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Predictive Hiring: Find Candidates Who Will Succeed in Your Organization
 

Predictive Hiring: Find Candidates Who Will Succeed in Your Organization

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The facts are clear: Most companies today need to do a better job selecting talent. Recent survey data collected by the Corporate Executive Board indicates that nearly a quarter of all new hires leave ...

The facts are clear: Most companies today need to do a better job selecting talent. Recent survey data collected by the Corporate Executive Board indicates that nearly a quarter of all new hires leave their companies within a year, and that hiring managers wish they never extended an offer to one of every five members of their team. And a recent Gallup survey found that 52 percent of American workers were “not engaged” with their work.

Can you afford to miss an opportunity to learn how best-in-class organizations are using new technologies to scientifically assess talent before hiring, resulting in lower turnover, higher job performance and greater employee engagement?

In this presentation, you will:

Learn about new solutions that predict candidate success.
Discover how best-in-class organizations are incorporating these new solutions into their hiring process.
See the bottom-line results realized by these best-in-class practitioners.

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    Predictive Hiring: Find Candidates Who Will Succeed in Your Organization Predictive Hiring: Find Candidates Who Will Succeed in Your Organization Presentation Transcript

    • Predictive Hiring Find Candidates Who Will Succeed in your Organization
    • Agenda     Analytic applications and the rise of talent science Predictive hiring: the use of analytics in recruiting Not big data but the right data for better hiring decisions Action plan – what you can do now
    • Analytic applications Hype Cycle for Analytic Applications, 2013 Published: 31 July 2013 Analytical capability is increasingly packaged as a solution to address specific business issues, rather than created with generic business intelligence tools.
    • Talent Science, an Analytics Solution in Its Infancy Real Time Customer Offer Engine Talent Science
    • Talent Science “Talent Science is not about the technology, but rather a mindset that sees data as a basis for decision making.” Gartner Analytics Hype Cycle, December 2013
    • Why the Interest in Talent Science? “…this tale about baseball [Moneyball] may turn out to be the opening chapter of a much larger story about jobs. Predictive statistical analysis, harnessed to big data, appears poised to alter the way millions of people are hired and assessed.” Atlantic Monthly, December 2013
    • Why the Interest in Talent Science? Leading companies like Google, Cisco, KPMG, GE and Facebook have already made the shift from gut feel to data-driven talent decision making.
    • Leaders Are Starting With Recruiting
    • Recruiting Has the Biggest Impact on Business Results HR Function or Process Profit Growth Profit Margin Total Improvement Recruiting 3.5x 2.0x 5.5 On-boarding and retention 2.5x 1.9x 4.4 Managing Talent 2.2x 2.1x 4.3 Employer branding 2.4x 1.8x 4.2 Performance management and rewards 2.1x 2.0x 4.1 Developing Leadership 2.1x 1.8x 3.9 Mastering HR Processes 1.8 1.8 3.6 Global people management/global expansion 1.8 1.7 3.5 Enhancing employee engagement 1.8 1.6 3.4 Providing shared services and outsourcing 1.6 1.7 3.3 Source: BCG/WFPMA, 2012
    • Hiring for a Competitive Advantage McKinsey study shows the value of hiring top performers: 40% 49% increase in productivity in operations roles increase in profits in management roles 67% greater revenue in sales positions Source: McKinsey’s “War on Talent”
    • Your Gut Lies “46% of new hires leave after 18 months” Forbes, May 2013 For most managers, intuition is the primary guide to choosing from a pool of candidates. Unfortunately, it’s also a hugely unreliable predictor of success. Hiring managers wish they’d never extended an offer to one out of every five members on their team Corporate Executive Board Only 30% of American workers felt a strong connection to their company and worked for it with passion. 52% emerged as “not engaged,” and another 18% as “actively disengaged.” Gallup Survey
