<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Measuring the organization’s performance is essential for continuous improvement and operational excellence. Appropriate organizational measures include multiple dimensions. The relative importance of the multiple dimensions varies depending on the organization’s context and the management team’s visions. The vagueness and ambiguity in the management team’s perspective toward the dimensions and associated sub-indicators show fuzzy property. This paper aims to synthesize the overall organization performance in one aggregated index, engage the management team through index formulation, deal with ambiguity and vagueness in the management team perspective using fuzzy mathematics, and use the synthesized index in monitoring and controlling the organization’s performance to achieve operational excellence. The proposed approach is implemented in manufacturing organizations to prove practicality. The implementation of the proposed method shows a positive impact on the organization’s performance monitoring as the management team focused on one measure. Furthermore, it has engaged the management team in selecting and weighing the leading group and associated KPIs. The R programming and Minitab 19 are used in the collected data processing.</p>
</abstract>

Measuring the organization’s performance is essential for continuous improvement and operational excellence. Appropriate organizational measures include multiple dimensions. The relative importance of the multiple dimensions varies depending on the organization’s context and the management team’s visions. The vagueness and ambiguity in the management team’s perspective toward the dimensions and associated sub-indicators show fuzzy property. This paper aims to synthesize the overall organization performance in one aggregated index, engage the management team through index formulation, deal with ambiguity and vagueness in the management team perspective using fuzzy mathematics, and use the synthesized index in monitoring and controlling the organization’s performance to achieve operational excellence. The proposed approach is implemented in manufacturing organizations to prove practicality. The implementation of the proposed method shows a positive impact on the organization’s performance monitoring as the management team focused on one measure. Furthermore, it has engaged the management team in selecting and weighing the leading group and associated KPIs. The R programming and Minitab 19 are used in the collected data processing.

Organization Performance Composite Index Under Fuzziness: Application on Manufacturing Organization

Production Engineering Archives

This work is licensed under the Creative Commons Attribution 4.0 International License.

Measuring the organization’s performance is essential for continuous improvement and operational excellence. Appropriate organizational measures include...

Organization Performance Composite Index Under Fuzziness: Application on Manufacturing Organization

Publié en ligne: 15 févr. 2023

Pages: 14 - 22

Reçu: 26 mai 2022

Accepté: 08 nov. 2022

DOI: https://doi.org/10.30657/pea.2023.29.3

Mots clés
Performance measures under, fuzziness, Composite index, Performance improvement, Excellence model

© 2023 Mohamed Ibrahim El Santty et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Organization Performance Composite Index Under Fuzziness: Application on Manufacturing Organization

Publié en ligne: 15 févr. 2023

Pages: 14 - 22

Reçu: 26 mai 2022

Accepté: 08 nov. 2022

DOI: https://doi.org/10.30657/pea.2023.29.3

Mots clésPerformance measures under, fuzziness, Composite index, Performance improvement, Excellence model

© 2023 Mohamed Ibrahim El Santty et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Mots clés
Performance measures under, fuzziness, Composite index, Performance improvement, Excellence model