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Hi Process Observer community,

Today I want to show you another interesting approach for applying process mining techniques on top of log information for your business processes created with Process Observer. To do so, we will use the open-source process mining toolkit ProM that is provided by the Process Mining Group, Eindhoven Technical University. In a follow up article we are examining Process Mining with Process Observer and Fluxicon Disco.

Although the current ProM version is 6.2, we are using version 5.2, as some of the functionality that is used is available only in this version. You will find the link for downloading ProM 5.2 at http://www.promtools.org/prom5/ together with some samples and documentation. You can find the latest version of ProM at http://www.promtools.org/.

To export Process Observer log data from your SAP Business Suite system, you can use sample report POCR_LOG_MXML_EXPORT (or use transaction POC_LOG_MXML_EXPORT). For information about the installation of the report in your system, see note 1832016 (and update note 2011730). The report allows you to the specify start and end date and time as well as the Process Definition relevant for the export. Using further options, you specify exporting only those processes with the status ‘finished’, extract further Business Object (BOR) attributes – which may be useful for a more in-depth analysis in ProM, and to delete user information during the export.

In this example, we are exporting logged data from procurement processes, as defined in Instrumentation for Procure-to-pay process on item level in Process Observer.

The result is stored as a file in Mining eXtensible Markup Language (MXML) format on the local PC.

The exported file structure looks like this:

It is then imported for further processing in ProM using the ‘File – Open supported File…’ functionality of the ProM Workbench. Chose the import plugin for ‘MXML Log reader’.

The imported file is now visible in ProM and immediately allows you to see some statistics for the imported processes, therefore check the ‘Dashboard’ and the ‘Summary’ view. Note: The process observer instances are referred to as ‘cases’ in ProM, while ProM’s ‘events’ correspond to activities in Process Observer.

In the filter view, you can restrict your log even more:

The heuristics miner (path Mining - Log - Heuristics Miner) returns a model of the process execution and gives information about the frequency of the activities and transitions:

One way of  identifying process variants, is to create Markov Chains by selecting the ‘Sequence Clustering’ plugin in the Analysis menu. You can
then further inspect or view the created Markov Chains:

Alternatively, you can identify the most frequent path alternatives with their throughput times running the ‘Performance Sequence Diagram Analysis’ in the Analysis menu:

Finally, I would like to show you how you can identify paths that, on average, take too much time, the critical sub-paths, or the routes using ProM. To do so, you use the heuristic process model described above, and use the ‘Conversion – Heuristic – Heuristic Net to Petri Net’ function to get a Petri Net as a result. Then run ‘Analysis – Petri Net Model - Performance Analysis with Petri Net’, set the ‘Times Measured In’ to an appropriate value. Steps with long durations / high waiting times are now marked in purple:

When reviewing the ProM tutorials and playing around with the tool, you will find that you can do a lot more mining and analysis around your process logs, such as evaluating organizational-related information of the process, activity sequence, conformance checking, decision point analysis, and so on. Note that size of data sets that can be processed with ProM is limited; you may need to limit the data size of the export accordingly.

The ProM Toolkit has proven to be a useful and very versatile tool for process analysis with Process Observer. I hope this little introduction has given you some ideas, and I’ll be happy if one of our followers gives an example in their blog about how they're mining and analyzing data.

Some disclaimer about the ProM Toolkit itself: It is an open source tool for which SAP takes no responsibility. The above article is for illustrative purposes only how it could be used in the Process Observer context.

Thank you for staying tuned to this series!