Advanced Topics in HR Employee Selection and Staffing

Advanced Topics in HR Employee Selection and Staffing
MGT 467/667 Dr. Yvonne Stedham Advanced Topics in HR Employee Selection and Staffing

Pre-requisites MGT 323 Organizational Behavior MGT 367
Human Resource Management

Course Content and Purpose
Major? Management, IB, Other Focus on HR? Management degree with concentration in HR Practical background in HR Limited interest in HR

Managerial Skills Listening Persuading Goal setting Providing Feedback
Technical, Conceptual, Human Relations Skills Human Relations Skills (Examples) Listening Persuading Goal setting Providing Feedback Running meetings Empowering people Resolving conflicts Coaching Interviewing Building Teams

Course Materials available on

Readings Several Readings Five with assignments or quizzes
In-class handout, website, or find online Five with assignments or quizzes Sign-up for presentations

Employee Selection Course Introduction Content Overview
Format Overview (Syllabus) – Readings/ HRMagazine/WSJ/Fortune SHRM – Society for Human Resource Management ( Personal Introductions Instructor Students – Background Sheet

Employee Selection Course Introduction What do you know about HR?
Organizational Performance and HR External Environment

What do you know about HR? Table Tents
What is Human Resource Management? How does it contribute to the success of an organization? List the specific functions entailed in HRM. What does KSAs stand for? What is a JE and a JA? What is the FMLA? List the most important federal anti-discrimination laws. What are the primary provisions of Title VII? What is a BFOQ?

What do you know about HR?
Distinguish two types of Sexual Harassment. Does money motivate employees? Explain. How do you determine whether an individual has the skills and knowledge required for job? What is the primary purpose of an employee interview? To what extent is employee turnover desirable?

This Course The Staffing/Employment Function
The most important HR function Budget and time spent Staffing Mutual process by which the individual and the organization become matched to form the employment relationship. Mutual Process: Series of interrelated activities - Recruitment, Selection, Decision Making, job offers, hiring.

Definitions Recruitment Selection
Generating a pool of qualified applicants Selection Assessing/Measuring Applicant KSAs – Development of KSA Measures

Definitions Selection The process of obtaining and using information
about job applicants to determine who should be hired. Focus here is on how to collect relevant info on applicants’ KSA’s.

Course Format Syllabus

Selection and the Bottom Line - A Framework
Why a course in employee selection? What is the relationship between organizational effectiveness and HRM?

HR and Organizational Performance
What is an organization? What is organizational effectiveness? How does HR contribute?

HR and Org effectiveness
Individual effectiveness is the foundation for organizational effectiveness. Individual effectiveness depends on ….

Individual effectiveness = Performance Individual effectiveness = f(Ability,Motivation) Performance = Ability * Motivation

Individual Performance
Ability Motivation Performance

Match Person KSAs Needs Job KSA requirements Rewards

The HRM Framework External Environment MATCH HR Activities HR Outcomes
Legal Environment Economy Labor Market Social Environment MATCH HR Outcomes Job Satisfaction Org. Commitment Attraction Attendance Turnover HR Activities Recruitment Selection Compensation Benefits Training Labor Relations Employee Relations PERSON KSAs Needs JOB Rewards

Personal Introductions
Students – Table Tents and Background Sheets? Name and Major HR Games? Share a “hiring” experience

Introductory Exercise
Have you ever been involved in hiring an employee? Describe. Did you like being involved in the hiring process? Why/why not? When selecting an employee, what do you think is the most important criterion to consider? Why? How do you know whether you have an effective hiring/selection process in place?

A Word about Recruitment
Quantity? Type – what KSAs? Size of applicant pool to fill how many positions? Yield Ratios Sources? Formal/Informal Relevant Labor Market Timing

SNC – HR Internship I wanted to inform you of a new internship position that just opened up at SNC -Training and Development Intern. We are looking for an energetic individual, preferably Junior or Senior, with strong technical/PC skills, excellent verbal and written communication, and strong interest in Org Development/Training to join our team. Work hours range between 7:30-5:30, working with the individual's school schedule, preferably committing hours a week. This is a great opportunity to gain first-hand corporate experience in the training and development field. As you may know, we've had two recent successful HR interns from UNR: - Amy Mendel, training intern, joined us in February, graduated in May, and recently landed a position outside of SNC as a Training and Development Manager - Adrian Nunez, HR Intern, joined us after graduation in May and has received a permanent offer to stay on our HR Team supporting our Corporate Org Development Manager If you know of students that you recommend for this position, please have them contact me via with their resume. We are looking to fill this position as soon as possible, and will extend an offer as soon as the right candidate comes our way! Feel free to contact me if you have any questions- Kind Regards, Pam Durfee, PHRHuman Resources444 Salomon Circle Sparks, NV 89434Ph: Faax:

External Environment Labor Markets, Global Economic Crisis, and HRM
Legal Environment

Economic conditions Current conditions What? Why? Predictions?
Effect on HRM?

Labor Market Demand – Derived Demand
Quantity - Job growth Quality - Types of jobs and KSA’s Supply – Workforce Quantity and Quality Number Composition – Diversity, Generations, Values KSA’s

Psychological Contract
Labor Market Psychological Contract

What is the number one reason for employees to quit their job?

Study on Turnover in Gaming
Importance of perceptions of “fairness” Following rules and procedures Making arbitrary decisions Consistency

What is important to employees?
Job attributes and rewards

How do you believe a typical non-supervisory employee would rank the following 10 job attributes?
___ Job security ____Good wages ____Promotion and growth in the organization ____Good working conditions ____Personal loyalty to employees ____Tactful discipline ____Sympathetic help with personal problems ____Interesting Work ____Full appreciation of work done ____Feeling of being in on things

Survey Results Interesting Work Full appreciation of work done
Feeling of being in on things Job security Good wages Promotion and growth in the organization Good working conditions Personal loyalty to employees Tactful discipline Sympathetic help with personal problems

Role of HR The Human Equation Jeffrey Pfeffer Seven common practices:
Employment security. Selective hiring, Self-managed teams and decentralization, High compensation, Extensive training, Reduction of status differences, Sharing information

Role of HR The Human Equation
Theoretical foundation – how/why do these practices work? Increased involvement and commitment, more control and say in their work, work smarter because they are encouraged to build skills and competence.

