As such, IT and BPM are often exactly antagonistic to a pleasant customer journey. Customers, except for most misanthropic ones, naturally prefer human interaction instead of an IT system. It is enough to remember all frustration, which anybody had a chance to encounter at least once, while wandering across innumerous levels of auto-responder menu in desperate attempts to speak with a human operator. For a customer, automated service looks in most cases hostile and heartless.
On another hand, any company is keen to automating customer journey with modern IT and BPM technologies because it gives enormous savings and improvement of control against comparable staff of human operators. For an organization, automation of customer services is a vital technology of survival and an essential competitive advantage.
To avoid disappointment of clients in this contradictory situation, where interests of a business and its clients are predominantly opposite, a company must utilize modern BPM approaches, which allow for modeling and building complex, dynamic and responsive customer journeys corresponding to high expectations of contemporary consumers.
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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