June 21 marked the beginning of summer, also known as the summer solstice. As a major celestial event, the summer solstice results in the longest day and the shortest night of the year. From here on out, we will have less daylight. It’s over folks, and frankly I haven’t even donned my bathing suit yet. Oh well, no one really wants to see a 66-year-old man in a Speedo anyway.

Be that as it may, and because I have signaled the end of extended daylight, there are a number of other items, issues, and events that have also reached their longevity. Did you see that iconic retailer Eddie Bauer has declared bankruptcy? It doesn’t appear that all the stores will close, but in my opinion it manifests another miscue on the part of management. Since 1920, Eddie Bauer has been a purveyor of sporting goods, outdoor apparel, and gear. It was the first company to use quilted goose-down to insulate a garment. Many of us, I’m sure, have seen or even used a down sleeping bag. I have a Gortex down-filled parka from Eddie Bauer that is more than 20 years old and still in great shape.

One of the most useful diagnostic tools for understanding what is going on in a process is the statistical process control chart (SPC).  This is also a frequently misunderstood tool, and these misunderstandings lead to misdirected effort during a Six Sigma process, resulting in lost time and money. All the questions related to these foiled efforts boil down to this, “I used my software to make a control chart, but the chart looks all messed up.  Why doesn’t SPC work?” 

It does, if you avoid some common pitfalls.  So today, I am kicking off a few articles about these pitfalls that I hope will make your projects less frustrating and more efficient.

No Measurement System Analysis

In my experience, the most common error in doing SPC is not performing a measurement system analysis first.  This is an occurrence that calls for a real head thumping on the desk (yours, or maybe the person’s who didn’t do the study, if you can get away with it).

"The only man who behaved sensibly was my tailor: he took my measure anew every time he saw me, whilst all the rest went on with their old measurements and expected them to fit me.”

—George Bernard Shaw

Can you think of a more rousing or appropriate quotation to justify the ISO 9001 requirements relating to monitoring and measuring? How about the requirements for periodic internal audits? Or management review?

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Things change. How can we possibly expect reliable outputs when we’ve failed to recognize that the inputs may not be the same? Not only is it possible that the requirements (inputs) may have changed; it’s equally likely that support processes, interrelated activities, and available resources may also have changed.

You know the fable, the Emperor who glorified in himself and considered no one to be above him. Having been told that the clothing he would be wearing could only be seen by someone wise, he proceeded to “wear” his new clothes. Not one of his trusted advisers dared tell him that he appeared to be completely naked (for fear of the Emperor’s wrath and wanting desperately to believe what they had been told by the Emperor himself, that only wise people could see his clothes). Off the Emperor went in a public display. Only when a child shouted out, was the truth made plain.

Imagine how often this plays out in the business world, with emperor’s wooed by their own sense of perfection, with underlings cowed into a permanent state of voicing admiration regardless of underlying thoughts to the contrary. Yes, emperors, that is, business leaders, can knowingly or unwittingly find themselves proudly wearing no clothes. Of course, there comes a day when a voice shouts the truth, and oh how quickly the facade is revealed. Sadly, we don’t have to look far today to see not just the cracking of the facade, but the crumbling of entire kingdoms. Look no further than the entire financial sector, with emperors and their entourages now cast as villains and nations on the verge of falling.

Charles Kettering, the famous inventor, once said: “A problem well stated is a problem half solved.” This implies that a good portion of problem solving should be devoted to a thorough understanding of what’s going on before any corrective action steps are taken.

In many cases, too much time is spent on proposing various solutions before the problem has been correctly defined. Observation is a powerful technique that can be used to help understand problems. Often, clues about how to solve a problem can come from simply observing the process. Following are a couple of examples.

One particular problem I was involved with concerned damaged product being received by an internal customer. A team had worked on the problem previously and had made the assumption that the root cause was due to shipping damage. They took measures to improve the packaging and better protect the product during shipment to the customer. This resulted in adding cost, but didn't protect the customer who continued to find defective product.

