Generating the optimal process structure for decision sequences by Separation Network Synthesis

Abstract

In this paper it is examined whether efficiency improvements and cost reductions could be achieved by changing the order of certain predefined tasks in decision processes. A method has been developed based on log analysis and mathematical modelling. A Separation Network Synthesis (SNS) model has been constructed from the business process related historical data, and extended by further constraints for resource parameters and prerequisites. By transforming the model to a Process Network Synthesis (PNS) problem, optimal and alternative suboptimal structures, i.e., decision sequences can be generated and global optimality can be guaranteed.

In this paper it is examined whether efficiency improvements and cost reductions could be achieved by changing the order of certain predefined tasks in decision processes. A method has been developed based on log analysis and mathematical modelling. A Separation Network Synthesis (SNS) model has been constructed from the business process related historical data, and extended by further constraints for resource parameters and prerequisites. By transforming the model to a Process Network Synthesis (PNS) problem, optimal and alternative suboptimal structures, i.e., decision sequences can be generated and global optimality can be guaranteed.