A Model-Driven Engineering Approach to Complex Performance Indicators: Towards Self-Service Performance Management (SS-PM)

Research output: Contribution in Book/Catalog/Report/Conference proceedingConference contribution

Abstract

Every modern organization nowadays produces data and consumes information through Decision-Support Systems (DSS) which produce more and more Complex Performance Indicators (CPI). This allows business monitoring, decision-making support and tracking of decisions effects. With the increasing complexity, DSS suffer from two main limitations that inhibit their use. First, DSS tend to be opaque to Business Managers who cannot observe how the data is treated to produce indicators. Second, DSS are owned by the technicians, resulting in an IT-bottleneck and a business-exclusion. From a Business Management perspective, the consequences are damaging. DSS result in sunk costs of development, fail to receive full confidence from Business Managers and to fit dynamic business environments. In this research, preliminary insights are proposed to build a solution that tackles the previous limitations. The literature review, the research contributions and methodology are presented to conclude with the work plan of the PhD.

Translated title of the contributionUne Approche d'Ingénierie Dirigée par les Modèles pour les Indicateurs de Performance Complexes: Vers une Gestion Self-Service de la Performance (SS-PM)
Original languageEnglish
Title of host publicationResearch Challenges in Information Science - 15th International Conference, RCIS 2021, Proceedings
Subtitle of host publication15th International Conference, RCIS 2021 Limassol, Cyprus, May 11–14, 2021 Proceedings
EditorsSamira Cherfi, Anna Perini, Selmin Nurcan
PublisherSpringer
Pages661-669
Number of pages9
Volume415
Edition15
ISBN (Electronic)978-3-030-75018-3
ISBN (Print)978-3-030-75017-6
DOIs
Publication statusPublished - 8 May 2021

Publication series

NameLecture Notes in Business Information Processing
Volume415 LNBIP
ISSN (Print)1865-1348
ISSN (Electronic)1865-1356

Keywords

  • Complex Performance Indicators
  • Decision Support System
  • Model-Driven Engineering
  • Performance Management

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