A critical component to successfully implementing Process Mining

A critical component to successfully implementing Process Mining


I have conversations with people at all levels each week on the topic of Process Mining and more specifically Business Process Improvement. It’s been incredible to watch the level of interest in Process Mining explode in the last couple of years as process improvement people and executives alike discover the benefits in operational efficiency this type of technology can drive.

From common use cases like “how do we improve our order to cash process” to more unique ones like “how can we improve our hire to retire process for a better employee experience”, process mining is leading the charge in transforming how companies leverage data and think about their business.

That said, every conversation I have it’s really focused on the visualization and how deploying process mining technology will allow “us” to see our company’s workflows and identify bottlenecks and opportunities to improve them. And although this is correct and a great example of the power of process mining I find myself doing a lot of education along the way. As I discuss process mining with people and the potential for it I remind them that what I refer to as the visualization is only one piece of the puzzle. The data itself is the other piece and in order to truly maximize the value of process mining both of these two components need to work hand in hand. If you apply the visualization to bad or incorrect data what you end up with is something that is either not useable or not valuable, in either case, a failed process improvement project.

In order to successfully implement process mining technology, you must also understand the data and how to transform it in a way that process mining tools can help. When I speak with people what I like to explain is the fact that process mining data in many instances is what I like to refer to as non-obvious data. It is not the same as using a BI tool and pulling data to generate a report for example that shows the number of sales orders. You need to think about things differently and understand that you are looking to analyze the activities or steps that are in a process so you can see where changes and corrections constantly occur, where approvals take too long, or where you failed to get back to a candidate in time and so they withdrew from your hiring process. In all of these processes, the data that is essential to understanding and analyzing them usually need to be extracted and transformed in unique ways. To successfully accomplish the task companies either need to have the resources that understand the system and data to build these process logs or engage with professionals from external firms who can help them.

In either of the two mentioned scenarios, companies need to realize as they begin to look at implementing process mining that this is a critical step and essential to their success. So as they look at tools and resources, they need to make sure that they are selecting the right tools and individuals who can help ensure this success.

Another common suggestion that I make to businesses as part of this is that they try to avoid eating the elephant in one bite. Seeing the complete process is extremely valuable but also can be difficult as it may require more unique transformations or even merging data from multiple systems. What I always try to suggest is that their process mining project begins focused on data from one or two systems to start. Focusing on getting the essential data and the baseline process in place and then building from there. This helps greatly improve what I refer to as “Time to Value”, how quickly you start to see some real business results as in many cases issues and bottlenecks can start to be identified. It is also a great way for companies to see the process and discover where they may want to start looking and invest their time first (if it’s an approval workflow they may start by connecting data from another system that captures that step).

One thing is for certain is that we have only just begun to scratch the surface of the use cases and value proposition for process mining. As we see new people joining the space and learning the technology this will grow exponentially. With more knowledge of both the data and the tools, I believe we will continue to see a rapid expansion of process mining across companies of all sizes. We are seeing it now that process mining technology will not simply be used by the largest companies across the globe but smaller companies will continue to rapidly adopt the technology to drive their operational efficiency. And as they do so it will drive a whole new set of industry expertise and tools that will give them the ability to easily mine the data they need and analyze it to drive valuable business insight.

James Henderson, CEO mindzie

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