AI turns retail returns from cost burden to competitive edge: McKinsey

In its report, ‘From cost center to competitive advantage: Modernizing reverse logistics with AI,’ McKinsey & Company noted that US consumers returned nearly $1 trillion worth of merchandise in 2024, forcing retailers to spend about $200 billion annually on processing and recovering value from returns. AI-driven decision engines can personalise return policies and optimise real-time dispositioning, directing returned goods to the highest-value channel, including restocking, refurbishment, resale, liquidation or recycling, to improve margin recovery.

However, McKinsey also noted that many retailers still depend on static rules and manual inspections, resulting in slower processing and margin erosion. Integrating customer, product and supply chain data into intelligent systems can enhance resale value, curb fraud, including identifying serial returners and wardrobing patterns, and accelerate turnaround times.

Dynamic, customer-specific return policies do not significantly deter shoppers, with 71 per cent of surveyed consumers indicating that tailored policies would not reduce future purchases. The report further highlighted the need to integrate return management into product design, pricing frameworks and lifecycle strategies to enhance value recovery and reduce waste.

The consultancy outlined six key levers for modernising reverse logistics: managing demand, improving data and insights, AI-led decisioning, operational optimisation, re-commerce strategies and structured feedback loops.

The firm emphasised that turning returns into a competitive advantage requires cross-functional alignment across merchandising, supply chain, finance and customer experience functions. Retailers that treat reverse logistics as a core business capability rather than a back-end process can protect margins while strengthening customer loyalty.

Fibre2Fashion News Desk (CG)