An increasing numbers of companies are becoming keenly interested in process mining. For example, the main track of the recent “International Conference on Process Mining (ICPM 2020 [7])” had almost 2000 registered participants. While it was a virtual event due to Covid 19 – that level of participation is impressive nevertheless.
Why the rapidly growing interest in process mining? Unlike process modeling workshops, where the model is largely based on people’s perception of how work is done, process mining is data based. It extracts insights from processes by the means of analyzing the event data generated in IT systems. The potential benefits of process mining are principally related to process discovery and conformance checking. In other words, process mining compares data from the event log step-by-step with the process documentation or model to find discrepancies.
This way, organizations can identify deviations from the IT model and can examine how processes are actually running — including key variations and exceptions. Process professionals need to understand how to use process mining as an important tool. But it’s just a tool. And it does take significant time, effort and expense to deploy. So, process professionals have a responsibility to help organizations take best advantage of process mining and remind IT professionals and especially IT vendors that as John Seely Brown once said “processes don’t do work – people do [8].”
Examining the event logs of information systems is useful, but can only be optimized when combined with input from people who do the work and those who set policies. Only a partial – and often incomplete – picture of reality is captured by just looking at system records. The city council of Granada [9] found this to be the case when they analyzed the complaints process. They used Fluxicon [10]’s process mining tool “Disco” to identify delays and bottlenecks in the tax collection process. However, they discovered that input from people who did the work was needed to truly understand why there were delays and why work appeared to stop from time to time. Process professionals have long recognized the importance of involving people who do the work in process analysis. They can and should play a crucial role in helping the IT team look at the true end-to-end process and structuring workshops that optimize the use of process mining.
Combining process mining work with insights from people who do the work is just the first step. Then, integrating process mining capabilities with other tools such as robotic process automation (RPA) multiplies the digital business potential of these technologies. The application of RPA to opportunities identified by process mining discovery can produce significant gains. Of course, RPA simply automates high volume, transactional tasks that people do. On its own – it just automates – it does not redesign. That’s why some organizations find it difficult to scale it – and sometimes automate a broken process. However, as Gero Decker [11] aptly pointed out – when a company takes time to first improve processes it can better determine what should or should not be automated.
While the integration of process mining and RPA, when accompanied by attention to what people do, is a strong first step, process practitioners can lead the way to even greater synergies through the integration of artificial intelligence (AI). Celonis [12], a leading process mining vendor has begun to explore the potential of integrating AI to create more advanced capabilities and take process mining from a largely analytical tool to improvement action [13]. Even more significant gains could be grasped if techniques such as design thinking were also to be incorporated.
When process professionals collaborate with the digital team, they can make a major contribution to the success of digital transformation efforts by taking action in the following four areas:
- Advocating that digital transformation should start with customers [14] and that it’s the set of end-to-end processes that create value. This requires more than just abstract models. Genuine discussion of the enterprise’s value creating processes at both senior management and mid-management levels is needed. This also means that the practice of modeling small processes inside departmental boundaries needs to cease.
- Acknowledging that while IT tools are important, process professionals need to advocate that people do the real work – so it’s important to go beyond what is evident by examining the event logs of IT systems. This means paying attention to “who does what” – i.e. the cross functional nature of end to end processes and working diligently to break down silos.
- It’s equally important to encourage the practice of integrating IT tools for performance improvement. For example, while process mining can be used to identify possible areas of opportunity to apply RPA – conducting process improvement workshops can be instrumental in determining what should be automated and for what results.
- Finally, it’s essential to embed cross functional collaboration in taking process mining to the next level. This enhances going beyond simple process discovery and conformance checking to genuine process improvement by integrating AI and design thinking.
When process professionals take a central role in these four areas, a renaissance in customer focused, process based thinking may occur and this can generate a greater opportunity to improve organizational performance.
