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SAJEMS NS Vol 6 (2003) No 1  89 

An Exploratory Study of Group Adverse 
Impact in a Recruitment and Selection Strategy 
________________________________________________________________ 
 
R J Snelgar and T Potgieter 
 
Department of Industrial and Organizational Psychology, University of Port 
Elizabeth 
________________________________________________________________ 
 
ABSTRACT 
 
The Adverse Impact model was developed by the judicial system of the United 
States of America and the United Kingdom as a practical method to make legal 
judgements to determine whether designated groups are being unfairly 
discriminated against at any stage of an assessment process. The model has been 
used to assess various recruitment and selection instruments and measures. This 
study has been groundbreaking in that the application of the Adverse Impact 
model within the South African employment scenario is relatively new. An 
exploratory research design was used to analyse Adverse Impact at each stage of 
a recruitment and selection strategy. The model was applied to assess whether 
the instruments used, had an adverse impact on any of the designated groups.   

JEL J70 
 
1 INTRODUCTION 
 
Ensuring fairness should be the priority of any selection strategy, particularly in 
South Africa, where attempts are being made to rectify past practices that have 
had a discriminatory effect on certain sections of the population. The South 
African Employment Equity Act awards priority to the issue of group 
representivity in employment outcomes and ensures equal representation in all 
occupational categories and levels in the workplace (Mdladla, 2001). 
Affirmative action is a strategy for manoeuvering equal opportunities in the 
workplace.  Although the purpose is to redress the disadvantages in employment 
experienced by certain groups, there are restrictions and limitations to enforcing 
this policy. An objective appraisal of the inherent abilities of specific job 
applicants is still a procedural requirement (Taylor, 1999). 
 
Thus, because of the vital importance of fairness, the issue of fairness should be 
based on the end to end process of the entire recruitment and selection strategy, 
and not be isolated to one aspect of measurement. Any recruitment and selection 
decision is based on one or other selection model of decision-making. The 



SAJEMS NS Vol 6 (2003) No 1 90

question that must be asked is whether the model itself is “fair”, as well as 
whether or not the instruments of evaluation and assessment employed, allow 
for equal treatment of all candidates. Ensuring fairness, therefore, should be the 
priority of any selection strategy.  

 
An overview of the literature shows that there is a real and pressing need to 
explore the concept of adverse impact in more detail, particularly regarding the 
role it plays in determining the fairness of recruitment and selection strategies. 
Research on adverse impact has revealed that the ongoing search for objective 
measures, on which all applicant groups perform the same (thus resulting in no 
adverse impact and equality of employment results) has generally not been 
productive (Barrett, 1995; Barrett, 1996; Schmidt, Rodgers, Chan, Sheppard & 
Jennings, 1997; Wollack, 1994). 

 
The Adverse Impact model or 4/5th's rule has been developed by the courts of 
the United States of America, and has also been adopted by enforcement 
agencies in the United Kingdom as a practical way of making legal judgements 
on whether designated groups are being unfairly discriminated against at any 
stage of an assessment process (Barrett, 1996). As a result of the search for 
objective measures, the Adverse Impact model has been used as a means for the 
assessment of various measures, and the research results have been used to 
improve selection strategies (Hattrup, Rock & Scalia, 1997; Ironside, Guion, & 
Ostrander, 1982; Maxwell, 1993; Mckinney & Collins, 1991; Raju & Edwards, 
1984; Robertson & Kandola, 1982; Ryan & Ployhart, 1998; Sackett & 
Ellingson, 1997). 
  
 
2 ADVERSE IMPACT 
 
Muchinsky (1987: 132) defines Adverse Impact as: 

 
The results of any selection method that causes a disproportionate 
percentage of people of a given category to be hired compared to another 
group.  Adverse Impact exists if the selection ratio associated with a 
particular passing score on a test for one sub-group of job applicants is 
less than 4/5th’s or 80 per cent of the selection ratio for the largest sub 
group of applicants.  Adverse impact represents a difference in selection 
ratios for members of different groups and is generally the result of white-
black mean differences on ability tests that are approximately one 
standard deviation in magnitude.  

