Tag: Process Behavior Charts

Here is a recorded webinar... I played host (along with KaiNexus) for this webinar that was held Tuesday, August 14 at 1 pm ET.

Here is a chart from a team in San Antonio, where I teach a class on Lean for quality and patient safety twice a year. This team was basically using the “A3” improvement methodology to look at a problem that really impacted patients. My understanding is that a contaminated blood culture bottle leads to false positive results that indicate that a patient has a bloodstream infection when they really don't.

I started my career in manufacturing, so that's just one reason I'm interested in the topics of offshoring (sending manufacturing work overseas) and what's now called "reshoring," or bringing jobs and factories back to the U.S. Somebody at A.T. Kearney sent me a link to their recent report on reshoring, with the headline: Reshoring in Reverse Again US manufacturers are not exactly coming back in droves. In fact, the 2018 Reshoring Index shows that imports from traditional offshoring countries are at a record high. When you learn to look at data and workplace metrics through the "Process Behavior Chart" methodology, you learn to be skeptical of text descriptions like "a record high." Does "a record high" mean that the data point is statistically meaningful? Not always.

Here is the recording of the webinar I told you about recently, with themes from my book Measures of Success. What is "management by emoji?"

Here is my latest article that I published on LinkedIn: Is the Reported Drop in Major League Baseball Attendance a "Signal" or "Noise" in the Data?

For a long time, I've wanted to attend a "Statistical Process Control" (SPC) class taught by Donald J. Wheeler, Ph.D.  I'm finally doing this in September and I'd like to invite you to join me.

I'm still working on my book Measures of Success, as I've mentioned here a few times.  The partial "in-progress" book is available through LeanPub.com. Or, when it's done, it will also be available through the Amazon Kindle bookstore and I will probably also produce a paperback version. My goal is to have the book done by the Lean Healthcare Transformation Summit in mid-June (hope to see you there at the Summit and/or my workshop on these topics).  Here is a recorded webinar that I did for my friend Mike Stoecklein and his organization, the Institute for Excellence (IEX).

Last week, I wrote Part 1 of this piece about TQM and "Small Kaizen" at a Japanese Hospital pharmacy. The hospital was happy that employees were participating in their "Small Kaizen" process, but there was a month in which they saw the number of submitted Kaizens drop, from about 138 to 58 or so. As I write about in Measures of Success, two data points usually don't make a trend.

Thanks to Eric Ries and the organizers for Lean Startup Week for allowing me to share video of my 15-minute talk from last year's event. One reason for sharing this today is to celebrate yesterday's initial release of the in-progress version of my book Measures of Success. If you buy the book now, you'll get a PDF of the first three chapters, or about 40% of the book's expected content.

Today, I’m giving a keynote talk at the Lean & Six Sigma World Conference being held in Las Vegas. I don’t normally attend or speak at “Lean Sigma” events, but I had an opportunity to give a new talk that touches on two of my favorite themes in recent years – the need to apply statistics and psychology to our “Lean Management” practices or Six Sigma or whatever.

Are minor league games taking longer? Well, yes and no, depending on the league. My next book, Measures of Success, is about the use of this Process Behavior Chart methodology in the workplace, as applied to our performance measures.  This post explores some data, how asking for more data can be more helpful, and how to use charts to evaluate a metric over time.

As I blogged about yesterday, things went well at the Oscars... or, at least, no errors were made in the announcements. But that thing that didn't go well was the TV ratings. Two Data Points Are Not a Trend The headlines I saw had a lot of two-data-point comparisons. Headlines sometimes gave the percentage decrease in viewers or how many million fewer viewers there were. Many talked about "record low" but if you're tracking a metric "record low" or "all-time high" doesn't mean there's a "special cause." That "record low" could still be noise in the system.