HRM – Four Pillars Involvement Communication Commitment Community

Labor Market Generations at work WWII Generation 60+ Baby Boom 40-60
Generation X 20-40 Millennial Generation birth-20 (Gen Y)

Generations WWII 60+ Outlook: practical Work Ethic: dedicated
View of Authority: respectful Leadership by: hierarchy Relationship: personal sacrifice Perspective: Civic

Generations Baby Boom 40-60 Outlook: optimistic Work Ethic: driven
View of Authority: love/hate Leadership by: consensus Relationship: personal gratification Perspective: team Also: workholic – defined by work, competitve, trophies, rebellion

Generations Generation X 20-40 Outlook: skeptical Work Ethic: balanced
View of Authority: unimpressed Leadership by: competence Relationship: reluctant to commit Perspective: self

Generations Millennials (Y) 20 and younger environmentally conscious
connected more tolerant of differences generally optimistic achievement oriented team players sociable want to fit in not revolutionize

Generations in the Workplace
WWII BB X Y Outlook practical optimistic skeptical connected Work Ethic dedicated driven balance Leader ship hierarchy consensus competence Relation personal sacrifice personal gratification reluctant to commit ?

Generations in the Workplace
Implications for Management, HR, and Selection????

Summary Labor Market Demand Supply - QUN and - QUL - Labor Shortage
- QUL - Composition and KSA type and level; and, needs and values of employees

Summary Labor Market Diversity of values Generational Differences WWII
Baby Boomers Generation X Generation Y

Legal Environment The Employment Relationship Exchange relationship
Psychological Contract Employment Contract Formal agreement, voluntary: Defines and governs the terms and conditions of the employment relationship; promises and expectations … change with time Written or oral --- both are legally enforceable

Common Law Refers to laws applied in the English-speaking world when there were few statutes. Courts wrote opinions explaining the bases for their decisions These opinions became precedents for later decisions in similar cases

Workplace Torts A Tort is a “civil wrong”
a violation of a duty by the ER that leads to harm or damages suffered by others

Workplace Torts breaches of legal duty by ER
Are breaches of legal duty by ER when establishing or modifying the initial relationship (common law)

Workplace Torts Fraud or misrepresentation: lie/mislead applicant when communicating conditions and terms -> ER violates a duty to be truthful in the presentation of information 2. Negligent hiring: ER violates duty to protect Ees and customers against unreasonable and foreseeable risk of harm 3. Wrongful Discharge

Wrongful Discharge Tort – civil wrong – due process – just cause
Good faith – fair dealing Implied contract Contract renewal Performance evals Fire for cause (Employment at Will) Violation of company policy Poor performance

Need for Laws and Regulations
Balance of Power  Laws limit discretion of ER in establishment of terms and conditions Protection of EEs Employment Standards - Minimum acceptable terms and conditions of employment … min. wage, overtime, safety and health (FLSA 1938, OSHA)

Need for laws Individual Rights Labor Relations,
Civil Rights Protection, Restrictions on employment-at-will Consistency of Treatment: Procedural justice  Standardized Systems

Legal Environment Protection of ERs
Permissble and impermissible practices: what is OK … e.g., to use ability tests Administrative predictability and stability

Sources of Laws and Regulations
Common Law England; Court-made Law; Case-by-case decisions  Precedence (Germany and other country code-based law); States – develop and administer own common law. Constitutional Law Supersedes; Prohibits deprivation of employment right without due process.

Legal Environment Statutory Law Agencies
Derived from written statutes that are passed by legislative bodies (Federal – Congress; State – Legislature/Assemblies; Local – Municipal/Councils) Agencies Interpret, administer, enforce law. DOL (OFCCP); EEOC - publish rules and regulatory guidelines that are given “great deference” by courts.

EEO Framework U.S. Constitution 5th Amendment 14th Amendment
Due Process of law --- Prohibition upon federal government; no person shall be deprived of life, liberty, or property; does not speak directly to specific subjects such as employment  Courts prefer to defer to existing statutory laws because it is more specific!! 14th Amendment Prohibition for States to enacts any law that does not “guarantee” equal protection for all.

Statutory Laws EEO Framework Civil Rights Act 1866:
Right to make and enforce contracts for employment … for all citizens as enjoyed by white citizens. Civil Rights Act of 1871: Right to sue if deprived of any rights or privileges guaranteed by the Constitution and laws for ALL citizens. Must show intention. Equal Pay Act 1963: Equal pay for equal work regardless of SEX (female employees only); amendment to FLSA .

EPA Equal pay for equal work regardless of SEX (female employees only); amendment to FLSA . “Equal” Work: Substantially similar – Requirements concerning skill, effort, responsibilities, working conditions. Exceptions: Seniority; Merit; Quantity of production Note: If in violation of EPA, ER may not LOWER wages. Consider --- Internal equity and job evaluation; Comparable worth.

Title VII of CRA 1964: Coverage: ERs with 15 or more employees; Federal, State, Local governments; Educational Institutions; Employment Agencies; Labor Unions; Congress Not covered: Private Clubs; Religious Organizations. CRA 1964: Several Titles each focusing on discrimination in a different “sector” of society (education, right to vote,… ) Title VII focuses on discrimination in employment.

Title VII Enforcement: EEOC Language of TVII: 703 (a)
Employer may not discriminate on the basis of race, color, national origin, sex, and religion in any employment decision.

Title VII Color: White, black, yellow, brown, red.
Race: Local geographic or global human population distinguished by genetically transmitted physical characteristics … Caucasian; Negro; Hispanic; Oriental; Indian. National Origin: Citizenship; Heritage; Any country, nation. Religion: All kinds; not associated with any of the other characteristics; Christian, Hindu, Muslim, Buddhist.

Title VII 703 (b) …. Nondiscriminatory apprenticeship program
704 (a) …. Unlawful to discriminate … if opposed unlawful employment practice … assisted in TVII investigation. 704 (b) …. Prohibits ads concerning employment indicating preference for any of the prohibited factors. 1978 Amendment: Pregnancy Discrimination Act --- prohibits discrimination on the basis of pregnancy, childbirth, or related condition. Reinstatement right for similar position; no loss of seniority; coverage of disability insurance.

Title VII - Exemptions that are written into the law Discrimination on the basis of the “protected factors” is permissible when such qualification is a bona-fide occupationl qualification (BFOQ) = reasonably necessary to the operation of that particular business or enterprise; burden of proof is with ER; very narrowly interpreted --- preferences of ER, coworkers, clients are irrelevant. Seniority Systems: Bona fide seniority or merit systems are lawful if no intention to discriminate; job or departmental systems are not seen as “bona fide”, plant or company-wide systems are seen as “bona fide”.

Exemptions to TVII Testing: Employer may give and act upon professionally developed ability tests if they are not used to discriminate on the basis of the protected factors. Preferential Treatment: It is unlawful to interpret TVII as requiring preferential treatment of individuals of protected groups - reverse discrimination National Security: Discrimination is permitted

Further TVII Issues Fetal Protection
Johnson Controls 1991: An employer’s exclusion of fertile women, but not fertile men, could not be justified on grounds that the rule protected the woman’s reproductive capacity and the physical welfare of the fetus. The safety qualification is limited to those instances where sex or pregnancy presents danger to customers or third parties. A fetus is not a “third party” whose safety is essential to the operation of the employer’s business, and thus cannot be the basis of a BFOQ.

