Multi-phase process mining

1. Multi-phase process mining Building instance graphs

2. Overview • Introduction to the area of Process Mining • Introduction to process performance monitoring • Using process mining to deploy a monitoring system • Conclusion

3. Process mining overview 3) organizational model 2) process model 4) social network 1) basic performance metrics 5) performance characteristics 6) Security issues If …then …

4. Multi phase process mining 3) organizational model 2) process model 4) social network 1) basic performance metrics 5) performance characteristics 6) Security issues If …then …

5. Process Performance Monitoring – The concepts • Process/control-flow perspective: flow -, waiting -, processing - and sync-times. Questions: • What is the average flow time of orders? • What percentage of requests is handled within 10 days? • What is the average time between scheduling an activity and starting it? • Resource perspective: frequencies, time, utilization, and variability. Questions: • How many times did John withdraw activity go shopping? • How many times did Clare suspend some running activity? • How much time did people with role Manager work on this process? • What is the average utilization of people with role Manager?

6. Process Performance Monitoring – Commercial systems HP Business Process Cockpit Aris PPM • Process aware information system are capable of producing log filesPerformance monitoring can use these files for calculating performance metrics

7. Process Performance Monitoring – The downsides • Deploying performance monitoring systems is expensive • Process modelling requires deep knowledge of organization and processes • People tend to think in a linear way Use the Process Mining Framework to overcome these problems. • Describe each case or process instance as a a-cyclic graph automatically • Convert these graphs into a human-readable format such as EPCs or Petri nets • Export these graphs to commercial tools such as Aris PPM

8. Multi-phase process mining – Source system abstraction • Store Log files in a generic XML-formatCalculate causal dependencies between tasks:If A is followed by B in some case, and B is never followed by A, then A and B are causally related.

9. And the following Causal relations: C A D E B Multi-phase process mining – Source system abstraction • Using the causal relation, we construct a general base graph for all cases: Assume we have the following cases: A,B,C,D,E A,C,B,D,E A,D,E

10. Multi-phase process mining – Creating instance graphs • For each instance, we walk through the base graph and make instance graphs for each case. C Process instance: A,B,C,D,E and A,C,B,D,E A D E B C A Process instance: A,D,E D E B

11. Process instance: A,B,C,D,E and A,C,B,D,E Multi-phase process mining – Converting to EPCs • Each instance-graph is then converted into a human readable format, such as an EPC Process instance: A,D,E

12. Multi-phase process mining – Exporting to commercial tools • The instance EPCs are exported into Aris PPM • Analyse the process using the advanced capabilities of PPM

13. Conclusions • We have shown a way to automatically deploy an advanced process performance monitoring system, such as Aris PPM or the HP business cockpit. • No deep knowledge of the processes as they take place is required in this process. Instead, process mining techniques are used. • A great insight is provided in the deviations between the intended process, and the process as it is actually being executed.