In an interview with TimesTech, Priyadarsanie Ramasubramanian, Engineering Director – Supply Chain, Tesco Technology, shares Tesco’s strategies for achieving net-zero emissions by 2050. From leveraging AI and ML to optimise transport and reduce waste to adopting renewable energy and driving circular economy practices, she outlines how technology plays a pivotal role in creating a sustainable future.
Read the full interview here:
TimesTech: Can you outline Tesco’s key strategies for achieving net-zero emissions by 2050 and the role of technology in this journey?
Priyadarsanie: Engineering and technology are crucial in driving sustainability and enabling large organisations to operate without negatively impacting the environment, communities, or society. At Tesco, we recognise our responsibility to address the impact the food system has on climate and nature as part of our core purpose: to serve our customers, communities, and planet a little better every day.
Central to this plan is our commitment to reaching net-zero emissions across our full value chain by 2050. Credible leadership, industry collaboration in the transition towards net zero, and leveraging technologies such as artificial intelligence, machine learning, virtual reality, video analytics, the Internet of Things, and cloud computing play a key role.
TimesTech: How is Tesco using AI to optimise routes and capacity during the shift to decarbonised transport, and what impact has it made?
Priyadarsanie: Transport comprises a significant portion of every retailer’s emissions. Intelligent metaheuristic algorithms (a combination of many) help efficiently scan through millions of options to find effective demand splits, store pairings, trip pairings, and driver optimisation. This helps optimise transport by ensuring trucks run at full capacity and take the most efficient routes, reducing miles travelled and drastically cutting down CO2 emissions. This optimisation is crucial, considering the trips from suppliers to distribution centres, stores, and our end customers. Tesco is also working to switch our fleets to low-carbon alternatives based on available market solutions.
TimesTech: How does machine learning help Tesco manage waste efficiently and predict emissions reductions accurately?
Priyadarsanie: Waste reduction across our supply chain and stores is key. AI and ML help predict customer demand through advanced forecasting algorithms, optimising ordering decisions, and ensuring an accurate view of stock levels across the system to prevent over- and under-ordering. These capabilities, built on big data platforms using machine learning algorithms, reduce waste by ensuring optimal availability and minimising waste.
To prevent waste, engineering solutions automate intelligent fresh food reductions. Applications help identify and process donations to local charities efficiently and transparently, benefiting communities in need. Validations ensure charities are notified about ingredients and allergens, preventing the donation of age-restricted or unauthorised products.
TimesTech: What steps is Tesco taking to adopt renewable energy through solar technology and power agreements, and how has it improved energy efficiency?
Priyadarsanie: We continually work to enhance energy efficiency and reduce emissions by shifting from fossil fuels to renewable electricity. We have established power purchase agreements (PPAs), wind generation, and on-site solar, and are trialling innovations such as on-site battery storage to increase clean electricity consumption annually.
TimesTech: Can you share how Tesco’s 4Rs packaging strategy is driving sustainable and circular economy practices?
Priyadarsanie: Remove what we can; reduce what we can’t; reuse more; and recycle what’s left. Our ambition is to have fully recyclable packaging, with technology-enabled intelligence key to enabling a circular economy.
TimesTech: How is Tesco leveraging data analytics and digital twins to create sustainable supply chains?
Priyadarsanie: We work with our suppliers to take a landscape-based approach to transforming our supply chains holistically, achieving lasting environmental benefits for both climate and nature. This includes sharing more accurate and long-term forecasts, providing data visibility to optimise ordering decisions, and reducing waste and supplier transport. Efforts are underway to materialise digital twins—visual representations of the end-to-end ecosystem that simulate real-life scenarios to drive sustainability and reduce maintenance costs and carbon footprints.
Sustainability seeks long-term solutions, and engineering plays a vital role through early design thinking, improved infrastructure, and digital technologies.
