Applying Predictive Analytics to Improve Talent Retention

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1 Applying Predictive Analytics to Improve Talent Retention Thomas Daglis Associate Data Scientist: Ultimate Software

2 Goals for today Focus on solving problems through a data driven approach Hone your skills as an analytical storyteller Motivate you to act on your analytics 2

3 Ever purchased a Car? 3 3

4 Judgment vs. Data Predictions Judgment Gut-level input Planned Periodically Manually Updated Highly Subjective Data Employee records Always Available Always Up-to-date Unbiased 4 4

5 A simple philosophy to become data-driven Data Knowledge Action 5 5

6 Workshop #1 Practice Data Identification How might you measure employee engagement? Team Dynamics Meaningful work Source: SHRM Employee Job Satisfaction and Engagement Report

7 If we have data, let s look at data. If all we have are opinions, then let s start with mine. Jim Barksdale, Former CEO, Netscape 7 7

8 Successful CHROs are assertive and data-driven 4% 16% 80% 28% 80% of executives agree that their company can t succeed without an assertive, datadriven CHRO, who takes a strong stance on talent issues and uses relevant facts to deliver an informed point of view. Strongly Agree Strongly Disagree 52% Somewhat Agree Somewhat Disagree Source: Februrary 2015 Harris poll survey of 301 corporate executives across America 8 8

9 Current State of Analytics? What new analytics and big data solutions are you most focused on? CRM/ERP User productivity Mobility Collaboration Social media Supply chain HR 11% 20% 27% 26% 24% 38% 44% Source: Gatepoint Research / IBM Strategies for Integrating Analytics May

10 Employee retention is #1 problem for CHRO s Top organizational challenges cited by HR professionals Empoyee retention/turnover Employee engagement Succession planning Recruitment Culture management Performance management Employee satisfaction Relieving employee frustration Employee enablement - providing Productivity *Employee happiness *Employee brand Revenue per FTE Other 4% 4% 7% 11% 10% 9% 9% 10% 12% 14% 18% 18% 19% 26% 24% 22% 22% 33% 35% 29% 35% 31% 40% 39% 39% 47% Source: SHRM/Globoforce 2015 Employee Recognition Survey 10 10

11 Replacing Employees Is Expensive 30-50% Annual Salary Entry Level Employees 1.5x Annual Salary Mid-Level Employees 4x Annual Salary High-Level or Highly Specialized Employees Source: TLNT What Was Management Thinking? The High Cost of Employee Turnover,

12 12 Predictive and Prescriptive Talent Analytics

13 Predictive vs Prescriptive Predictive Analytics Prescriptive Actions Suggesting the best action to take to influence a different outcome The power to use what happened yesterday to accurately predict what will happen tomorrow An analytic without action is useless Steve VanWieren 13

14 16 million data points of workforce data only 4% successfully executed datadriven HCM programs 14 14

15 There are drivers in your HR data Compensation History Identify Retention Risks 15 15

16 Each Employee Gets a Score HIGH RISK HPI HPI HPI HPI MEDIUM RISK LOW RISK 16

17 Retention Predictor Results % of Employees / Expected Success Rate 60% 50% 40% 30% 20% 10% 0% HIGH RISK 10% MED RISK 40% LOW RISK 50% Retention Predictor Historical Score Ranges # Terminated # Retained 17 17

18 Retention Use Case Financial Services Analytics identified 3X more at risk employees than manager assessment alone 152 terminated Judgment 4.3% tagged 43% actually left 16 employees correctly identified Analytics 10% lowest scores tagged 61% actually left 47 employees correctly identified 18

19 HIGH PERFORMER Save the most valuable employees High Risk of Leaving 19 19

20 HIGH PERFORMER Optimize investment in employees Low Risk of Leaving 20 20

21 High Performer Predictor Results % of Employees / Expected Success Rate 40% 35% 30% 25% 20% 15% 10% 5% 0% HIGH CHANCE 10% of employees MED CHANCE 40% of employees LOW CHANCE 50% of employees High Performer Predictor Historical Score Ranges High Perf Not High Perf 21 21

22 High Performer Use Case Financial Services Analytics was 2X more effective at identifying current high Best practice = 5-10% of talent pool Judgment ~27% tagged 13% received >5% raise Data ~9% tagged 28% received >5% raise 22

23 A simple philosophy to become data-driven Data Knowledge Action 23 23

24 Why do people leave? 31% don t like their boss Aberdeen Group 31% do not feel empowered Aberdeen Group 35% due to internal politics/turf Aberdeen Group 43% for lack of recognition Aberdeen Group >60% do not feel like they get enough feedback Gallup Poll 75% of people leave because of work relationship issues Saratoga Institute 75% of people who leave voluntarily don t quit their jobs; they quit their boss Roger Herman 89% of managers believe that most employees are pulled away by better pay but 88% of voluntary resignations happen for reasons other than pay Leigh Branham, The Seven Hidden Reasons Employees Leave #1 reason is lack of recognition Bersin #1 reason for millennials: not learning enough Business Insider 79% of those who quit their job cite lack of appreciation as primary reason SHRM 24

25 A SCARY STATISTIC 3 in 4 full-time workers are open to or actively looking for new job opportunities Source: CareerBuilder

26 What makes people STAY? GROWTH MONEY POWER RECOGNITION AUTONOMY Receive Special Training Issue Cash Award Become A Mentor Send Handwritten note Offer Flex Hours 26 26

27 Prescriptive My Leadership Actions Analytics UltiPro prescriptive actions provide practical advice and inspirational messages about effective leadership. 27

28 The groups receiving actions have up to 50% lower turnover 28 28

29 10 employees X $75,000 X 1.5 (replacement factor) = $1,125,000 in savings FOR EXAMPLE: SUPPOSE YOU SAVE 10 MID-LEVEL PEOPLE AVERAGE SALARY: $75,

30 Workshop #2 Practice 6 Great Traits of Leaders Vision Conviction Humility Integrity Credibility Collaboration Source: Follow Your Conscience Frank Sonnenberg How would you measure these things? What actions could you plan and take? 30 30

31 Waiting is not an option YOU NEED TO BE THE GAME CHANGER 31 31

32 Game Changer 32 32

33 YOUR PEOPLE are YOUR BUSINESS 33

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