Staffing Organizations Chapter 11: Decision Making PDF

Staffing Organizations Chapter 11: Decision Making Because learning changes everything. ® Copyright 2022 © McGraw Hill LLC. All rights reserved. No r...

Staffing Organizations Chapter 11: Decision Making Because learning changes everything. ® Copyright 2022 © McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.  Learning Objectives for Chapter 11 Be able to interpret validity coefficients Evaluate diversity implications of various decision processes Evaluate the utility of selection systems Learn about methods for combining multiple predictors Establish hiring standards and cut scores Compare methods of making a final selection choice Understand the roles of decision makers in the staffing process © McGraw Hill LLC  Decision Making 1 Choice of Assessment Method © McGraw Hill LLC  Validity Coefficient Relationship between predictor and criterion scores Measured through correlations Practical significance Sign is positive versus negative Magnitude ranges from -1 to +1; zero means no relationship Statistical significance Likelihood that other samples will get the same result Validity for multiple criteria Core job tasks Organization and goal direction Cooperation and group facilitation Creativity © McGraw Hill LLC  Workforce Diversity Concerns about factors not related to performance on the job: al credentials may screen low-income applicants Leadership behaviors that are more typical of men than of women fail to recognize the value of alternative modes of leadership Difficult issue: one predictor has high validity and high disparate impact while another predictor has low validity and low disparate impact Using a variety of different selection tools together Putting greater weight on lower disparate impact sections of the test Adding measures with lower disparate impact © McGraw Hill LLC  Correlation with other predictors Small correlation with other Task Task existing predictors is better performance performance Hypothetical example in setting Validity Increment where experience and GPA are Cognitive ability 0.35 0.27 already used Conscientiousness 0.18 0.12 Cognitive ability and structured Situational judgment 0.43 0.13 interviews have moderate Structured interview 0.22 0.18 validity and incremental prediction Innovation Innovation Validity Increment Situational judgment has high validity and but low Cognitive ability 0.28 0.20 incremental prediction Conscientiousness 0.08 0.02 Means situational judgment (in Situational judgment 0.35 0.14 this case) is very similar to Structured interview 0.39 0.33 what’s already being used, whereas cognitive ability and structured interviews add more © McGraw Hill LLC  Hiring Success Gain Selection ratio Number hired divided by number of applicants High selection ratio means nearly every applicant must be hired Low selection ratio means the organization can be more selective Base rate Number of successful employees divided by number of employees Indicates how difficult the job is—higher base rate means easier job Taylor-Russel Tables Combine information on selection ratios, base rates, and validity Conclusion is that selection tools are most valuable when the selection ratio is low, the base rate is low, and validity coefficient is high © McGraw Hill LLC  Taylor-Russell Tables Source: H. C. Taylor and J. T. Russell, "The Relationship of Validity Coefficients to the Practical Effectiveness of Tests in Selection," Journal of Applied Psychology, 1939, 23, pp. 565 -578. Access the text alternative for slide images. © McGraw Hill LLC  Economic Gain Technique Sources of What is evaluated? Links to other areas information Utility analysis Data on predictor Expected value of Line manager validity, applicant test improved job judgments of scores, and estimated performance if a new employee value; dollar value of selection tool is expected financial performance implemented returns for investing in variability selection Predictive analytics Historical information Contribution of Existing “hard” data on performance different from organizational outcomes for business characteristics of the records for valued units workforce to outcomes performance outcomes Kano analysis Line manager and Changes in economic Tool from marketing, director descriptions performance from manager judgments of strategic impact of enhanced levels of regarding critical performance across different types of competencies are domains employee skills incorporated © McGraw Hill LLC  Discussion Question 1 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? © McGraw Hill LLC  Decision Making 2 Determining Assessment Scores © McGraw Hill LLC  Determining Assessment Scores Single predictor Simple and fast Does not capture many candidate qualifications Multiple predictors More complicated and time consuming More complete picture of the candidates © McGraw Hill LLC  Multiple Predictor Methods 1 Compensatory model Adds all scores together into a single number Can be done through informal “clinical” weighting, unit weighting, rational weighting, or regression weighting Multiple hurdles model Uses selection tools in order from cheapest to most expensive Cuts candidates at each stage Results similar to compensatory model, but costs are much lower © McGraw Hill LLC  Multiple Predictor Methods 2 Access the text alternative for slide images. © McGraw Hill LLC  Combining Multiple Hurdle and Compensatory Models Access the text alternative for slide images. © McGraw Hill LLC  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? © McGraw Hill LLC  Discussion Questions 2 Under what circumstances should a compensatory model be used? When should a multiple hurdles model be used? © McGraw Hill LLC  Decision Making 3 Hiring Standards and Cut Scores © McGraw Hill LLC  Consequences of Cut Scores 1 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 © McGraw Hill LLC  Consequences of Cut Scores 2 Access the text alternative for slide images. © McGraw Hill LLC  Methods to Determine Cut Scores Minimum competency set on the basis of the minimum qualifications deemed necessary to perform the job Compensatory: single aggregate score across predictors Conjunctive: must pass standards for each predictor Maximum competency Screen for “overqualified” candidates © McGraw Hill LLC  Use of Cut Scores Access the text alternative for slide images. © McGraw Hill LLC  Discussion Questions 3 What are the positive consequences associated with a high predictor cut score? What are the negative consequences? © McGraw Hill LLC  Decision Making 4 Methods of Final Choice © McGraw Hill LLC  Methods of Final Choice 1 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 and banding Finalists are banded together into rank-ordered categories Differential weighting Incorporating weights on scores for determining final candidate eligibility © McGraw Hill LLC  Methods of Final Choice 2 Access the text alternative for slide images. © McGraw Hill LLC  Discussion Question 4 What are the advantages of ranking as a method of final choice over random selection? © McGraw Hill LLC  Decision Making 5 Decision Makers © McGraw Hill LLC  Decision Makers Organizational leaders Uniquely valuable, holistic understanding of the purpose of a selection system. Buy-in enhances the success of any policy initiative Human Resource Professionals Technical expertise needed to develop sound selection decisions Access to quantitative information from HR information systems that can be used to quantify predictor-outcome relationships Line managers Accountable for the success of the people hired Identify critical needs in the selection system that might not be addressed Coworkers Select members compatible with the goals of the work team © McGraw Hill LLC  Decision Makers in Selection Access the text alternative for slide images. © McGraw Hill LLC  Discussion Questions 5 What roles should HR professionals play in staffing decisions? Why? © McGraw Hill LLC  Decision Making 6 Legal Issues © McGraw Hill LLC  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 Diversity and hiring decisions Exclude issues of demography in hiring decisions Evaluation based on KSAOs relevant to job-related diversity competence © McGraw Hill LLC  Discussion Questions 6 What guidelines do the UGESP offer to organizations when it comes to setting cut scores? © McGraw Hill LLC  Ethical Issues in Staffing Issue 1 Do you think companies should use banding and related methods to enhanced diversity in selection decisions? Defend your position. Issue 2 Is clinical prediction the fairest way to combine assessment information about job applicants, or are statistically based weighting methods more fair? Why? © McGraw Hill LLC  Because learning changes everything. ® www.mheducation.com Copyright 2022 © McGraw Hill LLC. All rights reserved. No reproduction or distribution without the prior written consent of McGraw Hill LLC.