Success Criteria for Process Mining
This article has been previously published as a guest article on KDnuggets, on the Data-Science-Blog (German), in the AutomatiseringGids (Dutch), and in the Process Mining News.
By using Process mining, organizations can see how their processes really operate. The results are amazing new insights about these processes that cannot be obtained in any other way. However, there are a few things that can go wrong.
Process mining doesn’t usually begin as a top-down initiative. Typically, there are a few enthusiastic people who want to do something with it. When they start a process mining initiative within their organization, they need to bypass the following classic pitfalls.
First of all: Being too fascinated with the technology itself can lead to an inability to show the added value from a business perspective. Secondly: An unrealistic image of the data availability, coming from the promise of Big Data, can lead to overblown expectations. And the third pitfall: Due to a wrong understanding of what process mining can do, the first project is often too ambitious in scope. Too much is being promised and it takes too long before the first results can be shown. This undermines the belief within the business that process mining produces a good ROI. A failed project then not only leads to a decrease in the entrepreneurial and innovative spirit among the process mining enthusiasts, but there is also the risk that process mining will not be picked up again in a new project for years.
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