a Process Owner about how their process is being performed, or look how it is documented, the structure is typically relatively simple (“First we do A, then, we do B, etc.”). In reality, processes are much more complicated than they may seem at first.

Sometimes, you have to redo certain steps because they weren't done right initially. Special situations require handling things differently, and different people may approach the same process in their own unique ways. There is a clear difference between how people think processes work and how they actually happen in practice. In fact, usually processes are so complex that nobody has an overview about how the real process looks like in the first place.

Process mining software (e.g. Celonis, Disco, Signavio etc) fills that gap by showing the process reality based on actual data, that is extracted from IT-supported log systems. They build the "As-is" process maps by tracking at least 3 attributes: Case ID, Activity and Timestamp.

Process mining shows us how the process is performed in real life, allowing a comparison between real vs desired/assumed process.

If a discrepancy between the assumed process and the process reality emerges, there are multiple actions that the Process Owner can take:

1. If the process really should be performed as it is documented, you may want to enforce the process in reality. This can happen, for example, through a system change or by a targeted training to teach people how to work differently. BPM tools have a feature that allows you to track that adherence: "Conformance".

2. Sometimes, you will find that your understanding of the process was wrong, and that what is happening in reality actually is the real process as it should happen, or needs to happen. You will then revise your picture of the assumed process—either in your head or in the documentation.

3. Finally, there is also a third option: You may find that, quite often, there are certain discrepancies that do not necessarily need to be reflected in the documented process. Typically, you do not want to have every little exception in your process documentation, because the documentation is supposed to show the normal process. But it will still be very useful to know about these discrepancies to improve the process and have a complete picture of what is actually happening.

The key point is that you need both sides of the picture to decide which of these three consequences are appropriate for your process. Process mining does not tell you what is right but enables the comparison by filling the gap of how the process is running in reality. How it works? Celonis automatically discovers a fact-based process visualization out of the raw IT data and shows you how the process was actually performed. By using process mining, the actual ‘As-is’ process can be shown right away. It can then be interactively analyzed with the subject matter experts to quickly find problems and improvement opportunities. The benefits are faster and more accurate insight into the actual processes, speeding up process understanding and providing transparency about the processes that are really happening. What is Process Mining, and what it's not? In addition to understanding the typical Process Mining Use Cases it is also important to understand what process mining is not. Process mining is an analysis tool while BI-dashboards are for monitoring and reporting. These are different use cases. A process mining analysis can result in a new KPI that then should be monitored, but it can also lead to a process change. In a BI dashboard or reporting environment, you focus on a limited number of characteristics that you want to see every day. In contrast, with process mining as an analysis tool you explore the process from the ground up and into many different directions. The goal is to first understand the process in detail. Process mining is often used in interactive workshop sessions, where you analyze the data together with a process expert. The process expert can point out things you might otherwise miss and, together, you can immediately answer any question that you come up with right there and then. With a dashboard tool, you can’t have such interactive analysis sessions but that’s also not their purpose. Their purpose is monitoring, not analysis. It's critical to point out that Process mining does not automatically identify improvements and suggestions for your process. This is not possible, because you need an understanding of the process and domain knowledge to interpret the process mining results correctly. For example, sometimes a loop pattern in the process is an indication of excessive rework, sometimes it is a good thing, and sometimes it does not mean anything.