An Approach for Automatically Deriving Key Performance Indicators from Ontological Enterprise Models

U.A. Aksu, D.M.M. Schunselaar, H.A. Reijers

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

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Abstract

Organizations use Key Performance Indicators (KPIs) to monitor whether they attain their goals. Software vendors that supply generic software provide predefined KPIs in their software products for these organizations. However, each organization wants KPIs to be tailored to its specific goals.Th erefore, software vendors spend significant efforts on tailoring KPIs to organizations. That tailoring process is time-consuming and costly due to differences in the real-world phenomena of these organizations. In this context, we present our novel Automated KPI Derivation Approach. To automate the derivation of KPIs, our approach obtains the exact meaning of the terms in the real-world phenomena of an organization that is modeled in the form Ontological Enterprise Models (OEMs). As a proof-of-concept we implemented our approach. We demonstrate its use in a real-life setting and present preliminary results.
Original languageEnglish
Title of host publicationSIMPDA 2017 Data-driven Process Discovery and Analysis
Subtitle of host publicationProceedings of the 7th International Symposium on Data-driven Process Discovery and Analysis (SIMPDA 2017) Neuchâtel, Switzerland, December 6-8, 2017
EditorsPaolo Ceravolo, Maurice van Keulen, Kilian Stoffel
PublisherCEUR
Pages38-53
Number of pages15
Volume2016
Publication statusPublished - 8 Dec 2017

Publication series

NameCEUR Workshop Proceedings

Keywords

  • Enterprise Resource Planning
  • Key Performance Indicators
  • Ontological Enterprise Modeling

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