Companies strive for superior results. Focusing on return, performance, and profitability is mainstream; this reasoning is constantly present in the decisions of the strategic operational management of companies. Based on this assumption, the objective of this work is to evaluate empirically whether the degree to which a company implements a combination of Just in Time (JIT) or Lean Manufacturing practices systematically affects the company's operational, financial, and/or organisational performance. For this, a meta-analysis was carried out; the final sample consisted of 28 articles, with 41 studies and 12,708 included subjects who provided the effects that explain the proposed relationship. The data were collected in the Web of Science, EBSCO, and Science Direct databases, with an open period, considering all works available until July 2020. Among the main findings, JIT practices and the company's operational performance present a positive, significant, medium effect. Lean manufacturing practices demonstrate a positive and significant relationship in operational, financial, and organisational performance, all with an average impact on the effect size. No direct relationship was found between the JIT variables and organisational performance (financial, operational, and environmental), based on the TBL. Additional research is needed regarding the relationship of JIT and Lean Manufacturing practices with the organisational performance (financial, operational, and environmental) based on the TBL, as well as an in-depth analysis of previous research related to green Lean practices and their relationship with organisational performance, based on the TBL.

The application of Big Data Analytics (BDA) plays a crucial role in promoting sustainability across various organizational contexts. It strengthens sustainability initiatives in diverse areas, such as Supply Chain Management, where it helps identify socially responsible suppliers, reduces logistics costs, and enhances delivery efficiency. In the energy sector, BDA supports energy consumption modeling, forecasting, storage, and distribution, enabling more efficient energy management. Despite existing literature linking BDA and sustainability, few studies have provided an integrative and strategic view that connects data‐driven technologies to the tensions and trade‐offs involved in sustainable development. This study investigates the use of BDA in fostering sustainability, identifying key practices, outcomes, challenges, and opportunities. By focusing on organizational tensions and strategic outcomes, this research offers an original contribution to the field. A systematic literature review was conducted to explore the role of BDA in advancing sustainability. The findings highlight the potential of BDA to align sustainability with more effective, data‐driven strategies, delivering positive impacts for both internal and external stakeholders. The benefits are observed across both private and public sectors. In industry, BDA improves energy efficiency by mapping real‐time data, optimizing natural resource use, and reducing costs. BDA also enhances mobility, identifying bottlenecks, improving public transport, and alleviating congestion. In circular processes, BDA aids waste management by promoting recycling and reuse. A conceptual framework is proposed, integrating sectoral applications, enablers, barriers, and outcomes, to support both academic research and managerial practice. The article concludes with recommendations for further discussion and research on the role of BDA in sustainability.