This paper aims to address the limited success of Lean Six Sigma (LSS) initiatives in Gulf Cooperation Council (GCC) contexts, where cultural and linguistic misalignment often undermines adoption. It introduces and pilots BASEER, a bilingual Arabic–English digital platform designed to embed LSS tools into public sector and service organizations while accounting for linguistic nuance and organizational culture.
Using a minimum viable product (MVP) approach, BASEER was iteratively developed and refined through workshops involving Omani Government ministries. Feedback from participants guided system enhancements, while natural language processing (NLP) models were trained and evaluated on a data set of 1,041 Arabic operational statements across eight waste categories to classify Lean wastes. Qualitative feedback, observational notes and system outputs formed the empirical base for analysis.
Results suggest that BASEER made improvement initiatives more inclusive by enabling broader staff participation, especially among younger and frontline employees. Compared with traditional board-and-sticker approaches, the platform facilitated faster input collection, more systematic waste classification and easier dissemination of visual analysis. Participants perceived BASEER as better aligned with local context than consultant-led interventions, though findings remain perception-based rather than quantitatively validated.
As an MVP pilot, this study is limited to workshop settings in Oman and relies largely on participant feedback. Broader testing across GCC countries, the private sector and larger data sets is required to confirm generalizability. Dialectal variation in Arabic also presents ongoing challenges for NLP integration.
BASEER demonstrates that LSS tools can be localized for Arabic-speaking environments. By embedding improvement tools in culturally sensitive, bilingual formats, the platform provides a more sustainable model for government and service-sector organizations pursuing digital transformation.
By enabling staff at all levels to contribute feedback in their native language, BASEER promotes more inclusive decision-making within government and service organizations. This fosters greater transparency, reduces barriers to participation and supports a shift from individual blame to systemic improvement. In the wider social context, culturally adapted quality platforms can strengthen public trust in services, enhance citizen satisfaction and reduce the dependency on external consultants whose recommendations may not reflect local realities. This study highlights how digital transformation, when culturally grounded, can advance both organizational excellence and social equity.
To the best of the author’s knowledge, this is among the first studies to integrate Arabic NLP with LSS for public-sector applications. It contributes to the Quality 4.0 literature by suggesting that digital transformation must address not only technological sophistication but also linguistic inclusivity and cultural alignment. The paper offers an early model for adapting global methodologies into locally relevant, user-friendly digital tools.
