When forecasts go wrong
In 1987, the south-east of Britain was hit by some very strong winds. The BBC weatherman, Michael Fish, has had to live with the broadcast that he made the night before. The piece that everyone remembers is taken out of context, when he said there wasn't a hurricane on the way. He went on to say that people in the south-east should batten down the hatches because there would be some very strong winds, but most people forget this and remember the words about the non-existent hurricane. Even so, it is admitted that the forecast that night was not accurate, because the path of the strong winds was not predicted correctly.
Mistakes in forecasting in operational research are usually much less serious, but this week, Marks and Spencer (M&S) shares dropped 3% in one day as a result of the admission of some poor forecasting, coupled with poor supply chain management. In February this year, there was a spell of very cold weather in the U.K., which drove customers to M&S to stock up with warm clothing. Sadly, the shops ran out of several lines of womenswear and the sales of the chain (Britain's largest clothing retailer) suffered. Newspaper reports and the company's spokesmen have concentrated on this mistake, while ignoring the fact that the forecasts for menswear and clothes for children were satisfactory. A lesson for practitioners -- you are remembered for mistakes, like Michael Fish, and not for your successes, even if the latter outnumber the former!
Forecasting fashion is traditionally very difficult, leaving aside the effects of the British weather. In the same reports of the shortages of warm clothes, there was a note about how demand outstripped supply for ballet shoes in M&S. The demand for these was only vaguely connected to the weather, and much more about fashion. M&S say that they could have sold twice the number of pairs than they did. (As an aside, how do they know that? How can you record lost demand very accurately in a store where customers serve themselves? Mind you "twice" sounds a good number, implying that they have measured it and they accept that their estimate is not precise.)
The company commented on the problem of supply chain management in two ways. First, there was some unspecified bottleneck which had affected the supply in advance of the demand (so the forecasts must have been closer to demand, and the errors in the forecasts would have been smaller if this glitch had not happened), and second, the lag in the "warm womenswear supply chain" was about four to six weeks. The delay because goods come from the Far East.
As usual, the media reports gloss over the "hidden science" of operational research which helped manage the forecasts and the supply chain planning.
Mistakes in forecasting in operational research are usually much less serious, but this week, Marks and Spencer (M&S) shares dropped 3% in one day as a result of the admission of some poor forecasting, coupled with poor supply chain management. In February this year, there was a spell of very cold weather in the U.K., which drove customers to M&S to stock up with warm clothing. Sadly, the shops ran out of several lines of womenswear and the sales of the chain (Britain's largest clothing retailer) suffered. Newspaper reports and the company's spokesmen have concentrated on this mistake, while ignoring the fact that the forecasts for menswear and clothes for children were satisfactory. A lesson for practitioners -- you are remembered for mistakes, like Michael Fish, and not for your successes, even if the latter outnumber the former!
Forecasting fashion is traditionally very difficult, leaving aside the effects of the British weather. In the same reports of the shortages of warm clothes, there was a note about how demand outstripped supply for ballet shoes in M&S. The demand for these was only vaguely connected to the weather, and much more about fashion. M&S say that they could have sold twice the number of pairs than they did. (As an aside, how do they know that? How can you record lost demand very accurately in a store where customers serve themselves? Mind you "twice" sounds a good number, implying that they have measured it and they accept that their estimate is not precise.)
The company commented on the problem of supply chain management in two ways. First, there was some unspecified bottleneck which had affected the supply in advance of the demand (so the forecasts must have been closer to demand, and the errors in the forecasts would have been smaller if this glitch had not happened), and second, the lag in the "warm womenswear supply chain" was about four to six weeks. The delay because goods come from the Far East.
As usual, the media reports gloss over the "hidden science" of operational research which helped manage the forecasts and the supply chain planning.
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