Tuesday, July 14, 2020

Best Visual Options for Process Mining

Until bots can be cognitive enough to complete closed-loop improvements on processes or data stores on their own, visualization for humans will be key for making process improvements. Today many of those improvements are made through data mining in real-time or after the fact by humans. They do it by setting tolerances and monitoring outcomes or looking at the visualization of process instances that travel through processes or collaborations. The best visual options for any organization will depend on their culture, maturity, and desired business outcomes. I've laid out three categories of process mining visualization techniques that typically match maturity levels. I have used examples from vendors to help sort out the options, so your favorite vendor may have been left out of this post. 

Basic Visualizations

Basic visual analysis sometimes starts with an ideal process, sometimes called a "happy path", and look for the actual paths taken by a process. Organizations sometimes start with the outliers and try to reign them in closer to the ideal. Other organizations start with clusters of most common deviant paths and try to improve them. See the visualization below for a representation of this approach. Most organizations do a before and after to measure change effects, also depicted below. This shows the process before changes are made and the resulting process with deltas in certain instances. 

Intermediate Vizualizations

More mature organizations try to add important business contexts to show the actual delivery made by processes in terms of key measures. One of the more important contexts, shown below, are the actions shown on a timeline. This gives "time to results" a high priority while counting key costs and resource utilization specifics. This is an effective way to eye-ball opportunities. Another key approach is to show the process instances in light of desired outcomes versus real outcomes usually represented by dashboards or scorecards also depicted below. This is the start of the journey to adding more intelligence to the process of mining efforts. Simple Step through visualization with or without simulation of proposed changes is another nifty approach pictured below. 


Advanced Visualizations

One of the proven visualization techniques is animations that attract humans to opportunities through either speed or color indicators. This typically shows choke points and bottlenecks, but there are additional uses to simulate alternatives to show the value of different change opportunities. See below for an example. Predictive analytics combined with virtual reality can be used to visualize points of view or personas to fine-tune processes from different perspectives walking through a process or journey as depicted below. For those organizations that want to learn as they go, they can add machine or deep learning to improve processes as depicted below. 

Net; Net:

The visualization approaches can have a great impact on the resulting processes and finding opportunities for more automation, tuning for better results, and trying alternatives without the negative impacts of breaking or breaking optimized processes. Your chosen visualization might be a personal preference, but as organizations mature more sophisticated visualizations will be needed until the smart autonomous bots or agents can do this work as a partner or autonomously.  


  1. Hey Jim -

    I agree that Process Mining is great for seeing your happy path. It is even good for finding possible irregularities. Unfortunately many paint it as a magic bullet that will solve all your process whoa's.

    One thing to remember is that process mining is data driven and therefore can only see where you have been. For this current series of disruptions, no one had dealt with a mass mobilization of a globally remote workforce. It was only those that actually took the time to capture their process landscape, business architecture, and the impact to those processes that were strategic and business critical along with the end to end dependencies had a true prioritized contingency plan.

    However, as noted, once an event has occurred, process mining can be great for seeing those various paths and measuring cycle times.

  2. The weakness of mining is it only shows where you have been or what tactical shifts can be simulated. That's why scenario planning needs to be in an organizations toolbox. Scenarios can be simulated in some cases with mining data

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