    • Agenda     Analytic applications and the rise of talent science Predictive hiring: the use of analytics in recruiting Not big data but the right data for better hiring decisions Action plan – what you can do now
    • How Do You Predict Candidate Success Today? Typical recruitment practices gather insight from the candidate’s perspective
    • Resumes and Interviews Interviews may not provide a true representation because candidates:  can be coached;  can research interview questions and appropriate answers online;  are ready to tell you what you want to hear.
    • Finding the Authentic Candidate “Over 50% of candidates lie on resumes…” Steven D Levitt – co-author “Freakonomics” 46% of employer, education, and/or credential reference checks conducted in 2008 revealed discrepancies between what the applicant provided and what the source reported… ADP 2009 Hiring Index Report “81% of people in a study lied about themselves during job interviews, with the more extroverted being more apt to tell untruths …” Brent Weiss and Robert S. Feldman, University of Massachusetts
    • Personality Assessments One problem – results can be faked! Review of 22 studies that examined actual faking:  The estimated number of fakers on self-assessments ranges from 15% to 49% (average = 30.5%).
    • Gaming the System
    • Skills Assessments Limited correlation with job failure  When new hires fail, 89% of the time it is for soft skills vs. job skills.* Cheating  Estimates are that up to 1 in 10 candidates engage in it *Forbes, 2012
    • Cognitive Assessments Cognitive Measures can show Adverse Impact Adverse impact occurs when protected classes of applicants (e.g., females, non-whites) show differences on selection tests that negatively affect hiring for diversity. Data from a large number of studies show large average differences by race/ethnicity on cognitive ability tests.
    • Agenda     Analytic applications and the rise of talent science Predictive hiring: the use of analytics in recruiting Not big data but the right data for better hiring decisions Action plan – what you can do now
    • A Way to Get More Predictive Data
    • Support for The Importance of Behavioral Assessments by Others “Nothing in the science of prediction and selection beats observing actual performance in an equivalent role.” Peter Cappelli Director, Center for Human Resources, The Wharton School “When the criterion was academic achievement or job performance, other-ratings yielded predictive validities substantially greater than and incremental to self-ratings” Connelly & Ones, 2010, p. 1092 In other words, other people’s ratings of an employee add more value toward predicting job success.
    • Here’s How You Do it… • Focus on job-relevant competence at work – Specific soft skills needed for the job • Gather feedback via observations from relevant others – Managers, peers, direct reports, clients • Strictly adhere to scientific principles and best practices discussed here today • Leverage the benefits of technology to expedite the process and gather large amounts of data
    • What Are Competencies? Refers to an individual’s knowledge, skills or abilities that are necessary to perform in a job successfully. – Some examples : dependability, accepting feedback, building relationships, clearly communicating – Unique for each job
