Question of reusing standard process libraries always arises in an organization starting its digital transformation. At first glance, ready process sets might look very attractive to borrow and avoid complex procedures of mapping your own processes. On another hand, blind implementation of standard process templates will effectively destroy all corporate culture and experience previously accumulated in an organization.
Boundaries of applicability for standard processes are easy to distinguish by scale. Elementary business operations in most cases already exist as established and proven best practices, which are senseless to re-discover. Sometimes, changing these ground bricks is even prohibited by government standards and compliance requirements. However, these standard bricks are absolutely insufficient to comprise a building of successful company.
To fuel continuous business growth company must combine standard business patterns common for the whole industry into unique combination, which will define its competitive advantage. Complex end-to-end processes always require careful crafting in unique business context. Bigger grows business model, more standard patterns it absorbs on micro-scale, but also more it diverts from any given standard template globally.
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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