SlideShare a Scribd company logo
1 of 16
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.”
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.
“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.
The question of what metrics
a personality test uses to
gauge “success.”
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.
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.
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.
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.
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.
The assumptions built into a test
can themselves be biased
against certain traits and so
discriminate unfairly.
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.
Sachin Kumar Singh
REC Sonbhadra

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"What People Analytics Can’t Capture" by Daniel Goleman

  • 1.
  • 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.