Part 5 Staffing Activities: Employment Chapter 11: Decision Making Chapter 12: Final Match McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved. Part 5 Staffing Activities: Employment Chapter 11: Decision Making 11-2 Staffing Organizations Model Organization Mission Goals and Objectives Organization Strategy HR and Staffing Strategy Staffing Policies and Programs Support Activities Core Staffing Activities Legal compliance Planning Recruitment: Selection: External, internal Measurement, external, internal Job analysis Employment: Decision making, final match Staffing System and Retention Management 11-3 Chapter Outline Choice of Assessment Method Single Predictor Multiple Predictors Hiring Standards and Cut Scores Description of Process Consequences of Cut Scores Methods to Determine Cut Scores Professional Guidelines Methods of Final Choice Random Selection Ranking Grouping Ongoing Hiring Decision Makers Determining Assessment Scores Validity Coefficient Face Validity Correlation with Other Predictors Adverse Impact Utility HR Professionals Managers Employees Legal Issues Uniform Guidelines on Employee Selection Procedures Diversity and Hiring Decisions 11-4 Learning Objectives for This Chapter Be able to interpret validity coefficients Estimate adverse impact and utility of selection systems Learn about methods for combining multiple predictors Establish hiring standards and cut scores Evaluate various methods of making a final selection choice Understand the roles of various decision makers in the staffing process Recognize the importance of diversity concerns in the staffing process 11-5 Discussion Questions for This Chapter Your boss is considering using a new predictor. The base rate is high, the selection ratio is low, and the validity coefficient is high for the current predictor. What would you advise your boss and why? What are the positive consequences associated with a high predictor cut score? What are the negative consequences? Under what circumstances should a compensatory model be used? When should a multiple hurdles model be used? What are the advantages of ranking as a method of final choice over random selection? What roles should HR professionals play in staffing decisions? Why? What guidelines do the UGESP offer to organizations when it comes to setting cut scores? 11-6 Choice of Assessment Method Validity Coefficient Face Validity Correlation With Other Predictors Adverse Impact Utility 11-7 Validity Coefficient Practical significance Extent to which predictor adds value to prediction of job success Assessed by examining Sign Magnitude Statistical significance Validities above .15 are of moderate usefulness Validities above .30 are of high usefulness Assessed by probability or p values Reasonable level of significance is p < .05 Face validity 11-8 Correlation With Other Predictors To add value, a predictor must add to prediction of success above and beyond forecasting powers of current predictors A predictor is more useful the Smaller its correlation with other predictors and Higher its correlation with the criterion Predictors are likely to be highly correlated with one another when their content domain is similar 11-9 Adverse Impact Role of predictor Discriminates between people in terms of the likelihood of their job success When it discriminates by screening out a disproportionate number of minorities and women, Adverse impact exists which may result in legal problems Issues What if one predictor has high validity and high adverse impact? And another predictor has low validity and low adverse impact? 11-10 Utility Analysis Taylor-Russell Tables Focuses on proportion of new hires who turn out to be successful Requires information on: Selection ratio: Number hired / number of applicants Base rate: proportion of employees who are successful Validity coefficient of current and “new” predictors 11-11 Utility Analysis Economic Gain Formula Focuses on the monetary impact of using a predictor Requires a wide range of information on current employees, validity, number of applicants, cost of testing, etc. 11-12 Limitations of Utility Analysis While most companies use multiple selection measures, utility models assume decision is Important variables are missing from model Whether to use a single selection measure rather than Select applicants by chance alone EEO / AA concerns Applicant reactions Utility formula based on simplistic assumptions Validity does not vary over time Non-performance criteria are irrelevant Applicants are selected in a top-down manner and all job offers are accepted 11-13 Discussion Questions Your boss is considering using a new predictor. The base rate is high, the selection ratio is low, and the validity coefficient is high for the current predictor. What would you advise your boss and why? 11-14 Determining Assessment Scores Single predictor Multiple predictors Three models shown Multiple hurdles model 11-15 Relevant Factors: Selecting the Best Weighting Scheme Do decision makers have considerable experience and insight into selection decisions? Is managerial acceptance of the selection process important? Is there reason to believe each predictor contributes relatively equally to job success? Are there adequate resources to use involved weighting schemes? Are conditions under which multiple regression is superior satisfied? 11-16 Ex. 11.4: Combined Model for Recruitment Manager 11-17 Hiring Standards and Cut Scores Issue -- What is a passing score? Score may be a Single score from a single predictor or Total score from multiple predictors Description of process Cut score - Separates applicants who advance from those who are rejected 11-18 Exh. 11.5: Consequences of Cut Scores 11-19 Hiring Standards and Cut Scores (continued) Methods to determine cut scores Minimum competency Top-down Banding Professional guidelines 11-20 Ex. 11.6: Use of Cut Scores in Selection Decisions 11-21 Discussion Questions What are the positive consequences associated with a high predictor cut score? What are the negative consequences? Under what circumstances should a compensatory model be used? When should a multiple hurdles model be used? 11-22 Methods of Final Choice Random selection Ranking Finalists are ordered from most to least desirable based on results of discretionary assessments Grouping Each finalist has equal chance of being selected Finalists are banded together into rank-ordered categories Ongoing hiring Hiring all acceptable candidates as they become available for open positions 11-23 Ex. 11.8: Methods of Final Choice 11-24 Decision Makers Role of human resource professionals Role of managers Determine process used to design and manage selection system Contribute to outcomes based on initial assessment methods Provide input regarding who receives job offers Determine who is selected for employment Provide input regarding process issues Role of employees Provide input regarding selection procedures and who gets hired, especially in team approaches 11-25 Discussion Questions What are the advantages of ranking as a method of final choice over random selection? What roles should HR professionals play in staffing decisions? Why? 11-26 Legal Issues Legal issue of importance in decision making Cut scores or hiring standards Uniform Guidelines on Employee Selection Procedures (UGESP) If no adverse impact, guidelines are silent on cut scores If adverse impact occurs, guidelines become applicable Choices among finalists 11-27 Discussion Questions What guidelines do the UGESP offer to organizations when it comes to setting cut scores? 11-28 Ethical Issues Issue 1 Do you think companies should use banding in selection decisions? Defend your position. Issue 2 Is clinical prediction the fairest way to combine assessment information about job applicants, or are the other methods (unit weighting, rational weighting, multiple regression) more fair? Why? 11-29