From Implementation To Value – Making Process Mining Simpler

From Implementation To Value – Making Process Mining Simpler

The gap between successfully transforming and unsuccessfully transforming companies is widening and unsurprisingly, the market shows that those who do not keep up are left behind.

Transformation in the new

The gap between successfully transforming and unsuccessfully transforming companies is widening and unsurprisingly, the market shows that those who do not keep up are left behind. By now, every business function has seen multiple transformational and so-called “digital” projects kicking off, most of them including new technologies or software applications. Many projects are successful, but just as many fail to deliver what was planned.
When it comes to Process Mining, many organizations struggle to initiate the process of continually setting up and completing separate improvement projects after they completed the implementation and go their software of choice up and running. The question at hand is, what is crucial to ensure real value creation after this initial set-up?
While the term “digital transformation” implies a one-dimensional and clear, linear process, it isn’t. Every company has its own framework and structure, and every transformation is different. Organizations need to define their own strategy, and if Process Mining is part of your digital transformation, there are crucial matters to look out for, especially after implementing Process Mining and beginning to create value.  


1.    Don't start with the largest project.

It might be tempting to start off with the largest improvement project, but often, the largest project is complex, multilayered and brings a lot of change with it. For long-term success, it is better to begin with an important, yet small and clear-defined improvement project. It will more likely take off, deliver good first results and convince managers and leaders across the organization of the approach, while the right stakeholders build valuable hands-on experience with Process Mining. When too much is being promised and it takes too long before the first results can be shown, the belief that Process Mining produces a good ROI is undermined. A failed project or unmet goals then not only lead to a decrease in the innovative spirit among the stakeholders, but there is also the risk that Process Mining will not be picked up again for new projects.

2.    Begin with hypotheses.

Insights don’t come from nothing. In other words, well-organized data without context and intuition will neither bring you insights nor recommendations for action and change. Separate areas of applications (e.g. conformance, network analysis, cycle times, automation, etc.), and further divide those into narrow hypotheses that you can confirm or disprove with Process Mining. Start off with something like “There is a gut feeling that this sub-process takes too long”. From there, you can start working: How long does the process really take? How much does it deviate from the expectation? Which product groups deviate the most? Where are the bottlenecks that cause the delays for this product group in this process? What can we change here?

3.   Don't do everything at once.

Don’t try to immediately answer all questions. The first insights often raise further questions, which in turn requires further analysis. When managers try to answer all possible questions and dive into multiple topics at once, the risk of getting lost in the data and its possibilities is shockingly high. This is also known as “analysis paralysis”. Start with the initial hypothesis, deliver actionable insights, act on them, and then continue with the next hypothesis or topic.

4.    Be clear on goals.

The three key questions that your organization or project team needs to answer are: Where do we stand? Where do we want to go? Finally, how well did get there? Ensure checkpoints anda clear orientation on what must be delivered.

5.   Don't put all eggs in one basket.

There are often multiple ways to get answers for your questions, and often it is useful to combine multiple data analysis techniques, BI tools and stakeholders to get the full picture. Do not become fixated on ‘only’ using Process Mining and don’t underestimate the value of different perspectives. Whether it is your BI tool of choice or surveys of business stakeholders, make complementing Process Mining insights with other sources of information part of your strategy.

6.    Create a cross-structural team.

While you will need IT and business stakeholders to participate in the project in any case, the importance of effective collaboration and team set-up is most important for the value creation. Projects often face roadblocks, and cross-divisional or cross-functional projects have serious complexity to them. So, for example, involve a change management resource or put a change management team together that has the competency to handle resistance. Furthermore, include experts from the business process domain as well the IT-domain for a sanity check of the data and the analysis, and high-level project support to bypass organizational barriers.


With more than 80 completed projects, Processand can help and provide you with the right expertise throughout your Process Mining implementation and ensuing projects, enabling, or replacing needed resources in your initiative and ensuring your Process Mining success.


Andreas Klötzel
Co-Founder & Co-CEO

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Alexandra Tyrkich

Alexandra Tyrkich

Data Science Team Lead

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