During the 1980s using flowcharts was the “in thing” to do. Today, technology has provided us with a much more effective and useful tool: simulation modeling. If a picture is worth a thousand words, then one that logically simulates tasks and collects data has to be worth a million. Simulation models have the capability of considering complex interrelated tasks and structurally projected outcomes in a matter of seconds, providing users with validated, and usually quite reliable, results.

Author Charles R. Harrell defines simulation as “a means of experimenting with a detailed model of a real system to determine how the system will respond to changes in its structure, environment, or underlying assumptions.” It allows for a better understanding of processes with a goal of improving performance. Simulation modeling provides a means to evaluate, redesign, and measure or quantify customer satisfaction, resource utilization, process streamlining, and time spent.

Recently a strategy consultant was overheard saying she writes romantic novels. Look into many organizations and, although said in jest, it has more than a modicum of truth to it.

Don’t get me wrong. The high-level strategic plans are important and necessary. But, the devil is in the details, the down-and-dirty task and activities that really make things happen. Back in 1999, a Fortune magazine study suggested that 70 percent of CEOs who fail do so not because of bad strategy, but because of bad execution. ("Why CEOs Fail," R. Charan and G. Colvin, Jun 21, 1999.)

Strategy implementation is an internal, operations-driven activity that involves organizing, budgeting, motivating, culture-building, supervising, and leading to make the strategy work as intended. It involves people understanding their role in the big scheme, how it links throughout the organization, and the impact it has along the way. Hoshin Planning is one methodology that helps organizations through this process. This tool helps to cascade out detailed work plans: it indicates how projects are to be led and resourced, shows linkages to the organization’s vision and mission, identifies the accountable or responsible parties, aligns the work plans, and indicates how progress and results will be measured.

Editors note: The author submitted this just days before he lost his job. What is ironic about this "rant," as Bruman puts it, is that it was written seven years ago. Do we never learn?

Recent months have brought disturbing news about the U.S. economy, the stock market, and business leadership in general. While some people try to blame it on an apparent moral decay on the part of our financial watchdogs and business leaders, I am here to say it’s not all their fault.

Yes, they ended up robbing from Peter to pay Paul, and yes they had to endorse what some people may call "creative" accounting practices to make the numbers all come out right. We would be unfair however, if we blame it on a lack of moral character, ethics, or greed. Our leaders have merely followed the same courses of action that seemed to work in the past, and what they were taught in many of our graduate business schools.

I will not attempt to detail all that was done in each of the Enron, World-com, QUEST cases, or any of the other past or emerging financial crises we’ve all witnessed these past few months. I will attempt, however, to draw your attention to some basic similarities that should point us toward some things we were warned about many decades ago by (of all people) Dr. W. Edwards Deming.

None of us, I suspect, are fond of visiting our physician, making an unexpected trip to the hospital emergency room, or undergoing an operation. From time to time, we hear about the unanticipated results of a botched operation where the wrong leg was removed or an incorrect diagnosis resulted in complications. On the other hand, the medical profession, day in and day out, performs intricate, complicated life-saving operations that go unnoticed to those outside of family members .

Last month we showed the X chart in figure 1. The four lowest values and the three highest values were seen to be “outliers” when we looked at the histogram. When we fitted a bell-shaped curve to the histogram, the outliers corrupted the model and resulted in a poor fit. Yet we used all the data to compute the limits seen in figure 1. How can the outliers corrupt one computation but not another?

The answer lies in how we compute limits for the X chart. The central line is commonly taken to be the average value. Now, while it’s true that the average may be influenced by extreme values, this effect is generally smaller than you might expect. In this case, deleting the seven outliers would only change the average from 595.4 to 595.6. The average value is a very robust measure of location. However, in cases where we think the average may have been unduly influenced by extreme values, we may always resort to using the median value instead. In this case the median is 596. Thus, one way or another, we’re going to have a reasonable estimate of location regardless of the outliers.