For retailers, figuring out what to stock in their stores for the holiday selling season is often the most difficult merchandising decision they face. It is especially challenging for retailers selling winter products, such as clothing, footwear and snow removal equipment, because weather prediction is extremely challenging. Consequently, estimating customer demand for winter products is quite difficult. And because retailers must determine how much inventory to order months in advance of the selling season, making the wrong decision on what customers will buy can mean missing out on significant sales (i.e., not enough inventory) or being forced to slash prices (i.e., too much inventory).
As part of their planning for seasonal sales, store-based retailers often turn to weather analytics firms that use highly advanced software for estimating future weather patterns. Their forecasts are especially useful in aiding retailers to not only decide what type of products to sell, but also to suggest when the best time will be to ship products to stores in a particular regional area.
While forecasting the weather has improved and is helping retailers with their inventory decisions, it is far from perfect. For example, even though most weather analytics firms have already predicted a relatively mild winter for much of the U.S., so far temperatures have been even higher than forecasted. Consequently, as discussed in this Advertising Age story, U.S. retailers have already lost a large amount of sales due to unusually warm weather.
Though the amount of lost sales cited in the story, $185 million for the month of November, seems high, it is almost certainly much lower than what it could have been if the science of weather prediction was not where it is today.