2 Decision Making CHAPTER ELEVEN Screen graphics created by: Jana F. Kuzmicki, PhDTroy State University-Florida and Western Region
3 Staffing Organizations Model Vision and MissionGoals and ObjectivesOrganization StrategyHR and Staffing StrategyStaffing Policies and ProgramsSupport ActivitiesCore Staffing ActivitiesLegal complianceRecruitment: External, internalPlanningSelection: Measurement, external, internalJob analysisEmployment: Decision making, final matchStaffing System and Retention Management
4 Chapter Outline Choice of Assessment Method Validity CoefficientCorrelation with Other PredictorsAdverse ImpactUtilityDetermining Assessment ScoresSingle PredictorMultiple PredictorsHiring Standards and Cut ScoresDescription of ProcessConsequences of Cut ScoresMethods to Determine Cut ScoresProfessional GuidelinesMethods of Final ChoiceRandom SelectionRankingGroupingDecision MakersHR ProfessionalsManagersEmployeesLegal Issues
5 Choice of Assessment Method Validity coefficientCorrelation with other predictorsAdverse impactUtility
6 Validity Coefficient Practical significance Statistical significance Extent to which predictor adds value to prediction of job successAssessed by examiningSignMagnitudeValidities above .15 are of moderate usefulnessValidities above .30 are of high usefulnessStatistical significanceAssessed by probability or p valuesReasonable level of significance is p < .05Face validity
7 Correlation With Other Predictors To add value, a predictor must add to prediction of success above and beyond forecasting powers of current predictorsA predictor is more useful theSmaller its correlation with other predictors andHigher its correlation with the criterionPredictors are likely to be highly correlated with one another when their content domain is similar
8 Adverse Impact Role of predictor Issues Discriminates between people in terms of the likelihood of their job successWhen it discriminates by screening out a disproportionate number of minorities and women,Adverse impact exists which may result in legal problemsIssuesWhat if one predictor has high validity and high adverse impact?And another predictor has low validity and low adverse impact?
9 Utility Analysis Expected gains derived from using a predictor 1. Hiring success gain from using a new predictor (relative to current predictor): Uses Taylor-Russell TablesFocuses on proportion of new hires who turn out to be successfulRequires information on:Selection ratio: Number hired / number of applicantsBase rate: proportion of employees who are successfulValidity coefficient of current and “new” predictors2. Economic gain from using a predictor (relative to random selection): Uses Economic Gain FormulaFocuses on the monetary impact of using a predictorRequires a wide range of information on current employees, validity, number of applicants, cost of testing, etc.
10 Utility Analysis: Taylor-Russell Tables If base rate = .30, impact of validity and selection ratioIf base rate = .80, impact of validity and selection ratioSelection RatioValidity.10.70.2043%33%.6077%40%Selection RatioValidity.10.70.2089%83%.6099%90%
11 Utility Analysis: Economic Gain Formula ∆U = (T * N * rxy * SDy * Zs) – (N * Cy)Where:∆U = expected $ increase to org. versus random selectionT = tenure of selected group (how long new hires are expected to stay)N = number of applicants selectedrxy = correlation between predictor and job performance valueSDy = standard deviation of job performanceZs = average standard predictor score of selected groupN = number of applicantsCy = cost per applicantApply the formula above. Assume the following estimates are reasonable:T = 3; Ns=50; r = .35; 40% of pay = $15,000; Zs = .7; N = 200; C = $200Discuss the issues involved in estimating gain in this example
12 Limitations of Utility Analysis 1. While most companies use multiple selection measures, utility models assume decision isWhether to use a single selection measure rather thanSelect applicants by chance alone2. Important variables are missing from modelEEO / AA concernsApplicant reactions3. Utility formula based on simplistic assumptionsValidity does not vary over timeNon-performance criteria are irrelevantApplicants are selected in a top-down manner and all job offers are accepted
13 Determining Assessment Scores Single predictorMultiple predictors - 3 approachesCompensatory model - Exh. 11.3Clinical predictionUnit weightingRational weightingMultiple regressionChoosing among weighting schemes - Exh. 11.4Multiple hurdles modelCombined model - Exh. 11.5: Combined Model for Recruitment Manager
14 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?
15 Exh. 11.5: Combined Model for Recruitment Manager
16 Hiring Standards and Cut Scores Issue -- What is a passing score?Score may be aSingle score from a single predictor orTotal score from multiple predictorsDescription of processCut score - Separates applicants who advance from those who are rejectedConsequences of cut scoresExh. 11.6: Consequences of Cut Scores
18 Hiring Standards and Cut Scores (continued) Methods to determine cut scoresExh. 11.7: Use of Cut Scores in Selection DecisionsMinimum competencyTop-downBandingProfessional guidelinesExh. 11.8: Professional Guidelines for Setting Cutoff Scores
19 Exh. 11.7: Use of Cut Scores in Selection Decisions
20 Methods of Final Choice Random selectionEach finalist has equal chance of being selectedRankingFinalists are ordered from most to least desirable based on results of discretionary assessmentsGroupingFinalists are banded together into rank-ordered categories
21 Decision Makers Role of human resource professionals Role of managers Determine process used to design and manage selection systemContribute to outcomes based on initial assessment methodsProvide input regarding who receives job offersRole of managersDetermine who is selected for employmentProvide input regarding process issuesRole of employeesProvide input regarding selection procedures and who gets hired, especially in team approaches
22 Legal Issues Legal issue of importance in decision making Cut scores or hiring standardsUniform Guidelines on Employee Selection Procedures (UGESP)If no adverse impact, guidelines are silent on cut scoresIf adverse impact occurs, guidelines become applicableChoices among finalists
23 Ethical Issues Issue 1 Issue 2 Do you think companies should use banding in selection decisions? Defend your position.Issue 2Is 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?