Lean Six Sigma Moneybelt - Page 67 of 74

Improvement Insights Blog

Latest Posts

Use XmR Charts instead of c, np, p and u Charts

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.

  • defects per day could be a c chart, but an XmR chart works just as well
  • defects/samplesize could be np, p or u chart, but XmR chart works just as well using 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.

Posted by Jay Arthur in QI Macros, Six Sigma, Statistics.

What USL/LSL Do I Need for Cp>1?

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:

Cp-to-LSL-USL

 

Posted by Jay Arthur in QI Macros, Six Sigma, Statistics.

Cpk and Hard vs Specification Limits

A customer called upset about Cpk. He had a runout of 0.010, but was getting a very low Cpk. Turns out he’d made the classic mistake of confusing a hard limit (e.g., zero) with a specification limit. I had him use QI Macros with an Upper Specification limit (USL) and no Lower Specification Limit (LSL). His Cpk immediately jumped to a more expected value of 1.78.

Later in the day another customer asked why Cpk is calculated as the minimum of the upper or lower Cpk? Because you use the one closest to the average. I think that customer may have had the same problem, confusing a hard limit with a specification limit.

Posted by Jay Arthur in QI Macros, Six Sigma.

Lean Insights from “The Founder” Movie

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.

Posted by Jay Arthur in Healthcare, Lean, Manufacturing, Service.

Is Fear of Math Holding You Back?

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?

Posted by Jay Arthur in QI Macros, Six Sigma.

The Great Training Robbery

October 2016 HBR article, Why Leadership Training Fails-and What to Do About It, calls the $160 Billion spent on training in the U.S. the Great Training Robbery. The authors say: “Learning doesn’t lead to better organizational performance, because people soon revert to their old ways of doing things.”

Unfortunately, this is true of most Six Sigma training courses. If you don’t apply what you’ve learned immediately to reducing delay, defects and deviation, the learning is lost in 72 hours.

That’s why my Lean Six Sigma workshops focus on solving real problems using existing data. Once people connect the methods and tools to results, it’s hard to go backward.

Posted by Jay Arthur in Healthcare, Lean, Manufacturing, Service, Six Sigma.

Nobody Wants to Read Your Spreadsheet!

Nobody wants to read your spreadsheet! No matter how hard you try to make it pretty, create great labels or whatever, the only person who can read your spreadsheet is a CFO or Excel spreadsheet geek. And the Excel geek is going to tell you 10 ways to make it prettier.

The purpose of data is to provide insights for action, not just report past performance.

How Do I Know That Most Excel Users Try to Make Their Spreadsheets Readable By People?

According to Renu Davi, Sr. Program Manager for Excel, Microsoft tracks how people use Excel. The vast majority of the 650 million users use it for lists and reports.

Posted by Jay Arthur in Data Mining, QI Macros, Six Sigma.

Why Six Sigma Fails

Over the last 25 years, I’ve gotten to see Six Sigma failures and successes. But in spite of all of the belts trained and investments made, why isn’t product and service quality any better? Why is there so much hassle? Why aren’t more customer experiences hassle-free? I’ve developed a mental list of the most common types of failures. Here’s my fishbone diagram for Six Sigma failures. I’d encourage you to develop your own.

six-sigma-failures-fishbone

80% of the businesses in the U.S. are service businesses, yet Six Sigma training is extensively focused on the manufacturing factory floor. It takes too long to teach people everything they might need to know to solve all of the problems they might ever encounter.

Posted by Jay Arthur in Healthcare, Manufacturing, QI Macros, Service, Six Sigma.

Mistake-Proofing Simplified

urinal-mistake-proofing

Posted by Jay Arthur in Jay Arthur Blog.

Users Barely Using Excel

Renu Davi, Sr. Program Manager for Excel, reported at Excelapaloosa that two-thirds of the 650 million users use Excel to make lists. The other third of users do deeper analysis, but I’m wondering how? Microsoft keeps tabs on Excel usage. Here’s some statistics for usage in an Excel workbook:

  • Only 4.3% have a function like SUM(A1:B2)
  • 7.5% have Pivottables
  • 17% use Freeze Panes
  • 54% use Merged Cells (instead of Center Across Selection which works much better in many ways)

I wonder why we need any new features if the vast majority of users don’t or won’t use them. Maybe we need to invest in teaching people how to use the Excel features they have.

Posted by Jay Arthur in QI Macros, Statistics.