Data driven business decisions (and the offshoot being discussed here
- design decisions) is a significant movement… much of it being
fostered from engineers and statisticians. The notion that we, the
humans, do not need to know the why, but only what he data tells us
to do is at the core of its controversy. There have been many
articles published on this recently and even a few in the popular
press (Time and Business Week as I recall).
There are a couple of issues here. The first, is the notion that
human understanding of the ‘why’ in insignificant. I find this
troubling. More and more I run into folks who want a decision that is
not encumbered by ‘mistake prone’ humans. This is silly, and frankly,
it is a weak ass approach to decision making. It is unrealistic and
devoid of an important part of decision-making… judgment. Statistics
do in fact lie. Following this purely data driven approach,
executives often become the victim of type 3 errors (sometimes called
a type 0 error) in which the wrong questions was asked.
A wise professor once told me that having research is much better
than not, but in the end… once you have absorbed and evaluated all of
the data, you still have to make a decision. The same is true whether
you are using qualitative research, quantitative research, accounting
numbers or other business metrics… it must be interpreted, weighed
and assessed for significance… then you make a decision. The data
should never render the decision for you.
Further… making the choice between selections A, B, and C is the easy
step (as pointed out by Tichy and Bennis in their recent book
‘Judgment’). You still have to evangelize, execute and follow through
with the decision. That is hardly do-able if you have let the data
take the first step. Not knowing the why is crippling in the ‘whole’
of the decision process.
Mark
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