I’m evaluating whether to invest in process mining capabilities or stick with traditional BPMN-based process analytics in Creatio 7.18. We have about 50 active business processes with good execution data.
Traditional analytics gives us predefined dashboards showing process duration, bottlenecks, completion rates - all based on our designed BPMN models. Process mining promises to discover actual process flows from event logs and find deviations we didn’t anticipate.
From a configuration perspective, traditional analytics is straightforward - the process schema defines what gets measured. Process mining requires event log configuration, entity relationship mapping, and activity definition - significantly more setup.
For those who’ve implemented both: What are the real-world trade-offs? Does process mining reveal insights that justify the additional configuration complexity? Or is traditional BPMN analytics sufficient for most process improvement initiatives?
We implemented process mining last year after using traditional analytics for three years. The key difference: traditional analytics shows you how your designed process performs. Process mining shows you how the process actually executes - including all the workarounds, manual interventions, and undocumented variations.
Configuration is definitely heavier for process mining. You need to map every system event to process activities, define case identifiers, and configure timestamp extraction. But the discovered process models revealed execution patterns we never designed for. In one case, we found that 30% of orders were following a completely different path than our BPMN model showed.
Configuration complexity is real, but Creatio 7.18’s process mining templates help. The initial setup is time-consuming, but once configured, it runs automatically. Traditional analytics needs manual dashboard updates whenever you change the process model. Process mining adapts automatically because it’s discovering patterns, not measuring predefined paths. That adaptability becomes more valuable as your processes evolve.
Great insights everyone. The consensus seems to be that both have their place, and the configuration investment in process mining pays off for process improvement projects, while traditional analytics is better for routine monitoring.