Recursos

Dynamically allocating the most appropriate resource to execute the different activities of a business process is an important challenge in business process management. An ineffective allocation may lead to an inadequate resources usage, higher costs, or a poor process performance. Different approaches have been used to solve this challenge: data mining techniques, probabilistic allocation, or even manual allocation. However, there is a need for methods that support resource allocation based on multi-factor criteria. We propose a framework for recommend- ing resource allocation based on Process Mining, that does the recommendation at sub-process level, instead of activity-level. We introduce a resource process cube that provides a flexible, extensible and fine-grained mechanism to abstract historical information about past process executions from process event logs. Then, several metrics are computed over the cube, considering different criteria: fitting between resources expertise and the expertise required to perform an activity, past performance (frequency, duration, quality and cost), and resources workload. These metrics are combined to obtain a final recommendation ranking based on the BPA algorithm. The approach is applied to a help desk scenario to demonstrate its usefulness.

This article describes the process of implementing a business process management supported by a service-oriented architecture from a business perspective. Also, it is to suggest how you can do to effectively balance the use of BPM and SOA as an entity differentiator for modern companies that drive the achievement of agile and flexible processes in their businesses.