Title VII - Sexual Harassment
Employer is liable Supervisor is liable Unwelcome sexual advances in exchange for a favorable employment condition - Quid pro quo

Sexual Harassment Hostile work environment sexual harassment
Pattern of behavior. Policy and process. Examples Onclae v. Sundowner --- allows employers to be sued by members of the same sex. Faragher v. Boca Raton --- ER liable even if the employer had no knowledge of the harassment. Burlington v. Ellerth --- allows employers to be sued for quid pro quo even if the employee suffered no tangible loss of job benefits for declining the supervisor’s sexual advances

Sexual Harassment Reading #1 – Three Pronged Approach
Typical SH Situation Typical Victim Two Responses Reactance – confrontational Learned helplessness – passive and acquiescent Likely Response Typical Remedy – Policy assumes which response? Three pronged approach provides remedy considering the typical victim Org Communication – Zero tolerance; complaint process; third party Involvement – Training of all employees; role playing; consequences Proactive Actions – Investigation; implementation of consequences

Executive Order 11246 Contractors doing business with federal government ($ amount of contract specified). Same provisions as TVII AND requires contractors to develop affirmative action plans: Formal, specific personnel programs that are designed to increase the participation of protected groups. 1967 … sex-based discrimination added as prohibited

Age Discrimination in Employment Act 1967
Amended Protects EEs and applicants who are 40 years old and above (no upper limit). No mandatory retirement age (except law enforcement officers, firefighters, tenured professors, executive under certain conditions, top policy makers.); No reverse discrimination.

Americans with Disabilities Act 1990
Since 1994 covers Ers with 15 or more Ees. 43 mill. Disabled Americans. Protects: Physical or mental impairment that substantially limits one or more life activities (walk, see, ..) Record of impairment Regarded as having impairment … about 1,000 disabilities (affective disorders, biochemically based disorders - AIDS, Cancer, Anxiety Disorders, Eating Disorders, Infertility, Epilepsy) Disability evaluated with adjustive equipment (glasses)

ADA How it protects Punitive damages Essential job functions
Reasonable accommodations Restructuring of physical facilities Perceptual restructuring … ,500 complaints (25% more than were expected)

ADA … cultural change; education vs compliance
… “Be reasonable, thoughtful, caring, and you can comply” Janet Reno

Other Laws Rehabilitation Act 1972 Vietnam Era Readjustment Act 1974

Family and Medical Leave Act 1993
Employers with more than 50 employees have to provide 12 weeks of unpaid leave for family or medical emergencies. Employer must guarantee the employee the same or a comparable job. The employer must also pay the health-care coverage for the EE --- which the EE has to be back if he/she fails to return to work. ERs are allowed to exempt “key” employees – defined as the highest paid 10% of their work force whose leave would cause substantial economic harm to the employer. Also exempt are EEs who have not worked at least 1,250 hours (25 hrs a week) in the previous 12 months.

Enforcement of Laws and Court Process
Filing a Discrimination Complaint Local EEO Agency NERC (Nevada Civil Rights Commission) EEOC Investigation Right to sue letter

Evidence of Discrimination
Intentional Discrimination Disparate Treatment: different standards applied to various groups Adverse Impact: same standards are applied but disproportionately less minority applicants are selected

Plaintiff  Defendant  Plaintiff
Federal Court Process PRESENTATION OF EVIDENCE IN TITLE VII CASES Burden of Proof Plaintiff  Defendant  Plaintiff Prima Facie Evidence 1. Disparate Treatment Job-based/legitimate Pretext McDonnell Rule: 4 conditions explanation 2. Adverse Impact Business Necessity, 2. Other BFOQ, Validation method 80% or 4/5 Rule

Disparate Treatment 4 Conditions- McDonnel Rule Green vs McDonnel Douglas
Plaintiff must show belongs to protected class applied and was qualified for the job despite the qualifications - was rejected position remained open and the employer continued to seek applications from persons with the complainant’s qualifications Applied also for ADEA cases

Adverse Impact: 80% or 4/5 Rule
Selection Ratio: Number of nonminority applicants selected DIVIDED BY Number of nonminority applicants applied = Nonminority selection ratio

Adverse Impact: 80% or 4/5 Rule
Selection Ratio: Number of minority applicants selected DIVIDED BY Number of minority applicants applied = Minority selection ratio

Adverse Impact Compare the two selection ratios
If the ratio for nonminorities is smaller there may be evidence of discrimination If the ratio is less than 80% or 4/5 of the nonminority ratio, then there is evidence of adverse impact (because the difference in the ratios is statistically significant)

Adverse Impact - Example
100 White applicants 20 of the White applicants are selected 20:100 = .2 Nonminority Selection Ratio 100 African American applicants 5 of the African Americans are selected 5:100 = .05 Minority Selection Ratio .05 : .2 = .25 = 25% and does NOT meet the % rule! The minority selection ratio would have to be .16 to be 80% of the nonminority ratio

General Statistical Evidence for Discrimination
Stock Statistics # of women managers in org. DIVIDED BY # of skilled women managers in the work force Total # of managers in the org. Total # of skilled managers in the work force What is the relevant labor market? EEO 1 form

Landmark Selection Cases
Resulted in establishing burden of proof requirements

EEO Legislation - How effective?
EEO Laws clearly address societal problems --- safeguarding fair treatment in employment of traditionally disadvantaged groups. Hire the most qualified applicant -- the role and effect of stereotypes Internalization v Compliance

Review Statutory Laws Early Civil Rights Acts Equal Pay Act
Title VII of CRA 1964 Coverage Who is protected? How? Pregnancy Discrimination Act 1978

Review Exemptions: BFOQ, business necessity, seniority system, testing
Preferential Treatment and Reverse Discrimination Fetal Protection Sexual Harassment

Review BFOQ and SH Exercises/Scenarios Discrimination Cases
Two Readings SH and Torts

Measurement in Selection
Selection decisions are based on what information? Purpose is to ……..

Measurement in Selection
Selection decisions are based on what information? Need information about both: JD -> KSA’s required for the job Purpose is to match the individual and the job ?? -> KSA’s of the individual How can we mess up? Measure irrelevant KSA’s Measure KSA’s inaccurately

How can we “accurately” capture applicants’ KSA’s?
We must determine the type and level of KSA’s that applicants have. The assumption is that the higher the level of KSA’s, the higher will be the level of predicted performance. Level - Measurement - Quantification

Definition of Measurement
Application of rules for assigning numbers to objects to represent quantities of attributes. So that the differences between applicant scores are due to actual differences in KSA’s. Rules Specified algorithms to assign numbers (She is a 10) – same results by different users;

Attributes to be measured
Measurement Attributes to be measured Physical and psychological Examples Intangible ones must be inferred from indicants of these objects.

