United KingdomRetail and e-commerce2026 – ongoingOcado Group
Machine learning for robot routing and storage placement in fulfilment centres
Ocado used machine learning on warehouse data to cut robot travel and picking time
Problem
Ocado's fulfilment centres can run hundreds or thousands of robots at once. Their routes, traffic and the placement of products all affect how fast orders are picked.
Approach
Ocado's algorithms analyse operational data from its fulfilment centres. They tune robot routing and traffic management. Order patterns and movement data decide where products are stored, so robots travel less and picking takes less time.
Results
No published figures
Takeaway
The same report links Ocado's automation gains to a restructuring of about 1,000 job cuts and a roughly 150 million pound cost-base reduction. It did not attribute those cuts to machine learning alone.
Categories
- Size
- Large enterprise
- Industry
- Retail and e-commerce
- Business function
- Production and qualityLogistics and supply chain
- Innovation type
- Process innovation
- AI technology
- OptimizationPredictive analytics and ML
- Adoption
- Built in-house
- Evidence
- Press reporting
Sources
Source summaries
The article describes how Ocado's machine learning uses fulfilment-centre data to improve robot routing, traffic management and product placement. It also reports about 1,000 job cuts, roughly 5% of the global workforce, as part of a plan to reduce the cost base by about 150 million pounds. It gives no measured result for the machine learning itself.
Full details are in the original sources.