Optimizing Staffing Practices for Enhanced Firm Performance

1. Chapter 6 Staffing Decisions

2. Module 1:Conceptual Issues in Staffing • Staffing decisions • Associated with recruiting, selecting, promoting, & separating employees Keith Brofsky/Getty Images

3. Sequential View ofthe Staffing Process Figure 6.1

4. Impact of Staffing Practices on Firm Performance • High performance work practices • Include use of formal job analyses, selection from within for key positions, & use of formal assessment devices for selection • Staffing practices have positive associations with firm performance

5. Stakeholders in the Staffing Process • Line managers • Seek accurate, easy-to-administer, & easy-to-defend staffing process • Co-workers • Among other considerations, layoff decisions have practical & emotional consequences • Applicants • Manner in which staffing decision carried out will be influential in their perception of organization

6. Staffing from International Perspective • Job descriptions used universally • Educational qualifications & application forms widely used for initial screening • Interviews & references are common post-screening techniques • Cognitive ability tests used less frequently; personality tests used more frequently

7. Module 2: Evaluation of Staffing Outcomes • Validity: Accurateness of inferences made based on test or performance data • Validity designs • Criterion-related • Content-related • Construct-related

8. Levels of Relationship Between a Test & a Criterion Figure 6.2 Scatterplots Depicting Various Levels of Relationship between a Test and a Criterion

9. Validity • Selection ratio (SR) n = number of available jobs N = number of people assessed SR = n/N

10. Selection Decisions False positive • Applicant accepted but performed poorly False negative • Applicant rejected but would have performed well True positive • Applicant accepted & performed well True negative • Applicant rejected & would have performed poorly

11. Cut score or cutoff score • Specified point in distribution of scores below which candidates are rejected • Raising cut score will result in fewer false positives but more false negatives • Strategy for determining cut score depends on situation

12. Effect on Selection Errors of Moving the Cutoff Score Figure 6.4 The Effect on Selection Errors of Moving the Cutoff Score

13. Establishing Cut Scores • Criterion-referenced cut score • Consider desired level of performance & find test score corresponding to that level • Norm-referenced cut score • Based on some index of test-takers’ scores rather than any notion of job performance

14. Utility • Addresses cost/benefit ratio of one staffing strategy versus another • Base rate • % of current workforce performing successfully • If performance is high, then new system will likely add very little to productivity

15. Utility Analysis • Assesses economic return on investment of HR interventions like staffing or training • Calculations can be very complex

16. Feelings of unfairness lead to: • Initiation of lawsuits • Filing of formal grievances with company representatives • Counterproductive behavior

17. Module 3: Practical Issues in Staffing • Staffing Model • Comprehensiveness • Enough high quality information about candidates to predict likelihood of their success • Compensatory • Candidates can compensate for relative weakness in one attribute through strength in another one, providing both are required by job

18. Combining Information • Clinical decision making • Uses judgment to combine information & make decision about relative value of different candidates • Statistical decision making • Combines information according to a mathematical formula

19. Combining Information (cont'd) • Hurdle system of combining scores • Non-compensatory strategy: individual has no opportunity to compensate at later stage for low score in earlier stage • Establishes series of cut scores Anthony Saint James/Getty Images

20. Hurdle System of Combining Scores • Constructed from multiple hurdles so candidates who don’t exceed each of the minimum dimension scores are excluded from further consideration • Often set up sequentially • More expensive hurdles placed later • Used to narrow a large applicant pool

21. Combining Information (cont'd) • Combination scores by regression (compensation approach) • Multiple regression analysis • Results in equation for combining test scores into a composite based on correlations of each test score with performance score

22. Relationship Between Predictor Overlap & Criterion Prediction Figure 6.4 The Relationship between Predictor Overlap and Criterion Prediction

23. Combination Scores by Regression • Cross-validation • Regression equation developed on first sample is tested on second sample to determine if it still fits well

24. Score banding • Individuals with similar test scores grouped together in category (score band) • Selection within band made based on other considerations • Controversial

25. Score Banding • Standard error of measurement (SEM) • Provides measure of amount of error in a test score distribution • Function of reliability of test & variability of test scores

26. Score Banding • Fixed band system • Candidates in lower bands not considered until higher bands have been exhausted • Sliding band system • Permits band to be moved down a score point when highest score in a band is exhausted

27. Subgroup Norming • Develop separate lists for individuals in different demographic groups who are then ranked within their respective group • In general, subgroup norming is not allowed as staffing strategy • However, there is no explicit prohibition of age norming

28. Selection vs. Placement • Sometimes, the challenge is to place an individual rather than simply select an individual • Placement • Process of matching multiple applicants & multiple job openings • Strategies • Vocational guidance • Pure selection • Cut & fit

29. Deselection • 2 typical situations • Termination for cause • Individual is fired for a particular reason • Generally not unexpected • Layoff • Job loss due to employer downsizing or reductions in force • Often occurs with little or no warning

30. Large Staffing Projects • Concessions must be made: Labor intensive assessment procedures are not feasible • Requires an actuarial strategy • Utility can be an issue (Cost of testing can be expensive) • Fairness is a critical issue • Standard, well-established, & feasible selection strategies are important

31. Small Staffing Projects • Luxury of using wider range of assessment tools • Adverse impact is less of an issue • Fairness is still a key issue • Rational, job-related, & feasible selection strategies are important

32. Module 4: Legal Issues inStaffing Decisions • Charges of employment discrimination • Involve violations of Title VII of 1964 CRA, ADA, or ADEA • I-O psychologists often serve as expert witnesses in these lawsuits • Consequences can be substantial • Most often brought by individual claiming unfair termination

33. Intentional Discrimination or Adverse Treatment • Plaintiff attempts to show that employer treated plaintiff differently than majority applicants or employees

34. Unintentional Discrimination or Adverse Impact (AI) • Acknowledges employer may not have intended to discriminate against plaintiff but employer practice had AI on group to which plaintiff belongs

35. Determination of Adverse Impact • Burden of proof on plaintiff to show: a) he/she belongs to a protected group, & b) members of protected group were statistically disadvantaged compared to majority employees

36. “80%” or “4/5ths” rule • Guideline for assessing whether there is evidence of AI • Plaintiffs must show that protected group received only 80% of desirable outcomes received by majority group in order to meet burden of demonstrating AI • Results in AI ratio

37. “80%” or “4/5ths” Rule(cont'd) • Crude & can be substantially affected by sample sizes • Burden of proof shifts to employer once AI is demonstrated