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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.

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Page 1: Chap011 decision making_editing

Part 5Staffing Activities: Employment

Chapter 11: Decision Making

Chapter 12: Final Match

McGraw-Hill/Irwin Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

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Part 5Staffing Activities: Employment

Chapter 11:

Decision Making

11-2

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Organization StrategyOrganization Strategy HR and Staffing StrategyHR and Staffing Strategy

Staffing Policies and Programs

Staffing System and Retention Management

Support Activities

Legal compliance

Planning

Job analysis

Core Staffing Activities

Recruitment: External, internal

Selection:Measurement, external, internal

Employment:Decision making, final match

OrganizationMission

Goals and Objectives

Staffing Organizations Model

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Chapter Outline

Choice of Assessment Method Validity Coefficient Face Validity Correlation with Other

Predictors Adverse Impact Utility

Determining Assessment Scores 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 HR Professionals Managers Employees

Legal Issues Uniform Guidelines on

Employee Selection Procedures

Diversity and Hiring Decisions

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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

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Choice of Assessment Method

Validity Coefficient

Face Validity

Correlation With Other Predictors

Adverse Impact

Utility

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Validity Coefficient

Practical significance Extent to which predictor adds value to prediction of

job success Assessed by examining

Sign Magnitude

Validities above .15 are of moderate usefulness Validities above .30 are of high usefulness

Statistical significance Assessed by probability or p values Reasonable level of significance is p < .05

Face validity

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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

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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?

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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

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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.

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Limitations of Utility Analysis

While most companies use multiple selection measures, utility models assume decision is Whether to use a single selection measure rather than Select applicants by chance alone

Important variables are missing from model 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

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Determining Assessment Scores

Single predictor Multiple predictors

Three models shown

Multiple hurdles model

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Relevant Factors: Selectingthe 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?

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Ex. 11.4: Combined Modelfor Recruitment Manager

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Hiring Standards and Cut Scores

Issue -- What is a passing score?Score may be a

Single score from a single predictor orTotal score from multiple predictors

Description of processCut score - Separates applicants who

advance from those who are rejected

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Exh. 11.5: Consequences of Cut Scores

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Hiring Standards and Cut Scores(continued)

Methods to determine cut scoresMinimum competencyTop-downBanding

Professional guidelines

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Ex. 11.6: Use of Cut Scores in Selection Decisions

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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?

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Methods of Final Choice

Random selection Each finalist has equal chance of being selected

Ranking Finalists are ordered from most to least desirable

based on results of discretionary assessments Grouping

Finalists are banded together into rank-ordered categories

Ongoing hiring Hiring all acceptable candidates as they become

available for open positions

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Ex. 11.8: Methods of Final Choice

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Decision Makers

Role of human resource professionals Determine process used to design and manage

selection system Contribute to outcomes based on initial assessment

methods Provide input regarding who receives job offers

Role of managers 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

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Legal Issues

Legal issue of importance in decision making Cut scores or hiring standards

Uniform Guidelines on EmployeeSelection Procedures (UGESP) If no adverse impact, guidelines are silent on cut

scores

If adverse impact occurs, guidelines become applicable

Choices among finalists