Measurement Criterion Predictors (KSAs)
Indicants of relevant attributes - predict criteria Must be important to the job (job related) Must be measures of attributes that are identified as critical to job success Criterion measure or definition of what is meant by employee success on the job; e.g., employee behaviors, attitudes, supervisor ratings

Measurement and Individual Differences
Measurement is prerequisite for any statistical analysis How precisely can we measure – can we detect small differences Classification of success as “yes” or “no” OR degree of success?? Scale Means by which individuals can be distinguished on a specific variable

Scales Nominal scale: Scale composed of mutually exclusive categories (sex, race, job class); the numbers are “labels”; only frequencies Ordinal scale: Ranks objects (hi, lo); differences between numbers yield additional information but not on the magnitude of the differences among ranks; e.g., percentile (represents the proportion of persons taking a test who made below a given score – 70th percentile means that 70% scored lower and 30% scored higher; does not tell how much higher and lower) Interval scale: Arbitrary – no absolute zero; interpretation of differences – 40 vs 80 points does not mean 2 times the level of skill; e.g., zero on a test for math skills does not mean that the individual has zero math skills Ratio scale: physical measures (height) and counting; has absolute zero.

Groups What are descriptive statistics? Purpose and examples?
Answer the following questions What are descriptive statistics? Purpose and examples? Why do we look at both – the mean and SD? What is a correlation? In Selection, what do we correlate? What does a correlation of.8 and a t-value of 7.44 tell us? What is a normal distribution? What is statistical significance – hypothesis testing?

Standardization of Selection Measures
Definition Selection Measure Systematic instrument, technique, or procedure for assigning scores to a characteristic or attribute of an individual Detect a true difference Standardized if Content – measures same information; Administration - information collected the same way; Scoring – rules for scoring are pre-specified Individual Differences Applying the scale, each applicant receives a score – how do we interpret the scores? What do they mean?

Central tendency Understand your data Mean
Mode – most often observed score Median – 50% of the scores are above and 50% are below this score

Frequency Distribution
Understand your data Frequency Distribution How many times did we get each score? First understanding of what our sample (applicant pool looks like) – did applicants tend to score higher or lower or are scores evenly distributed? Frequency distribution is a frame of reference to give meaning to scores. Most characteristics are normally distributed – bell curve! That means that most applicants score around average (have an average level of the characteristic, a few have more and a few have less).

Variation Understand your data
Mean of squares of the deviation scores (variance) depends on the extent to which scores cluster together The square root of the variance is the standard deviation – a large standard deviation means that the scores a widely spread around the mean, a small standard deviation means that the scores are clustered around the mean

Understand your data Histogram

Understand your data Frequency

Skewness Understand your data
Scores are symmetrically or asymmetrically distributed around the mean; If the scores are symmetrically distributed then the mean = median;

Understand your data The distribution is positively skewed if the mean is larger than the median; Negatively skewed if the mean is smaller than the median.

Skewness

Skewness A distribution is skewed if one of its tails is longer than the other. The first distribution shown has a positive skew. This means that it has a long tail in the positive direction. The distribution below it has a negative skew since it has a long tail in the negative direction.

Sample Data Applicant Test A Score (max 50) Test B Score (max 30) 1 30
26 2 18 14 3 35 15 4 27 10 5 25 6 42 7 21 8 9 47 20

Understand your data Descriptive Statistics Frequencies Mean Median
Mode Range SD =

Assignment #1 Purpose: Review of Statistical Concepts and Overview of Measurement Concepts Test A and Test B - measure the same KSA Type of Data Descriptive Statistics - Range A, Range B => SD for A compared to B Interval size for Test B and Test A Normally distributed test scores VS our test results Negatively or positively skewed? (32.5) Significance t-test and p-value

Stat Assignment #1 Descriptive Statistics
Two employment tests with scores for 10 employees Which test should be used? Which applicant should be hired? Determine the correlation between test scores and performance. The magnitude and significance of the correlation are used to determine which test should be used.

Are two variables related?
Correlation Meaning Range between and -1.00 r = ∑ZxZy) where ZX = Xi-mean SD N

Is this a chance relationship?
Statistical Significance Hypothesis Testing T-statistics

Understand your data Normal Distribution

Probability Distributions
In order to draw conclusions about the scores that applicants receive, we have to evaluate whether our results are statistically significant We want to make inferences (draw conclusions) from our sample about the population Statistical significant results are not random but are truly describing the population.

Probability Distributions
Probability distribution or probability density function – the normal distribution is a theoretical density function It is symmetric if: mean=mode=median Entire area under the curve = 1.00

Standardized normal distribution
mean = 0 and SD = 1 68% of the scores are within + and – 1 SD around the mean

Normal Distribution In selection we assume that most characteristics that we measure are normally distributed in the population – that means if we had an endless number of observations our frequency distribution would look like a normal curve This is important because evaluating the statistical significance of what we are interested in (hypotheses testing) is based on the assumption of a normal distribution.

Normal Distribution If we assume a normal distribution, we can calculate z-scores that means we can transform our raw scores (the score that the applicants received) into a score “on the normal curve” by deducting the mean from each raw score and dividing that number by the SD (this is called the Z score); So for each raw score, we get a z score that is important because we can now more easily calculate other statistics such as correlations

Hypothesis Testing In order to draw valid conclusions from our sample, we must show that our results are statistically significant and not random We would like to reject the null hypothesis which says that our results are not truly reflecting the population For example: We want to conclude that the correlation between test scores and performance that we calculated for our sample is “true” Null Hypothesis: rxy = 0 which means that there is no relationship between x (test scores) and y (performance score).

Hypothesis Testing If H0 is true (no relationship) but we reject it, we make a Type I error which would be bad and we want to avoid it; Therefore, we allow only a minimum level of error in rejecting the H0 (traditionally .05 or .01 – this is your alpha level). Based on the observed correlation and the number of observations in our sample, we calculate a t-statistic. We then find the corresponding values, based on the sample size and the alpha level in the table for the t-distribution. t= rxx If our obtained t-value is larger than the value in the table then our result is significant and we can reject the notion that there is not really a relationship between the two variables.

p-Value p-value for a sample outcome is the probability that the sample outcome could have been more extreme than the observed one Large p-values support H0 while small p-values support the alternative hypothesis. Compare the p-value to the specified alpha risk. If p < alpha then conclude H1 (significance)

Tests and Reference Sources
Buros’s Mental Measurement Yearbooks The Mental Measurement Yearbooks Database Journals

Review How do we evaluate whether two variables are related to each other? Why and how do we determine whether our result is statistically significant? Why do we need to evaluate the quality of our measures? What does it mean when a measure is reliable? Using the test-retest method, how do we assess whether a measure is reliable? What does a p-value of .02 imply?

