Towards context-aware business process cost data analysis including the control-flow perspective: A process mining-based approach

Abstract

Nowadays, it is crucial for several organizations to look for solutions allowing to reduce costs incurred by the execution of their business processes. Previously, we proposed a general approach for the extension of business process models with cost perspective based on process mining, independently of the model notation. This approach includes a cost data analysis based on applying classification algorithms selected dependently on the case in hand. Moreover, the proposed cost data analysis allows extracting knowledge about factors influencing on cost at process and activity levels. These factors include attributes corresponding only to the organizational and data perspectives. However, the control-flow perspective is not taken into account while it may also have influence on the business process incurred costs at the process level. Moreover, the proposed approach for selecting the appropriate classification algorithm is generally presented and illustrated. Thus, in this paper, we propose to improve the cost data analysis approach by including the control-flow perspective and by providing formal details about the context-aware classification algorithm selection as well as a detailed illustration of the proposed approach. This leads to improve decision making support for business process incurred cost reduction.