Don’t Overcomplicate Your Problem Solving Efforts

Posted by on Jan 20, 2012 in Problem Solving | 0 comments

I recently had the opportunity to help a client solve a major customer satisfaction issue that they had worked on for several months.  Many people were involved and of course everyone had their own opinion as to what the root cause was.  As I listened to their comments, I couldn’t help but wonder if they were making the problem more complicated than it needed to be.  I heard all kinds of theories and hypothesis about the problem from differences in raw material suppliers to how the atoms bond together to form the molecules.  My head started to hurt!

Since I was called in to help make sense of all this, I suggested we start by walking the process and eliminate the irrelevant families of variation that would not contain the root cause.  We used the 6M’s and a process analysis map to help us converge on the relevant family of variation which was material.  The plant personnel had collected a lot of data on different characteristics of the materials used.  Our job was then to use Minitab to compare the different material characteristics that made good product from those that made bad product.  Within a matter of hours, we had the root cause identified and then it was just a matter of running trials to turn the problem on and off.

I spent most of my evenings and early mornings thinking about how teams get started down the wrong path.  The following are some of my thoughts:

  • Not knowing the difference between divergent thinking and convergent thinking.  The tendency is for teams to want to brainstorm different ideas as to the source of the problem.  This is wrong!  Brainstorming is divergent thinking.  What you want to do is to converge on the root cause by using a process of elimination.  By eliminating families of variation you reduce the possibilities exponentially.
  • Not taking the time to understand the current situation.  Failure to walk the process and look for the obvious is a problem.  Maybe teams are too close to the issue and take certain things for granted.  I’m not sure, but I always walk the process looking for the obvious and ask dozens of questions about what’s going on.
  • Failure to compare the extremes whenever possible.  If you have the data, you can compare the different characteristics of good and bad lots of material to see if something jumps out at you.  This is very easy in Minitab, using box plots, run charts, etc
  • Failure to have the right people on the team.  Sometimes it just takes that one person to say they saw or observed something that can help the team solve the problem.  I try to reinforce the fact that there are no stupid or dumb statements to help people open up and give their insights.
  • Failure to torture your existing data.  Again I don’t know if teams are too close to a problem, but I’m amazed that many times they fail to take advantage of the data they already have.  Torture the data — make it scream!  Look at it from every angle to see if something pops out at you.
If you have any other ideas why teams struggle in their problem solving efforts, please make a comment below.

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