This document presents a guide for practitioners on process mining. It introduces process mining and discusses its main use cases. These use cases are categorized into discovery oriented, future and change oriented, alignment oriented, variant oriented, and performance oriented. The document also provides a framework to classify use cases and discusses the business-oriented questions that can be answered using different process mining use cases, such as improving transparency, quality, agility, efficiency and conformance.

1. Process Mining:
A Guide for Practitioners
Fredrik Milani, Katsiaryna Lashkevich, Fabrizio
Maria Maggi , and Chiara Di Francescomarino
University of Tartu,
Narva mnt 18, 51009 Tartu, Estonia
16th International Conference on Research Challenges
in Information Science (RCIS 2022)

2. 2
Introduction Method Results Framework Conclusion
Read data related to a
businss process
Transform data
to event log
Visualize
business process

3. 3
Aalst, van der, W. M. P. (2011). Process mining : discovery, conformance and enhancement of business processes. Springer.
Introduction Method Results Framework Conclusion

4. 4
Introduction Method Results Framework Conclusion

5. 5
What are the main use cases for existing process mining
methods?
What business-oriented questions do existing process
mining use cases answer?
RQ1:
RQ2:
Introduction Method Results Framework Conclusion

6. 6
Introduction Method Results Framework. Conclusion
Step 1 Step 2
Final List of Papers
833
Introduction Method Results Framework Conclusion

7. 7
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
Main use cases + business-oriented questions they answer
Papers within the domain of process mining
IC1
IC2
IC3
IC4
Applied process mining to real-life event logs
Exclude process mining for applications unrelated to business
Provide sufficient information to elicit business-oriented questions

8. 8
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion

9. 9
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Process Model Discovery (procedural, declarative, or hybrid)
- Social Network Discovery (performers and their relations)
- Goal Mining (process goals)
- Rule Mining (rules behind the choices)
- Model Enhancement (repaire or extend with data)
Discovery Oriented

10. 10
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Predictive Monitoring (predicting outcome, next step, time, risks, etc.)
- Prescriptive Monitoring (path, activity, resource, etc.)
- Concept Drift (process change over time)
Future & Change Oriented

11. 11
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Conformance Checking (Process execution conforms with expected behaviour)
- Compliance Monitoring (Conformance for ongoing process cases – compliant
with predefined rules and constraints)
Alignment Oriented

12. 12
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Variant Analysis (Identify and assess
differences/similarities between variants)
- Deviance Mining (Aims at explaining why a
certain variant deviates from the most frequently
taken path)
Variant Oriented

13. 13
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Duration-, resource-, quality-related
- Multiple connected processes
- Performance change over time
Performance Oriented
Speed
Cost
Quality

14. 14
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion

15. 15
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion

16. 16
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
Transparency
Quality Agility
Efficiency
Conformance
- Process Model Discovery
- Social Network Discovery
- Goal Mining
- Rule Mining
- Model Enhancement
- Predictive Monitoring
- Prescriptive Monitoring
- Concept Drift
- Conformance Checking
- Compliance Monitoring
- Variant Analysis
- Deviance Mining
- Performance Mining

17. 17
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion

18. 18
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion

19. 19
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Process mining has evolved beyond
initial set of use cases
- Framework to categorize use cases
- Questions that business people can
address with process mining use cases

20. Thank you!

21. 21
Introduction Method Results Framework. Conclusion
Introduction Method Results Framework Conclusion
- Process mining has evolved beyond
initial set of use cases
- Framework to categorize use cases
- Questions that business people can
address with process mining use cases
Questions?