Monday, June 23, 2008

What is the Relevant Decision Making Criteria

How will you measure whether your decision will be effective?  To make the most effective decisions, you need to know what to measure. You also need to select among alternatives of measurement so that you can truly understand what's at stake.  In  The Essential Drucker: The Best of Sixty Years of Peter Drucker's Essential Writings on Management , Peter F. Drucker writes about how you need to figure out the most appropriate and relevant measurements.

What is the Criterion of Relevance?
The most effective decisions are made by finding the appropriate measurement.  Drucker writes:

Perhaps the crucial question here is, What is the criterion of relevance?  This, more often than not, turns on the measurement appropriate to the matter under discussion and to the decision to be reached.  Whenever one analyzes the way a truly effective, a truly right, decision has been reached, one finds that a great deal of work and thought went into finding the appropriate measurement.

The Traditional Measurement is Not the Right Measurement
The traditional measurement reflect's yesterday's decision.  Drucker writes that you need to know what's relevant for today:

The effective decision-maker assumes that the traditional measurement is not the right measurement.  Otherwise, there would generally be no need for a decision; a simple adjustment would do.  The traditional measurement reflects yesterday’s decision.  That there is need for a new one normally indicates that the measurement is no longer relevant.  The best way to find the appropriate measurement is again to go out and look for the “feedback” discussed earlier – only this is “feedback” before the decision.

Example of How Traditional Measurements Can Be Irrelevant
Drucker provides an example to illustrate how traditional measurements can be irrelevant for making effective decisions:

In most personnel matters, for instance, events are measured in “averages,” such as the average number of lost-time accidents per hundred employees, the average percentage of absenteeism in the whole workforce, or the average illness rate per hundred.  But the executive who goes out and looks for himself will soon find that he needs a different measurement.  The average serve the purposes of the insurance company, but they are meaningless, indeed misleading, for personnel management decisions.  The great majority of all accidents occur in one or two places in the plant.  The great bulk of absenteeism is in one department.  Even illness resulting in absence from work, we now know, is not distributed as an average, but is concentrated in a very small part of the workforce, e.g. young unmarried women.  The personnel actions which dependence on the averages will lead – for instance, the typical plantwide safety campaign – will not produce the desired results, may indeed make things worse.

Finding the Appropriate Measurement is Risk-Taking Judgement
Drucker writes that appropriate measurement is risk-taking judgment:

Finding the appropriate measurement is thus not a mathematical exercise.  It is a risk-taking judgment. 

Effective People Insist on Alternatives of Measurement
Drucker writes that effective people insist on alternatives of measurment:

Whenever one has to judge, one must have alternatives among which to choose.  A judgment is which one can only say yes or no is no judgment at all.  Only if there are alternatives can one hope to get insight into what is truly at stake.  Effective people therefore insist on alternatives of measurement – so that they can choose the appropriate one.

Key Take Aways
Here's my key take aways:

  • To make the most effective decisions, find the most relevant measurements.
  • Traditional measurements are not the right measurement or there would be no need for a decision.
  • Finding the right measurements is risk-taking judgment.
  • Insist on having alternatives to choose from.

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2 comments:

Barbara Swafford said...

Hi J.D.

The part about "averages" makes sense. If a company generalizes and uses "average" based on the "whole", they're missing the big picture.

I don't think you can put a large group of people in one "pot" and gain too much useful information (except maybe average age). There's too many variables.

J.D. Meier said...

Hey Barbara -

Right on. It reminds me of that saying "If you always do what you've always done. You'll always get what you've always got."

To find better answers, we need to ask better questions, and that means going beyond the "averages."