    • A Job-Specific Assessment Library is Essential 346 surveys based on specific job competencies in SkillSurvey’s extensive library allows you to get predictive feedback on candidates for every position. Some examples include: Engineering    Engineering Managers Engineering Technician Mechanical Engineer Healthcare      Pharmacist Physician Assistants Physician Physical Therapist RN Education    Admissions Officer Faculty K-12 Educators Sales    Sales - Field Sales - Inside Sales Manager Customer Service    IT    Customer Service Manager Customer Service Professional Customer Service Rep - Online Database Administrator Helpdesk Support Software Developer Customer Service Hourly Skilled Trades Worker Warehouse Order Selector Finance        Administrative Managers Customer Service Manager Operations Manager Retail Hourly    Managerial Accountant Accounts Payable Finance Manager Financial Advisor    Loss/Prevention Specialist Retail Cashier Seasonal Worker Hospitality    Food Service Manager Hotel Clerk Housekeeper Administrative     Administrative Managers Administrative Professionals EPIC Administrative Professional Executive Assistant
    • Engineer Survey
    • Sales Professional Survey
    • Customer Service Representative Survey
    • RN Survey
    • All Valid Assessment Methodologies Have Psychometric Integrity • Consistency Reliability Psychometric Integrity Validity Compliance • Measures what it’s intended to measure • Predictive • No adverse impact • No bias
    • Study Results Prove Behavioral Assessments From Others Have Psychometric Integrity Areas of Focus Results Reliability  Internal Consistency  Test-retest Consistency  Inter-rater Consistency Validity  A statistically significant predictor of turnover  A statistically significant predictor of supervisor evaluations Compliance No statistically significant difference based on  Race/Ethnicity  Gender  Age
    • SkillSurvey Published Research 11 studies conducted….34,054 new hires tracked….observed over 21 months
    • 69% Decline In First Year Turnover For Cause % Termed for Poor Performance Within 365 Days of Hire 8.00 7.32 7.00 6.00 Percent 5.00 4.00 3.00 2.24 2.00 1.00 0.00 Year 1 [144/1968] Year 2 [116/5178] Year Using SkillSurvey [Termed for poor performance/Total number hired] *new hires across 3 companies and 3 industries (healthcare, retail, engineering)
    • 36% Decline In Voluntary First Year Turnover % Termed for Poor Performance Within 365 Days of Hire 20.00 18.24 18.00 16.00 Percent 14.00 11.53 12.00 10.00 8.00 6.00 4.00 2.00 0.00 Year 1 [359/1968] Year 2 [597/5178] Year Using SkillSurvey [Voluntarily termed/Total number hired] Data from our combined 11 validity studies *new hires across 3 companies and 3 industries (healthcare, retail, engineering)
    • Statistically Significant Predictor of Supervisor Evaluations Meta-Analysis ρ SDρ CI-Low CI-High % var 1. Bare-bones .10 .06 .02 .18 38 2. Corrected for unreliability .13 .08 .03 .24 38 3. Corrected for unreliability & indirect range restriction .26 .14 .08 .44 41 Notes. Number of studies (K) = 7. Total sample size (N) = 2789. ρ = sample size mean weighted correlations. SDρ = standard deviation of ρ. CI-Low = lower 10% of correlation. +CI-High = upper 10% of correlation. % var = percentage of variance accounted for by all artifacts.
    • HCAHPS (government survey* – collects patient satisfaction with care) • Hospitals using SkillSurvey’s Pre-Hire 360® reference assessment solution in their recruitment process have statistically higher HCAHPS scores than other hospitals • Hospitals using SkillSurvey’s Pre-Hire 360® for reference checking their job applicants, outperforming similar hospitals in nine out of ten areas of patient quality. • Followed 5,754 new hires in healthcare companies (9 companies). Results: Those with low (vs. high) scores are 200% more likely to be fired for poor performance Those with low (vs. high) scores are 24% more likely to terminate within the first year *for a review see - (www.cms.gov or www.hcahpsonline.org or www.medicare.gov)
    • Predictive Power of Others’ Ratings Higher ratings by others were accurate predictors of: • Future behavior • Voluntary and involuntary turnover • Improved satisfaction of line managers • Increased customer and patient satisfaction • Enhanced employee engagement
    • Validity Study – Large E&C Corp Validity Study on New Hires (2007 – 2012)
