2. • 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.
1st Insight:
3. • Data analysis, for instance, there will be
random correlations that look “significant” but
actually are noise, not signal.
• Statistics means never having to say you are
certain.
4. • 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.
5. • while destroying the emotional climate that
sustains the life-blood of any organization.
• A manager – like the demotivating petty
tyrant mentioned above –can force his
people to work hard to meet quarterly
targets.
6. • 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.
7. 2nd Insight
• 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.
8. • At Google, that bastion of algorithms
emerging from giant data sets, engineers
refused to use just such a method to decide
on promotions.
9. • Company knows so much about algorithms
lets it see their limits.
• The assumptions built into a test can
themselves be biased against certain traits
and so discriminate unfairly.
10. • Biggest objection comes from the fact that the
strongest predictor of a person’s future
behaviour is their past performance itself.
• And that performance gets evaluated best by
people who know that person well.
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