 
Since policy promoting an investigation of a company’s selection program is 
evidence of Adverse Impact, companies hire people (white/black, male/female) 



SAJEMS NS Vol 6 (2003) No 1  91 

in proportions that comply with government standards (Taylor, 1999). Thus, 
Adverse Impact has become a useful tool to determine the differences in 
selection ratios such that these proportions may be complied with.  
 
Adverse Impact is based on the logic of proportionality.  Ratios of 
accepted/rejected applicants are compared across designated and non-designated 
groups with the assumption that these ratios should be similar across groups if 
unbiased decision-making is occurring (Muchinsky, 1987).  The advantage of 
this approach is that it provides a simple decision rule for checking potential 
biased assessment outcomes in organisations.  A disadvantage may be that the 
shortage of black skills in certain areas will necessitate the distortion of ratios, 
but the magnitude of the ratio differences provides valuable information for 
analysis.  
 
The data needed for Adverse Impact analysis is simply the number of designated 
and non-designated applicants who are accepted and rejected at each hurdle in 
the assessment process.  If it is established that a difference of less than 80 per 
cent exis ts in the acceptance ratios for different groups, then the organisation 
would be required to explain the circumstances and if necessary demonstrate the 
validity of any assessment hurdle which may be associated with the adverse 
impact finding.  The 80 per cent figure is accepted by courts as a reasonable 
indicator of similarity in outcomes in comparing the selection ratios of groups, 
since in reality it is unreasonable to expect identical outcomes (Barrett, 1996). 
From the above it may be noted that one of the positive features of the Adverse 
Impact model is the simplicity of its application. 
 
Equal Employment Opportunity asserts that all selection tests that result in 
adverse impact must be validated (Disability Information Partnership, 1999).  If 
adverse impact is found to exist, the employer is obligated to validate the 
selection procedure to prove that the resulting personnel decisions were indeed 
based on a correct and valid method.   

 
Psychological assessment instruments are, however, likely to provide useful and 
objective means of assessing candidates, as long as the test or instrument 
measures attributes required to achieve job success. Employers need to justify 
and defend their decision-making processes by relating criteria on which these 
decisions are based, to the requirements of the job (Saville & Holdsworth, 
1997).  This way they can identify exactly what the requirements of the job are 
to ensure selecting the most competent applicants and ensuring that all 
employees are trained to perform at their optimum potential.  
 
New legislation has therefore forced organisations to look more closely at the 
requirements of the organisation and the people employed within the 



SAJEMS NS Vol 6 (2003) No 1 92

organisation. Research on Adverse Impact indicates that it is evident that there is 
the potential for this technique at any stage of a selection process (Muchinsky, 
Kriek & Schreuder, 1998: 195-210).  
 
 
3 RESEARCH METHODOLOGY 
 
This research took place in a Telecommunications Call Centre environment.  
There were sixteen vacancies in the department.  The Call Centre selection 
strategy consisted of a validated battery of instruments and measurements.  

 
The validity and effectiveness of a selection procedure, to a large degree, 
depends on how the organisation uses the information.  The success or failure of 
the selection system depends on effective construction of the process for 
gathering predictor information.  Applicants are rarely selected using only one 
selection procedure.   
 
The Telecommunications Call Centre recruitment strategy consisted of a 
combination of measuring instruments and selection "obstacles".  Using multiple 
procedures can provide more complete information and allows the selection 
process to be adjusted in response to particular situations (Milkovich & 
Boudreau, 1994).  
 
The multiple hurdle approach was adopted for the Telecommunications Call 
Centre recruitment process.  In this approach, each predictor operates 
independently.  Applicants must pass the first hurdle to proceed to the next, and 
failure in a particular hurdle resulted in the applicant's rejection from the 
process.  Applicants needed to comply with the minimum qualifications in their 
Curricula Vitae to proceed to the psychological testing stage, and needed to 
qualify on the ability tests to proceed to the role-play exercise.  Applicants who 
demonstrated required competencies and potential in the role-play progressed to 
the interview stage. 
 
