The development of an organizational excellence architecture model to support the implementation of business excellence

Abstract

Purpose

The purpose of this study is to address a critical gap in the existing literature on business excellence implementation. While various studies have examined different aspects of business excellence, there is still a lack of comprehensive research on the optimal organizational excellence architecture (OEA) for an award-winning business excellence journey. The absence of a unified framework has led to inconsistent practices across organizations. The aim of this research based on data collected from 50 organizations across 17 countries is to address this gap and present a refined OEA model.

Design/methodology/approach

This study employed quantitative and qualitative data collection methods. Member organizations from the Global Excellence Model (GEM) Council participated through an online survey administered via the Qualtrics software platform. Quantitative data were analyzed using the SPSS and Microsoft Excel software tools, while content analysis techniques were applied to the qualitative data to gain detailed insights.

Findings

The findings refine and extend the OEA model. These contributions lead to a refined OEA definition and open avenues for future research, enriching the current understanding of BE implementation.

Originality/value

This study introduces a novel concept of OEA to the literature on business excellence implementation. The refined OEA model provides a fresh perspective on the critical components necessary for an award-winning business excellence journey. This research offers significant value to both practitioners and academics by presenting a unified approach to BE implementation, effectively addressing the previously identified gap in BE research.

Citation

Baig, A., Mann, R., Lockhart, J. and Macpherson, W. (2024), "The development of an organizational excellence architecture model to support the implementation of business excellence", The TQM Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/TQM-11-2023-0375