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Combining Lean Six Sigma and Process Mining

Combining Lean Six Sigma and Process Mining

The digital transformation does not only impact the expectation of the customer. It also affects the techniques and methods that companies use to delight customers every day. The Lean Six Sigma methodology has proven itself as a solid approach to continuously improve the quality of products, and how they are produced and brought to the customer. It has its background in the production industry, where it was initially used by manufacturing companies like Toyota, Motorola, and General Electric. It has also been adopted by many service organizations today.

The DMAIC (Define, Measure, Analyze, Improve, and Control) improvement cycle lies at the heart of Six Sigma. It breaks up the improvement cycle into several stages: First understanding the problem, measuring it, then identifying the root cause from the potential causes, and ultimately developing a solution that can be implemented under a control plan. This overarching DMAIC approach remains in place also in the digital era. However, as more and more data is being collected within organizations, new Data Science techniques enter the Lean Six Sigma domain to speed up the DMAIC improvement cycle. This gives the Lean Six Sigma practitioner new perspectives and tools to find root causes quickly.

Process mining is one of these innovations that is an excellent addition for various stages in the DMAIC to analyze the real complexity of value streams. Value Stream Mapping is a great Lean tool to understand a process and identify opportunities to improve. The drawback of this approach is that it can be time-consuming. It requires a lot of effort from the facilitator and experts to elicit all the required information to understand the current situation. It typically takes at least half a day to create a value stream that is aligned with the stakeholders. Another problem is that it is a subjective exercise, which heavily relies on the knowledge of the people involved in the mapping exercise. The participants often have their own view of the processes and represent their own agendas. It is also not possible to capture all the complexity and variations, so you could argue how close it actually represents the reality.

This article series will show you how process mining can be applied as part of a Lean Six Sigma project following the DMAIC methodology based on a concrete example from a loan provider. We show the advantages of using process mining and highlight the limitations from a Lean Six Sigma practitioner’s point of view.

Process mining itself is agnostic with respect to the methodology that is used around it. For example, you can apply process mining in the context of a BPM project, with a Theory of Constraints approach, in a Plan/Do/Check/Act cycle, or, as an auditor, within the audit methodology of an audit practice. However, you do need some methodology around it to interpret the results that your process mining analysis is giving you. 

So, while this guide is written from the perspective of a Lean Six Sigma practitioner, it is also useful for process miners who want to know how they can embed their process mining activities into a framework that helps them to translate their insights into actions that make an impact for the organization, which is, of course, where the ultimate value is for most process mining projects.

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