The Value of Weather Information for E-Commerce Operations
Sebastian Steinker, Kai Hoberg and Ulrich Thonemann study about two and a half years of daily orders at a European online fashion retailer. Sunshine, temperature and rain significantly affected demand, especially in summer, at weekends and in extreme weather, with good weather cutting orders strongly and bad weather raising them by much less. Adding weather data to statistical forecasting models cut forecast errors by 8.6 to 12.2 per cent on average, and by up to 50.6 per cent on summer weekends, against a baseline that ignored the weather. A workforce-planning scenario at a fulfilment centre with perfect weather knowledge cut excess costs by 11.6 per cent.
Sebastian Steinker, Kai Hoberg and Ulrich Thonemann study about two and a half years of daily orders at a European online fashion retailer. Sunshine, temperature and rain significantly affected demand, especially in summer, at weekends and in extreme weather, with good weather cutting orders strongly and bad weather raising them by much less. Adding weather data to statistical forecasting models cut forecast errors by 8.6 to 12.2 per cent on average, and by up to 50.6 per cent on summer weekends, against a baseline that ignored the weather. A workforce-planning scenario at a fulfilment centre with perfect weather knowledge cut excess costs by 11.6 per cent.
Written from the abstract read 2026-10-21 and a university summary.
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Steinker, S., Hoberg, K., & Thonemann, U. W. (2017). The Value of Weather Information for E-Commerce Operations. Production and Operations Management, 26(10), 1854-1875. doi:10.1111/poms.12721