relation: https://khub.utp.edu.my/scholars/15737/
title: Competency driven resource evaluation method for business process intelligence
creator: Sohail, A.
creator: Dominic, D.D.
creator: Hijji, M.
creator: Butt, M.A.
description: Enterprises are continuously aiming at improving the execution of processes to achieve a competitive edge. One of the established ways of improving process performance is to assign the most appropriate resources to each task of the process. However, evaluations of business process improvement approaches have established that a method that can guide decision-makers to identify the most appropriate resources for a task of process improvement in a structured way, is missing. It is because the relationship between resources and tasks is less understood and advancement in business process intelligence is also ignored. To address this problem an integrated resource classification framework is presenting that identifies competence, suitability, and preference as the relationship of task with resources. But, only the competence relationship of human resources with a task is presented in this research as a resource competence model. Furthermore, the competency calculation method is presented as a user guider layer for business process intelligence-based resource competence evaluation. The computed capabilities serve as a basic input for choosing the most appropriate resources for each task of the process. Applicability of method is illustrated through a heathcare case study. © 2021 Tech Science Press. All rights reserved.
publisher: Tech Science Press
date: 2021
type: Article
type: PeerReviewed
identifier:   Sohail, A. and Dominic, D.D. and Hijji, M. and Butt, M.A.  (2021) Competency driven resource evaluation method for business process intelligence.  Computers, Materials and Continua, 69 (1).  pp. 1141-1157.  ISSN 15462218     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107821904&doi=10.32604%2fcmc.2021.018023&partnerID=40&md5=53e32f0ceeee636f0a447b7d6b21fe65
relation: 10.32604/cmc.2021.018023
identifier: 10.32604/cmc.2021.018023