A Flexible Framework to Ensure Traceability, Consistency, and Propagation of KPIs Evolution

ABSTRACT Organizations use key performance indicators (KPIs) to assess the effectiveness and efficiency of their procedures and processes. In a world that is constantly evolving and hyperconnected via the internet, it is of great interest to analyze how changes (organizational, legal, technological...

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Vydané v:Journal of software : evolution and process Ročník 37; číslo 2; s. 1 - n/a
Hlavní autori: Domínguez, Eladio, Pérez, Beatriz, Rubio, Ángel L., Zapata, María A.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Chichester Wiley Subscription Services, Inc 01.02.2025
Predmet:
consistency conditions
constraint logic programming
Evolution
evolution framework
KPIs
Logic programming
propagation
reasoning
traceability
ISSN:2047-7473, 2047-7481
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Shrnutí:ABSTRACT Organizations use key performance indicators (KPIs) to assess the effectiveness and efficiency of their procedures and processes. In a world that is constantly evolving and hyperconnected via the internet, it is of great interest to analyze how changes (organizational, legal, technological or other) can lead to modifications in the KPIs involved. However, little attention has been paid to KPI evolution either in the scientific literature or in developed solutions. This paper presents A Flexible Framework for the Evolution, Consistency and Traceability of KPIs (AFFECTK) that aims at establishing the basis for suitable KPIs' evolution management. The feasibility of this proposal is demonstrated through a proof‐of‐concept developed using a reasoning tool based on Constraint Logic Programming. The framework is further evaluated, using real KPI case studies, to assess the functional suitability of our approach. Key findings A Flexible Framework for the Evolution, Consistency and Traceability of KPIs (AFFECTK) is proposed which is established along three levels (method, organizational, and application). The framework considers three key elements (traceability, consistency condition, and propagation). The feasibility of the proposal is demonstrated in two different ways: through a proof‐of‐concept developed using a reasoning tool based on Constraint Logic Programming, and with an evaluation, using real KPI case studies, aimed at assessing the functional suitability of our approach.
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ISSN:2047-7473
2047-7481
DOI:10.1002/smr.70004