“In God we trust; all others must bring data.”

W. Edwards Deming

“It is a capital mistake to theorize before one has data.”

Arthur Conan Doyle

“When human judgment and big data intersect, there are some funny things that happen.”

Nate Silver

Quality is based on a series of facts and statistics collected together and analyzed. To produce a quality product—and continue producing a quality product—you need data. Data you can trust doesn’t simply appear; you need to collect it and then analyze it properly. Luckily, there are several tools available to you for this use. For the sake of this article, we will take a look at three you may or may not be familiar with.

Box and Whisker Plot

Imagine you have multiple machines creating the same product. You want to know which are most effective. An applicable, easy and graphical method for displaying data variation is the box and whisker plot. The advantage of the box and whisker plot—over another helpful tool, the histogram—is that multiple sets of data are displayed on the same graph. Before you plot your data set you need to determine the following numbers:

• Minimum value—smallest value in the data set
• Maximum value—largest value
• Median value—middle number in the range (when set has an even number of values, the median is calculated as the average of the two middle values)
• Second quartile—the value at which the lower 25% begins
• Third quartile—the value at which the upper 25% begins

Once you plot the numbers, you find the range for each set (unlike the frequency of each number, as you do in a histogram) and can easily determine which machine is producing the better product. To download a box and whisker plot template, visit the ASQ Learn About Quality page (asq.org/learn-about-quality).

Control Chart

While keeping track of your organization’s equipment and product is important, you need to collect and analyze data for your processes as well. To do that, try a control chart. The control chart graphs the changes within a process over time and can serve many goals. Use a control chart when you want to:

• Find and correct process problems as they occur
• Predict the expected range of outcomes
• Determine if a process is stable or unstable
• Analyze whether patterns of process variation stem from special (non-routine) or common (built into the process) causes
• Determine whether to make fundamental changes or prevent specific problems