Consumer Packaging and Food Waste
Atheon Analytics CEO, Guy Cuthbert, explains how new retail food portions and packaging materials can help reduce consumer waste.
According to a recent study from WRAP, approximately 60 per cent of household food waste arises from products that are not used in time. The study finds consumers need clearer information and innovation in packaging to help reduce this waste which is valued in the United Kingdom at £6.7 billion annually.
How, then, can retailers and suppliers introduce, test and measure the effectiveness of changes to packaging?
Innovations including split-packs, resealable packaging and sustainable alternatives to plastic may help to reduce waste but will not survive if sales are adversely affected.
The answer therefore lies in robust analysis of the performance of individual products, sold in individual stores, on a daily basis. This may sound obvious but, despite all large retailers collecting this data, much of their analysis uses highly-aggregated data-sets whilst additionally ignoring valued detail.
When considering packing changes it is necessary to include key product details including case size, product shelf life, and limitations relating to the type of packaging currently in use. Additionally, it is necessary to set these in the context of promotional patterns, local shopper behaviour, and price architecture.
These details become key to reducing waste with specific customer groups.
By way of (obvious) example, single-person households present significant opportunity for lowering waste whilst simultaneously enhancing supplier brand perception by combining single-portion packaging with low-plastic innovation.
Despite a widely held perception that single-portion products reduce profitability, the reality is many such products perform very well. Detailed analysis shows that they can simultaneously increase sales and reduce waste with specific shopper groups. Unsurprisingly perhaps, they are more likely to achieve or exceed target performance in metropolitan centres rather than rural areas. Single-person households are more common in urban areas, so aggregated analysis which ignores this might suggest that they perform poorly.
Retailers need to embrace modern analytical technologies which blend machine learning and data visualisation to create tools which point the way. The discipline of visual analytics enables rapid exploration from macro-patterns to micro-details, whilst retaining context. This is a powerful approach for monitoring short-cycle ‘test and measure’ product trials.
Rapid, detailed analysis drives rich understanding, leading to better-informed decisions around packaging innovation.