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Men versus women in industrial sales: A performance gap
Men Versus Women in Industrial Sales: A Performance Gap John E. Swan
Charles M. Futrell
Sales managers have typically directed an all-male sales force. Today, they are recruiting women for positions in industrial sales. Whereas such managers may have a number of questions about women, probably the single most important
a sales performance gap exists between men and women in the companies participating in the research.
question is how men and women compare in job per$ormance. Although trade publications report that women have done quite well in sales [I 1, the question should not be considered resolved. Trade reports are extremely useful but are not based on systematic evidence. Another difJiculty with trade reports is the failure to test for spurious relationships, that is, apparent relationships due to variables correlated with both sex and per$ormance. In particular, variables that may be related to both sex and job performance should be examined to see whether job performance dtfherences are actually due to the sex of the person or whether such relationships are spurious.
PURPOSE
OF THE STUDY
Earlier research has indicated that the higher the similarity between the customer and the salesperson, the greater the chances of success of the sales transaction [3]. Since relatively few women were customers of the pharmaceutical and hospital supply firms in this study, the saleswomen would be at a disadvantage relative to the males, which could be reflected in lower performance ratings. Thus the main purpose of this study was to see if @ Elsevier North-Holland,
Inc., 1978 Industrial Marketing Management
RESEARCH
PROCEDURES
Data-Collection
Method
This article is based on a larger study in which the total sales staff and the salespersons’ immediate supervisors in two national pharmaceutical companies and one national hospital supply company were surveyed through the use of two mail questionnaires. The salespersons were sent one questionnaire. The salespersons’ supervisors were sent a different questionnaire and asked to evaluate each of their salespersons’ job performance. A subject was used in the study only if both his questionnaire and the supervisor’s performance rating were completed. The final sample was based on the analysis of 431 set of matched, usable questionnaires-representing a 5% percent response rate. Of the 43 1 respondents, 35 were female. This represented 83 percent of the three firm’s 42 female salespeople. Even though females are entering the sales profession at an increasing rate, it is difficult to find an industrial salesforce with a large number of women. The response rate among the 72 supervisors was 83 percent, and 65 percent of the 743 salespeople returned their questionnaires. The 43 1 respondents ’ ages, longev-
I, 369-373 (1978)
369 0019-8501/78/060293+05$01.75
ity of employment with the firm, and percent who graduated from college were measured. According to officals in each company, the measured characteristics of the respondents were similar to those of all salespeople in their company.
Work Environment of the Salespeople To find out if the salepeople from the three companies faced a similar work environment, supervisors were asked to describe their salespersons’ work activities and their firm’s channel of distribution, training, and organizational structure. The only basic difference between the pharmaceutical and hospital-supply salespersons’ jobs was that the pharmaceutical salespeople contacted retail pharmacists and physicians in their offices. The hospital-supply salespeople did not make such calls, although they did contact physicians at hospitals. All salespersons were responsible for selling company products and disseminating information to customers in a particular sales territory.
Measurement of Job Performance The 10 factors measuring job performance were developed by modifying the “district sales manager’s appraisal form” of the largest company in the study. The other two participating firms believed that the measuring device also adequately represented the manner in which their salespeople were evaluated. Sales figures were not used because each of the three organizations distribute their products through drug wholesalers. Since the companies do not sell directly to their customers, the companies believed that sales dollars should not be utilized as a formal indicator of job performance.
JOHN E. SWAN is Professor of Marketing at the University of Alabama. He received his D.B.A. from Indiana University. He has authored articles appearing in such journals as the Journal of Marketing Research, and Journal of Applied Psychology. He is on the editorial board of the Journal of Marketing Research and Decision Sciences.
CHARLES M. FUTRELL is Assistant Professor of Marketing at Texas A&M University. He received his Ph.D. from the University of Arkansas in 1974. He spent 8 years in sales with Colgate, Upjohn, and Ayerst Laboratories. His publications include articles in the Journal of Marketing Research, Journal of Marketing, and Academy of Management Journal.
