© 2013 by Nelson Education1 Decision Making. © 2013 by Nelson Education2 Chapter Learning Outcomes After reading this chapter you should: ◦ Appreciate

© 2013 by Nelson Education 1

Decision Making


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


◦ 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

◦ Be able to discuss the benefits of using best practices in recruitment and selection

Chapter Learning Outcomes (continued)


Satisficing: making an acceptable or adequate choice rather than the best or optimal choice

Organizational fit: an applicant’s overall suitability for the organization and its culture

The Context of Selection Decisions


Implicit theories: personal beliefs that are held about how people or things function, without objective evidence and often without conscious awareness

Selection Errors


False positive error: occurs when an applicant who is assessed favourably turns out to be a poor choice

False negative error: occurs when an applicants who is rejected would have been a good choice

Outcomes of the Selection Process


Pure judgment approach: an approach in which judgemental data are combined in a judgmental manner

Trait rating approach: an approach in which judgmental data are combined statistically

Methods of Collecting and Combining Applicant InformationTable 10.1


Methods of Collecting and Combining Applicant InformationTable 10.1(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

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

Methods of Collecting and Combining Applicant InformationTable 10.1(continued)


Researchers conclude that groups are generally better at problem solving and decision making than the average individual◦ Groups make better selection decisions than

individuals

Group Decision Making


1. Think about the types of decisions you make on a daily basis. What would be some examples of routine and non-routine decisions?

2. Is it better to discuss the decision making process as a group or on an individual basis? What has been your experience in this area?

Class Activity


Incremental validity: the value in terms of increased validity of adding a particular predictor to an existing selection system

Cut-off score: a threshold; those scoring at or above the cut-off score pass, those scoring below fail

Selection ratio: the proportion of applicants for one or more positions who are hired

Incremental Validity and Cut-off Score


Decision-Making Models

Unit and Rational Weighting Multiple Regression Model Multiple Cut-Off Model Multiple Hurdle Model Combination Model Profile Matching Model


Top-down selection: involves ranking applicants on the basis of their total score, selecting from the top down until the desired number of candidates has been selected◦ Based on the assumption that individuals

scoring higher will be better performers on the job than those scoring low

◦ Considered the best approach for maximizing organizational performance

Making Selection Decisions


Banding: refers to a grouping process that takes into account the concept of standard error of measurement involves grouping applicants based on ranges of scores◦ Cut-off scores are actually a form of banding

where there are two bands

Banding


Selection systems are made more effective by the following recommendations:

1. Use valid selection instruments2. Dissuade managers from making

selection decisions based on gut feelings or intuition

3. Encourage managers to keep track of their own selection “hits” and “misses”

Making Selection Decisions: Conclusions


4. Train managers to make systematic selection decisions

5. Periodically evaluate or audit selection decisions in order to identify areas needing improvement

Making Selection Decisions: Conclusions (continued)


Recruitment and Selection Notebook 10.1

Making the Selection Decision1. Identify all of the sources of information

about the applicant available to you

1. Use reliable, valid selection instruments whenever possible

1. Determine which decision-making model you will use

Recruitment and Selection Notebook 10.1(continued)

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

Recruitment and Selection Notebook 10.1(continued)

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)


Selection decisions are made by groups, rather than by individuals

Methods that involve combining applicant information in a statistical manner are better methods in reducing errors and predicting job performance

Various decision-making models are used

Summary


1. What are the common decision-making errors made in employee selection? Can these be eliminated? If so, how? If they cannot be eliminated, can they be reduced? If so, how?

2. What is the difference between judgmental and statistical approaches to the collection and combination of applicant information?

Discussion Questions


Discussion Questions (continued)3. Why do organizations tend to use groups

to make selection decisions? What are the advantages and disadvantages of group decision making?

4. Why is it better to use predictors that are uncorrelated or that have a low correlation with each other than predictors that are highly correlated with each other.

Documents

© 2013 by Nelson Education1 Decision Making. © 2013 by Nelson Education2 Chapter Learning Outcomes After reading this chapter you should: ◦ Appreciate