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The current paper aims to discuss the implementation of Green Lean Six Sigma (GLSS) in the food industry to improve sustainable practices. The focus is more specifically on dairy processors to ascertain the current state of the literature and aid future research direction.

Utilising a systematic literature review (SLR), the paper addresses various terms and different written forms in the literature. The study characterises the current deployment of GLSS in the food industry and explains the reported benefits of this approach.

GLSS, a concept that has yet to be fully explored in the food industry, as in other sectors, holds significant potential to enhance the food industry’s sustainability practices. The dairy sector, a subsector of the food industry known for its high greenhouse gas emissions, is a prime candidate for the application of GLSS. In instances where it has been applied, GLSS has demonstrated its effectiveness in improving sustainability, reducing waste, lowering greenhouse gas emissions and minimising water usage. However, the specific tools used and the model for GLSS implementation are areas that require further study, as they have the potential to revolutionise food industry operations and reduce their environmental impacts.

Benchmarking of this research by the food industry sector and by academics can aid understanding of the practical application of GLSS tools and aid implementation of these practices to evolve the dairy processing sector in the next decade as sustainability champions in the sector.

This study extensively analyses GLSS in the food industry, with a particular focus on dairy processors.

This project aims to optimise a secondary agricultural company’s reporting and data lifecycle by providing self-help business intelligence at an optimal price point for all business users.

A design for Lean Six Sigma approach utilising the define, measure analyse, design and verify methodology was utilised to design a new reporting and data product lifecycle.

The study found that this approach allowed a very structured delivery of a complex program. The various tools used assisted greatly in delivering results while balancing the needs of the team.

This study demonstrates how improving data analysis and enhanced intelligence reporting in agribusinesses enable better decision making and thus improves efficiencies so that the agribusiness can leverage the learnings.

Improving data analysis increases efficiency and reduces agrifood food wastage thus improving sustainability and environmental impacts.

This paper proposes creating a standardised approach to deploying Six Sigma methodology to correct both the data provisioning lifecycle and the subsequent business intelligence reporting lifecycle. It is the first study to look at process optimisation across the agricultural industry’s entire data and business intelligence lifecycle.