370
Supervisors were asked for a rating of the salespersons on the following 10 job-performance factors using the following phrases: (1) “improvement in total job performance over last year,” (2) “current product knowledge,” (3) “current human-relations ability,” (4) “current sales ability,” (5) “current overall job performance,” (6) “current general attitude,” (7) “willingness to work hard, ” (8) “planning ability,” (9) “coverage of territory, ’ ’ and (10) “activity reporting. ” A seven-point “poor” to “excellent” scale was used. In making performance evaluations, the supervisors were asked to take into consideration the length of time each salesperson had been with his present employer. Assuming the supervisor did consider job longevity in his appraisals, each salesperson would be evaluated on an equal basis.
Analysis The analysis was done in two steps. First, males were contrasted to females for the entire sample, and a x2 test of significance was used (Table 1). Next, longevity was held constant by using a subsample of males and females who were similar in respect to longevity (Table 2). Three characteristics of the salespeople were considered as possible controls: longevity, age, and education. A control for education was not necessary as men and women were similar in education. Females were younger than males. However, only longevity was used as a control variable because of a high correlation (r = 0.72) between age and longevity; it appeared that using age as a control would be redundant. The particular categories of longevity used where chosen to retain the maximum number of females for analysis while producing as close to equal proportions of males and females in the longevity categories as possible. The result was that 27 females were retained out of the 35 total females and the subsample was primarily of salespeople with short longevity. A possible disadvantage of the cross-classification analysis is that some female subjects were lost when longevity was held constant. As a check of the cross classification, a multiple regression analysis using sex as a categorial predictor (0,l) and longevity as a second predictor and the 10 performance dimensions as criterion variables was run. Sex was a significant predictor in the regression analysis for the same 10 performance dimensions as in Table 2 (results not reported for brevity). It was concluded that the results were not an artifact of the x’) analysis. The x2 method was used because it was appropriate for the ordinal level of measurement obtained by the ratings.
TABLE 1 Comparison of Male and Female Salespersons on 10 Job-Performance Measures Distribution of Performance Scores"
Performance Measure
Med.
Med.
Low
Low
High
High
Respondents with Med.-High and High Scores
32% 54%
36% 34%
27% I 1%
5% 0%
26% 60%
30% 34%
29% 6%
29% 71%
30% 29%
28% 54%
X~
DF
p
32% 1 1%
9.24
3
0.026
15% 0%
44% 6%
24.61
3
0.000
32% 0%
9% 17%
41% 17%
34.99
3
0.000
30% 29%
29% I 1%
13% 6%
42% 17%
12.06
3
0.007
20% 37%
29% 34%
37% I 1%
15% 17%
52% 28%
10.82
3
0.013
26% 54%
21% 17%
29% 17%
24% 11%
53% 28%
16.73
4
0.002
27% 37%
25% 29%
34% 17%
14% 17%
48% 34%
4.56
3
0.216
15% 26%
21% 29%
37% 17%
26% 29%
63% 46%
6.58
3
0.086
18% 20%
19% 29%
20% 23%
34% 29%
64% 52%
2.52
3
0.472
30% 49%
31% 29%
28% 17%
12% 6%
40% 23%
6.27
3
0.099
Improvement Male"
Female ~' Product knowledge Male Female Sales ability Male Female Overall performance Male Female Territority coverage Male
Female Activity reporting Male Female Human relations Male Female Attitude Male Female Work hard Male Female Planning Male Female
" M a l e , N = 396; total N = 431. t, Female, N = 35.
"Totals may not equal 100% due to rounding.
RESULTS
Controlling for L o n g e v i t y
Total Sample
In order to test for a possible confounding of sex and longevity a subsample of 27 females was compared to 152 males with similar longevity. The results in Table 2 indicated that males were judged higher on nine of the 10 performance dimensions, all except human-relations ability.
