Big data analytics cannot capture everything and can sometimes make unhelpful assumptions. Random correlations in data may appear significant but are actually just noise. Readily available metrics for analyzing performance may not be the most important variables. For example, a manager forcing people to meet short-term targets could be ruinous long-term. Additionally, the strongest predictor of future behavior is past performance as evaluated by those who know the person well, which data cannot replace. As a manager, one should use analytics while also recognizing its limitations to avoid being misled.

1. WHAT ANALYTICS
CAN’T CAPTURE
Submittted by: Saurabh Ranjan
Institute: Jadavpur University
Under the guidance of:
Prof. Sameer Mathur

2. Using big data
analytics and
personality test
scores to predict
who is best for a
given job

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

4. Sometimes
random
correlations
look
“significant
” but
actually are
noise, not
signal.

5. Now we need to have a hard
outcome metric for analysing
the performance, but the
most readily available
metrics may not actually be
the most important variables

6. Take for an example
 A manager forcing his
people to work hard
to meet quarterly
targets may be
ruinous to the
organization over the
long term.
 Using an outcome
metric like an
executive’s earnings
performance

7. But the biggest objection
comes from the fact that the
strongest predictor of a
person’s future behavior is
their past performance
itself. And that performance
gets evaluated best by
people who know that person
well.

8. MANAGERIAL
RELEVANCE

9. •Being a manager, one should
be privy to the facts that
not only data analytics cant
capture everything and also
that it can be quite
misleading sometimes as
well.
One should reap the benefits
of data analytics while
keeping in track of the
downsides of it.