Six Sigma is about reducing costly variation and achieving zero-defect performance.  A “defect” can be defined as any undesirable outcome – a product that does not work, a process that generates scrap, a disappointed customer, etc.  Dot plots are a great way to see data points and quickly compare two or more sets of data, without performing a single calculation.  Dot plots are easily constructed:  each dot represents a data point along an axis, and dots of the same value are stacked on top of one another.  Dot plots look very similar to histograms, but are easier to construct and can be more valuable for generating clues into potential causes.

There are a few different formats that dot plots can take, but the simple format noted below has worked well for us.  The example below came from a team working on a downtime reduction project (we’ve also seen dot plots used for comparing production tooling, machines, operators, etc.).  One of the team members suggested that the night shift crew generally experienced less downtime than the day shift crew, so the team collected downtime data and compared the two shifts.  One can see from the data that the suspected difference in downtime between the shifts was real.  A hypothesis test could have been conducted to ensure that the observed difference was statically significant, but there was so such much separation in the data that a hypothesis test was not needed in this case:

Take a another look at the above dot plot – do you see any clues that could ultimately lead to less downtime?  Here are a few possibilities:

• Night shift does outperform day shift consistently, and finding out why and confirming the findings through an experiment could create a major breakthrough for the project team.
• While night shift has significantly less downtime most of the time, there are a few outliers in the data where night shift experienced unusually high downtime – it would be worth going back through the data to understand the downtime-causes on those nights.
• Day shift shows some outliers on the “good” side of the distribution (days with unusually low downtime).  These are equally valuable in terms of understanding why and possibly applying some lessons-learned to standard work practices, etc.

The dot plots on this page were constructed with MINTAB® software, but dot plots can easily be constructed by hand in team meetings, and they are an excellent tool that can be utilized by Green Belts through Master Black Belts.  Dot plots are one of many tools in the DMAIC process.