Perreault−McCarthy: Basic
Marketing: A
Global−Managerial
Approach, 14/e
- Developing Innovative
Marketing Plans
Text © The McGraw−Hill
Companies, 2002Developing Innovative Marketing Plans 619Specifically, the manager divided the trade association estimates by government
data on the number of people employed in each industry NAICS group (column
2). The result, shown in column 3, is simply an estimate of the value of boxes used
per employee in each industry group. For example, furniture and fixture manufac-
turers buy an average of $245 worth of boxes per employee.
Then the manager multiplied the value per employee number by the number of
people employed in each industry group in the target county (column 4). This
results in an estimate of the market potential for each industry group (column 5)
in that county. For example, since there are 616 people in this county who work in
furniture and fixture companies, the sales potential in that industry is only about
$151,000 (616 employees $245 per employee). The sum of the estimates for spe-
cific industries is the total market potential in that county.
A firm thinking of going into that market would have to estimate the share it
could get with its own marketing mix in order to determine its sales forecast. This
approach could be used county by county to estimate the potential in many geo-
graphic target markets. It could also aid management’s control job. If the firm is
already in this industry, it can compare its actual sales (by NAICS code) with the
potential to see how it’s doing. If its typical market share is 10 percent of the market
—and it has only 2 to 5 percent of the market in various NAICS submarkets—
then it may need to change its marketing mix to get better penetration.Not all past economic or sales behavior can be neatly extended with a straight
line or some manipulation. Economic activity has ups and downs, and other uncon-
trollable factors change. To cope with such variation, statisticians have developed
time series analysis techniques. Time seriesare historical records of the fluctuations
in economic variables. We can’t give a detailed discussion of these techniques here,
but note that there aretechniques to handle daily, weekly, monthly, seasonal, and
annual variations.^5
All forecasters dream of finding an accurate leading series—a time series that
changes in the same direction but ahead ofthe series to be forecast. For example,
car producers watch trends in the Index of Consumer Sentiment, which is based on
regular surveys of consumers’ attitudes about their likely future financial security.
People are less likely to buy a car or other big-ticket item if they are worried about
their future income. As this suggests, a drop in the index usually “leads” a drop in
car sales. It is important that there be some logical relation between the leading
series and what is being forecast.
No single series has yet been found that leads GNP or other national figures.
Lacking such a series, forecasters develop indices—statistical combinations of sev-
eral time series—in an effort to find some time series that will lead the series they’re
trying to forecast. Government agencies publish some indices of this type. And busi-
ness publications, like Business Weekand The London Financial Times,publish their
own indices.Times series and
leading series may help
estimate a fluctuating
futurePredicting Future Behavior Calls for More Judgment and Some Opinions
Jury of executive
opinion adds judgmentThese past-extending methods use quantitative data—projecting past experience
into the future and assuming that the future will be like the past. But this is risky
in competitive markets. Usually, it’s desirable to add some judgment to other fore-
casts before making the final forecast yourself.One of the oldest and simplest methods of forecasting—the jury of executive
opinion—combines the opinions of experienced executives, perhaps from market-
ing, production, finance, purchasing, and top management. Each executive estimates