Product returns are goods that retailers or consumers send back to manufacturers due to reasons that are either non-preventable or preventable. Both are collectively bucketed under a manufacturer’s total warranty returns (TWR). While returns are often an afterthought, they impact the average manufacturer’s profitability by 3.8%, a significant cost item that incrementally chips away at their profit margins. Manufacturers often lack the information needed to deeply understand the volume of expected returns and why returns occur. While there are numerous solutions manufacturers can establish to learn about the past, what remains to be true is that there is a wide gap in the manufacturer’s ability to have forward-looking insights that can help reduce the financial impact of returns.
AI analyzes historical data that you collect on product returns to learn patterns that can help it predict which products are likely to be returned in the future. With advancements in interpretability, AI will also offer your supply chain managers the top reasons why each individual product is likely to be returned. Using these insights, your supply chain managers can conduct a root cause analysis to prevent avoidable returns and to make iterations to their product or manufacturing processes. For products that have a high risk of being returned, supply chain managers can conduct a cost and benefit analysis on whether they will incur a net loss with the shipment required to deliver the product to and back from the customer. Product returns may also reveal insights on other challenges such as identifying quality defects. Identifying returns can not only help on the product level but can also enable financial analysts to embed forecasted returns into their cash flow projections, ensuring that your organization is prepared for worst-case scenarios.
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Manufacturers use AI to deliver the best products on the market as quickly and ethically as possible, while increasing productivity and profits. They can significantly improve demand forecasting, supply chain management, predictive maintenance, and many other operational areas with the help of artificial intelligence.