Models and Algorithms for Business Value-Driven Adaptation of Business Processes and Software Infrastructure

This research investigates how to provide automated analysis and decision-making support for adaptation of business processes and underlying software infrastructure, in the way that both maximizes business value metrics (e.g., profit, return on investment) and maintains alignment between business strategies and adaptation decisions. Among its expected contributions are improved modeling of business value metrics and business strategies in business process models and novel business value-driven techniques and algorithms that support primarily automatic and dynamic (runtime) adaptations, but also manual and static (designtime) adaptations. The proposed solutions will be implemented in software prototypes to demonstrate feasibility. Their usefulness will be evaluated through realistic case studies. 1. Problem description Business process management (BPM) [1] is a set of techniques, metrics, management best practices and software tools that help organizations model, execute, monitor and optimize their work activities. Despite the fast growing popularity of business process management software systems in the industry, they are significantly challenged by the need for constantly available and adaptable business processes. In a recent BPTrends survey [1], 56 % of the surveyed companies (and 65% among the surveyed large companies) reported that the major driver for focusing on business process change is the need to save money by reducing costs or improving productivity. To this end, providing adaptation of business processes and underlying software infrastructure in a way that continually and transparently deliver