Bill Bittner

RSR Research: Retail Connections - Predictive Analytics in a Down Economy

March 1, 2010

FROM RETAILWIRE:
At an analytics roundtable at RetailConnections' Third Annual Business Executive Summit, the CIO of a major jewelry retailer said predictive analytics had been completely helpful to his company. In many ways, 2009 was a very profitable year, with little excess inventory. What do you think of the value of predictive analytics?      [more...]

Forecasting applications can be put into three categories: the historical simulation method uses past performance, the variance-covariance method attaches the series of interest to some other variable, and the Monte Carlo or stochastic simulation method uses probabilities and random number generators to generate a range of possible outcomes. All of them assume some type deterministic characteristic for the future. None of them plan for the "Black Swan Event," the event that is so rare no one would expect it to occur but when looking back seems so obvious. The general economy suffered just such an event in September of 2008 and despite all the warnings that seem so obvious now, we were not ready. Only a few wise people had pulled away from the punch bowl.

I don't think it is wise to make any long-range decisions based on the results of 2009. Because the circumstances of 2008 were so extremely (we hope) unusual, the accurate predictions for 2009 can be thought of as nothing more than good guesses. As the economy returns to the "new normal" and economic events follow predictable patterns again, forecasting algorithms will adapt to the new standard. These will be helpful in forecasting category demand and planning purchasing activity. That's good because the channel options have added a level of complexity that did not exist before. It is no longer "how much will people buy" but also "how will they buy" that must be answered. So if we get the demand right, then we have to know which channel will be used.

Forecasting algorithms are important, but they will not make good merchandisers great. Just like any tool, the algorithms will keep you from making horrendous mistakes but the really great merchandisers combine the algorithms with a dose of wisdom. The great merchandisers had a good 2008 holiday season.