Overlapping Normalcurves
Compare the means

Quality of Measures - Reliability
How well does my test measure KSAs? The scores obtained on a measure are X obtained = X true + X error If there was no error in the measure, every time we apply the measure to the same person, we should get the same score. A reliable measure is a consistent measure. The reliability of a measure reflects the measures consistency.

Reliability Three methods to evaluate the reliability of a measure
Each method focuses on a different source of measurement error. Measurement error are those factors that impact the obtained score but are not at all related to the attribute that is being measured. The methods Test-Retest Reliability Parallel or Equivalent Forms Reliability Internal Consistency Reliability Split-Half and Odd-Even; Cronbach Alpha Spearman-Brown Adjustment

Spearman-Brown Formula to Correct a Split-Half Reliability Coefficient

Reliability of an Interview
Inter-rater Reliability

Reliability The conclusion that a measure is reliable
can only be drawn if, and only if, the reliability coefficient (a correlation coefficient) is statistically significant (as determined by a t-test).

Reliability Interpretation of the reliability coefficient
The reliability coefficient is equal to the correlation coefficient between the obtained and the true score squared page 141 Acceptable magnitude of reliability The standard error of measurement - is the amount of error to be expected in an individual’s score. We calculate the standard error of measurement as the SD of the sample multiplied by the square root of 1 minus the reliability coefficient

Standard Error of Measurement

Standard Error of Measurement
Important The difference in the scores between two applicants is only significant if it is at least two times the standard error of measurement. Example The standard error of measurement for a test is 1.5. Candidate A scores 18, candidate B scores 24. Does candidate B really have more of the attribute that is being measured?

Assignment #1 Hire #9, score 47
Purpose: Review of Statistical Concepts and Overview of Measurement Concepts Test A (Minnesota Clerical 50) and Test B (Purdue Clerical Aptitude 30) - measure the same KSA: Clerical Skills Type of Data Descriptive Statistics Understand your data Interval size (5 groups) for Test B (10-27) and Test A (18-47) – Histogram Normally distributed test scores VS our test results Negatively or positively skewed? Relationship to performance Test A – correlation .9 t*=7.44 alpha .01 (N=15; 2.65) Test B – correlation .55 t*=2.41 alpha .05 (N=15; 1.77) Hire #9, score 47

Assignment #2 Service Repair Technician
Reliability of written test and interviews Reliability of written test: Test - Re-test – Reliability coefficient Magnitude Significance Internal Consistency - Split Half Reliability of interviews (Interrater reliability coefficients – evaluate magnitude and significance): Supervisor wit technician at .05 Screening with supervisor – lowest .32 and NS Screening with technician at .05 SEM - which candidate to choose – Confidence intervals .05 – overlap – 2 times SEM? F=94; G=91

Quality of Measures - Validity
Validity in Selection concerns the following question: How appropriate is it to make inferences from the scores on a measure to performance? Is the score a good predictor of performance? Is the score actually related to future performance? Relationship between reliability and validity

Quantitative Relationship between Validity and Reliability

Validity Three methods to evaluate the validity of a measure.
Content Validity Construct Validity Criterion-Related (Empirical) Validity Predictive Validity Concurrent Validity

Major Steps in Conducting Concurrent Validation Studies
Conduct analyses of the job Determine relevant KSAs and other characteristics required to perform the job successfully Choose or develop the experimental predictors of these KSAs.

Major Steps in Conducting Concurrent Validation Studies
Select criteria of job success Administer predictors to current employees and collect criterion data Analyze predictor and criterion data

Major Steps in Conducting Predictive Validation Studies
Conduct Analyses of the job Determine relevant KSAs and other characteristics required to perform the job successfully Choose or develop the experimental predictors of these KSAs.

Major Steps in Conducting Predictive Validation Studies
Select criteria of job success Administer predictors to job applicants and file results After passage of a suitable period of time, collect criterion data Analyze predictor and criterion data

Requirements for a Criterion-Related Validation Study
The job should be reasonably stable and not in a period of change or transition A relevant, reliable criterion that is free from contamination must be available or feasible to develop

Requirements for a Criterion-Related Validation Study
It must be possible to base the validation study on a sample of people and jobs that is representative of people and jobs to which the results will be generalized A large enough sample of people on whom both predictor and criterion data have been collected must be available

Content versus Face Validity
Content Validity deals with the representative sampling of the content domain of a job by a selection measure Face Validity concerns the appearance of whether a measure is measuring what is intended

Strategies for Selection Decision-Making
How to transform DATA into relevant information Data Collection Data Combination Judgmental and Mechanical Methods Selection Decision-Making Strategies Multiple Regression - Compensatory Model Multiple Hurdle Combination Profile Matching

Regression Analysis Y = f(X) - linear relationship
Collect data on X and Y Scatterplot Estimate the equation that describes the linear relationship between X and Y Estimate in such a way so that the predictions that are made for Y (based on X using the equation) contain a minimal amount of error Least Squares Estimates beta = regression coefficient The equation for estimation is Y = beta0 +beta1X1

Example Assignment #3 - Multiple Regression
Empirical Weights for Selection Devices X1 = Mechanical Ability Test X2 = Supervisor Interview X3 = Technician Interview X4 = Initial Screening Interview Y = beta + beta1 X1 + beta2 X2+beta3 X3 +beta4 X4 The weights reflect the extent to which each selection device contributes to explaining performance Question: Is a compensatory model what we want?

Assignment #3 Validation of several selection devices and interpretation and use of validity information Magnitude and Significance Variation explained Validity Coefficient for each predictor Mechanical ability test .76 Validity coefficient squared indicates how much of the variation in performance is explained by this predictor alone: .58% (.76*.76) Reliability: Best was mechanical ability test, then technician interview

Major Steps for Implementing a Construct Validation Study
The construct must be carefully defined and hypotheses formed concerning the relationships between the constructs and other variables A measure hypothesized to assess the construct is developed

Major Steps for Implementing a Construct Validation Study
Studies testing the hypothesized relationships between the construct measured and other, relevant variables are conducted.

Major Factors Affecting the Size of Validity Coefficients
Reliability of Criterion and Predictor Restriction of Range Criterion Contamination

Validity Interpretation of Validity Coefficients
Magnitude and Significance Cross-validation Correction for attenuation Correction for Restriction of Range Criterion Contamination

Utility Analysis Using dollar-and-cents terms as well as other measures such as percentage increase in output, it shows the degree to which the use of a selection measure improves the quality of individuals selected over what would have happened if the measure had not been used.

