Crucial and often missed factor of success for an automation initiative is careful evaluation of process interaction with other processes. As a rule, processes, which have excessive dependencies and external communications are especially difficult to automate. Complexity of automation may grow exponentially with the increase in process linking.
Overall degree of link density for processes inside a business model is essential but rarely discussed measure of integration and stability of business as a whole. Cascading process links with progressive nested dependencies further complicate and potentially delay positive process outcomes.
To correctly estimate true potential of process improvement, business analysts should never consider any process standalone but only in the context of its interaction with other parts of business model. Automating a process alone is as artificial as running a single department without the whole company in place. Preparing to enterprise automation, always begin with the study of business dependencies.
Density of links in a model can be objective and inherent to business. In this case it is not so easy to change voluntarily. Density of links can be also a distinguishing factor expressing business identity.
By analogy with chemistry, there can exist many entirely different chemical substances composed out of exactly same base elements. For instance, coal and a diamond are just different arrangements of one and the same carbon composite. Drastic difference in properties is just a result of different links between atoms inside. In the same way, structure and quality of links inside an organization may alone well make it a coal or a diamond.
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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