When people hear the words data mining, they nowadays have an idea what it means. With data mining we often mean a process of analyzing data from several perspectives and summarizing it into useful information. With the support from this information we can then make decisions that affect the success of a company. However, if data mining is familiar to people, process mining still seems to be a new topic for many. Very often I encounter the questions “What is process mining? What do you do when you do process mining?”
On a general level, with process mining we aim to do the same as with data mining; to analyze data from different perspectives and summarize it into information that can be used when making business decisions. But this time the context are the business processes of an organization. In process mining we take the data that exists in the information systems of a company and use that to visualize what is actually happening in the company’s processes and how they are executed in real life. Almost all IT systems store data in data bases and create logs that can be described in process mining terms as event data. This is the basis for process mining and the analyses conducted.
Why Process Mining?
Process bottlenecks are often hidden. People have a gut feeling what could be wrong or inefficient but they lack proof. They don't have the data to back their assumptions. This is where Process Mining comes into the picture. One of the main goals in process mining is to be able to see the big picture of a company’s business processes and still be able to drill down to the root causes of e.g. deviations, bottlenecks, or process variations. With process mining we don’t have to settle for averages but dig out the reasons behind unwanted behavior. To bring this closer to organisations and industries, I’ll give a couple of examples.
Where can Process Mining be applied?
Process Mining fits for any industry and process. The requirement is having data that can be used as basis. Most companies having an IT system supporting business have this data.
In manufacturing industry a timely and accurate delivery to a customer is the ultimate goal. If a company has several factories in different regions, there usually are differences between the reliability of deliveries. It’s quite easy to see they exist but harder to understand exactly where or why that is. Also, very often people with the loudest voice gets the most attention regardless of whether their problems actually are the biggest. With process mining we can compare objectively the performance of different regions down to individual process steps, duration of a step, cost of a step, or the person performing the step and many more. Whatever event data is available in the systems it can be used in process mining.
In financial sector it is crucial to follow rules and regulations and to be able to prove you have done so. By using the event data from the systems we can visualize even individual cases as a process flow. We can also show how often deviations and variations occur and what has been the reason causing these. With process mining we can both prove our actions but also pinpoint the improvement needs in the business processes.
To summarize; in process mining we use the event data in company IT systems to bring insight to the company’s business operations. This we do by visualizing the data in process context (e.g. process flow charts) and creating analyses that give information on needed improvements and deepen the understanding of what is going on in the business processes. We can show both the big picture as well as the detailed ground-floor view on process execution.
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