Jay,
Thank you for a most thoughtful post.
It reminds me of a concept that helped me to gain new perspective on
"top" performance: regression to the norm, i.e. - in performance terms,
behavior will move to a norm, In other words, outstanding behavior will
be balanced by lukewarm or poor behavior to maintain a norm.
When I learned this concept many years ago, it helped me see that an
expectation or demand for constant "top" performance is unreasonable -
unless that "norm" is defined at "top"performance, e.g. Michael Jordan.
I saw that a more useful focus point on determining expectations of a
performer is the "norm" of his/her performance. That perspective, in
turn, made it easier to forgive the honest mistake or low performance
that came after "top" performance because I saw them as a cost exacted
for that "top" performance. .
If one subscribes to the idea that performance is predicated on risk
and risk is predicated on trust, then it follows that great risk can
bring great performance. However, regression to the norm tells us that
the great performance will be counter-balanced by a lesser - or a series
of "lesser" - performances. (Of course, "lesser" is in the eye of the
beholder. The "lesser" performance of a maestro may be far superior
than the 'top" performance of the student. However, that is
understandable because they will have different norms.)
From another perspective, regression to the norm also helped me see
that part of extending trust for risk for greater performance meant
building tolerance for the periodic failures. Trust-risk-performance
operates in an iterative, corrective cycle/system. If punishment is
imprudently placed in the cycle, then it has a dampening effect on
risk-taking so the deviation from the norm becomes less. In turn, the
occurrence of "high" performance becomes less. In some cases, the norm
also moves "down".
With that in mind, Dr. Blanchard's advice in the One Minute Manager on
differentiating between "winners" and "learners" is most useful.
Because at some point on the risk curve/scale, every performer moves
from being a "winner" (knows how to do something with a high norm of
success) to a "learner", I think those seeking "top" performance should
discipline high risk-taking performers as "learners", as a rule.
Best wishes.
Ed
Drive On!
>>> Jay Warner <
a2q@EXECPC.COM> 12/19/99 10:23PM >>>
<snip>
We tend to forget the folks who hit for the stands, and missed.
<snip>
Could we not say that the 'rational' view cited above aims to minimize
the standard deviation of the result, settling for a steady positive
gain? Then those who aim higher, at greater risk, have a larger
standard deviation. With luck, they also have a positive gain, on
average. When we cull out those who aim high but miss on the early
tries, the long term record would favor grand gesture. The celebrated
successes would thus be censored data, and misleading at that.
Jay