Table 1 shows that for six of the 10 performance dimensions a significantly greater proportion of males were in the higher performance categories than were females. The more striking differences between the sexes were in sales ability, product knowledge, overall performance, territory coverage, and activity reporting. The proportion of males in the two highest categories exceeded females by a ratio of about 2:1 or higher. Females were rated similarly to males on willingness to work hard, general attitude, human relations, and planning ability. The results suggest that females exert as much effort as do males.
CONCLUSIONS The results suggest that females may experience some difficulty in terms of job performance in a maledominated occupation. Since some females were represented in the higher performance categories for most of
371
TABLE 2 Comparison of Male and Female Salespersons (with Similar Longevity) on Job Performance Distribution of Performance Scores" Respondents Performance Measure
[.o;~
Mcd. Low
Meal. High
High
with M c d . - H i g h and High Scores
Xe
DF
p
15.15
3
0.002
]ll/prt )vel/lerl[ Male"
22%
31%
41 cA
6%
47%
Female ~'
56%
30%
15%,
0%
15%
39% 7()~
30% 30%
22% 0%
8c/~ 0%
30~ 0%
13.03
3
0.005
---
42% 85%
3()c~ 7c/~
29% 7c4
59% 14c7~,
16.87
2
0.000
34% 63%
31%
28%
8%
36%
10.76
3
0.013
30%
7%
0%
7%
19% 41%
34% 44e/~
37 % 15%
1()~ 0%
47% 15%
10. 95
3
O. 012
21% 56%
27% 22%
34~a 22%
18% 0%
52% 22%
16.03
3
O. 001
27% 41%
27% 37%
33% 15%
13% 7"14
46% 22c/~
5.09
3
0. 165
5% 26%
20% 37%
42% 22%
33% 15%
75% 37%
19.14
3
0.000
8c~ 19%
[6% 37%
40% 30%
36% 15%
76% 45%
I I. 19
3
O.OIl
27% 56%
38% 30%
28c/~ 15%
7'~
35% 15c~
9.38
3
0.025
0%
Product knowledge Male Female Sales ability Male Female Overall p e r f o r m a n c e
Male Female Tcrrilority coverage Male
Female Activity reporting Male
Female Human relations Male Fenlale
Attitude Male Female W o r k hard Male Female Planning Male Fcnlalc
" M a l e . N = 125; totaI, N = 152. t, Fcmale. N = 27. "Totals may not equal 100% due to rounding.
the perfornaance dimensions, it is doubtful that unalterable barriers exist to excellent performance by female salespersons. A recent article by Swan et al. [2J has presented evidence that the responses of females to sales supervisory systems are somewhat different than those of males. It could be possible that sales management has not been able to fully utilize female abilities as such systems are probably male oriented at present. It is also possible that customer acceptance of female salespeople is a problena. The implication for sales management is that although average performance by females may be lower than males, females can do the job. For example, they were in" the highest performance categories except for two performance dimensions (see Table l). It should be noted
372
that in those two aspects of performance, improvement in job performance and product knowledge, relatively few males (5% and 15%, respectively) were found in the "'high" category. Since acquiring product knowledge depends on learning ability and training, any performance gap can be eliminated through sales-force training.
ACKNOWLEDGMENT The authors are grate rid to Prqfbssor Herman S. Napier for suggesting this anah'sis of variances a s a test fi)r bias.
REFERENCES 1. Stanton, William J. and Buskirk, Richard H., Management Force, Richard D. Irwin, Homewood, Ill., 1974.
of the Sales
3. Woodside, Arch G. and Davenport, J. William, Jr., The Effect of Salesmen Similarity and Expertise on Consumer Purchasing Behavior, Journal ofMarker& Research 11, 198-202 (1974).
2. Swan, John E., Futrell, Charles M., and Todd, John T., Same Job Different Views: Women and Men in Industrial Sales, Journal of Marketing 42, 92-98 (1978).
