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  • SPOTLIGHT - What is process mining?

  • SPOTLIGHT - What is process mining?

March 2021

In this issue, we talked to our colleague Wiebke about Process Mining.

What is process mining — how can we imagine it?

Simply put, process mining is a process analysis. This means it is a technical solution that can show a real-time image of process flows based on data from the IT system. This gives businesses an objective, data-driven look at their processes and the various process paths. The goal of process mining is always to expose process inefficiencies.

Can process mining be implemented by anyone, or is it specifically for companies that are already digitized?

There are various process mining tools on the market. It’s important to have the right basis of data. This applies to any data project. The outcome succeeds or fails based on the data quality.

For process mining, we need a digital footprint: ID, time stamp and event — who does what when. Any system can be connected to a process mining tool. We are certified as data engineers and analysts. This means we can perform the entire process, from data acquisition and the data connection to the process mining tool, all the way to data analysis.

How do you see process mining adding value for the customer?

In recent years we’ve strongly focused on data visualization. We have visualized data using various tools and gotten good insights from them. However, the focus was always on key performance indicators (KPIs) that we looked at during a specific point in time.

But we want to be able to analyze and view entire processes and process chains. Where does a process start and end, and what various process activities and process paths exist overall? This means that by looking at a KPI, I can say, for example, whether they match the goals management has set and what actions I can derive from it.

By looking at a process chain, on the other hand, I can see where the real inefficiencies in my process are and where costs can be reduced or where customers are lost in the process, for example. This allows a data-driven decision on where and how I have to optimize my process.