Management makes its second key decision on personal-selling strategy when it decides the size of the sales force. Having determined the kind of salesperson that best fits the company’s needs, management now determines how many are required to meet the sales volume and profit objectives. If the company has too few salespersons, opportunities for sales and profits go unexploited, and if it has too many, excessive expenditures for personal-selling (even though they may bring in additional sales dollars) reduce net profits. It is difficult, perhaps impossible, to determine the exact number of salespersons that a particular company should have. Three basic approaches are used in approximating this number: (1) the work-load method, (2) the sales potential method, and (3) the incremental method. Each provides needed insights on the “right size” of sales force, although none produces a definitive answer.

**1. Work Load Method**

In the work load method the basic assumption is that all sales personnel should shoulder equal work loads. Management first estimates the total work load involved in covering the company’s entire market and then divides by the work load that an individual salesperson should be able to handle, thus determining the total number of salespeople required. Companies applying this approach generally assume that the interactions of three major factors—customer size, sales volume potential, and travel load—determine the total work load involved in covering the entire market.

The six steps in applying the work load approach are shown in the following example:

- Classify customers, both present and prospective, into sales volume potential categories. (Classification criteria, other than sales volume or sales volume potential, can be used as long as it is possible to distinguish the differences in selling effort required for each class.) Assume that there are 880 present and prospective customers, classified by sales volume potential as

Class A, large 150 accounts

Class B, medium 220

Class C, small 510

- Decide on the length of time per sales call and desired call frequencies on each class. (Several inputs are used in making these two decisions, for example, personal judgment, the opinions of sales personnel, and actual time studies). Assume that both present and prospective customers require the same amounts of time per sales call and the same call frequencies per year as follows:

Class A: 60 minutes/call x 52 calls/year = 52 hours/year

Class B: 30 minutes/call x 24 calls/year = 12 hours/year

Class C: 15 minutes/call x 12 calls/year = 3 hours/year

- Calculate the total work load involved in covering the entire market. In our example, this calculation is

- Determine the total work time available per salesperson. Suppose that management decides that salespeople should work 40 hours per week, 48 weeks per year (allowing 4 weeks for vacations, holidays, sickness, etc.), then each salesperson has available

40 hours/week x 48 weeks = 1,920 hours/year

- Divide the total work time available per salesperson by task. As sume that management specifies that sales personnel should apportion their time as follows:

- Calculate the total number of salespeople needed. This is a matter of dividing the total market work load by the total selling time available per sales person:

The work load approach is attractive to practicing sales executives. It is easy to understand and easy to apply. Many large firms like Celanese, IBM, and AT&T have used this approach.

A basic flaw in the work load approach is that, as usually applied, it disregards profit as an explicit consideration. However, of course, management can take profit criteria into consideration in determining lengths and frequencies of sales calls. But the optimum length and frequency of any particular sales call depends upon many factors other than account size (in terms of sales volume or sales volume potential). Such factors as the gross margin on the product mix purchased by an account, the expenses incurred in servicing an account, and an account’s likely responses to changed levels of selling effort all influence profitability.

Still another shortcoming traces to the inherent assumption that not only should all sales personnel have the same work load but that they all can and will utilize their time with equal efficiency. Although a relation exists between the amount of time spent on calling on an account and the size of the order received, some salespeople accomplish more in a shorter time than others can. The “quality of time invested in a sales call” is at least as important as the “quantity of time spent on a sales call.”

**2. Sales Potential Method**

The sales potential method is based on the assumption that performance of the set of activities contained in the job description represents one sales personnel unit. A particular salesperson may represent either more or less than one sales personnel unit. If the individual’s performance is excellent, that individual may do the job of more than one unit; if the individual’s performance is below par, he or she may do less. If management expects all company sales personnel to perform as specified in the job description, then the number of salespersons required equals the number of units of sales personnel required. Generally, it must be noted, sales job descriptions are constructed on management’s assumption that they describe what the average salesperson with average performance will accomplish. With that assumption, then, one can estimate the number of dollars of sales volume that each salesperson (that is, each sales personnel unit) should produce. Dividing this amount into forecasted sales volume—the company’s sales volume objective—and allowing for sales force turnover results in an estimate of the number of salespeople needed. These relationships are summarized in the equation

where

N = number of sales personnel units

S = forecasted sales volume

P = estimated sales productivity of one sales personnel unit

T = allowance for rate of sales force turnover

Consider a firm with forecasted sales of $1 million, estimated sales productivity per sales personnel unit of $100,000, and an estimated annual rate of sales force turnover of 10 percent. Inserting these figures in the equation, we have

N = 11 sales personnel units.