3.1 Aims 
 
The aims of this study are: 
• To identify whether Adverse Impact occurs in the Call Centre selection 

strategy. 
• To ensure fairness in future selection outcomes. 
• To deliver recommendations to the Management team regarding the 

strengths and limitations of the research. 



SAJEMS NS Vol 6 (2003) No 1  93 

3.2 Research design 
 
An exploratory research design was employed in this study.  This research 
method was chosen as an appropriate way of gathering the data in order to meet 
the aims of the study since insufficient published research has been conducted in 
the area of Adverse Impact in the South African context. 
 
3.3 Sample 
 
The population under investigation includes all the candidates that applied for 
the position of Service Representative, CFH (Customer Fault Handler) in the 
Call Centre, Central Region.  The population consisted of 150 candidates.  The 
majority of the candidates (105) were internal applicants (N=150). Forty-five of 
the applicants were from outside the company, and were introduced into the 
sample via Placement Agencies.   

 
Due to the fact that all candidates who applied for the positions in the Call 
Centre were included in the research study, no particular sampling method was 
used.  The requirement for inclusion in the sample was Grade 12, with 
Mathematics and/or Science, irrespective of age, culture or gender. 
 
The original sample consisted of 150 applicants.  A shortlisting exercise was 
initiated and job relevant criteria were assessed based on information presented 
in the curricula vitae.  This process resulted in a compressed shortlist of 25 
candidates. 

 
3.4 Measuring instruments 
 
The following evaluation instruments were applied in the recruitment and 
selection strategy: (i) job analysis; (ii) pre-screening exercise; (iii) ability tests; 
(iv) role-play; (v) interview; (vi) job-compatibility questionnaire and (vii) 
performance evaluation. 
 
Each of the seven instruments measures certain job-related competencies.  The 
Adverse Impact model was used as the foundation of the study and the 4/5th's 
formula was applied at the testing, interview and appointment stages of the 
selection process to determine the extent to which Adverse Impact was evident. 
The job analysis formed the basis of the entire selection strategy as critical 
competencies were classified at this point.  The pre-screening and ability testing 
comprised stage 1 of the Adverse Impact analysis.  The role-play was 
administered but due to internal complications, there was insufficient 
information for analysis.  The interview represented the second stage of 
analysis.  The appointment phase was analysed in stage 3.  The Job 



SAJEMS NS Vol 6 (2003) No 1 94

Compatibility Interview and Performance Evaluation aspects provided 
additional information pertaining to person-environment congruence.  These 
aspects were not exposed to an Adverse Impact analysis. 
 
 
4 RESULTS 
 
Table 1 reveals the results of the Adverse Impact analysis at stages of the 
recruitment and selection strategy. Adverse Impact analysis has been conducted 
for population as well as for gender groups. 
 
Table 1 Adverse Impact analysis 
 

Designated 
groups 

No. of qualified 
applicants (meet 
min. req.ments) 

A 

Selected to undergo 
testing 

Above cut-off on 
learning potential test 

B percentage of A 

All Black 23 21 12   12/21x100=57 
White 2 2 2    2/2x100=100% 
Adverse 
Impact analysis 

  57 / 100 = 57% 
Adverse Impact 
Black 

Female 5 4 3    3/4x100=75% 

Male 20 19 11   11/19x100=57% 

Adverse Impact 
analysis 

  57/75x100=76% 
Adverse Impact 
Males 

Total  25   
Designated 
groups 

Selected for an 
interview 

Above cut-off in the 
interview 
C percentage of B 

Employed 
 
D percentage of A 

All Black 23 11  11/23x100=47% 14   14/23x100=60% 
White 2 2    2/2x100=100% 2   2/2x100=100% 
Adverse Impact 
analysis 

 47 / 100 = 47% 
Adverse Impact 
Black 

60 / 100 = 60% 
Adverse Impact  
Black 

Female 5 3    3/5x100=60% 3   3/5x100=60% 
Male 20 10  10/20x100=50% 13   13/20x100=65% 
Adverse Impact 
analysis 

 50/60x100=83% 
No Adverse Impact 

60/65x100=92% 
No Adverse Impact 

Total 25   
 



SAJEMS NS Vol 6 (2003) No 1  95 

The first stage of the impact analysis was the testing stage. The All Black 
population group reflected Adverse Impact at this stage. The All Black group 
consisted of African, Coloured and Indian population groups. The male gender 
group also reflected Adverse Impact at this stage.  
 
