Resource articles

Alternatives to knee-jerk reaction: Understanding variation

To get to the heart of an issue and begin appropriate improvement efforts, it’s critical to understand the difference between common-cause and special-cause variation, so the right actions can be taken

Capable? Who needs capability analysis?

Confusion about whether you need to apply standard methods of calculating capability sometimes means that this powerful statistical application is either applied when it isn’t needed, or not used when it would provide useful information. When is capability analysis called for, anyway? Some guidelines will help.

Extracting business value from data

Collecting data for one purpose often generates a response to other questions—if the data can be accessed.

Healthy control charts: What to look for in your charting software

If you are to garner useful information from your data, be sure that your software will offer that information. Here are some things to look for to assure that your control charts will be healthy and accurate.

Minding your g’s and t’s: Charting rare events effectively

Data analysis that focuses on the intervals between rarely-occurring events can diminish the chance of their recurrence.

Multiple control limits: A long shot, or just a bad slice?

In the world of continuous improvement, it might seem that one does not want to look back. After all, as systems improve, old data is no longer useful, and keeping it around—like keeping old love letters—may someday get you into trouble. However, knowing when to recalculate control limits is important, as quality managers know.

Pareto: The Ferrari of charts

While the name of Vilfredo Pareto, the Italian economist and sociologist, may not ring a bell in quite the same way that Enzo Ferrari’s name does, it is nonetheless true that Pareto’s contribution to data analysis may be commensurate to Ferrari’s impact on auto sports—at least in some circles.

Pick the right chart in three easy steps

Selecting the right chart is fundamental to control chart accuracy. If the wrong control chart is selected, control limits will not be correct for the data. Knowing this, facing the possibility of an array of control charts may engender confusion, if not panic. Should I create charts, charts, np-charts, n-charts, p-charts, c-charts, or u-charts? Who’s to know?

Six simple steps to sound sampling

Using correct sampling techniques will save time and money—and avoid destructive processes. The key is knowing what questions you want to answer, and going from there.

What kind of data? A quick-and-dirty guide to variables, attributes data

A simple distinction between the two.

Who moved the data? Transforming data into information

Useful data is everywhere these days: in the accounting office, sales department, lab, classroom, stock market, medical records office. In fact, it would be hard to find a department or business that does not have its cup running over with data.

Of course, the key to transforming data into information lies in the ways that the data is used. This starts with knowing where the data is stored, and how to make it accessible.

Why capability? And how?

Let’s face it: you may be avoiding capability analysis because it sounds too complex. Here’s why this important statistical analysis should be among the panoply of tools you need to assure quality of the products and services that your organization provides.