Beyond Roles: Prediction Model-Based Process Resource Management
The outcome of a business process (e.g., duration, cost, success rate) depends significantly on how well the assigned resources perform at their respective tasks. Currently, this assignment is typically based on a static resource query that specifies the minimum requirements (e.g., role) a resource has to meet. This approach has the major downside that any resource whatsoever that meets the requirements can be retrieved, possibly selecting resources that do not perform well on the task. To address this challenge, we present and evaluate in this paper a model-based approach that uses data integration and mining techniques for selecting resources based on their likely performance for the task or sub-process at hand.
KeywordsBusiness Process Resource Dependency Resource Model Work Item Resource Assignment
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- [AHM06]Anvik, J., Hiew, L., Murphy, G.C.: Who should fix this bug? In: Proceedings of the 28th International Conference on Software Engineering, pp. 361–370. ACM (2006)Google Scholar
- [DKDBvdV02]De Koster, R.B.M., De Brito, M.P., van de Vendel, M.A.: How to organise return handling: an exploratory study with nine retailer warehouses. International Journal of Retail & Distribution Management 30(8/9), 407–421 (2002)Google Scholar
- [HK06]Han, J., Kamber, M.: Data mining: concepts and techniques. Morgan Kaufmann (2006)Google Scholar
- [JT09]Jablonski, S., Talib, R.: Agent assignment for process management: agent performance evaluation. In: Proceedigns FIT 2009 (2009)Google Scholar
- [LR00]Leyman, F., Roller, D.: Production Workflow. Prentice-Hall, Englewood Cliffs (2000)Google Scholar
- [NRM10]Niedermann, F., Radeschütz, S., Mitschang, B.: Deep Business Optimization: A Platform for Automated Process Optimization. In: Proceedings BPSC 2010 (2010)Google Scholar
- [Qui92]Quinlan, J.R.: Learning with continuous classes. In: 5th Australian Joint Conference on Artificial Intelligence (1992)Google Scholar
- [RNB10]Radeschütz, S., Niedermann, F., Bischoff, W.: BIAEditor - Matching Process and Operational Data for a Business Impact Analysis. In: Proceedings EDBT (2010)Google Scholar
- [YJJ07]Yingbo, L., Jianmin, W., Jiaguang, S.: A machine learning approach to semi-automating workflow staff assignment. In: Proceedings of the 2007 ACM Symposium on Applied Computing (2007)Google Scholar