Why you shouldn’t fear assessments
April 25, 2012
Paul Basile, CEO Matchpoint Careers, Inc [email protected]
POLL
What is most important? What do you think about?
• My family • Sports • Religion • My work • Other
What’s an assessment?
Face the fear!
Why assess at all?
What are we frightened of?
Fear 1: Being exposed
Fear 2: Being judged
Fear 3: Messing up
Fear 4: Being messed around
Fear 5: Wasting time, money & effort
Can we get past the fear?
Beating the fear of exposure
• Truth as an enabler, not a punishment
• Bias towards good news • Privacy protection • Contrast with other recruitment /
information getting methods
Beating the fear of being judged
• Let the candidate control access • Emphasize fit, not results • Don’t share assessment results
directly • Show the fair and valid basis for
assessment
Beating the fear of messing up
• Clear instructions • Practice questions • Emphasize no wrong answers • Reassuring UX • Sensitive feedback
Beating the fear of being messed around
• Demonstrate fairness in process and results
• Share basis for assessments and research validity
• Show benefits before, during and after assessment
• Have a user-friendly, transparent process
Beating the fear of wasting time, $,effort
• Make the results count • Ipsative assessment where
possible • Use innovative value pricing • Core assessments for all,
extras for shortlist • Emphasize how short 1hr /
20 minutes really is
Fear-free assessment • Use serious assessments • Focus on fit • Use highly user-friendly test platforms • Make everyone a winner • Emphasize intrinsic rewards
The science of long-term relationships
eHarmony: • Uses science, research into thousands of married
couples • Has identified 29 dimension of compatibility • Recognizes that it is very hard a person to find and
identify the few people who are deeply compatible • Has 20 million members • Is not for getting a date… • Generates nearly 5% of all new marriages in the US
The science of humanity
Research into performance prediction
0
-0.1
0.1
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0.7 Correlation coefficient
Weak predictors
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-0.1
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Unstructured interviews (0.18)
Years of education (0.10) Years of job experience (0.18)
Graphology (0.02)
Age (-0.1)
Weakly predictive
Correlation coefficient
Medium predictors
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-0.1
0.1
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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
Personality tests (0.40)
Correlation coefficient
Fit (0.26)
Strong predictors
0
-0.1
0.1
0.2
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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
Structured interviews (0.51)
Fit (0.26)
Powerful predictors
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
Structured interviews (0.51)
Fit (0.26)
Measure what predicts job performance
Competencies
Skills
Work
preferences
Baselines and differentiators
27
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
28
Differentiators • Cognitive ability • Behaviors
• Preferences
Differentiators predict high performance
29
Competencies
How it works
Competencies
Preferences
Skills
How it works
Competencies
Preferences
Skills
HIGH HIGH HIGH
How it works
Competencies
Preferences
Skills
HIGH HIGH
MEDIUM
HIGH
MEDIUM MEDIUM
How it works
Competencies
Preferences
Skills
HIGH HIGH
MEDIUM
LOW LOW
HIGH
LOW
MEDIUM MEDIUM
How it works
Competencies
Preferences
Skills
HIGH HIGH
MEDIUM
LOW LOW
HIGH
LOW
MEDIUM MEDIUM
How it works
Competencies
Preferences
Skills
HIGH HIGH
MEDIUM
LOW LOW
HIGH
LOW
MEDIUM MEDIUM
Fit for purpose
36
How poor fit appears
Gathering data via assessments • Consistently
• Objectively
• Fit for purpose
• Timely
• Cost-effectively
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…
Gathering data: candidate skills & knowledge
• Thousands of different skills • Accurate, skill-specific
assessments exist (many online)
• Skill testing usually quick and reliable
• Often assessed at relatively early stage
Gathering data: candidate competencies • Limited number of
competencies, but different combination each job
• Psychologist interview • Observation at work • Psychometric tests • Costly, so often assessed
at late stage only
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
Timing of data gathering Application forms / résumés
Interviews / other assessments
Psychometric assessments
Traditional recruitment pipeline
Timing of data gathering Application forms / résumés
Interviews / other assessments
Psychometric assessments
Self-selection, employer-specific assessments
Interviews / other assessments
Psychometric assessments
New benchmarking recruitment pipeline
Traditional recruitment pipeline
Compare
Job
Candidates
Compare
Job
Candidates
Rank shortlist
Compare
Job
Candidates
Rank shortlist
Hire
Hiring companies using assessments, compared to those
that do not, get:
• 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
Results
The new war for talent
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