What You Can Do With Process Mining

Source: https://fluxicon.com/blog/2015/10/why-process-mining-is-ideal-for-data-scientists/

Process Mining is not a reporting tool, but an analysis tool. It enables you to quickly analyse any and very complex processes. For example so-called Click Streams from websites that show how visitors navigate a webpage (and where they “drop out” or “wander around” due to poor usability of the page). Or take the new workflow system in your company, which has only recently been established and from which the department now wants to know how many processes really follow the redesigned, streamlined process path.

You can display the activity flow as well as the transfer between departments in different views of the process, identify bottlenecks, and investigate unwanted or long-running paths within the process.

These process views can also be animated to help in the communication with the department: the actual processes based on the timestamps from the data are ‘replayed’ and show in a very tangible way where the problems in the process are.

Why Data Scientists Should Become Familiar with Process Mining

Data science teams around the world begin to start looking into Process Mining because:

1. Process Mining fills a gap which is not covered by existing data-mining, statistics and visualization tools. For example, data mining techniques can extract decision trees, predictions, or Frequent Patterns, but cannot display complete processes.
2. Data scientists with their skills to extract, link, and prepare data are ideally equipped to exploit the full potential of Process Mining. For example, the data of different IT systems such as the CRM data calls in the call center of a bank and the interactions with the customer advisor in the branch must be linked with each other in a ‘Customer Journey’ analysis.
3. Analytical results must be communicated with the business. Data Science Teams do not analyse data for themselves, but to solve problems and issues for the business. If these questions revolve around processes, then charts and statistics are only meaningful in a limited way and are often too abstract. Process Mining allows you to provide a visual representation to the process owner, and also to directly profit from their domain knowledge in interactive analysis workshops. This allows you to find and implement solutions quickly.

Next Steps

Are you curious and want to know more about Process Mining? We recommend the following links:

• 15 minute recording, Presentation on Process Mining at bpmNEXT (with introduction and live demo): youtu.be/ql1S1wAxJ0E?t=10s
• Introductory article on Process Mining: fluxicon.com/s/pmarticle

2 free online courses (so-called MOOCs) have recently started, which offer an introduction to the topic of Process Mining:

• The ‘Process mining: Data science in Action’ MOOC at Coursera is a course given by Prof. Wil van der Aalst himself and provides a comprehensive picture of the foundations and the background of Process Mining algorithms: www.coursera.org/course/procmin
• The ‘Fundamentals of BPM’ MOOC of the Queensland University of Technology has generally a business process management focus but also includes a practical segment about Process Mining:moocs.qut.edu.au/learn/fundamentals-of-bpm-october-2015

To really get a good picture of what Process Mining can do (and what it can‘t do), it is best to try it out yourself. Here are two easily accessible ways to get started:

• The academic Process Mining platform ‘ProM’ is Open Source and contains hundreds of plug-ins the with the latest Process Mining algorithms: promtools.org
• For an easy introduction and for the professional Power User you can download the demo version of our Process Mining software ‘Disco’ from the following webpage: fluxicon.com/disco/