The following points are not things I especially dislike about Celonis.
They should be reminders of obstacles we had and still must overcome to reap the benefits of process mining in general and implications one must be aware of when embarking on data-based process mining.
Firstly, big improvements might be achievable without a process mining tool because they are so obvious to the organization and might have been already fixed in past.
What remains are the “left over potentials” in much smaller size pertaining to value. So, to gain measurable benefits one must be prepared to implement a lot of smaller process improvement projects, each providing a bit of value. The benefit will be visible as the sum of the value of those realized projects will increase. It is like Gulliver who is tied up by thousands of strings in Lilliput. Cutting or loosening any string only has small value. But once you solved a critical mass of small problems you can really improve your organizations process performance.
Secondly, one cannot put process mining into practice as an en passant activity.
An organization must commit resources to this area on a regular basis. The topic is much too complex to have it carried out part time.
So, clear responsibilities and a decision from top management to allocate capacity of the work force to process mining are success factors which come with a cost.
Finally, you might not have the personnel with the skill and/or mind set required for working with a process mining tool.
Taking time for exploration, developing a curiosity of underlying correlations and delving deeper and narrower into the processes and data is a skill which is scarcely found
in companies where problem solving with quick fixes is the norm. Review collected by and hosted on G2.com.