373
Charles M. Futrell
Sales managers have typically directed an all-male sales force. Today, they are recruiting women for positions in industrial sales. Whereas such managers may have a number of questions about women, probably the single most important
a sales performance gap exists between men and women in the companies participating in the research.
question is how men and women compare in job per$ormance. Although trade publications report that women have done quite well in sales [I 1, the question should not be considered resolved. Trade reports are extremely useful but are not based on systematic evidence. Another difJiculty with trade reports is the failure to test for spurious relationships, that is, apparent relationships due to variables correlated with both sex and per$ormance. In particular, variables that may be related to both sex and job performance should be examined to see whether job performance dtfherences are actually due to the sex of the person or whether such relationships are spurious.
PURPOSE
OF THE STUDY
Earlier research has indicated that the higher the similarity between the customer and the salesperson, the greater the chances of success of the sales transaction [3]. Since relatively few women were customers of the pharmaceutical and hospital supply firms in this study, the saleswomen would be at a disadvantage relative to the males, which could be reflected in lower performance ratings. Thus the main purpose of this study was to see if @ Elsevier North-Holland,
Inc., 1978 Industrial Marketing Management
RESEARCH
PROCEDURES
Data-Collection
Method
This article is based on a larger study in which the total sales staff and the salespersons’ immediate supervisors in two national pharmaceutical companies and one national hospital supply company were surveyed through the use of two mail questionnaires. The salespersons were sent one questionnaire. The salespersons’ supervisors were sent a different questionnaire and asked to evaluate each of their salespersons’ job performance. A subject was used in the study only if both his questionnaire and the supervisor’s performance rating were completed. The final sample was based on the analysis of 431 set of matched, usable questionnaires-representing a 5% percent response rate. Of the 43 1 respondents, 35 were female. This represented 83 percent of the three firm’s 42 female salespeople. Even though females are entering the sales profession at an increasing rate, it is difficult to find an industrial salesforce with a large number of women. The response rate among the 72 supervisors was 83 percent, and 65 percent of the 743 salespeople returned their questionnaires. The 43 1 respondents ’ ages, longev-
I, 369-373 (1978)
369 0019-8501/78/060293+05$01.75
ity of employment with the firm, and percent who graduated from college were measured. According to officals in each company, the measured characteristics of the respondents were similar to those of all salespeople in their company.
Work Environment of the Salespeople To find out if the salepeople from the three companies faced a similar work environment, supervisors were asked to describe their salespersons’ work activities and their firm’s channel of distribution, training, and organizational structure. The only basic difference between the pharmaceutical and hospital-supply salespersons’ jobs was that the pharmaceutical salespeople contacted retail pharmacists and physicians in their offices. The hospital-supply salespeople did not make such calls, although they did contact physicians at hospitals. All salespersons were responsible for selling company products and disseminating information to customers in a particular sales territory.
Measurement of Job Performance The 10 factors measuring job performance were developed by modifying the “district sales manager’s appraisal form” of the largest company in the study. The other two participating firms believed that the measuring device also adequately represented the manner in which their salespeople were evaluated. Sales figures were not used because each of the three organizations distribute their products through drug wholesalers. Since the companies do not sell directly to their customers, the companies believed that sales dollars should not be utilized as a formal indicator of job performance.
JOHN E. SWAN is Professor of Marketing at the University of Alabama. He received his D.B.A. from Indiana University. He has authored articles appearing in such journals as the Journal of Marketing Research, and Journal of Applied Psychology. He is on the editorial board of the Journal of Marketing Research and Decision Sciences.
CHARLES M. FUTRELL is Assistant Professor of Marketing at Texas A&M University. He received his Ph.D. from the University of Arkansas in 1974. He spent 8 years in sales with Colgate, Upjohn, and Ayerst Laboratories. His publications include articles in the Journal of Marketing Research, Journal of Marketing, and Academy of Management Journal.
