“Our evolutionary instincts sometimes lead us to see patterns when there are none there. People have been doing this all the time – finding patterns in random noise.” – Tomaso Poggio
People just need a way to separate the Signal from the Noise.
Here are some insights from the book by Nate Silver.
People often get stuck before the “Analyze” phase of DMAIC because of ugly data.
You can’t analyze data until it is in the right format for analysis.
In this data about medications that might affect patient falls, we have to:
You can watch the video below:
Continue Reading "It’s Hard to Do Data Analysis on Ugly Data… Part 2"
This recent article talks about how GE measured Six Sigma success:
“Engineers and scientists were measured on how many Six Sigma projects they completed during the year.”
Since I know that 4% of the business is causing over half of the waste, rework and lost profit (the 4-50 rule), making everyone do “Six Sigma projects” is a form of overproduction (violating a Lean rule). It creates waste, rework and unhappy employees. It makes people put trivial improvements in Six Sigma format to achieve the goals.
Measure Six Sigma success by bottom-line, profit and productivity enhancing results, not projects. Use data to focus improvements to maximize results and minimize effort.
Lean Six Sigma Fundamentalists believe:
– Get management commitment
– Train lots of black and green belts
– Implement wall-to-wall floor to ceiling
Lean Six Sigma Revolutionaries believe:
-Engage informal leaders
-Train money belts
-Laser-focused, data-driven breakthrough improvements
Continue Reading "Lean Six Sigma Fundamentalists vs Revolutionaries"
The next time you hit a glitch are you going to
0. Ignore it
1. Find a work around
2. Take heroic action to fix it.
3. Fix the glitch and then take the time to prevent it from ever happening again?
The July/August 2017 HealthLeaders magazine had a series of charts about the impact of Adverse Events. In general, the magazine used column charts:
But wouldn’t a Pareto chart illuminate the important adverse events more clearly? The first three accounted for over 57% of 2013 deaths.
Continue Reading "Excel Bar Charts Hide The Signal in Noise"
I have found that an XmR chart is the easiest way to display attribute data. Simply convert the numerator/denominator into a ratio and plot the ratio.
Almost two decades ago, Tom Pyzdek said: X chart provides an excellent approximation to the p chart.
More recently, Donald Wheeler noted that XmR chart limits will be very close to c, np, p or u chart limits if the underlying distribution is correct.
Continue Reading "Use XmR Charts instead of c, np, p and u Charts"
Customer asked me what seemed like a strange question: What specification limits do I need to get a Cp greater than one? Usually her customer should set specification limits, but her boss wanted to know what they could deliver. Hmmmm!
Then I realized that since QI Macros templates (e.g., XmR chart) calculate the average and sigma estimator, the LSL/USL for Cp = 1.0 would be:
LSL = Average – 3*SigEst USL = Average+ 3*SigEst
For Cp = 1.33, just change the 3 to a 4; Cp = 1.66, change the 3 to a 5. Here’s an XmR chart template with some sample data and calculations to reverse engineer spec limits:
Early in the movie, the McDonald’s brothers describe how they came up with the concept for speedy service. It’s Lean.
They had too many menu items, so they decide to simplify down to burgers, fries and soft drinks. (Think Lean inventory.)
They go to a tennis court and use chalk to lay out a possible floor plan to deliver service fast. One brother stands on a ladder watching while the employees pantomime cooking burgers, fries and soft drinks.
They go through several iterations to converge on their final design. (Think value stream mapping and spaghetti diagramming.)
I think they might have done it faster with cardboard boxes, but I wasn’t there.
Many people avoid Six Sigma because they think it involves a lot of math and statistics. You know, formulas. I don’t think you need any formulas. You don’t need to be a statistician. You just need software that went to college and knows the formulas.
In The Math Gene, Author Keith Devlin explores “why so many people find mathematics impossibly hard.” He says: mathematics is the science of patterns. Isn’t that what we’re trying to do in Six Sigma, separate the wheat from the chaff, separate the signal from the noise and detect the underlying patterns of performance?
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