Sorry about that White Christmas, Philadelphia. It’s not looking good; temperatures are going to be at least in the 40s. Looking further ahead and afield: Come March, warm weather will boost shorts sales 28% in Chicago over last year, but the shorts business will be off a cool 15% in Tokyo. Oh, and good news for travelers: Flight delays at Philadelphia International Airport will be down 42% next year, compared with 2019, thanks to considerably less precipitation.
That is all according to Weather Trends International, a Pennsylvania-based company that sells long-range — as in 11 months in advance — forecasts to retailers and investors, writes The Philadelphia Inquirer (Dec. 9, 2019). Home Depot, Target and Walmart, JP Morgan, and Coca-Cola have all been customers. Reliable year-ahead forecasts would be invaluable to retailers. “Once merchandise has been put out for the season,” said an exec, “the cake is baked.” (Once a customer purchases an 11-month outlook, by the way, the company doesn’t change or update them).
Weather Trend’s formula is about two-thirds statistical analysis and the rest an analytical blend that includes weather “cycles,” primarily slow-occurring shifts in ocean temperatures and air pressure patterns, including the El Niño/Southern Oscillation and the Pacific Decadal Oscillation–plus 417 trillion bits of data. Temperature forecasts can be calibrated to retail sales: A one-degree difference makes a 15% change in air-conditioner sales and a 7% difference in the sunscreen business. A study by two climatologists concluded that for temperatures, the Weather Trends’ year-a-head forecast outperformed the U.S. Climate Prediction Center’s 3 month forecasts, which are updated monthly, four out of five times.
This is an interesting variation from the 3 types of forecasts (i.e., economic, technological, and demand) that we discuss in Chapter 4.
Classroom discussion questions:
1. Referring to “Forecasting Time Horizons” in your Heizer/Render/Munson text, how do short term forecasts differ from longer ones?
2. Why is a weather forecast an OM tool?