Applying Predictive Analytics to Improve Talent Retention Thomas Daglis Associate Data Scientist: Ultimate Software
Applying Predictive Analytics to Improve Talent Retention
Thomas Daglis Associate Data Scientist: Ultimate Software
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
1 2 3
2
3
Ever purchased a Car?
3
4
Judgment vs. Data Predictions
Gut-level input
Planned Periodically Manually Updated Highly Subjective
Employee records
Always Available Always Up-to-date
Unbiased
Judgment Data
4
5
A simple philosophy to become data-driven
Data Knowledge Action
5
6
Workshop #1 Practice Data Identification
How might you measure employee engagement?
Source: SHRM – “Employee Job Satisfaction and Engagement Report” - 2015
Team Dynamics Meaningful work
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
8
Successful CHROs are assertive and data-driven
80% of executives agree that their company can’t succeed without an assertive, data-driven CHRO, who takes a strong stance on talent issues and uses relevant facts to deliver an informed point of view.
Source: Februrary 2015 Harris poll survey of 301 corporate executives across America
4%
28%
52%
16%
Strongly Agree
Somewhat Agree
Strongly Disagree
Somewhat Disagree
80%
8
Current State of Analytics
11% 20%
24% 26%
27% 38%
44%
HRSupply chainSocial media
CollaborationMobility
User productivityCRM/ERP
What new analytics and big data solutions are you most focused on? ?
Source: Gatepoint Research / IBM – “Strategies for Integrating Analytics” – May 2014
9
10
Employee retention is #1 problem for CHRO’s
Source: SHRM/Globoforce – “2015 Employee Recognition Survey”
4% 10%
10% 19%
18% 18%
31% 35%
26% 39%
47% 33%
4% 7%
9% 9%
11% 12%
14% 22% 22%
24% 29%
35% 39%
40%
OtherRevenue per FTE
*Employee brand*Employee happiness
ProductivityEmployee enablement - providing
Relieving employee frustrationEmployee satisfaction
Performance managementCulture management
RecruitmentSuccession planning
Employee engagementEmpoyee retention/turnover
20152013
Top organizational challenges cited by HR professionals
10
11
Replacing Employees Is Expensive
Entry Level Employees
Mid-Level Employees
High-Level or Highly Specialized Employees
Source: TLNT – “What Was Management Thinking? The High Cost of Employee Turnover”, 2015
30-50% Annual Salary
1.5x Annual Salary
4x Annual Salary
11
12
Predictive and Prescriptive Talent Analytics
Predictive vs Prescriptive
Suggesting the best action to take to influence a different outcome
Predictive Analytics
Prescriptive Actions
The power to use what happened yesterday to accurately predict what
will happen tomorrow
“An analytic without action is useless”
– Steve VanWieren
13
16 million data points of
workforce data
only 4% successfully
executed data-driven HCM programs
14 14
Com
pens
atio
n Hi
stor
y
Identify Retention
Risks
15
There are drivers in your HR data
15
Each Employee Gets a Score
99.9 99.2 98.7
18.4
59.7
64.5
80.3
25.7 36.7
48.1
60.4
42.5
72.8
87.0
96.9 94.7 90.3
10.3
HPI
HPI
HPI
HPI
HIGH RISK LOW RISK
MEDIUM RISK
16
17
Retention Predictor™ Results HIGH RISK
10% MED RISK 40%
LOW RISK 50%
0%
10%
20%
30%
40%
50%
60%
10.3 - 59.7 59.7 - 93.1 93.1 - 99.9% o
f Em
ploy
ees
/ Ex
pect
ed S
ucce
ss
Rate
Retention Predictor Historical Score Ranges # Terminated # Retained
17
Retention Use Case – Financial Services
10% lowest scores tagged 61% actually left
47 employees correctly identified
Judgment Analytics 4.3% tagged
43% actually left
16 employees correctly identified
Analytics identified 3X more ‘at risk’ employees than manager assessment alone
152 terminated
18
HIGH PERFORMER
High Risk of Leaving
Save the most valuable employees
19 19
HIGH PERFORMER
Low Risk of Leaving
Optimize investment in employees
20 20
21
High Performer Predictor™ Results HIGH CHANCE
10% of employees
MED CHANCE 40% of
employees
LOW CHANCE 50% of
employees
0%
5%
10%
15%
20%
25%
30%
35%
40%
21.4 - 80.3 9.6 - 21.4 0.2 - 15.3
% o
f Em
ploy
ees
/ Ex
pect
ed S
ucce
ss
Rate
High Performer Predictor Historical Score Ranges High Perf Not High Perf
21
High Performer Use Case – Financial Services
~9% tagged 28% received >5% raise
Judgment Data ~27% tagged 13% received >5% raise
Analytics was 2X more effective at identifying current high
Best practice = 5-10% of talent pool
22
23
A simple philosophy to become data-driven
Data Knowledge Action
23
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
Why do people leave?
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”
>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
#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 - http://careerbuildercommunications.com/candidatebehavior
25
26
What makes people STAY?
POWER
GROWTH Receive Special Training
RECOGNITION
MONEY
AUTONOMY
Issue Cash Award
Become A Mentor
Send Handwritten note
Offer Flex Hours
26
My Leadership Actions
Prescriptive 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
FOR EXAMPLE: SUPPOSE YOU SAVE 10 MID-LEVEL PEOPLE
AVERAGE SALARY: $75,000
10 employees X $75,000 X 1.5 (replacement factor) = $1,125,000 in savings
29 29
30
Workshop #2 – Practice 6 Great Traits of Leaders
Vision Conviction Humility
Integrity Credibility Collaboration
How would you measure these things? What actions could you plan and take?
Source: “Follow Your Conscience” – Frank Sonnenberg
30
YOU NEED TO BE THE GAME CHANGER
Waiting is not an option
31 31
32
Game Changer
32
33
YOUR PEOPLE are YOUR BUSINESS
34