Are you ready to make the most of your engagement surveys? Find out how to leverage its predictive analytics to make work better every day!

1. HR’S GUIDETO
PREDICTIVE WORKFORCE ANALYTICS

2. Big data, fast data, business analytics, machine
learning, the list goes on and on. Data are in, and
they’re here to stay.

3. The most important aspect of data is how they’re used.
Using data well can make the difference between good and
great organizations, and even the difference between barely
surviving and absolutely thriving. That’s why HR analytics is
such a hot trend right now.

4. If you search online for images of “analytic
evolution,” you’ll see a variety of charts,
graphs, and tables that basically look like
the following:
Prescriptive
Predictive
Descriptive

5. Descriptive analytics is the first step in an
organization’s analytics journey. How well is
this team performing? How engaged is that
department? The answers to these
questions describe certain qualities.
Prescriptive
Predictive
Descriptive

6. Descriptive analytics become stale after
awhile, only taking you so far in
understanding your organization...
Prescriptive
Predictive
Descriptive

7. To become more analytically proactive, we
need predictive analytics. Predictive
analytics is the use of current or past data to
offer insights about unknown events. In
other words, we can use known data to
offer a roadmap into the unknown.
Prescriptive
Predictive
Descriptive

8. Predictive analytics can be complicated and
often requires some background in statistics
to set up and calculate. But what is more
important is how you approach and think
about predictive analytics, even if you’re not
a statistician.
Prescriptive
Predictive
Descriptive

9. LEVERAGE PREDICTIVE ANALYTICS
2 W A Y S T O

10. LEVERAGE PREDICTIVE ANALYTICS
2 W A Y S T O
Identify Retention Risks

11. LEVERAGE PREDICTIVE ANALYTICS
2 W A Y S T O
Identify Retention Risks
+
Identify Recruitment Risks

12. IDENTIFY RETENTION RISKS
The first example can help you
identify at-risk employees. On this
heat map, you can see the
perceptual differences between
individuals who took the survey and
are either still employees or have
since termed.

13. IDENTIFY RETENTION RISKS
Termed employees had much lower
favorability than existing employees
across a variety of themes. This
indicates that we can be more
confident that employees who have
lower ratings to engagement
surveys are more likely to term
within the next 6-12 months.

14. IDENTIFY RETENTION RISKS
Let’s dig deeper…

15. IDENTIFY RETENTION RISKS
The category with lowest favorability for
termed employees was Feeling Valued. This is
where a “predictive analytics mindset” comes
into play: we can hypothesize that employees
who rate Feeling Valued items lower are more
likely to term. Feeling Valued is predictive of
employee turnover.

16. IDENTIFY RETENTION RISKS
In other words… Employees who don’t feel
valued are more likely to leave.

17. IDENTIFY RETENTION RISKS
TEST THE HYPOTHESIS
Focus on teams or departments with higher-than-average turnover, and
potentially implement strategies to boost recognition and help them feel
valued. After implementing those strategies, track turnover in those same
teams or departments – does turnover decrease, increase, or remain about
the same? This constant measurement, tracking, evaluation, and refinement
is at the heart of predictive analytics.

18. IDENTIFY RETENTION RISKS
TAKE IT A STEP FURTHER
A lot more questions can emerge from the “existing vs. termed” data. Which
survey items have the largest differences between existing and termed
employees? Which teams have the most termed employees? How can we
use these data to determine at-risk employees? That last question is the
most crucial because it emphasizes the predictive analytics mindset, of trying
to shine light on the unknown with what is known.

19. IDENTIFY RECRUITMENT RISKS
The second can help you identify
potential recruitment risks. We can
see perceptual differences across
employee generations here:

20. IDENTIFY RECRUITMENT RISKS
Let’s dig deeper…

21. IDENTIFY RECRUITMENT RISKS
Millennials had much lower favorability than Gen Xers and Baby Boomers
across the board. As Millennials become a larger and larger part of the
workforce — especially for newer and entry-level positions — recruitment
efforts need to take at least some generational differences into account.
With Millennials having the lowest favorability in that organization, it may
encounter recruitment risks with Millennials, ultimately hurting
organizational growth and competitive advantage.

22. IDENTIFY RECRUITMENT RISKS
TEST THE HYPOTHESIS
Analyze your data to uncover the following questions: Which survey items
have the largest differences between Millennials and Baby Boomers? Which
teams have the highest proportions of Millennials? How can we use these
data to enhance Millennial employees’ perceptions? How can heightened
perceptions among Millennial employees be leveraged to make our
organization more attractive to Millennial job seekers?

23. IDENTIFY RECRUITMENT RISKS
Focus on teams or departments with higher millennial population, and
potentially implement strategies that cater to their unique needs and wants
you identified. After implementing those strategies, track engagement in
those same teams or departments – does favorability on items decrease,
increase, or remain about the same?
TAKE IT A STEP FURTHER

25. Having a predictive analytics mindset is crucial to determine which HR strategies and
initiatives to pursue, and being more informed with engagement survey data can refine
those efforts even further.
With all that said, it never hurts to have a partner who has a strong background in
behavioral statistics, whether inside or outside your organization.

26. We didn’t forget about
prescriptive analytics…
Prescriptive
Predictive
Descriptive

27. Prescriptive
Predictive
Descriptive
Prescriptive analytics answer questions that
include would, could, or should, such as
“What should we do?” or “What should be
done?”
These analyses are quite
advanced and sophisticated.

28. Prescriptive
Predictive
Descriptive
But even so, it’s good to know that after
predictive analytics become fully embraced
within your organization, there’s yet another
step toward better understanding the
employee experience and making work
better every day.

29. Click below to learn more about our Employee Engagement Survey – and how you
can leverage its predictive analytics to make work better every day.
Smart Predictive Analytics Start Here.
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