370
Supervisors were asked for a rating of the salespersons on the following 10 job-performance factors using the following phrases: (1) “improvement in total job performance over last year,” (2) “current product knowledge,” (3) “current human-relations ability,” (4) “current sales ability,” (5) “current overall job performance,” (6) “current general attitude,” (7) “willingness to work hard, ” (8) “planning ability,” (9) “coverage of territory, ’ ’ and (10) “activity reporting. ” A seven-point “poor” to “excellent” scale was used. In making performance evaluations, the supervisors were asked to take into consideration the length of time each salesperson had been with his present employer. Assuming the supervisor did consider job longevity in his appraisals, each salesperson would be evaluated on an equal basis.
Analysis The analysis was done in two steps. First, males were contrasted to females for the entire sample, and a x2 test of significance was used (Table 1). Next, longevity was held constant by using a subsample of males and females who were similar in respect to longevity (Table 2). Three characteristics of the salespeople were considered as possible controls: longevity, age, and education. A control for education was not necessary as men and women were similar in education. Females were younger than males. However, only longevity was used as a control variable because of a high correlation (r = 0.72) between age and longevity; it appeared that using age as a control would be redundant. The particular categories of longevity used where chosen to retain the maximum number of females for analysis while producing as close to equal proportions of males and females in the longevity categories as possible. The result was that 27 females were retained out of the 35 total females and the subsample was primarily of salespeople with short longevity. A possible disadvantage of the cross-classification analysis is that some female subjects were lost when longevity was held constant. As a check of the cross classification, a multiple regression analysis using sex as a categorial predictor (0,l) and longevity as a second predictor and the 10 performance dimensions as criterion variables was run. Sex was a significant predictor in the regression analysis for the same 10 performance dimensions as in Table 2 (results not reported for brevity). It was concluded that the results were not an artifact of the x’) analysis. The x2 method was used because it was appropriate for the ordinal level of measurement obtained by the ratings.
TABLE 1 Comparison of Male and Female Salespersons on 10 Job-Performance Measures Distribution of Performance Scores"
Performance Measure
Med.
Med.
Low
Low
High
High
Respondents with Med.-High and High Scores
32% 54%
36% 34%
27% I 1%
5% 0%
26% 60%
30% 34%
29% 6%
29% 71%
30% 29%
28% 54%
X~
DF
p
32% 1 1%
9.24
3
0.026
15% 0%
44% 6%
24.61
3
0.000
32% 0%
9% 17%
41% 17%
34.99
3
0.000
30% 29%
29% I 1%
13% 6%
42% 17%
12.06
3
0.007
20% 37%
29% 34%
37% I 1%
15% 17%
52% 28%
10.82
3
0.013
26% 54%
21% 17%
29% 17%
24% 11%
53% 28%
16.73
4
0.002
27% 37%
25% 29%
34% 17%
14% 17%
48% 34%
4.56
3
0.216
15% 26%
21% 29%
37% 17%
26% 29%
63% 46%
6.58
3
0.086
18% 20%
19% 29%
20% 23%
34% 29%
64% 52%
2.52
3
0.472
30% 49%
31% 29%
28% 17%
12% 6%
40% 23%
6.27
3
0.099
Improvement Male"
Female ~' Product knowledge Male Female Sales ability Male Female Overall performance Male Female Territority coverage Male
Female Activity reporting Male Female Human relations Male Female Attitude Male Female Work hard Male Female Planning Male Female
" M a l e , N = 396; total N = 431. t, Female, N = 35.
"Totals may not equal 100% due to rounding.
RESULTS
Controlling for L o n g e v i t y
Total Sample
In order to test for a possible confounding of sex and longevity a subsample of 27 females was compared to 152 males with similar longevity. The results in Table 2 indicated that males were judged higher on nine of the 10 performance dimensions, all except human-relations ability.
