the predictors of performance
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The Predictors of Performance
August 3, 2011
ERE.net
Paul Basile, CEO Matchpoint Careers, Inc paul.basile@matchpointcareers.com
Introductions
2
POLL: who are we?
• In-house talent acquisition specialist • Talent management specialist • HR generalist • Professional recruiter • None of the above
Our agenda • Why performance prediction matters • What predicts performance • How to measure those predictors • Results
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Every hire is a prediction
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The impact of predicting performance in hiring
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Perf
orm
ance
pre
dict
ive
sele
ctio
n cr
iterio
n
Job performance
False negatives
True positives
False positives
True negatives
Predicting performance – the gain • ≈2/3 of the market value of the S&P 500 is driven by
intangible assets, primarily people • Top performing employees are:
– 40% more productive in operational roles – 46% more productive in management – 67% more productive in sales
“People are not your most important asset. The right people are.”
– Jim Collins, Good to Great
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Predicting performance – the gain
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Top 15% of performers
Bottom 15% of performers
Minus 40% Plus 40%
$48,000 $80,000 $112,000
“With recruiting costs, salary, benefits, bonus, and training costs, along with overhead, regular pay increases, and normal tenure expectations, it’s not hard to view any six-figure hire as a million-dollar investment.”
– David Jones, Million Dollar Hire
Predicting performance – avoiding pain
• 85% of applicants are unfit for the job
• 55% of employees are dissatisfied with their job
• 46% of new hires leave within 18 months
• 30% of business failures are due to poor hiring decisions
8
What predicts performance?
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The research
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0
-0.1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Cognitive ability tests (0.51)
Cognitive ability tests with behavioral assessment (0.67)
Knowledge of the job (0.48)
References (0.36)
Unstructured interviews (0.18)
Years of education (0.10) Years of job experience (0.18)
Graphology (0.02)
Age (-0.1)
Weakly predictive
Somewhat predictive
Powerfully predictive
Personality tests (0.40)
Correlation coefficient
Adapted from I. Robinson and M. Smith, Personnel Selection (2001) British
Psychological Society
Structured interviews (0.51)
Baselines and differentiators
11
Employee performance
Baselines • Skills • Knowledge
Differentiators • Cognitive ability • Behavior • Preferences
Baselines • Knowledge
– eg. Law degree, plumbing course, programming languages – Learnable – Often come from formal education
• Skills – Technical abilities – Learnable – Often come from experience
Higher knowledge and/or skills do not equate to higher
quality hire
12
Differentiators • Cognitive ability • Behaviors
– Apply to all roles, in different combinations – Relatively stable over time for an individual – Strongest reliable predictors of human performance
• Preferences – Different for each individual, and can change over time – Account for around 26% of engagement, 12% of
performance and 26% of managerial potential
Are higher competency and preference levels linked to superior work performance? Yes, but…
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Competencies
Fit for purpose • Similar roles make similar demands… • …but every organization is different
– Different competencies and preferences – Different levels of individual competencies and preferences
• Need for tailoring by role and by organizational context
Fit, not absolute score, predicts performance
14
Example: Project Oxygen
15
Example: Project Oxygen
Technical ability the least important success factor
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Measuring performance predictors • Gather data
– Predictors of superior performance in the specific job – Candidate profiles
• Compare job and person • Hire and place
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Gathering data • Consistently
• Objectively
• Fit for purpose
• Timely
• Cost-effectively
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Gathering data: the job • Need to assess baseline and
differentiating requirements and job context
• Groundwork done by consultants & psychologists
• Established, validated methodologies & normed reference databases
• Used to be expensive & time consuming…
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Gathering data: the job
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Gathering data: candidate skills & knowledge • Thousands of different skills • Accurate, skill-specific
assessments exist (many online) • Skill testing usually quick and
reliable • Usually assessed at relatively
early stage
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Gathering data: candidate skills & knowledge
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Gathering data – candidate competencies
Psychologist interview
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Psychologist interview
Observation at work
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Gathering data – candidate competencies
Psychologist interview
Observation at work
Psychometric tests
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Gathering data – candidate competencies
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Gathering data – candidate competencies
Gathering data: candidate preferences • Good tools exist, but.. • Too few are specific to work • Too few tools are online • Often undervalued and
underused despite dramatic impact of employee engagement on results
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Gathering data: candidate preferences
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Gathering data: timing
Application forms / résumés
Interviews / other assessments
Psychometric assessments
Traditional recruitment pipeline
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Gathering data: timing
Application forms / résumés
Interviews / other assessments
Psychometric assessments
Self-selection, employer-specific assessments
Interviews / other assessments
Psychometric assessments
Performance-predicting recruitment pipeline
Traditional recruitment pipeline
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Compare
Job
Candidates
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Compare
Job
Candidates
Rank shortlist 32
Compare
Job
Candidates
Rank shortlist
Hire
33
Effective comparison • Demonstrates objectivity and consistency • Is validated against performance • Scalable and cost-effective • Easy for recruiter • Delivers results quickly • Gives practical inputs to final selection
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Example: effective comparison
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Hire and place Performance predictors: • Guide final selection
– Focus structured interviews – Define additional assessment requirements
• Inform talent management & career planning – Baseline for development – Can be matched to job families & career paths – Can be used to assess talent bench strength
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Results
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Companies that use scientific performance prediction, compared to those who don’t, have:
• 75% greater year-on-year increase in hiring manager satisfaction
• 75% greater yr-on-yr reduction in hiring costs • 2.5 x greater year-on-year increase in profit per
employee
Thank you
Paul Basile
paul.basile@matchpointcareers.com
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