About the research
Comprehensive, data‑driven view of the UK’s manufacturing waste landscape including: Total scale of sector waste. Where the recovery opportunities lie. 1. By food/drink category. 2. By location of waste i.e. where it is found and what causes it in the supply chain. What it would cost to recover.
Proprietary COGS tool quantifying the incremental cost of recovering waste and meals generated per £ reinvested.
Deep operational insight and benchmarking to estimate and locate waste across UK manufacturing.
About: Proprietary COGS tool quantifying the incremental cost of recovering waste and the meals generated through re-investment directly into manufacturing To estimate the cost of recovering surplus food into the human supply chain, we used Newton’s proprietary COGS (Cost of Goods Sold) tool to break down every constituent element of a manufacturing value chain, building a granular, bottom‑up view of the costs associated with producing and recovering each unit of food. It was used to model the incremental cost of intervening at different points in the manufacturing process to recover products that would otherwise become waste. By quantifying the specific inputs involved, it produced a transparent, data‑driven estimate of the cost of recovery.
Comprehensive, data‑driven view
Additionally, we used this capability to estimate the total number of meals that could be generated through re- investment of the total savings through reducing waste in the supply chain. About: Deep operational insight to estimate and locate waste across UK manufacturing In parallel, a detailed and category‑specific estimate of waste generated across UK food manufacturing was developed to create a category benchmark, drawing on: Over 25 years’ operational experience in the sector. Work with 300+ manufacturers across the UK and Europe. Insight spanning 100+ food categories. This insight base identifies with confidence where waste typically occurs along the manufacturing process for each category.
Combining the operational evidence with the benchmarking data produced an anonymised, industry‑representative view of: The expected volume of waste within each major food category. The points in the process where this waste is likely to arise. The degree to which different waste streams are accessible and recoverable into the human supply chain. The result is a Manufacturing Waste Map that reflects real manufacturing practices and provides the granularity needed to identify actionable opportunities to reduce or recover waste.
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