An Equation for Calculating the Utility of a Selection Program
Expected Dollar Gain from Selection= NsrxySDyZx-NT(C) Expected Dollar Gain from Selection=return in dollars to the organization for having a valid selection program

Ns=number of job applicants selected rxy=validity coefficient of the selection procedure SDy=standard deviation of job performance in dollars

Zx=average score on the selection procedure of those hired expressed in z or standardized score form as compared to the applicant pool NT=number of applicants assessed with the selection procedure C=cost of assessing each job applicant with the selection procedure

Customer Service Skills Test

Key Elements of Implementing a Content Validity Strategy
Conduct a comprehensive job analysis Selection of experts participating in a content validity study – SME’s (subject matter expert) Specification of selection measure content Assessment of selection measure and job content relevance

Content Validity Task List – Relative importance
KSA List – Relative importance KSA x Task Matrix Linkages – Strength Predictors Predictor x KSA Matrix Predictor Weights Integration of predictors

=> KSA Requirements Measures for KSA’s Content Validity??
Example -- Server JA => Tasks => KSA Requirements Measures for KSA’s Content Validity?? Selection Procedure

WRIPAC – Content Validation
Predict performance in Selection class Tasks? KSAs? Task x KSA Linkages? Predictors? Predictor x KSA Linkages? Selection Process

Designing a Selection Procedure
Job Analysis Identification of relevant job performance dimensions Identification of KSA’s necessary for the job Development of assessment devices to measure KSA’s Assessing the quality of the assessment devices - reliability and validity Use of assessment devices

JA Reading What is JA? Define!

Selection Methods Introduction
For each method To measure which KSA’s/Design Adverse Impact Validity

Application Forms and Resumes
Introduction Information about the applicant’s background and present status -- brief and general OR long and detailed?? Based on .. Past behavior is a good predictor of future behavior To determine … minimum qualifications and general suitability for job; permanent record; Determine relative strengths and weaknesses It is assumed that all data collected are used Training and Experience Requirements Job-related training - formal and informal Type of training; length; quality

Careful with degree requirements
Application Form …. Careful with degree requirements Why? Certification requirements

Application Blank Specific job-related experience and accomplishments
Minimum qualifications Maintained Filing System: YES NO Used computer and Microsoft Word TE Evaluation Form Specific tasks are listed – indicate YES NO For YES, describe experience

Application Blank Methods for collecting TE evaluation info
Holistic – general judgment about suitability p.433 Point Method – A priori scale p.435 Behavioral Consistency Method – Description of job behavior by ER and applicant p. 439

Application Blank Likely candidate for Adverse Impact -- Why?
Current forms % had at least 1 inappropriate question; on average 7 inappropriate questions. Are these questions acceptable? What do you really want to know? What was your maiden name? What is your date of birth? What is your age? What is your height and weight? What language do you commonly use? What is your religious faith? List the number and ages of your children? Do you have any physical or mental disabilites? List your birthplace. Have you ever been arrested? Do you own your car/residence?

Application Forms ... Adverse Impact: High Validity: On average .1
Select content Job-related - Job-related language Usefulness Fairness -- Face Validity

Validity of T&E Evaluation Methods (Schmidt and Hunter, 1998)

References and Recommendations
To verify information Issues Assess applicant’s job experience Assess applicant’s effectiveness in those jobs -- what done and how well?? Types of info received p.446

References Not appropriate to assess personality ..
Sources of and methods to collect Reference Data Methods: In-person; Mail p.448; Letter of R; Phone Sources: Former ER; Personal; Investigative agencies; Public record; Usefulness of reference data Reliability: .4 or less Validity: Reference giver-better if immediate supervisor Old and new jobs are very similar? Adverse Impact ??

References .. Validity -- not much evidence -- favorable info -- job related better if content of the new and old job are very similar low validity because low reliability and restricted range Recommendations Don’t use subjective info written consent by applicant ask only specific job-related info Development of reference checking system Guidelines for defensible references page 426 and 427

Application, resume, references
Design – Purpose Which KSA’s? Recommendations Adverse Impact? Validity?

WAB Choose criterion Sample size
As many predictors of HR outcomes as possible Regression => weights for items AI but can show validity

Questions about personal background and life experiences Why?
BIO Data Questions about personal background and life experiences Why?

BIO Data Past behavior=> Future behavior ACT
Autobiographical questions: academic achievement, work attitudes, self-perception, feelings, values, educational experiences, hobbies, family relations, use of leisure time, early work experiences -- focus on motivation??

BIO Data Enhances info in AB Types of BIO data items
Hard vs soft p.487 Response type p.486

BIO Data BIO data are good predictors of job success (validity) and have less adverse impact on minorities than do many traditional tests; Face validity??? –

BIO Data Include as one of several predictors
Criteria: tenure; performance in training; performance ratings; productivity Mean validity coeff: .35; Engineering .41; clerical .52; management .38; sales .5 Must be based on JA and must be empirically scored; reliable and accurate if verifiable

Developing BIO Data STEPS IN CONSTRUCTION Selecting a Job
Analyzing the Job and Defining the Criterion Life History Domain Forming Hypotheses of Life History Experiences Developing a Pool of Biodata Items Prescreening and Pilot-Testing Biodata Items

Develop BIO Data for Professor in HR
?

=> KSA Requirements Measures for KSA’s Content Validity??
Developing a Selection Procedure: Selection Process for Logistics Professor JA => Tasks => KSA Requirements Measures for KSA’s Content Validity?? Selection Procedure

Recent Study on Biodata
Personnel Psychology Volume 35 Issue 1, Pages 1 - 62 Published Online: 7 Dec 2006 VALIDITY AND FAIRNESS OF SOME ALTERNATIVE EMPLOYEE SELECTION PROCEDURES RICHARD R. REILLY 1 GEORGIA T. CHAO 2 1 American Telephone & Telegraph Co. 2 Pennsylvania State University ABSTRACT Despite extensive evidence that tests are valid for employee selection, Federal Guidelines have urged employers to seek alternative selection procedures that are equally valid but have less adverse impact on minorities. Research on the validity, adverse impact and fairness of eight categories of alternatives was reviewed. Feasibility of operational use of each type of alternative in an employment setting was also discussed. Only biodata and peer evaluation were supported as having validities substantially equal to those for standardized tests. Previous reviews and more recent research indicated that interviews, self-assessments, reference checks, academic achievement, expert judgment and projective techniques had levels of validity generally below those reported for tests. Data, where available, offered no clear indication that any of the alternatives met the criterion of having equal validity with less adverse impact. Results are discussed and several additional promising alternatives are described.