This is a simplified model for determining the size of a sales force. It does not, for instance, include the lead times required for seeking out, hiring, and training salespeople to the desired level of sales productivity. Actual planning models have built-in lead and lag relations to allow for such requirements. If two months of full-time training are required to bring a new salesperson up to the desired productivity, recruiting must lead to actual need for the new salesperson by two months. Another assumption implicit in this simple model is that sales potentials are identical in all territories, which is similar to the assumption that the number of sales personnel units required is the same as the number of salespersons needed; where this assumption does not hold, the model should be adjusted accordingly.

Difficulties in making estimates for this model vary with the factor being estimated (N, S, P, or T) and the company. The crucial estimate of the sales productivity of one unit of sales strength relies heavily on the accuracy and completeness of the sales job description; it depends also on management’s appraisal of what reasonably may be expected of those who fill the position. Estimating the sales force turnover rate is a matter of reviewing previous experience and anticipating such changes as retirements and promotions. In addition, both the estimates for unit sales productivity and the sales force turnover rate require management to have some means of evaluating the efficiency of individual salespersons and of determining the probabilities that individuals will remain with or leave the sales force during the planning period.

The estimate for forecasted sales volume deserves special comment. In many situations, the magnitude of the sales forecast is itself influenced by the planned size of the sales force. Indeed, since it takes time to add significant numbers to the sales force, a realistic sales forecast must take into account the number of salespersons (or sales personnel units) expected to be at management’s disposal during the planning period.

In a new and rapidly growing company, potential sales volume often depends chiefly on the number and ability of its sales staff. Management, actually, may derive the sales forecast by multiplying the estimated sales productivity of its average salesperson by the number it has, can expect to keep, and can recruit and train during the planning period. As a company expands distribution geographically and its growth rate slows down, the procedure reverses itself. Under these circumstances, the number of sales personnel units required is determined by making the sales forecast first, and dividing it by the expected sales productivity of an individual salesperson, making adjustments for anticipated sales force turnover, lead times for recruiting and training, and other relevant factors.

**3. Incremental Method**

Conceptually, the incremental method is the best approach to determining sales force size. It is based on one proposition: net profits will increase when additional sales personnel are added if the incremental sales revenues exceed the incremental costs incurred. Thus, to apply this method, one needs two important items of information: incremental revenue and incremental costs.

To illustrate, assume the following situation. A certain company has found that its total sales volume varies directly and significantly with the number of salespeople it has in the field. Its cost of goods sold does not vary significantly with increases in sales, but holds steady at 65 percent of sales. All company sales personnel receive a straight salary ($20,000 annually per person) and in addition are paid commissions of 5 percent on the sales volume they generate. In addition, each salesperson receives a travel and expense allowance of $12,000 per year, that is, $1,000 per month. The company now has fifteen people on its sales force and wants to determine whether it should add additional staff. Its sales executives estimate the following increases in sales volume, cost of goods sold, and gross margin that would result from the addition of the sixteenth, seventeenth, eighteenth, and nineteenth salespersons.

Next, they calculate the net profit contribution resulting from the addition of each salesperson. Adding the eighteenth salesperson brings in an additional net profit contribution of $13,000, but adding the nineteenth salesperson produces a negative net profit contribution of $2,000. Thus, the optimal size of sales force here is eighteen people.

Although this method is the most conceptually correct, it is also the most difficult to apply. It requires, first, that the company develop a sales response function to use in approximating (in terms of sales volume) the market’s behavior in relation to alternative levels of personal-selling effort. (A sales response function is a quantitative expression that describes the relationship between the amount of personal-selling effort and the resulting sales volume.) For the response function to be useful in setting the size of the sales force, sales volume must be sensitive to changes in the number of sales personnel.^{[1]}^{ [2]} Not many companies have the research sophistication required for development of sales response functions, but some apply the basic concept.^{[3]} It is doubtful that the incremental method is appropriate where personal-selling is not the primary means of making sales, that is, in cases where other forms of promotion, such as advertising, have stronger influences on sales volume than does personal-selling effort. Two additional problems in applying this approach are noted by T. R. Wotruba: “It fails to account for possible competitive reactions as well as for the longterm investment’ effect of personal-selling effort.

Source: Richard R. Still, Edward W. Cundliff, Normal A. P Govoni, Sandeep Puri (2017), Sales and Distribution Management: Decisions, Strategies, and Cases, Pearson; Sixth edition.

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