When looking at a line chart for an important metric, people often panic when the line goes down and celebrate when it goes up, even though those fluctuations can—and often should—be ignored because they're just random "noise" that doesn't need to be acted on.

There are, of course, also times when a metric genuinely does require attention because it's behaving in way that indicates that something meaningful has occurred and that action may be warranted.

Is there a way to tell the difference between random fluctuations that can be ignored and meaningful patterns that require action? When I first came across XmR charts a number of years ago via Stephen Few, it was a real revelation because they do exactly that. No more pointless panicking or celebrating!

Steve first discovered XmR charts (as far as I know, anyway) via Stacey Barr, a world-renowned expert on performance measurement and improvement, which is one reason why I was thrilled when Stacey asked if I'd be up for trying to improve the design of the XmR charts that she's been using for many years in her globally recognized courses and books.

While the chart design that she's been using worked well, I was able to suggest about a dozen small improvements to make it more visually obvious and self-explanatory.

Stacey and I recorded a video in which she briefly explains XmR charts, and I then review the various improvements that I proposed, along with my reasons for suggesting those changes. You can watch the video below and check out Stacey's blog post about the new chart design.

As a bonus, Power BI guru Greg Deckler created this super-helpful video that explains how to create the new XmR chart design in Power BI.