the predictors of performance

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The Predictors of Performance August 3, 2011 ERE.net Paul Basile, CEO Matchpoint Careers, Inc [email protected]

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ERE Webinar from 8/3/11, presented by Paul Basile.

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Page 1: The Predictors of Performance

The Predictors of Performance

August 3, 2011

ERE.net

Paul Basile, CEO Matchpoint Careers, Inc [email protected]

Page 2: The Predictors of Performance

Introductions

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POLL: who are we?

•  In-house talent acquisition specialist •  Talent management specialist •  HR generalist •  Professional recruiter •  None of the above

Page 3: The Predictors of Performance

Our agenda •  Why performance prediction matters •  What predicts performance •  How to measure those predictors •  Results

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Page 4: The Predictors of Performance

Every hire is a prediction

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Page 5: The Predictors of Performance

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

Page 6: The Predictors of Performance

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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Page 7: The Predictors of Performance

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

Page 8: The Predictors of Performance

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

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Page 9: The Predictors of Performance

What predicts performance?

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Page 10: The Predictors of Performance

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)

Page 11: The Predictors of Performance

Baselines and differentiators

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Employee performance

Baselines •  Skills •  Knowledge

Differentiators •  Cognitive ability •  Behavior •  Preferences

Page 12: The Predictors of Performance

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

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Page 13: The Predictors of Performance

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

Page 14: The Predictors of Performance

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

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Page 15: The Predictors of Performance

Example: Project Oxygen

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Page 16: The Predictors of Performance

Example: Project Oxygen

Technical ability the least important success factor

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Page 17: The Predictors of Performance

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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Page 18: The Predictors of Performance

Gathering data •  Consistently

•  Objectively

•  Fit for purpose

•  Timely

•  Cost-effectively

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Page 19: The Predictors of Performance

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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Page 20: The Predictors of Performance

Gathering data: the job

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Page 21: The Predictors of Performance

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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Page 22: The Predictors of Performance

Gathering data: candidate skills & knowledge

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Page 23: The Predictors of Performance

Gathering data – candidate competencies

Psychologist interview

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Page 24: The Predictors of Performance

Psychologist interview

Observation at work

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Gathering data – candidate competencies

Page 25: The Predictors of Performance

Psychologist interview

Observation at work

Psychometric tests

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Gathering data – candidate competencies

Page 26: The Predictors of Performance

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Gathering data – candidate competencies

Page 27: The Predictors of Performance

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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Page 28: The Predictors of Performance

Gathering data: candidate preferences

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Page 29: The Predictors of Performance

Gathering data: timing

Application forms / résumés

Interviews / other assessments

Psychometric assessments

Traditional recruitment pipeline

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Page 30: The Predictors of Performance

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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Page 31: The Predictors of Performance

Compare

Job

Candidates

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Page 32: The Predictors of Performance

Compare

Job

Candidates

Rank shortlist 32  

Page 33: The Predictors of Performance

Compare

Job

Candidates

Rank shortlist

Hire

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Page 34: The Predictors of Performance

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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Page 35: The Predictors of Performance

Example: effective comparison

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Page 36: The Predictors of Performance

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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Page 37: The Predictors of Performance

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

Page 38: The Predictors of Performance

Thank you

Paul Basile

[email protected]

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