H&M profit dive is a classic example of inaccurate forecasting

Following today’s news of H&M’s profit dive, Neil Chapman, Partner at Infosys Consulting, made the following comment highlighting the need for accurate forecasting and explaining how retailers can meet consumers’ growing demands while delivering more sales and boosting profits.

“H&M’s profit dive provides a classic example of a retailer inaccurately forecasting consumer spending – resulting in a warehouse full of stock, profits shrinking and inventories piling up. While H&M’s new logistics system and store concepts succeeded in increasing sales figures, profits have taken a nosedive. It seems that the budget fashion house did not predict just how vital the supply chain is when it comes to maximising sales.

 “H&M’s problem highlights the need for accurate forecasting and getting the product mix right. It’s great for retailers to work with marketing to boost new products, but if this isn’t communicated and shared with sales and supply, then the journey stops there and the warehouse is left with a surplus of incorrect stock.

 “This is where a fully digital supply chain will benefit retailers, commanding stronger communication skills and helping teams to liaise as effectively as possible with suppliers and within the business. Employing predictive analytics gives retailers the tools to understand and predict customer demand to streamline their procurement, and provide better customer experience at the same time. While this will demand a higher level of data analysis, so that employees can take advantage of the data being collected by AI and predictive analytics, it’s worth the investment.

 “The best way for retailers to meet consumers’ growing list of expectations – while delivering more sales and boosting profits – is to use technology to get ahead.”