Due to explosive growth in robotics and AI automated processes are quickly becoming an essential part of business. Wide adoption of automated processes creates significant challenges for business management.
Automated processes are both simpler and more complex to manage, compared to manual processes. Simpler, because automation is void of any personal attitude or bias of human workers. More complex, exactly for the same reason of absolute impersonation and concentrated responsibility.
In case of an error in manual process there is always a space for an additional control and adjustment of task by a worker. In contrast, automated tasks run autonomously and on far higher speeds. It makes a mission of controlling automated tasks far more stressful and dangerous. Any occasional error on a single process step can randomly propagate the whole running process chain causing catastrophic damages for the whole business.
These elevated control requirements for automated processes make it impossible to run wide scale enterprise automation without a detailed business model in place. Professional BPM and consistent EA are cornerstones in the success of process automation in any organization.
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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