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DATA SANITY: A Quantum Leap to Unprecedented Results

What they’re saying about Davis…

"I was fortunate to select your presentation at the patient safety academy today and was delighted!  Informative and insightful you were able to put data analysis into a wonderful perspective.
Thank You for probably the smartest, funniest and most useful program on QI that I have ever attended. When you think about special vs common cause it just makes good “common” sense.
Thank you for the program today - it was a refreshing and energizing alternate approach to our current morass of indicators, benchmarking and flashing colored lights to please the board...Your presentation of the Provider level C-Section data gave me a double take."

"Thank you so much for your presentation today.  I really learned a lot and I'm excited to take it back and apply it to my organization."

"Thank you so much for the conference today,  great information that I can put to use right away.  Enjoyed it very much."

"Wonderful presentation today; I feel less intimidated working with stats than I did prior to attending."

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A Statistician’s Favorite Answer: ‘It Depends,’ Part 1

Quality improvement people sure love those tools. A particular favorite, of course, is the control chart, of which, I think, seven are usually taught. Two questions I’m always asked are, “Which chart do I use for which situation?” and “When and how often should I recalculate my limits?”

Wrong questions!

Regarding the first (we’ll deal with second question in part 2), I’ve seen many flowcharts in books to help you determine which chart to use for which situation. I find them far too confusing for the average user. (They even give me sweaty palms.) I don’t even teach this in my work.

Uh-oh… Time for the (Dreaded?) Third Quarter Review Meeting

You know what the third-quarter review meeting means: a packet will be handed out  with bar graphs and, no doubt, trend lines on each of about a zillion “key performance indicators” that show:

• This month vs. last month vs. 12 months ago (maybe year-to-date as well)
• The three months’ performance of the current quarter
• The first three quarters of the year
• This quarter vs. last quarter vs. third quarter a year ago

Time to Lose the 10-Minute Overview

I attended a talk in 2006 given by a world leader in quality that contained a bar graph summary ranking 21 U.S. counties from best to worst (see figure 1). The counties were ranked from 1 to 21 for 10 different indicators, and these ranks were summed to get a total score for each county (e.g., minimum 21, maximum 210, average 110. Smaller score = better). Data presentations such as this usually result in discussions where terms like “above average,” “below average,” and  “who is in what quartile” are bandied about. As W. Edwards Deming would say, “Simple… obvious… and wrong!” Any set of numbers needs a context of variation within which to be interpreted.

Are You Becoming a ‘Qualicrat?’

During my recent travels, I have noticed an increasing tendency toward formalizing organizational quality improvement (QI) efforts into a separate silo. Even more disturbing is an increasing (and excruciating) formality. Expressions such as “saving dark-green dollars” are creeping into justifications for such “programs,” usually referred to as Six Sigma, lean, or lean Six Sigma. As always, Jim Clemmer pinpoints this trend perfectly:

“The quality movement [has given] rise to a new breed of techno-manager—the qualicrat. These support professionals see the world strictly through data and analysis, and their quality improvement tools and techniques. While they work hard to quantify the ‘voice of the customer,’ the face of current customers (and especially potential new customers) is often lost. Having researched, consulted, and written extensively on quality improvement, I am a big convert to, and evangelist for, the cause. But some efforts are getting badly out of balance as customers, partners, and team members are reduced to numbers, charts, and graphs.”

Given Two Numbers, Only One Can Be Larger

Customer satisfaction data resulting in various quality indexes abound. The airline industry is particularly watched. The April 10 Quality Digest Daily had an article with the title “Study: Airline Performance Improves” and the subtitle “Better on-time performance, baggage handling, and customer complaints.”

The analysis method? In essence, a bunch of professors pored over some tables of data and concluded that some numbers were bigger than others…and gave profound explanations for the (alleged) differences. If I’m not mistaken, W. Edwards Deming called this “tampering:” They treated all differences (variation) as special cause.

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