Employment Interview KSA’s to be measured Validity Adverse Impact

Characteristics and Purposed of the Selection Interview:
Employment Interview Characteristics and Purposed of the Selection Interview: Dialogue, Gather information Evaluate qualifications Selection interview: varies in type content

Employment Interview Problems with the interview
lacks standardization in questions and evaluation is not focused is worker rather than job-content oriented requires the interviewer to fulfill multiple functions Interviews involve cognitive and social processes Information processing and decision-making Interpersonal influences

Employment Interview Research
Interview does not add to selecting the most qualified candidate … because…..

Interview Sources of problems impression formation human perception

Interview Information processing and decision-making observe behaviors
attribute to traits impressions about applicant depend on interviewer’s knowledge structure, a priori beliefs, recall of information E.g.: High GPA = Diligence, hard work; Competitive sport = Aggressiveness; PA = Social Skills

Improve the Validity of the Interview
Decide on location and seating More than one interviewer – Panel KSA’s to be measured: interpersonal, communication skills Job-related questions only - Multiple Questions (Behavioral) Limit pre-interview info Semi-structure Use a rating format Train the interviewer

Interview Simulation Relevant Tasks
Relevant KSA’s - combine into categories or dimensions KSA’s to be measure in the interview Linkage between Question and KSA Quality of Questions Interview Structure/ Process - 1. Measure interpersonal, communication skills 2. Job-related questions only - Multiple Questions (Behavioral) 3. Limit pre-interview info 4. Use a panel 5. Use a rating format 6. Train the interviewer 7. Semi-structure

Interviewers Interviewee
Interview Role Play * Interview Process? Non-verbals? Bias? * What KSAs are being measured? * To what extent does the applicant possess the required KSAs? Interviewers Interviewee Drew, Adrian, Kevin Addie Amanda, Stacey, Andrew Sammy

Physical Attractiveness
What do you think??

Introduction Review the role of physical attractiveness in employment selection. Physical attractiveness is more salient during periods of impression formation such as selection.

Definition of Attractiveness
Physical features Hair Nose The degree to which one’s facial image elicits favorable reactions from others High reliability

Impact of Attractiveness
Attractive people have positive traits Less attractive people have less positive traits Attractive applicants are perceived to be more qualified for employment Organizations retain employees high in attractiveness and ability

Relationship between sex and physical attractiveness
Women are evaluated more than men Gender-linked bias May have impact on equal employment opportunity

Job Related Factors Type of job PA is generally an asset for men
Male applicants are preferred for masculine occupations Female applicants are preferred for feminine occupations PA is generally an asset for men PA might be a handicap for women depending on a types of jobs

Physical Attractiveness vs. Age Discrimination
Older applicants are judged as less attractive as younger applicants Preference for the young is surrogate preference for the young Three negative explanations: Older workers are less effective Young hires = better return on investment Preference for the PA

Race vs. Physical Attractiveness
No attention has been directed to race PA interactions Based on other research: PA blacks are more desirable dates and essay writers No real understanding if stereotype extends to non-white applicants Performance ratings are affected by the race of the rater

Conceptual and methodological problems in Physical Attractiveness research
Restriction in range in the measurement Control vs. generalizability Normative biases Magnitude of the physical attractiveness bias

Implications for the Study of Physical Attractiveness
Physical Attractiveness is related to some types of decisions Some crucial questions in regards to the relative magnitude of PA bias Whether it functions differentially for women as compared to men Whites as compared to nonwhites Whether age is a surrogate for PA

Ability Testing Testing – Definition Types of tests Job Relatedness
Mental Ability Tests - Wonderlic Mechanical Ability Tests - Bennett and McQuarrie Physical Ability Integrity Tests Clerical Ability – Minnesota Test Job Relatedness Adverse Impact Validity

Personality Assessment
Methods - Design Job Relatedness Adverse Impact Validity

Personality Personality refers to a person’s unique and relatively stable pattern of thoughts, feelings, and actions Personality is an interaction between biology and environment Genetic studies suggest heritability of personality Other studies suggest learned components of personality

Measures of Personality
Interviews Unstructured: “Tell me about yourself…” Structured: Set list of questions Observation: Psychologist learns about personality by observing the person Objective tests: Self-inventories that involve paper and pencil tests Projective tests: Subjects reveal aspects of their personality when they talk about ambiguous stimuli

Projective Tests Projection is an idea developed by Freud in which people are thought to reveal their true feelings and thoughts when describing ambiguous stimuli A projective test presents a series of ambiguous stimuli and asks that a subject describe each stimulus The idea is that their verbal descriptions will reveal key aspects of their personality

Specific Projective Tests
Rorschach Test Consists of 10 inkblots Reliability and validity of this test is low Thematic Apperception Test (TAT) TAT also consists of a series of ambiguous figures

Personality Measurement Issues
Objective self-report personality tests can be criticized on the basis of Deliberate deception and social desirability bias Can the test detect deception and attempts to enhance social desirability? Diagnostic difficulties: the test may not be sufficiently specific to allow for diagnosis Inappropriate use: when tests are used for purposes other than their designed use

Personality Traits Traits are relatively stable and consistent personal characteristics Trait personality theories suggest that a person can be described on the basis of some number of personality traits Allport identified some 4,500 traits Cattel used factor analysis to identify basic traits Eysenck argued there are distinct traits in personality Extraversion/introversion Neuroticism

The “Big 5” Modern personality research argues for 5 basic personality traits (OCEAN) Openness: whether a person is open to new experiences Conscientiousness: whether a person is disciplined and responsible Extroversion: whether a person is sociable, outgoing and affectionate Agreeableness: whether a person is cooperative, trusting, and helpful Neuroticism/Emotional Stability: whether a person is unstable and prone to insecurity

Overview of the Big “5”

Myers – Briggs Type Indicator
Temperament Theory 16 Personality Types

Four Dimensions of Personality Type
How we interact with the world and where we direct our energy (E/I) The kind of information we naturally notice (S/N) How we make decisions (T/F) Whether we prefer to live in a more structured way or a more spontaneous way (J/P)

E I Extraversion Introversion Interest Orientation
Outer world of actions, objects, and people Inner world of ideas and concepts

S N Sensing iNtuition Perception
Immediate reality and direct experience Inferred meanings and relationships

T F Thinking Feeling Judgment
Reliability of logical order – cause and effect Priorities based on personal importance and values

J P Judgment Perception Environment Orientation
Judging attitude – Control of events and systematic planning Spontaneity – Curious, awaiting events and adapting to them