    • Measureable Business Outcomes Overall, results of this study show that SkillSurvey predicts 3 critical business outcomes* of New Hires Lower Turnover Overall Lower Involuntary Termination (fired for cause) Higher Performance Evaluations *Note that these results are consistent with our published results based upon six previous client validity studies: Hedricks, Robie & Oswald (2013). Web-based multisource reference checking: An investigation of psychometric integrity and applied benefits. International Journal of Selection & Assessment, 21, 99-110.
    • Overall, Those Who Termed Were Significantly Less Likely to Have a SkillSurvey Pre-Hire 360® NO YES SkillSurvey Pre-Hire 360® SkillSurvey Pre-Hire 360® Terminated, overall (n=5,146) 53.8% 35.9% 33.3% less likely to terminate Involuntary term-fired; (n=556) 74.8% 25.2% 66.3% less likely to terminate Voluntarily terminated (n=2,513) 75.2% 24.8% 67.9% less likely to terminate * 2,900/10,256 (27.6%) had a Pre-Hire 360® Report % Less Likely to Terminate, if had SkillSurvey Pre-Hire 360® 40
    • Engineers Who Termed Were Significantly Less Likely to Have a SkillSurvey Pre-Hire 360® NO SkillSurvey PreHire 360® YES SkillSurvey PreHire 360® % Less Likely to Terminate, if had SkillSurvey Pre-Hire 360® Terminated, overall (n=546) 69.2% 30.8% 55.8% less likely to terminate Involuntary term-fired; (n=52) 84.6% 15.4% 81.8% less likely to terminate Voluntarily terminated (n=384) 69.5% 30.5% 56.1% less likely to terminate Feb 20, 2014 Confidential, for internal Gartner use only without prior approval from SkillSurvey 41
    • Engineers With Low Scores Were Much More Likely to Be Fired Engineers With Low Scores Were 507% More Likely to be Involuntarily Terminated (Fired) 9.1 Low (3/30) Medium (0/91) 0.0 1.5 High (5/340) 0.0 1.0 2.0 3.0 4.0 5.0 6.0 Percent Who Were Involuntarily Terminated Feb 20, 2014 Confidential, for internal Gartner use only without prior approval from SkillSurvey 7.0 8.0 9.0 10.0
    • 344 Work-Weeks Saved -- 95% Reduction in Time Spent Reference Checking 9,727 Candidates 400 364.8 350 300 Number of WorkWeeks to Ref Check 9,727 Candidates 250 95% reduction 200 150 100 20.4 50 0 Telephone SkillSurvey Pre-Hire 360® Feb 20, 2014 Confidential, for internal Gartner use only without prior approval from SkillSurvey 43
    • Lowest-Scoring Behaviors of Engineers Who Were Involuntarily Terminated (Fired) • Interpersonal Skills – Act as a business partner with peers and all levels of management to achieve business objectives – Communicate information, ideas and data clearly, concisely and so others will understand • Delivers Results: – – – – Handle multiple projects effectively in a fast-paced environment Plan and prioritize work effectively Handle multiple tasks effectively within demanding deadlines Consistently meet or exceed goals • Displays Professionalism: – Show the ability to be self-managed (e.g. can manage own time and prioritize work to meet deadlines) *the average score of these behaviors was “medium low” 44
    • Agenda     Analytic applications and the rise of talent science Predictive hiring: the use of analytics in recruiting Not big data but the right data for better hiring decisions Action plan – what you can do now
    • Determine How Behavioral Assessments From Others Will Fit Into Your Process 1. Recruiters Source Candidates 2. Screen Top 3-5 Candidates 3. SkillSurvey Pre-Hire 360® 4. Select top two, and use feedback to structure behavioral interviews
    • Getting Money From IT For a Test Position this as a Predictive Talent Analytics pilot Goal: Test a new cloud-based tool to predict which candidates have the highest probability of succeeding after they are hired. Expected Business Outcomes: • Lower first year turnover, both voluntary and for cause • Better supervisor ratings at 90, 180 and 360 days
    • The Risk of Failure is Low, SkillSurvey Has A Significant Track Record of Success 1.3 MM 850+ Candidates CLIENTS 7 of the Top 14 U.S. Hospitals 7 of the Top 20 Children’s Hospitals GROWTH SINCE 2009 6.5 MM Reference Providers Education Healthcare Hospitals 300%+ Energy & Utilities Financial Services Services & IT Technology Engineering & Construction Consumer Products Human Resources Manufacturing Pharma & Medical Devices Long-Term Care 45+ Magnet Hospitals 50+ Teaching Hospitals