Process Analytics:

Applying Process Mining to create value from process data

How to conduct a successful Process Mining project? With Process Mining getting more and more popular, many organizations wonder how to run a successful Process Mining initiative. Check out what motivates companies to use Process Mining, what are the achieved benefits of using this technology, and what success factors and challenges companies face in their Process Mining journey.

We have gathered valuable insights of successful Process Mining implementations from the interviews with Process Mining experts, as well as from publicly available case studies, such as success stories from Celonis customers and use cases from the book “Process Mining in Action” (L. Reinkemeyer, 2020). Overall, we categorise the insights into triggers, objectives (i.e. expected benefits), achieved benefits, as well as challenges and success factors.

Triggers and Objectives

One would expect organisations engage in Process Mining primarily to solve their business problems. Our research, however, indicates that it is mostly driven by the search for innovations and digital transformation trend. At the same time, by implementing Process Mining technology, organisations expect to improve their operational performance, standardise their processes in different regions and make it transparent for all users.


  • The bottlenecks in the processes are often hidden and it is difficult to uncover these inefficiencies without data.
  • Based on the collected insights, Process Mining technology allows firms to increase process transparency across all participants by shifting from subjective opinions to objective facts. Making decisions gets evidence-based.
  • Following the digitalisation trend, it further engages users for other technologies, such as Robotic Process Automation (RPA) and Machine Learning.


More and more companies implement Process Mining which is promising huge saving potentials, however struggling with actually realising those potentials. So what are the main challenges creating additional risks of Process Mining projects’ failure?

Data integration

Some cases mentioned data quality as a potential issue, but more importantly, long and problematic data integration was stressed.


Process Mining technology visualises processes, making them transparent for all process participants. However, uncovering process inefficiencies can lead to the rejection from the management side.

Process Mining vision

Many cases reported that projects suffer from the lack of vision of Process Mining technology opportunities in the set-up stage.

Process Mining skills

Another challenge is the need of specialists with Process Mining skills. Interview participants mentioned that it requires additional effort to acquire Process Mining skills, which is quite challenging for employees.

Success Factors

So, how do you solve those challenges and make sure your Process Mining initiative is successful? We provide you with an overview of all discovered success factors and discuss four the most often mentioned ones.

  • Highlight value of technology for end-users: Transparency lead to the rejection from the management side. The main success factor in this case is to highlight value of Process Mining technology for all users, including top-management.
  • Have IT involved or someone with technical knowhow of data and systems: One of the main challenges is a long and problematic data integration process. The project can, therefore, succeed by having IT or someone with technical knowledge of data and systems involved.
  • Motivate process participants, including offering trainings and educational sources: Many cases mentioned the lack of vision of PM opportunities as problematic. That is why motivating and training process participants from different process stages allows companies to achieve successful Process Mining implementation.
  • Involve stakeholders from different areas: It is also crucial to involve stakeholders from different areas with process knowledge to understand how a process works, where process inefficiencies come from, and that way solve the transparency paradigm.

Get more insights

If you are interested in the content related to our research on Process Mining, please get in touch with us!