Data and Facts Are Not the Same

Last week Steve Martin had a great post about data and going to see what is actually happening over at theThinkShack blog.  It struck a nerve with me because it reflects something I seen happening on a regular basis.  I am tired of people trying to solve problems while sitting in a conference room.

I listen to comments like, “Well they aren’t using the right codes for the defect.” or “People just need to put the coding in the system properly and we could figure the problem out.”


Don’t misunderstand me.  Ten years ago you would have heard me say some of the same things.  So, I do have patience with teaching people to go and see.  Once I learned to go and see it became very freeing because I didn’t stress about what the data said.  I spoke to facts.

Data is a good thing.  I am not saying we should ignore data, but we need to know its place.  Data can help point us in the direction of problems.  It can tell us where we should go and look for facts.

Facts to me are what you actually see happen.  What you have observed.  It isn’t the hearsay you get in a conference room.   Facts explain what is actually happening and add deeper meaning to the data.

I lived a great example recently.  In a conference room, managers looked at the data and saw a problem that was happening.  They started talking about what was happening and why.  They asked if I would look into fixing it.  I said I would look at what is actually going on.  I spent 2 hours directly observing the work and realized the one problem they were talking about was actually several different problems out on the floor.  I asked the person actually doing the work to take a couple weeks worth of data based on what was actually happening.  The data showed they actually had 2 big problems that made up 80% of the total errors the original data showed.  I then did another hour of direct observation between an area that had the problem and an area that did not.  I was able to explain the problem with facts that I observed and data to support those facts to add concrete to what I observed.  At that point, there was some obvious ways to correct the situation.

Data and facts are different.  They are not substitutes for each other.  Data and facts can be a very strong combination when used together to understand a problem.

data directional

facts truths – use eyes – go and see

Link to Steve Martin’s Blog Post:

Posted on March 14, 2011, in Learning, Metrics, Problem Solving and tagged , , , , , , , . Bookmark the permalink. 4 Comments.

  1. It’s similar to when a person regarded as not being very knowledgeable reports a problem to someone who thinks they know. You often find the “smarter” person dismissing the other’s observation or conclusion. If they both open-mindedly go to the site of the problem itself instead of getting into a battle of assumptions and conclusions, they don’t go away thinking the other one is an idiot, but can gain respect for each other by working together. It’s a matter of finesse. The less-knowledgeable person may indeed have an erroneous conclusion, but if the attitude is that something’s not right and let’s go take a look, no one loses face.

  2. Matt,

    Nice post! Teams definitely need to go to the Gemba as part of the problem solving process. You also mention data being a good thing. There is a balance between data and personal observation which you seemed to hit spot on in your example. We need to use data to avoid making emotional decisions and to get the most bang for our buck (see Pareto Principle ).
    At the same time, we need to validate the data. There are so many things that can go wrong with data as you illustrate. Spending time on the scene talking to operators and personally observing the issues can do much to help interpret the data.

    Thanks for sharing.


  3. Much the same in my experience. My job for about 10 years has been measuring planning and measuring project performance. You could say, it’s all about the data. What my introduction to lean revealed, however, is that the data only indicates where a problem might be – it does not determine what that problem is.

    All those reports poured over in conference rooms never revealed the underlying problem behind an anomalous stat. At best, they gave a guidepost directing us where to look. At worst, they obscured the truth and we embarked upon an action that didn’t address the root cause.

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