BUS203: Principles of Marketing

At best, a forecast is a scientific estimate, but really, a forecast is still just a sophisticated guess. Still, there are steps that can enhance the likelihood of success. The first step is to commit to accuracy. At Konica-Minolta, regional vice presidents are rewarded for being accurate and punished for being wrong about their forecasts, no matter what the direction of them is. As we mentioned earlier, underestimating is considered by Konica-Minolta leadership to be just as bad as overestimating sales.

We've also mentioned how salespeople and managers will lower estimates if the estimates are used to set quotas. Using forecasts properly is another factor that can improve forecasting accuracy. But there are other ways to make forecasts more accurate. These begin with picking the right methods for your business.

Pick the Right Method(s) for Your Business and Your Decision

Some products have very short selling cycles; others take a long time to produce and sell. What is appropriate for a fast-moving consumer good like toothpaste is not appropriate for a durable good like a refrigerator. A response model might work for Crest toothpaste in the short term, but longer-term forecasts might require a sophisticated time-series technique. By contrast, Whirlpool might find, for example, that channel surveys are better predictors of refrigerator sales over the long term.

Use Multiple Methods

Since forecasts are estimates, the more estimates generated from various methods, the better. For example, combining expert opinions with a trend analysis could help you understand not only what is happening but also why. Every forecast results in decisions, such as the decision to hire more people, add manufacturing capacity, order supplies, and so forth. In addition, practice makes perfect, as they say. The more forecasts you have to make and resulting decisions you have to live with, the better you will get at forecasting.

Use Many Variables

Forecasting for smaller business units first can result in greater accuracy. For example, JCPenney may estimate sales by region first, and then roll that information up into a national sales forecast. By forecasting locally, more variables can be considered, and with more variables comes more information, which should help the accuracy of the company's overall sales forecast. Similarly, JCPenney may estimate sales by market segment, such as women over age fifty. Again, forecasting in a smaller segment or business unit can then enable the company to compare such forecasts to forecasts by product line and gain greater accuracy overall.

Use Scenario-Based Forecasts

One forecast is not enough. Consider what will happen if conditions change. For example, how might your forecast change if your competitors react strongly to your strategy? How might it change if they don't react at all? Or if the government changes a policy that makes your product tax free? All of these factors will influence sales, so the smart executive considers multiple scenarios. While the executive may not expect the government to make something tax free, scenarios can be created that consider favorable government regulation, stable regulation, and negative regulation, just as one can consider light competitive reaction, moderate reaction, or strong reaction.

Track Actual Results and Adjust

As time goes on, forecasts that have been made should be adjusted to reflect reality. For example, Katie Scallan-Sarantakes may have to do an annual forecast for Scion sales, but as each month goes by, she has hard sales data with which to adjust future forecasts. Further, she knows how strongly competition has reacted and can adjust her estimates accordingly. So, even though she may have an annual forecast, the forecast changes regularly based on how well the company is doing.