
Offering delicious great quality food at competitive prices has been at the heart of what we do since John James and Mary Ann Sainsbury opened our first store in 1869.
Today, inspiring and delighting our customers with tasty food remains our priority and our purpose is clear – driven by our passion for food, together we serve and help every customer.
Our focus on great value food and convenient shopping, whether in-store or online is supported by our brands – Argos, Tu Clothing, Habitat, Sainsbury’s Bank and Nectar. Sainsbury’s has over 600 supermarkets and over 800 convenience stores. Argos is a leading digital retailer and is the third most visited retail website in the UK, with over 90 per cent of its sales starting online. Argos is conveniently available for customers to collect from hundreds of Sainsbury’s stores. Digital and technology enables us to adapt as customers shop differently and our profitable, fast-growing online channels offer customers quick and convenient delivery and collection capability.
Our 172,000 colleagues are our greatest asset and they are integral to our success, now and in the future.
Challenge background:
There is currently no method of detecting specific bacterial species on food products other than by destructive testing or through inadvertent consumption. Current testing methods are destructive, providing retrospective results that are indicative of an issue, rather than a guaranteed absence in the product sold for consumption.
For this challenge:
Sainsbury’s is looking to develop solutions to guarantee the absence of specific bacteria in the product sold for consumption. Optimal production hygiene is a key requirement for bacterial control but cannot ensure specific bacteria-free foods, therefore the ambition is to work in partnership with food producers to contain the problem early on in the value chain, before delivery to Sainsbury’s. The solution must help identification and potentially inactivation of specific bacteria species either on raw material (for example, smoked salmon) or finished product at point of pack (for example, post cook and slice for cooked meats) without altering the appearance, taste or nutritional properties of the RTE.
Once proven, there is an opportunity for the at scalable deployment of the solution across multiple other tiers of the food supply chain and microbiological challenges such as food poisoning, foodborne illness and extension of shelf life for fresh produce.
As part of the prototype phase of the programme, Ascalia worked with Sainsbury’s on the microbial control in ready to eat foods challenge: High-tech cameras and artificial intelligence (AI) to ensure food safety from microbes and rot.
Challenge background:
The drivers of food spoilage and reduced shelf life are relatively well understood yet food manufacturers fail to maximise shelf life and quality of food on a consistent basis, this is as a result of both supply chain and raw material complexities. The multiple inter-relationships between influencing factors (for example,. time, temperature, hygiene, environment and product composition) along farm to fork supply chains drive the complexities, resulting in the inability to deliver and implement relevant, timely, and effective interventions.
Current data capture and interrogation technologies fail to deal with the complexity of supply chains. As such, there is no way of clearly understanding the impacts of specific events or processes (such as a time delay or temperature spike) along the supply chain on an end product.
For this challenge:
Sainsbury’s is interested in the development of real-time data collection and interrogation mechanisms, and data based automated feedback and control loops that would allow inter-relationships to be identified and managed along an integrated supply chain. This would deliver the ability to optimise time, temperature and hygiene controls realising significant benefits in terms of product shelf life, reduced waste, quality and nutrition and enabling more effective business demand planning.
Data generation, interrogation and feedback would clearly benefit from the development of non-destructive technologies for the detection and enumeration of pathogens and spoilage organisms.
As part of the prototype phase of the programme, Singular Intelligence worked with Sainsbury’s on the increasing shelf life and sell through of products while reducing waste challenge: AI-based decision-making to develop a predictive shelf-life model for the supply chain, along with an automated, centralised optimal control system.