Hiring in an Unfair Game: The Moneyball of Recruiting

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ERE Webinar from 6/20/12, presented by Paul Basile.

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Hiring in an Unfair Game: The Moneyball of Recruiting

  1. Hiring in an Unfair Game: The Moneyball of Recruiting June 20, 2012Paul Basile, CEO Matchpoint Careers, Incpaul.basile@matchpointcareers.com
  2. Introductions
  3. POLL 1: who are we?•  In-house talent acquisition specialist•  Talent management specialist•  HR generalist•  Professional recruiter•  None of the above
  4. POLL 2: Moneyball and me•  I know the Moneyball story very well•  I know Moneyball, but what’s the link to recruitment?•  I have heard, vaguely, of Moneyball•  I hate baseball•  I know who Brad Pitt is…
  5. Why Moneyball?
  6. Why Moneyball?
  7. The Moneyball story
  8. The Lessons of Moneyball
  9. The Lessons of Moneyball
  10. The Lessons of Moneyball
  11. What’s the Moneyball of Recruiting?1.  Identify the problem to solve2.  Find the solution to that problem3.  Act on what we know: implement the solution4.  Eliminate everything else
  12. 1. What’s the problem?What we want What we can afford
  13. The difference top performers make Bottom 15% of Top 15% performers of performers $48,000 $80,000 $112,000 ↑↓ 40+%
  14. How do we recruit now?
  15. How do we recruit now?
  16. How do we recruit now?
  17. Our results
  18. Our results
  19. Our results
  20. Our results
  21. So, what’s going on?Selection approach False True positives positives True False negatives negatives Job performance
  22. What we getSelection approach False True positives positives True negatives False negatives Job performance
  23. What we want TrueSelection approach False positives positives True False negatives negatives Job performance
  24. 2. The solution: predict performanceCorrelation coefficient 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 -0.1
  25. Weak predictorsCorrelation coefficient 0.7 0.6 0.5 0.4 0.3 0.2 Unstructured interviews (0.18) Years of job experience (0.18) Weakly 0.1predictive Years of education (0.10) 0 Graphology (0.02) -0.1 Age (-0.1)
  26. Medium predictorsCorrelation coefficient 0.7 0.6 0.5 Knowledge of the job (0.48) 0.4 Personality tests (0.40)Somewhat References (0.36) 0.3predictive 0.2 Unstructured interviews (0.18) Years of job experience (0.18) Weakly 0.1predictive Years of education (0.10) 0 Graphology (0.02) -0.1 Age (-0.1)
  27. Strong predictorsCorrelation coefficient 0.7 Cognitive ability tests with behavioral assessment (0.67) 0.6 Cognitive ability tests (0.51)Powerfully 0.5 Structured interviews (0.51)predictive Knowledge of the job (0.48) 0.4 Personality tests (0.40)Somewhat References (0.36) 0.3predictive 0.2 Unstructured interviews (0.18) Years of job experience (0.18) Weakly 0.1predictive Years of education (0.10) 0 Graphology (0.02) -0.1 Age (-0.1)
  28. Strong predictorsCorrelation coefficient 0.7 Cognitive ability tests with behavioral assessment (0.67) 0.6 Cognitive ability tests (0.51)Powerfully 0.5 Structured interviews (0.51)predictive Knowledge of the job (0.48) 0.4 Personality tests (0.40)Somewhat References (0.36) 0.3predictive 0.2 Unstructured interviews (0.18) Years of job experience (0.18) Weakly 0.1predictive Years of education (0.10) 0 Graphology (0.02) Adapted from I. Robinson and M. Smith, Personnel Selection (2001) British -0.1 Age (-0.1) Psychological Society
  29. Predictive selection•  Cognitive ability•  Behavior•  PreferencesDifferentiators Employee performance
  30. Predictive selection•  Cognitive ability Baselines•  Behavior•  Preferences •  Skills •  KnowledgeDifferentiators Employee performance
  31. Example: Project Oxygen
  32. Example: Project Oxygen Technical ability the least important success factor
  33. 3. Act: Implement the solution
  34. Measure the job demands
  35. Measure candidate skills & knowledge
  36. Measure candidate cognitive ability
  37. Measure candidate cognitive ability
  38. Measure candidate behaviors
  39. Measure candidate behaviors
  40. Measure candidate preferences
  41. Bring the data togetherJob
  42. Bring the data togetherJob Candidates
  43. Bring the data togetherJob Candidates Rank & shortlist
  44. Bring the data togetherJob Hire Candidates Rank & shortlist
  45. Timing
  46. TimingApplication Interviews / Psychometricforms / other assessmentsrésumés assessments Traditio nal rec ruitmen t pipeli ne
  47. TimingApplication Interviews / Psychometricforms / other assessmentsrésumés assessments Traditio nal rec ruitmen t pipeli ne ine itme nt pipel ting recru anc e-predic PerformPsychometric Self-selection, Interviews /assessments employer- other specific assessments assessments
  48. 4. Eliminate all else
  49. What to eliminate
  50. But is it practical?Candidate time
  51. But is it practical?Candidate time< 1h 30 mins
  52. But is it practical?Candidate time Employer time< 1h 30 mins
  53. But is it practical?Candidate time Employer time< 1h 30 mins < 30 minutes
  54. But is it practical?Candidate time Employer time Data processing time< 1h 30 mins < 30 minutes
  55. But is it practical?Candidate time Employer time Data processing time< 1h 30 mins < 30 minutes < 1 minute
  56. But is it practical?Candidate time Employer time Data processing time< 1h 30 mins < 30 minutes < 1 minute Current cost-per-shortlist $$$
  57. But is it practical?Candidate time Employer time Data processing time< 1h 30 mins < 30 minutes < 1 minute Future cost-per-shortlist $$$
  58. Results
  59. Results
  60. Results
  61. Results
  62. Recap: Winning an Unfair Game1.  Identify the problem to solve: - Get performance and get it reliably and affordably, while competing with richer, bigger players.
  63. Recap: Winning an Unfair Game1.  Identify the problem to solve: - Get performance and get it reliably and affordably, while competing with richer, bigger players.2.  Find the solution to that problem - Predict performance; we know how to do it; the best companies do it – but don’t try to compete on their terms
  64. Recap: Winning an Unfair Game1.  Identify the problem to solve: - Get performance and get it reliably and affordably, while competing with richer, bigger players.2.  Find the solution to that problem - Predict performance; we know how to do it; the best companies do it – but don’t try to compete on their terms3.  Act on what we know: implement the solution - Assess people, assess jobs; use technology to do this quicker and cheaper than traditional means
  65. Recap: Winning an Unfair Game1.  Identify the problem to solve: - Get performance and get it reliably and affordably, while competing with richer, bigger players.2.  Find the solution to that problem - Predict performance; we know how to do it; the best companies do it – but don’t try to compete on their terms3.  Act on what we know: implement the solution - Assess people, assess jobs; use technology to do this quicker and cheaper than traditional means4.  Eliminate everything else - This is the hardest part; not done, you will lose an unfair game
  66. Thank you Paul Basilepaul.basile@matchpointcareers.com

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