The document discusses the limitations and risks of using big data analytics and personality tests to predict job performance. While businesses have seen benefits from these approaches, experts warn that the quality of data analysis depends on the questions asked. Algorithms can make incorrect assumptions, and large data sets may find random correlations that don't reflect real patterns. Additionally, the metrics and tests used may not capture the most important factors for organizational success over the long term. A manager focused only on short-term targets could undermine company culture and morale. The best evaluators of a person's future potential remain those who know them well through past performance.

2. TIME’s recent cover story on
the latest fad in human
resources, using big data
analytics and personality test
scores to predict who is best
for a given job – so-called
“XQ.”

3. Many businesses are
reaping rewards from
big data analytics.

4. But there are also some
areas of disappointment.

5. 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.

6. “Statistics means never
having to say you are
certain.”

7. In any massive data analysis,
for instance, there will be
random correlations that look
“significant” but actually are
noise, not signal.

8. The question of what metrics
a personality test uses to
gauge “success.”

9. 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.

10. A manager – like the demotivating
petty tyrant mentioned above –can
force his people to work hard to
meet quarterly targets, for
example, while destroying the
emotional climate that sustains
the life-blood of any organization.

11. We have long known that
managers who focus too much
on performance at the expense
of people can be ruinous to the
organization over the long
term.

12. Using an outcome metric like an
executive’s earnings performance,
while ignoring his role as a boss
and his impact on the morale,
loyalty, focus, and stress levels of
his direct reports, may result in a
false indication of who’s really the
best boss.

13. It’s telling that at Google, that
bastion of algorithms emerging
from giant data sets, engineers
refused to use just such a
method to decide on
promotions.

14. The assumptions built into a test
can themselves be biased
against certain traits and so
discriminate unfairly.

15. 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.

16. Sachin Kumar Singh
REC Sonbhadra