The Value of Weather Information for E‐Commerce Operations

Abstract

To be efficient, logistics operations in e‐commerce require warehousing and transportation resources to be aligned with sales. Customer orders must be fulfilled with short lead times to ensure high customer satisfaction, and the costly under‐utilization of workers must be avoided. To approach this ideal, forecasting order quantities with high accuracy is essential. Many drivers of online sales, including seasonality, special promotions and public holidays, are well known, and they have been frequently incorporated into forecasting approaches. However, the impact of weather on e‐commerce operations has not been rigorously analyzed. In this study, we integrate weather data into the sales forecasting of the largest European online fashion retailer. We find that sunshine, temperature, and rain have a significant impact on daily sales, particularly in the summer, on weekends, and on days with extreme weather. Using weather forecasts, we have significantly improved sales forecast accuracy. We find that including weather data in the sales forecast model can lead to fewer sales forecast errors, reducing them by, on average, 8.6% to 12.2% and up to 50.6% on summer weekends. In turn, the improvement in sales forecast accuracy has a measurable impact on logistics and warehousing operations. We quantify the value of incorporating weather forecasts in the planning process for the order fulfillment center workforce and show how their incorporation can be leveraged to reduce costs and increase performance. With a perfect information planning scenario, excess costs can be reduced by 11.6% compared with the cost reduction attainable with a baseline model that ignores weather information in workforce planning.

Choosing the delivery and return method in purchases: the effect of situational factors in omni-channel contexts

“…For instance, during peak office hours, consumers prefer to purchase online and receive the order at their preferred location. Steinker, Hoberg and Thonemann (2016) investigated the effect of weather conditions on online sales at the Zalando company. The results in Steinker et al (2016) indicate that the inconvenience caused by bad weather conditions leads consumers to be more likely to choose online rather than offline channels.…”

Hedging weather risk and coordinating supply chains

“…Existing methodologies used to isolate the effect of weather on sales typically require the ability to directly compare large amounts of business data with weather observations (Bahng and Kincade, 2012; Steinker et al, 2017; Bertrand et al, 2015; Starr‐McCluer, 2000; Lazo et al, 2011). They also make assumptions about or control for factors likely to cause a change in demand (e.g.…”

“…They also change consumers’ purchasing decisions about the product and the amount of product they buy (Parsons, 2001; Kirk, 2005). Even as retail is shifting from brick and mortar stores to online shopping, the weather continues to exert its influence on consumer behavior (Starr‐McCluer, 2000; Lazo et al, 2011; Steinker et al, 2017; WeatherUnlocked, 2014).…”

Information systems for supply chain management: a systematic literature analysis

“…First, with the availability of big data, and access to data science tools, it is possible to incorporate additional variables to the existing variables being used in the analyses. An example would be an incorporation of weather data in dynamic planning for logistics operation (Steinker, Hoberg, and Thonemann 2017). Achieving this requires incorporation of a mix of dynamic programming and data science tools for problem modelling purposes.…”