Table 1 shows that for six of the 10 performance dimensions a significantly greater proportion of males were in the higher performance categories than were females. The more striking differences between the sexes were in sales ability, product knowledge, overall performance, territory coverage, and activity reporting. The proportion of males in the two highest categories exceeded females by a ratio of about 2:1 or higher. Females were rated similarly to males on willingness to work hard, general attitude, human relations, and planning ability. The results suggest that females exert as much effort as do males.
CONCLUSIONS The results suggest that females may experience some difficulty in terms of job performance in a maledominated occupation. Since some females were represented in the higher performance categories for most of
371
TABLE 2 Comparison of Male and Female Salespersons (with Similar Longevity) on Job Performance Distribution of Performance Scores" Respondents Performance Measure
[.o;~
Mcd. Low
Meal. High
High
with M c d . - H i g h and High Scores
Xe
DF
p
15.15
3
0.002
]ll/prt )vel/lerl[ Male"
22%
31%
41 cA
6%
47%
Female ~'
56%
30%
15%,
0%
15%
39% 7()~
30% 30%
22% 0%
8c/~ 0%
30~ 0%
13.03
3
0.005
---
42% 85%
3()c~ 7c/~
29% 7c4
59% 14c7~,
16.87
2
0.000
34% 63%
31%
28%
8%
36%
10.76
3
0.013
30%
7%
0%
7%
19% 41%
34% 44e/~
37 % 15%
1()~ 0%
47% 15%
10. 95
3
O. 012
21% 56%
27% 22%
34~a 22%
18% 0%
52% 22%
16.03
3
O. 001
27% 41%
27% 37%
33% 15%
13% 7"14
46% 22c/~
5.09
3
0. 165
5% 26%
20% 37%
42% 22%
33% 15%
75% 37%
19.14
3
0.000
8c~ 19%
[6% 37%
40% 30%
36% 15%
76% 45%
I I. 19
3
O.OIl
27% 56%
38% 30%
28c/~ 15%
7'~
35% 15c~
9.38
3
0.025
0%
Product knowledge Male Female Sales ability Male Female Overall p e r f o r m a n c e
Male Female Tcrrilority coverage Male
Female Activity reporting Male
Female Human relations Male Fenlale
Attitude Male Female W o r k hard Male Female Planning Male Fcnlalc
" M a l e . N = 125; totaI, N = 152. t, Fcmale. N = 27. "Totals may not equal 100% due to rounding.
the perfornaance dimensions, it is doubtful that unalterable barriers exist to excellent performance by female salespersons. A recent article by Swan et al. [2J has presented evidence that the responses of females to sales supervisory systems are somewhat different than those of males. It could be possible that sales management has not been able to fully utilize female abilities as such systems are probably male oriented at present. It is also possible that customer acceptance of female salespeople is a problena. The implication for sales management is that although average performance by females may be lower than males, females can do the job. For example, they were in" the highest performance categories except for two performance dimensions (see Table l). It should be noted
372
that in those two aspects of performance, improvement in job performance and product knowledge, relatively few males (5% and 15%, respectively) were found in the "'high" category. Since acquiring product knowledge depends on learning ability and training, any performance gap can be eliminated through sales-force training.
ACKNOWLEDGMENT The authors are grate rid to Prqfbssor Herman S. Napier for suggesting this anah'sis of variances a s a test fi)r bias.
REFERENCES 1. Stanton, William J. and Buskirk, Richard H., Management Force, Richard D. Irwin, Homewood, Ill., 1974.
of the Sales
3. Woodside, Arch G. and Davenport, J. William, Jr., The Effect of Salesmen Similarity and Expertise on Consumer Purchasing Behavior, Journal ofMarker& Research 11, 198-202 (1974).
2. Swan, John E., Futrell, Charles M., and Todd, John T., Same Job Different Views: Women and Men in Industrial Sales, Journal of Marketing 42, 92-98 (1978).
373