Companies introducing innovative products during the holiday season often wind up with large surpluses from 'duds' or huge shortages from 'blockbuster' products—or what I call the “holiday misses.” Year in and year out, highly inaccurate forecasts torpedo the best-laid product introduction plans.

During my child-rearing years, holiday misses included Cabbage Patch Kids and My Little Ponies. This year it was Nintendo's turn with their wildly successful Wii product. A couple of years ago it was Microsoft with the Xbox.

Yet, have companies really learned from their prior mistakes and worked to improve forecasting and planning? Or are they really building enough flexibility into their supply chains to mitigate against inherent new product risks? Demand management techniques could alleviate some of these post-holiday blues.

The first step in avoiding holiday misses is to understand what is actually happening at the retail shelf. I once consulted with a high-end toy manufacturer to help it improve demand management processes. The VP of sales showed me pictures taken of a variety of store shelves during the holiday season. The photos showed his company's products on shelves in total disarray—to a degree that no consumer could find what they wanted, nor would they care to try! He used the pictures to support a new program in which merchandisers would be hired to go into stores and ensure that products were stocked and neatly displayed.

What I took away from the pictures was a recognition of the risk brand companies face when selling through a retailer: they are blind to what is really happening at the point-of-sale, and its impact on their sales, as well as brand image.

This is an important concern for gauging historical holiday demand. Does a company really understand what new products might have sold or did not sell last holiday season? Shortages are often only anecdotally conveyed to them by retail merchandisers and buyers. Surpluses are avoided, as retailers drastically mark down prices to dispose of products. This leaves a company with a dearth of good historical information from which to forecast and plan next year's new products.

At an MIT event I ran we discussed a survey (conducted by the Demand Management Solutions Group) that included questions on the industry's view of point-of-sale (POS) data. It showed that many respondents don't collect or use POS data for planning because they believed it to be inconsistent, cumbersome, or hard to use. The event's attendees, however, concurred with one research finding that showed that while POS data was less useful for planning routine 'turn' business, it is was more useful for gauging promotional and new product business.

Thus, a way product companies might alleviate missed holiday sales is to improve forecasting by leveraging historical information more closely aligned to what really happened at the shelf and understanding 'real' consumer demand, not just sales to retailers. This information might include the use of scan-based POS data supplemented by information on store-level pricing, product displays, competitive products and prices, etc. It would represent a clearer 'post-mortem' picture of what really happened last year, which can be useful in assessing next year's new product sales.

However, this improved forecasting will only be one part of the solution since forecast inaccuracies will still be too high.

The late English philosopher Francis Bacon said: “If a man will begin with certainties, he shall end in doubts: but if he will be content to begin with doubts, he shall end in certainties.”

Most companies don't heed his advice. They plan the supply of a new product assuming that a forecast will happen. In this way, they start with certainty and end in doubt with new product shortages and surpluses. Instead, Bacon might advise they start with the uncertainty of a forecast range, then build flexibility into supply plans to help mitigate against demand risk.

HP uses this type of risk management approach in purchasing scarce components. For example, it might have a forecast that says it will need anywhere from 200,000 to 300,000 units of a component to satisfy the demand of a new product. HP would use this information to contract with suppliers in a flexible way. HP might guarantee the purchase of 200,000 units at a low price, up front, when the forecast is most uncertain. It would then get an option to buy an additional 100,000 units at a higher price, at a later date when new information should improve forecast accuracy. Lastly, it might contract for an optional third purchase, should it look like over 300,000 units are needed to support a 'blockbuster'.

Companies could learn from HP's risk management techniques. Most use a point forecast to contract with a supplier (often overseas) to produce a total forecast in one big production run. A risk management approach dictates that it might be better to contract for one guaranteed production run, and negotiate options to purchase product from one or more future runs. These future runs would be executed only if new information or early sales indicators dictate a need for them.

Of course, this approach would increase a new product's total cost-of-goods and a company might have to manufacture the product itself (if suppliers balk). However, the opportunity to drastically reduce shortages and surpluses could more than compensate for the increased costs, especially for high-margin products with inaccurate forecasts. Put another way, why worry about saving 5 percent of manufacturing costs, if you can get an extra 60 percent margin on upside sales.

In summary, don't just accept new product holiday misses because you believe forecast errors are and will be inherently high. To “bring home the Bacon,” you might say, try improving forecast accuracy by leveraging historical shelf-level information and building flexibility into your new product supply plans.