The Business Forecasting Deal
Exposing bad practices and offering practical solutions in business forecasting
In 1965's Subterranean Homesick Blues, Bob Dylan taught us: You don't need a weatherman / To know which way the wind blows In 1972's You Don't Mess Around with Jim, Jim Croce taught us: You don't spit into the wind By combining these two teachings, one can logically conclude that:
Our tradition from Foresight’s birth in 2005 has been to feature a particular topic of interest and value to practicing forecasters. These feature sections have covered a wide range of areas: the politics of forecasting, how and when to judgmentally adjust statistical forecasts, forecasting support systems, why we should
We're entering the busy season for forecasting events, and here is the current calendar: Analytics2014 - Frankfurt The European edition of Analytics2014 kicks off tomorrow in Frankfurt, Germany. Five hundred of the leading thinkers and doers in the analytics profession hook up for two full days of interaction and learning.
As we saw in Steve Morlidge's study of forecast quality in the supply chain (Part 1, Part 2), 52% of the forecasts in his sample were worse than a naive (random walk) forecast. This meant that over half the time, these companies would have been better off doing nothing and
As we saw last time with Steve Morlidge's analysis of the M3 data, forecasts produced by experts under controlled conditions with no difficult-to-forecast series still failed to beat a naive forecast 30% of the time. So how bad could it be for real-life practitioners forecasting real-life industrial data? In two words:
The Spring 2014 issue of Foresight includes Steve Morlidge's latest article on the topic of forecastability and forecasting performance. He reports on sample data obtained from eight business operating in consumer (B2C) and industrial (B2B) markets. Before we look at these new results, let's review his previous arguments: 1. All