Posted by: davidhayden | April 24, 2010

Same Old Meetings, Same Old Delusions

Few things are more discouraging than attending daily production meetings.   Good news one day, bad news another day.  It seems, just when things are getting better, they fall apart again.  Does it make you think of red beads?

The Red Bead Experiment

W. Edwards Deming, statistician and quality expert made a powerful statement with his now famous red bead experiment.  It was the platform from upon which he built his 4-day intensive management seminars.

The set up is simple.  There is a box with 4000 wooden beads 3200 are white, 800 are red.  Statistically speaking there are 20% red beads.

The sample business is hired to produce white beads.  Red beads will not be paid for.  So, the six employees, randomly selected participants, are selected to produce white beads. 

To produce the white beads, the employees are given a paddle with with 50 depressions and told to stick the paddle in the box of beads and withdraw it and have their production inspected.

The inspector, also a participant out of the audience, records the daily production of white beads.

Each employee has 4 opportunities to prove they can produce white beads. 

As you can imagine, given the constraints of the system, exclusively producing white beads is impossible.  It is just a matter of statistical variation.

Statistical variation can not be avoided where processes are involved

Draw a line on a wall and start throwing darts at the line.  No matter how good you are, some are going to be to the left, some will be to the right and some will actually hit the line.  That is statistical variation.

So you are monitoring your business statistics right?  You  probably monitor your quarterly numbers, and daily production values.  But, what have you really learned by tracking those numbers?

We have been tracking our business stats for years and, it seems the more we do, the worse things get

That is a common problem.  Tracking does nothing for a business if you don’t do the following:

  • Track the right things
  • determine and understand the limits variation
  • utilize a control chart to monitor progress
  • Use the information to monitor if changes actually improve the system
  • Avoid treating common variation as if it has some special cause
  • Avoid treating special cause variation as if it has some common cause

Proper use of a control chart can help you achieve all of the above,

So what is a control chart?

A control chart is a statistical chart that shows

  • If a process is in control – if a process is not in control, you can not expect the results you are getting will repeat in the future
  • The limits of normal variation – This tells you what you can reliably expect.  If a 10% scrap rate or 15% late delivery is within normal variation, you can not ever expect it to get better without improving the process.  This requires systemic changes, not “band-aid” changes
  • Non-normal / special cause variation – This variation has a unique root cause.  Perhaps a delivery van was stolen with products on-board.  Trying to change the system to correct this cause will only waste money.  If chances of recurrence are likely, special causes need to be handled separately.   
  • Trends – When the data in the control chart shows anything besides normal variation, say five data points in succession above or below the mean (average) line you may be seeing a trend or you may want to suspect data manipulation.
  • Data manipulation – It is not uncommon when people feel they are being watched, to fudge the data to reflect what they think they want you to see.

How do control charts and statistical variation apply to my business?

All businesses are are a collection of processes that convert human or physical resources into a product  that someone else will pay money for.  Until, you understand the variation in your processes, you have no idea where to improve, or how to make more white beads, so to speak. 

There are 4 very common mistakes managers make when looking at statistical data.  First, they assume that every bad number can be easily addressed. In the case of the red bead experiment, a manager may try to fire the person who had a bad day and produced the most red beads. 

Second, when a special cause happens, they throw a lot of resources at trying to fix the system to prevent the special cause.  Often the cost of trying to avoid the statistically improbable, costs more than it is worth trying to prevent it.   

Third, managers fail to realize that the only way to reduce the variation is to address the issues in the process / system.  Firing people, hiring more inspectors, reprimands, rewards for good numbers do nothing to improve to reduce variation.  These behaviors only increase cost.

Finally, managers tinker with systems so much that they go out of control.  By chasing every special cause and treating it as a common cause or by treating every common variation as if it had a special cause, they throw the process out of control and make things much worse.

Managers must change these behaviors, if they want to see real improvement.

If you want something different than you have always gotten, you must do something different than you have always done

I hear this all the time, “If you want something different than you have always gotten, you must do something different than you have always done”

Sadly, the words are typically empty.  Managers try different things but they don’t do effective things.  Their impatience, prevents them from wanting to gather useful data, so they grasp at every positive indicator and proclaim, “we need to do more of this.”    Then they create policies that punish people for the negative indicators.

If managers truly want to improve their numbers, they must take the time to understand the limits of the system they force the people to work within.  To improve the numbers, the systems must be improved. 

Management is responsible for the systems.  If a machine is worn out, that is not the fault of the operator who can not make good parts consistently.   If the delivery vehicle breaks down frequently, unreliable delivery is not the fault of the driver.  If the receivables turn over ratio is bad, that is not the fault of the collection people if management gives credit to customers with poor payment history.

If you attend regular meetings, notice how management throws around praise when the numbers are good and take a somber tone when numbers are bad. 

Then ask yourself, I wonder if this is just normal variation.   

If you are really adventurous, ask the question out loud in the meeting, but don’t be surprised if you are reprimanded for challenging the status quo.


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