The interview phase was the next level of analysis.  Once again the All Black 
group has reflected Adverse Impact. Neither of the gender groups reflected 
Adverse Impact at this stage.  

 
The next stage of analysis involved the appointment step.  The analysis in this 
division was based on the number of candidates appointed in relation to the 
number of candidates who met the minimum criteria (n=25).  16 candidates 
were appointed.  Based on the four fifth's formula it is interesting to see that the 
all Black group was the only group that evidenced Adverse Impact in the final 
stage. Once again, there was no Adverse Impact indicated in terms of gender 
comparisons.   

 
It is imperative to remember that the Adverse Impact at each stage be calculated 
in isolation from the next stage, and dealt with accordingly. One cannot assume 
that if there was no evidence of Adverse Impact in the final and probably critical 
stage of the selection process that the complete strategy is free from Adverse 
Impact.   

 
Prior to 1982, Adverse Impact was defined using the bottom-line principle, 
which meant that there was no cause for action if the overall impact rate fell 
above the 80 per cent line.  However the United States Supreme Court in 1982 
overturned this rule making it possible to bring an action against any part of a 
process that had Adverse Impact (Barrett, 1996).  It is commonsensical to 
determine the level of impact at each assessment obstacle so that the fairness of 
each hurdle can be verified.  The validity of each assessment hurdle needs to be 
confirmed. 
 
 
5 RECOMMENDATIONS AND CONCLUSIONS 
 
Over the longer term a spin-off from this study will signify the use of the 
Adverse Impact model as a method of ensuring fairness in recruitment and 
selection.  Proposals will be made to encourage all HR practitioners to 
consistently benchmark outcomes of selection strategies against this model.  

  
Based on the extent of the Adverse Impact sustained in this selection strategy, 
recommendations will be made to the management team regarding the fairness 
of this procedure. A summary of the findings of the study will be presented to 



SAJEMS NS Vol 6 (2003) No 1 96

the management team with the recommendation of reviewing the current 
selection process and assessment instruments.  A further suggestion will be 
made to conduct a more recent job analysis to confirm whether the job 
requirements have remained the same and whether the psychometric tests are 
measuring the relevant attributes.  If the job analysis reveals changes in the 
requirements of the job, alternative ability tests and competencies will need to 
be considered. 

 
In order to prevent, or at least minimise the extent of Adverse Impact, 
companies need to embark on an ongoing search for objective measures on 
which all applicants perform the same, thus resulting in no Adverse Impact and 
equality of employment results.  Companies need to continually examine the 
relevance of the selection instruments they use before including them in the 
selection procedure, and if required, redesign and revalidate the strategy.  
Companies should also assess the level of the psychometric test to ensure that 
the tests being administered are aligned with the appropriate norm group.  If it 
has been determined that the level of the test is too high they should explore the 
possibility of using an alternative version of the same test. 

 
South African legislation today encourages companies, and specifically human 
resources practitioners, to keep record of every stage of a selection process, 
should the necessity to defend an employment decision emerge.  

 
Affirmative action and employment equity policies have their function and are 
meant to speed up the racial re-engineering of the workplace. Nevertheless, 
managers should not ruthlessly dispense with objective assessment of the 
inherent abilities of applicants to the job (Taylor, 1999). 

 
Ignoring the presence of Adverse Impact could result in inequalities in selection 
as well as erroneous selection and rejection.  If talented people are consistently 
and systematically disqualified from employment opportunities, then these 
excluded people represent wasted human resources.   

 
The legal implication of unfair and discriminatory recruitment and selection is 
formidable.  Personnel practices that have a differentiated approach to certain 
groups are illegal, unless these differences can be justified as necessary for the 
safe and efficient operation of the business, and are work-related. 

