A Framework for Recommending Resource Allocation Based on Process Mining

  • Michael Arias
  • Eric Rojas
  • Jorge Munoz-Gama
  • Marcos Sepúlveda
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 256)

Abstract

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 recommending 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. Then, several metrics are computed considering different criteria to obtain a final recommendation ranking based on the BPA algorithm. The approach is applied to a help desk scenario to demonstrate its usefulness.

Keywords

Resource allocation Process mining Business processes Recommendation systems Organizational perspective Time perspective 

Notes

Acknowledgments

This work is partially supported by Comisión Nacional de Investigación Científica – CONICYT – Ministry of Education, Chile, Ph.D. Student Fellowships, and by University of Costa Rica Professor Fellowships.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Michael Arias
    • 1
  • Eric Rojas
    • 1
  • Jorge Munoz-Gama
    • 1
  • Marcos Sepúlveda
    • 1
  1. 1.Computer Science Department, School of EngineeringPontificia Universidad Católica de ChileSantiagoChile

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