Basic Marketing: A Global Managerial Approach

Perreault−McCarthy: Basic
Marketing: A
Global−Managerial
Approach, 14/e

19. Implementing and
    Controlling Marketing
    Plans: Evolution and
    Revolution

Text © The McGraw−Hill

Companies, 2002

Implementing and Controlling Marketing Plans: Evolution and Revolution 563

With a straight performance analysis, the marketing manager can evaluate the

variations among sales reps to try to explain the “why.” But this takes time. And

poor performances are sometimes due to problems that bare sales figures don’t reveal.

Some uncontrollable factors in a particular territory—tougher competitors or inef-

fective middlemen—may lower the sales potential. Or a territory just may not have

much potential.

To get a better check on performance effectiveness, the marketing manager com-

pares what did happen with what ought to have happened. This involves the use

of performance indexes.

When a manager sets standards—that is, quantitative measures of what ought to

happen—it’s relatively simple to compute a performance index—a number like a

baseball batting average that shows the relation of one value to another.

Baseball batting averages are computed by dividing the actual number of hits by

the number of times at bat (the possible number of times the batter could have had

a hit) and then multiplying the result by 100 to get rid of decimal points. A sales

performance index is computed the same way—by dividing actual sales by expected

sales for the area (or sales rep, product, etc.) and then multiplying by 100. If a sales

rep is batting 82 percent, the index is 82.

We show how to compute a performance index in the following example, which

assumes that population is an effective measure of sales potential.

In Exhibit 19-6, the population of the United States is broken down by region

as a percent of the total population. The regions are Northeastern, Southern, Mid-

western, and Western.

A firm already has $1 million in sales and now wants to evaluate performance

in each region. Column 2 shows the actual sales of $1 million broken down in pro-

portion to the population in the four regions. This is what sales shouldbe if

population were a good measure of future performance. Column 3 in Exhibit 19-6

shows the actual sales for the year for each region. Column 4 shows measures of

performance (performance indexes)—Column 3 Column 2 100.

The Western region isn’t doing as well as expected. It has 20 percent of the total

population—and expected sales (based on population) are $200,000. Actual sales,

however, are only $120,000. This means that the Western region’s performance

index is only 60—(120,000 200,000)  100 —because actual sales are much

lower than expected on the basis of population. If population is a good basis for

A performance index is

like a batting average

A simple example

shows where the

problem is

Exhibit 19-6 Development of a Measure of Sales Performances (by region)

(1) (2) (3) (4)

Expected

Population Distribution

as Percent of of Sales Based Actual Performance

Regions United States on Population Sales Index

Northeastern 20 $ 200,000 $ 210,000 105

Southern 25 250,000 250,000 100

Midwestern 35 350,000 420,000 120

Western 20 200,000 120,000 60

Total 100 $1,000,000 $1,000,000

Performance Indexes Simplify Human Analysis

Comparing against

“what ought to

have happened”