 
If group Adverse Impact is disregarded, the elimination of unlawful employ-
ment practices will be compromised.  No matter how well intended the 
elimination of objective employment standards are in the pursuit of equal 
employment results, neglecting to attend to the development of alternative 
solutions, may well contribute to a productivity decline. 



SAJEMS NS Vol 6 (2003) No 1  97 

Although the concept of Adverse Impact and the use of 4/5th’s rule are not built 
into employment equity legislation in South Africa, it is likely to be a very 
important tool in South African organisations. There is an increasing demand for 
institutions to be accountable and to demonstrate that the assessment instruments 
and procedures that they use, are not only psychometrically valid and reliable, 
but also fair, free from bias, and thus being in line with the concept of Adverse 
Impact.   

 
 

REFERENCES 
 
1 BARRETT, R.S. (1995) Adverse Impact: Fair Employment Strategies in 

Human Resource Management, London: Quorum Books.      
2 BARRETT, R.S. (1996) Person-Environment Congruence. Fair 

Employment Strategies in Human Resource Management, London:  
Quorum Books. 

3 DISABILITY INFORMATION PARTNERSHIP (1999) The Law and 
Legal Issue. Summary of the Employment Equity Act, 55 of 1998, 
Available:  http://www.ability.org.za. 

4 HATTRUP, K., ROCK, J. & SCALIA, C. (1997) “The effects of varying 
conceptualizations of job performance on Adverse Impact, minority hiring 
and predicted performance”, Journal of Applied Psychology, 82. 

5 IRONSIDE, G.H., GUION, R.M. & OSTRANDER, M. (1982) “Adverse 
Impact from a psychometric perspective”, Journal of Applied Psychology, 
67. 

6 MAXWELL, S.E. (1993) “The search for predictors with high validity and 
low Adverse Impact”, Journal of Applied Psychology, 78. 

7 McKINNEY, W.R. & COLLINS, J.R. (1991) “The impact on utility, race, 
and gender using three standard methods of scoring selection 
examinations”, Public Personnel Management, 20. 

8 MDLADLANA, M.M.S.  (2001)  “Code of good practice on key aspects 
of disability in the workplace”, Employment Equity Act No 55 of 1998, 
Available: http://www.labour.gov.za.  

9 MILKOVICH, G.T. & BOUDREAU, J.W. (1994) Human Resource 
Management, Boston: Irwin. 

10 MUCHINSKY, P.M. (1987) Psychology Applied to Work: An 
Introduction to Industrial and Organisational Psychology, Homewood, 
Illinois: Dorsey Press. 

11 MUCHINSKY, P.M., KRIEK, H. & SCHREUDER, A. (1998) Personnel 
Psychology, Cape Town: Thompson International.  

12 RAJU, N.S. & EDWARDS, J.E. (1984) “Note on Adverse Impact from a 
psychometric perspective”, Journal of Applied Psychology, 69.  



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13 ROBERTSON, I.T. & KANDOLA, R.S. (1982) “Work sample tests: 
validity, Adverse Impact and applicant reaction”, Journal of Occupational 
Psychology, 55. 

14 RYAN, A.M. & PLOYHART, R.E. (1998) “Using personality testing to 
reduce Adverse Impact: A cautionary note”, Journal of Applied 
Psychology, 83. 

15 SACKETT, P.R. & ELLINGSON, J.E. (1997) “The effects of forming 
multi-predictor composites on group differences and Adverse Impact”, 
Personnel Psychology, 50. 

16 SAVILLE & HOLDSWORTH (2000) “Reliability study”, Research and 
Development, Available: http://www.shl.co.za.  

17 SCHMIDT, N., RODGERS, W., CHAN, D., SHEPPARD, L. & 
JENNINGS, D. (1997) “Adverse Impact and predictive efficiency of 
various predictor combinations”, Journal of Applied Psychology, 82.  

18 TAYLOR, J. (1999) “Using the Adverse Impact model to achieve fair 
assessment outcomes”, Unpublished Paper, Society for Industrial 
Psychology Conference, CSIR Convention Centre. 

19 WOLLACK, S. (1994) “Confronting Adverse Impact in cognitive 
examinations”, Public Personnel Management, 23.