Before any process is automated, there must be done careful process mapping. Although the idea looks trivial and self evident, it is often ignored in vast majority of automation initiatives. As a result, true mapping reveals itself already after implementation. Surprisingly, it often has nothing in common with original automation plan. This careless attitude to preliminary process study is one of the most common reasons for faults in process automation.
As a next step, it is useful to do an exploratory process mining to reveal true variability of the existing process. If process is volatile, it might be very laborious or even impossible to automate. It is wrong to think that mining is suitable only for processes, which are already automated. Simple mining can be done even for a purely manual process by just recording its steps by hand and comparing them with previously prepared process map.
Put together, these simple rules can ensure smooth implementation and good effect from automation.
There always exists a discrepancy between a model of business process, however well designed and accurate, and real execution of this process in a business environment. The reason for this gap is an unforeseen depth and hidden details inherent to any real process. Real business model of organization is ultimately unlimited in its depth. Going from highest management levels, it descends to individual departments, client relations, production units, technical code of equipment and controllers etc. In vast majority of cases, it is impossible and senseless to build a complete model covering all and every fine detail of the business. Omitted lower layers of the model create (pseudo) random fluctuations during execution of the model. Real execution paths of a process never follow its model exactly. However, in case of the correct model, we can expect to see that an ensemble of execution paths statistically converges to the model as to its average path over a significant set of observation...
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