Myers Briggs Dimensions of Temperament
Extraversion / Introversion Where do you get your energy - what “charges your batteries” . Sensing / Intuition How do you gather information. Present / future, practical / imaginative, details / patterns, sequential / random Thinking / Feeling How do you make decisions ? Thinking/feeling, laws/circumstances, justice/mercy Judgment / Perception How do you organize your environment Planned / open ended, control / adapt, resolved / pending

ISTJ ISFJ INFJ INTJ ISTP ISFP INFP INTP ESTP ESFP ENFP ENTP ESTJ ESFJ
“Take Your Time and Do It Right” ISFJ “On My Honor, to Do My Duty…” INFJ “Catalyst for Positive Change” INTJ “Competence + Independence = Perfection” ISTP “Doing the Best I Can With What I’ve Got” ISFP “It’s the Thought That Counts” INFP “Still Waters Run Deep” INTP “Ingenious Problem Solvers” ESTP “Let’s Get Busy!” ESFP “Don’t Worry, Be Happy” ENFP “Anything’s Possible” ENTP “Life’s Entrepreneurs” ESTJ “Taking Care of Business” ESFJ “What Can I Do For You?” ENFJ “The Public Relations Specialist” ENTJ “Everything’s Fine – I’m in Charge”

emotions toward others and the world-at-large
Expressiveness The outward display of emotions toward others and the world-at-large First-third Quiet Alone 0-33 percentile Second-third Reserved Spontaneous 34-66 percentile Third-third Gregarious Performer percentile ©EMERGENETICS, LLC

Easy Going Competitive
Assertiveness The degree of energy invested in expressing thoughts, beliefs and feelings First-third Peacekeeper Amiable 0-33 percentile Second-third Easy Going Competitive 33-66 percentile Third-third Driving Telling percentile ©EMERGENETICS, LLC

accommodate the thoughts
Flexibility The willingness to accommodate the thoughts and actions of others Likes defined situations Likes control 0-33 percentile First-third Second-third Strong Opinions Likes different point of view 34-66 percentile Likes ambiguity percentile Puts others’ needs before self Third-third ©EMERGENETICS, LLC

Emotional Intelligence
I/O psychologists have long been interested in the relationship between intelligence and success within the work environment In addition to the KSAs traditionally associated with task performance, success in today’s organizations may require a more personal configuration of individual competencies

Emotional Intelligence (cont.)
Competencies - the recognition, regulation, and expression of moods is currently receiving considerable attention These competencies may be subsumed under the rubric of Emotional Intelligence (EI)

What is Emotional Intelligence?
The ability to perceive accurately, appraise and express emotion The ability to access and/or generate feelings when they facilitate thought The ability to understand emotion and emotional knowledge The ability to regulate emotions to promote emotional and intellectual growth.

Goleman’s theory is specific to the domain of work performance Working with Emotional Intelligence (1998)

Goleman further separates his theory from that of others by asserting that EI competencies can be learned and emphasizes that the identification of these competencies can be used to predict work performance across a wide variety of organizational settings

Elements of Emotional Intelligence
Self-Awareness Self-Management Social Awareness Relationship Management

Elements of Emotional Intelligence (cont.)
The elements of EI can be categorized under two sets of competencies: Personal Competencies Social Competencies

Personal Competencies: Self-Awareness: knowing one’s internal states, preferences, resources, and intuitions Self-Management: managing one’s internal states, impulses, and resources Motivation: emotional tendencies that guide or facilitate reaching goals

Social Competencies: Empathy: awareness of others’ feelings, needs, and concerns Social Skills: adeptness at inducing desirable responses in others

EI So What?

Emotional Intelligence in the Workplace
The Emotional Competence Inventory 2.0 (ECI 2.0) assesses EI of individuals and organizations

Supporting Research Applicants scoring high on EI were more likely to be considered for employment (Maynard, 2003) High EQ (EI) is a predictor of job success and high performance (Fox, 2000) Positive correlation between a high EQ and Organizational Commitment and Organizational Citizenship Behaviors (OCB - Nikolaou & Tsaousis, 2002) Negative correlation between a high EQ and reported level of stress at work (Nikolaou & Tsaousis, 2002)

Implications for HR Professionals
Individuals with low EQ scores are more likely to respond negatively to aversive work events Decreased productivity Health concerns

Integrity and Drug Tests
Purpose Measurement Conditions and Issues

Selection Project CONTENT VALIDITY Job Analysis Matrices - Linkages
Empirical Validation Face Validity Job Analysis Matrices - Linkages KSA Measures - Appropriateness, Design Report - Completeness

Specific Jobs - Examples

The No-Asshole Rule and Blink
Questions for No Asshole Rule (Robert Sutton): What is the No asshole rule about? Describe the behaviors that characterize an AH. Explain how such behaviors can be detrimental to creating a productive workplace. From a practical perspective, what advice does Sutton give for the implementation of the no AH rule? What are the implications for employee selection of the no AH rule? Be specific. Make a list of “to do’s” for your classmates of how to deal with Ahs in the workplace.

The No-Asshole Rule and Blink
Questions for blink (Daniel Goleman): What is blink about? How can thinking that takes place so quickly be at all useful? Don't we make the best decisions when we take the time to carefully evaluate all available and relevant information? Relate the ideas presented in "blink" to the material that we covered in class. Does "blink" talk about when rapid cognition goes awry? Explain. What do you take away from "blink"? How will you apply what you have learned?

Individual effectiveness = f(Ability,Motivation) Performance = Ability * Motivation

What we have learned HR and Organizational Effectiveness
HRM and Employee Selection External Environment Principles Specific Methods

HR and Org. Effectiveness
Match Individuals (Knowledge, Skills, Abilities) with Jobs (Requirements and Rewards)

The HRM Framework

Selection Definition - Selection
The process of obtaining and using information about job applicants to determine who should be hired. Focus here is on how to collect relevant info on applicants’ KSA’s. Final decision must be accurate and fair.

Course Summary External Environment
The Labor Market – Generational Differences Legal Environment Principles of Selection - Measurement What do we measure? Quality of Measures Reliability Validity Selection Methods - Which KSA’s? Design? Adverse Impact? Validity Application Blank/T&E/Bio Data/References Employment Interview Ability Tests Personality

Readings Dealing with Sexual Harassment in the Workplace
Tort Law - Legal Trends: The Risk of Intentional Torts Too Good to Hire The Interview: Expecting A Quick Decision Physical Attractiveness and Selection Decision Making Employee Selection: Will Intelligence and Conscientiousness do the Job They don’t do it often but they do it well Elusive Criterion of Fit in Human Resources Staffing Decisions Seven common misconceptions about human resource practices HR Professionals’ Beliefs/Knowledge of Assessment Techniques Use of graphology International look at selection

Employee Selection THE END

Advanced Topics in HR Employee Selection and Staffing

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