People analytics refers to using analytics and data to help managers make decisions about employees. It involves collecting and analyzing large sets of talent data to make better hiring, performance, and retention decisions. However, experts warn that people analytics has limitations. Big data results can be influenced by the questions asked and algorithms used, and may miss important variables or find spurious correlations. Metrics also may not capture the most important factors for organizational success. Managing employees effectively still requires implementing analytics carefully while addressing their pros and cons.

1. What People
Analytics can't
Capture

2. PEOPLE ANALYTICS
PEOPLE ANALYTICS
People analytics, also known as talent analytics or HR
analytics, refers to the method of analytics that can help
managers and executives make decisions about their
employees or workforce.
People analytics applies statistics, technology and expertise
to large sets of talent data, which results in making better
management and business decisions for an organization.

3. People analytics helps organizations to make
smarter, more strategic and more informed
talent decisions. With people analytic,
organizations can find better applicants,
make smarter hiring decisions, and increase
employee performance and retention.
PEOPLE ANALYTICS

4. WHAT ARE WE
MISSING?
Many businesses are reaping rewards from
big data analytics. But there are also some
areas of disappointment. Experts caution
that big data, like any other, is only as good
as the questions being asked – and that
some algorithms can make unhelpful
assumptions.

5. STATISTICS
There’s a saying in the
sciences, “Statistics means
never having to say you are
certain.” In any massive
data analysis, for instance,
there will be random
correlations that look
“significant” but actually are
noise, not signal.

6. NEXT STEP
Big data needs a hard outcome metric for
performance, but the most readily
available
metrics may not actually be the most
important variables in organizational
flourishing.

7. T Y R A N T M A N A G E R S
Managers Over pressure
Sort term targets
Working environment depends on previous
work done.
Managers force his people to work hard to
meet quarterly targets

8. 01
Insights
Big data needs a hard
outcome metric for
performance, but the most
readily available metrics may
not actually be the most
important variables in
organizational flourishing.

9. Insights
Experts caution that big
data, like any other, is only
as good as the questions
being asked – and that
some algorithms can make
unhelpful assumptions
02

10. MANAGERIAL RELEVANCE
The more we depend on algorithm ,
numeric values the problem of employee
will not be reduced
Have to implement more technologies
knowing their pros and cons

11. S U S H A N T K U M A R
I N D I A N I N S T I T U T E O F T E C H N O L O G Y , K H A R A G P U R
THANK YOU
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