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By Quality Digest

Misadventures in Big-Box Land

Regarding “Big Boxes Beware” (“First Word,” Dirk Dusharme, November 2008): If you want to experience grocery-industry customer service at its finest, visit Wegmans. Their employees will load your groceries in your car for free, provide umbrellas for trips to your car in the rain for those who don’t have one, and personally take you to the items that you’re looking for when you can’t find something.

Those needing a lesson in customer service should shop there a time or two. They will learn what service is all about.

--Chris Wallen

 

Hear! Hear! My boss was commenting today that he went to “Wally World” on his way to work and tried to buy light bulbs. First of all, he was looking for 100-watt bulbs and the closest that they sell now are the 90-watt kind.

When he went to check out, the register sign was lit up, but no one was there to run the register. He stepped back far enough to see two workers stocking an end cap. They looked his way three times and still went back to stocking.

On the third time, my boss said he even waved at them so that they would see movement at the register. Needless to say, when he left, the light bulbs were still on the counter.

--Mike Janes

 

Donald J. Wheeler’s picture

By Donald J. Wheeler

Many have been taught that they must remove outliers prior to analysis. This is because much of modern statistics is concerned with creating a mathematical model for the data. Because all these models are created using algorithms, they tend to be severely affected by any unusual or extreme values.

Therefore, to use these mathematical techniques to obtain useful and appropriate models, it’s often necessary to polish up the data by removing the outliers. However, the act of building a model implicitly assumes that the data are homogeneous enough to justify the use of a model.

For example, the histogram in figure 1 has a bell-shaped curve superimposed. This curve is based on the average and standard deviation statistic for all 100 values in the histogram. It’s neither wide enough nor tall enough to provide a good fit to the data. The histogram in figure 2 contains the 93 values left after the seven extreme values (the four lowest and three highest) were deleted. Now the curve based on the average and the standard deviation statistic does a much better job of fitting the data. Thus, it’s true that outliers can undermine our efforts to create a model for our data.

Nicolette Dalpino’s default image

By Nicolette Dalpino

Quality Digest’s picture

By Quality Digest

Short on News

Federal Reserve Chairman Ben Bernanke said that financial institutions must address the “fundamental sources of financial strains” in Wall Street’s credit crisis by deleveraging, raising new capital, and improving risk management.
www.thestreet.com/markets/bonds-economy/10416480.html

 

The naval Surface Warfare Center is leveraging Actuate Corp.’s Performancesoft suite to underpin its Malcolm Baldrige and lean Six Sigma performance management efforts.
www.earthtimes.org/articles/show/
naval-surface-warfare-center-lever ages,
389822.shtml

 

Nicolette Dalpino’s default image

By Nicolette Dalpino

HEADLINES 

 

2008 Global Productivity Report

According to the “2008 Global Productivity Report,” the recent annual report from Proudfoot Consulting, staff shortages and internal communications problems are the main barriers to productivity around the globe, with staff shortages cited as the main barrier in the United States. Although companies in emerging markets such as Brazil, Russia, India, and China are most likely to have seen recent gains in productivity, North American executives are the least optimistic about their chances of increasing efficiency, stating that more than 40 percent of potential improvements will remain untapped.

Dirk Dusharme @ Quality Digest’s picture

By Dirk Dusharme @ Quality Digest

This issue is the first of three consecutive CMSC show-focus issues that highlight the yearly Coordinate Metrology Systems Conference. The CMSC is the largest U.S. trade show focused solely on large-scale 3-D metrology. Attendance has grown each year, with last year reaching nearly 600 attendees. All the key players in large-scale 3-D measurement are there representing every large-scale 3-D measurement technology, including laser scanners, structured-light scanners, laser radar, photogrammetry, theodolites, articulated arms, indoor GPS, and more.

Our CMSC cover story this month focuses on the use of articulated arms (portable coordinate measurement machines) to align collimators at CERN’s Large Hadron Collider in Switzerland. Steering two high-energy beams traveling in opposite directions around a 27 km-circumference accelerator so that they collide head on at a predetermined point requires the most accurate in 3-D metrology equipment. You can read how they did it starting on page 22.

Quality Digest is proud to have been the sole media sponsor for the CMSC show for four years, and we look forward to continuing our coverage of the ever-evolving field of large-scale 3-D metrology.

Dirk Dusharme @ Quality Digest’s picture

By Dirk Dusharme @ Quality Digest

It’s almost like some retailers finally read the memo. They seem to now understand that customer service is the new differentiator. With quality levels and prices across almost all product categories nearly at par, it’s service that sets retailers apart--and smaller retailers have taken note.

I was recently at a new Safeway supermarket looking for dried currants. I asked the nearest floor person where I could find them, expecting a simple “look at the end of aisle 10.” Instead, the clerk told me she wasn’t sure but she could find someone who would know. She came back with a young guy in tow who walked me to the produce department and helped me find the product. This has happened numerous times recently at Safeway, Raley’s/Bel Air, Trader Joe’s, and a few other national and regional retailers. In fact, this rush to help almost seems to have happened overnight.

Sometimes the service has been almost embarrassing. I almost felt bad when a Raley’s employee spent 15 minutes helping me find tahini. I mean, neither of us even knew what it was, but there we were, marching up and down the aisles just so I could satisfy my wife’s craving for homemade hummus.

Davis Balestracci’s picture

By Davis Balestracci

Eighty-four doctors treated 2,973 patients, and an undesirable incident occurred in 13 of the treatments (11 doctors with one incident and one doctor with two incidents), a rate of 0.437 percent. A p-chart analysis of means (ANOM) for these data is shown in figure 1.

This analysis is dubious. A good rule of thumb: Multiplying the overall average rate by the number of cases for an individual should yield the possibility of at least five cases. Each doctor would need 1,000 cases to even begin to come close to this!

The table in figure 2 uses the technique discussed in last month’s column, “A Handy Technique to Have in Your Back Pocket,” calculating both “uncorrected” and “corrected” chi-square. Similar to the philosophy of ANOM, I take each doctor’s performance out of the aggregate and compare it to those remaining to see whether they are statistically different. For example, in figure 2, during the first doctor’s performance, one patient in the 199 patient treatments had the incident occur. So, I compared his rate of 1/199 to the remaining 12/2,774.

by Nicolette Dalpino and Carey Wilson’s default image

By by Nicolette Dalpino and Carey Wilson

Short on News

NIST has developed the first detailed chemical analysis revealing what processing is needed to transform crude oil made from pig manure into fuel for vehicles and heating.
www.nist.gov/public_affairs/
techbeat/
tb2008_0610.htm#crude

 

The average refrigerator sold today consumes less energy than a 60-watt light bulb left on 24 hours a day.
www.aham.org/ht/a/
GetDocumentAction/i/34442

 

Donald J. Wheeler’s picture

By Donald J. Wheeler

As Davis Balestracci frequently emphasized in his column, “RealWorldSPC,” published in Quality Digest for four years, it is fundamental to understand the context of the data before you begin to do any computations. It is the background for your data that determines how you should organize the data, how you should analyze the data, and how you should interpret the results of your analysis. Once you ignore the context, you’re like a train that has gone off the track, with the inevitable result.

One day a company sent me some data that it had spent more than a month collecting. These data represented the results of an experimental study carried out using production batches. For each of 30 batches the company recorded all sorts of production information, along with the experimental conditions that applied to that batch. At the end of the production process it took 40 items from each batch and measured the property of interest. Thus, it had a total to 1,200 values: 40 values for each of the 30 batches.