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© 2013 by Nelson Education1 Decision Making. Chapter Learning Outcomes  After reading this chapter you should:  Appreciate the complexity of decision.

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Presentation on theme: "© 2013 by Nelson Education1 Decision Making. Chapter Learning Outcomes  After reading this chapter you should:  Appreciate the complexity of decision."— Presentation transcript:

1 © 2013 by Nelson Education1 Decision Making

2 Chapter Learning Outcomes  After reading this chapter you should:  Appreciate the complexity of decision making in the employee selection context  Be familiar with the sources of common decision-making errors in employee selection  Understand the distinction between judgmental and statistical approaches to the collection and combination of applicant information © 2013 by Nelson Education 2

3 Chapter Learning Outcomes (continued)  Understand the advantages and disadvantages of various decision-making models  Appreciate issues involved with group decision making  Know the basic principles in the application of cut-off scores, banding, and top-down selection © 2013 by Nelson Education 3

4 The Context of Selection Decisions  Satisficing: making an acceptable or adequate choice rather than the best or optimal choice  Employers typically have to contend with a number of constraints and competing demands when making selection decisions – e.g. time  Sometimes, rather than selecting for a specific job, employers select applicants for the organization and not based on skills (or visa versa)  One may accept a less-qualified applicant if the applicant pool is small instead of generating a new applicant pool © 2013 by Nelson Education 4

5 © 2010 Nelson Education Ltd. 5  Selection Errors:  Most employers hold implicit theories about personal beliefs that are held about how people or things function, without objective evidence and often without conscious awareness  Many employers make decisions based on “gut feelings” about the applicants.  Some employers do go through an elaborate process however the candidate they select may not perform how they had thought The Context of Selection Decisions (continued)

6 6 © 2013 by Nelson Education

7 Methods of Collecting and Combining Applicant Information  Before a selection decision can be made, information about the applicants must be collected from various sources and combined in an effective way. Methods include:  Pure judgment approach: an approach in which judgemental data are combined in a judgmental manner (“gut feeling”)  Trait rating approach: an approach in which judgmental data are combined statistically © 2013 by Nelson Education 7

8 Methods of Collecting and Combining Applicant Information (continued)  Profile interpretation: an approach in which statistical data are combined in a judgmental manner  Pure statistical approach: an approach in which data are combined statistically (test scores)  Judgmental composite: an approach in which judgmental and statistical data are combined in a judgmental manner  Statistical composite: an approach in which judgmental and statistical data are combined statistically © 2013 by Nelson Education 8

9 Group Decision Making  Although most employee selection research has explored individual models of decision making, several surveys indicate that in most organizations, selection decisions are made by groups  Researchers conclude that groups are generally better at problem solving and decision making than the average individual © 2013 by Nelson Education 9

10 Decision Making  Employers rely on various sources of information about applicants to make hiring decisions  Some sources of information provide unique information and some are redundant  If the source gives you redundant information then why use it – eg) interview questions that give you the same information contained in the resume or application form © 2013 by Nelson Education 10

11 © 2013 by Nelson Education 11

12 Decision-Making Models  There are several different decision-making models involving combining applicant information statistically regardless of how that information was collected.  Multiple Regression Model – weights are assigned to different information sources  Multiple Cut-Off Model – applicants are rejected if any of their scores fall below the cut-off  Multiple Hurdle Model – applicants must pass the minimum cut-off for each predictor before being assessed on the next  Combination Model  Profile Matching Model © 2013 by Nelson Education 12

13 Making Selection Decisions  Regardless which decision making model is used, the aim of the selection process is to decide which applicants to hire.  Two basic approaches exist:  Top-down selection – ranking applicants based on their total scores and hiring starting from the top ranked person  Banding – grouping applicants based on ranges of scores  Above Cut-off, Below Cut-off  “Very Good”, “Acceptable”, “Unacceptable” 13

14 © 2013 by Nelson Education 14 Making the Selection Decision: An Overview 1. Identify all of the sources of information about the applicant available to you 2. Use reliable, valid selection instruments whenever possible 3. Determine which decision-making model you will use

15 4. If using the regression or combination models, collect and save data over a period of time for all predictors as well as job performance data for those applicants who are hired 5. If using multiple cut-off or multiple hurdle models, determine appropriate cut-off scores for each predictor Making the Selection Decision: An Overview (continued)

16 6. Combine data from different predictors statistically to yield an overall score 7. Offer the position(s) to the candidate(s) with the highest overall score(s) Making the Selection Decision: An Overview (continued)

17 17 Key Course Learnings  Important things to remember in R&S: Use valid, reliable, and bias free selection instruments (legally defensible) Dissuade managers from making selection decisions based on “gut feelings” or intuition Encourage managers to keep track of their own selection hits and misses (including the selection ratio) Train managers to make systematic selection decisions using approaches discussed throughout this course Periodically evaluate or audit selection decisions in order to identify areas needing improvement


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