1. The Control Chart:
Our Control Chart shows no special cause variation
This means that there was only “Common Cause” variation operating in this
Process. The Process was stable and there were no “Special (assignable)
All the variation came from the process inputs of Materials, Machines, Methods
and Environment. There was NO evidence that any worker (people) was better
than another
In a Process with only Common Cause variation, the chance that any Worker
would get a low or high Red Bead count was entirely random. It was essentially
a lottery
Feedback: During the exercise, the Foreman gave very specific feedback on their
number of Red Beads, adherence to the Procedure. Management reacted to
every change in the numbers. But the Control Chart tells us that the numbers
were really NOT changing, statistically. Very predictable and stable.
Recognition (“Worker of the Day”) and Probation: These actions were taken
based on the individuals’ results. This causes damage that is unknown and
unknowable. For Workers that recognize or sense that this is a lottery, they
become angry and cynical. They sometimes work out ways to rig the “game” in
their favor. But the real tragedy is when many Workers accept the results as
valid and conclude that they are worthless failures. Their frustration and
despair increases as they “try harder” and harder still. When facing job loss,
they are tempted to cut corners or otherwise cheat to save their jobs.
Management is typically clueless to all of this. Even when they find a cheater,
they attribute it to one “bad apple”. The real causes are not even under
suspicion by Management.
Incentives: Such rewards go beyond “Recognition” in that they introduce
powerful extrinsic motivators. Pay for performance was futile. The damage of
extrinsic motivators is that they kill intrinsic motivation. Everything is reduced to
money and, when the lottery aspects of the Process are perceived, open gaming
of the results ensues.
2. Management Actions:
Rating and Ranking: Via the “Performance Appraisal” linked to a “Merit Pay”
system, the rating and ranking insults the intelligence of the Workers that know
better and crushes the lower ranked Workers that accept the results as valid. As
long as the results are within the Control Limits (of a stable Process), no
performance conclusions can be drawn about the Workers within that system.
Further, if you track the results long enough, the “Worker of the Day” will soon
be “below average” and the Probationary Worker will be in the “above average”
group. Regression to the mean will apply. Statistical Tools are powerful aids for
understanding and improving a Process. They are misused as techniques to rate
and rank Workers.
3. Key Principle:
All the above actions were taken under the assumption that there was a “Special
Cause” for each Worker’s result: If only the Worker would try harder, be more
motivated, follow the Procedure to the letter, etc.
Common Cause versus Special Cause Variation: The key principle here is
Common Causes and Special Causes. In the Red Bead experiment, we treated
the Workers as Special Causes, rather than focusing on the Common Causes
across the whole Process.
Clarify Purpose: We want to make White Beads. Clear enough.
What are the customer’s requirements? Three Red Beads or Fewer per batch.
We needed to use the Control Chart to know that we needed to find Common
Causes and not Special Causes.
o Special Causes require an Epidemiological approach to pinpoint them and
remove them so that the Process becomes stable (only Common Cause
variation left).
o Common Cause variation is reduced by using Quality Improvement
Theory (Lean Six Sigma, TQM/CQI, etc.).
What is our current process capable of? A range of 1 to 19 Red Beads with an
average of about 10.
Conclusion: Our current Process has far too much variation in it to produce
acceptable results. It must be improved or replaced. How?
Brainstorm and Literature Search: What are the Common Causes that most
account for the variation seen in the current Process? What have we observed
and what is in the literature as to Best Demonstrated Practices?
4. A Better Approach:
The dominant variable is that there are 20% Red Beads contaminating the supply
we are using.
Can the Supplier (or another Supplier) give us Beads with a very low (or
nonexistent) Red Bead content?
If the Red Bead contamination remains too high, can we economically extract
some or all of the Red Beads from the supply prior to production?
Is there a cost-effective way to filter out the Red Beads during Production or
color the Red Beads white?
Experiment with these ideas and involve the customer in the testing.
Adopt improvement(s) that get you to the customer’s requirements at a cost he
will pay.
Monitor to hold the gains.
5. Healthcare Examples
What “Red Beads” have you encountered in your work life? How did you and
others deal with them?