When you are in the consulting and training business long enough, very interesting patterns pop up from time to time. Since we last talked, I’ve found myself hopping all over North America the past few months helping many people learn about and implement an Op-Ex method called Lean.

One nice attribute of Lean is it includes a lot of tools people can learn in just a few minutes and put to use right away. I have been very proud of many of the people in my workshops taking what they just learned and applying it to make immediate impact in their lives and in very creative ways.

If you’ve never heard of Lean, there are many fine books out there, but a couple techniques you may want to start with right now include simply understanding the 8 types of waste, identifying waste in your processes, and chasing it out of your life. Also, 5S is a technique for preparing your physical workplace to be more efficient that can be learned and applied very quickly. Types of waste were covered in our July, 2012 e-zine (follow the E-zine Archive link in the sidebar) and a quick explanation of 5S can be found here.

Are you already an old-hand at Lean? How have you applied it? Please share your story with us and you may be featured in an upcoming issue – simply follow the sidebar link under the Contact Us banner to shoot us an e-mail with your story – we’d love to hear it!

Have an excellent month!

Best,

Jeff Cole

President

JCG Management Consulting

Does Your Project Suffer from the Hawthorne Effect?

In the 1920’s an interesting experiment was conducted in Western Electric’s Hawthorne, IL plant. Someone suspected there might be a relationship between the lighting levels and productivity. In short, the legend goes like this: The team went in, increased the lighting and workers got more productive. Great news!

They increased the lighting some more and the workers got even more productive. Excellent. End of experiment. They turned the lighting back down and the workers got even more productive! Bottom line: it turns out that when people know they are being observed, they behave differently. The phenomenon was christened “The Hawthorne Effect” by Elton Mayo in the 1950’s. Makes sense. Someone with a clipboard and stopwatch shows up at your workstation and says “Don’t mind me – just keep working.” Kind of hard to behave normally with this character staring at you. Unfortunately for many of us using methods like Lean, we are the guys with the watches and clipboards. What can we do short of hiding behind a potted plant to take our observations?

In some places like call centers (“this call may be monitored ...”) many measures can be taken transparently.
Let people know in advance that they will be observed at some point, answer their questions, and take care to ensure it’s not positioned as anything threatening to the workforce.
Use measurement personnel who are trusted by the workforce.
Understand that your first few measurements may be “off” as the people get accustomed to being observed. Take repeated measurements over an extended period of time if possible so the measurement task blends into the background.

Monty Python & Guided Missiles

What do Monty Python and guided missiles have to do with Operational Excellence? Quite a lot as it turns out. Do you know John Cleese – the tall fellow in the Pythons? Did you know that for decades he has run a successful business on the side making humorous business training videos?

One of his videos involves Cleese addressing a group of corporate managers and his topic is “Gordon the Guided Missile”. In a humorous fashion, Cleese explains that guided missiles are actually off-course over 90% of their journey. However, in the end they hit their targets because thousands of times a second they are running through a Plan-Do-Check-Act (PDCA) cycle. They site in a target and launch (Plan and Do). They then constantly monitor, detect they are off course, and adjust (Check and Act). In the end they consistently hit their targets.

PDCA has been around since 1925, when Walter Shewhart invented it at AT&T Bell Labs. Sometimes called the Continual Improvement Cycle, it is one of the simpler models for improving over time. For some quick tips on using PDCA to drive change, click here. To preview Cleese’s video, click here.

How Much is Poor Quality Costing You?

We all know that organizations with poor quality must pay a price, but how big is that price tag? According to a past ASQ/Gallup poll, 70% of executives either didn’t know their cost of poor quality (COPQ) or believed it was less than 5%. According to an Ernst & Young study, the typical COPQ for U.S. companies is between 20-30%.

That’s quite a gap between perception and reality! COPQ is often calculated as a % of sales for manufacturing firms and as a % of operating expenses for service organizations. Here are a few COPQ estimates from various authors based on their experience:

· Mikel Harry: 15-20% of sales is industry average

· Phil Crosby: >20% of sales for mfg; 35% of operating exp for service

· Joseph Juran: 5-35% of sales for mfg & 25-40% of operating expense for service depending on the complexity of the service or product

· Jay Arthur: Typical company COPQ is 25-40% of sales

While authors vary in their estimates, they are roughly in the same ballpark. How much extra in sales do you need to generate each year to cover your COPQ? How much of your service operating budget is going down the drain due to waste, defects, and rework? Happy number crunching!

Link of the Month

Looking to go beyond Excel to conduct some analysis? Maybe you need to brush up on a statistical concept? Rice University psychology professor David M. Lane has put together a set of free online tutorials and tools for

statistical analysis that should help. Called the Hyperstat Online Textbook, it contains free lessons, interactive demonstrations, and an extensive list of free statistical analysis tools. Visit the site by clicking here.

Negative Cycle Times and Sanity

In my seminars I often tell students “there’s something to be said for having a healthy level of suspicion regarding data.” A recent client shared a great example. He ran a first-responder call center with software that automatically measured call response and transfer times. When he plotted the data, it skewed to the right in a textbook fashion (just as it should). One minor problem – it actually showed some negative cycle times!

He got out the formulas that defined when the clock should start and stop on a call. He then audited a number of calls, manually timing them. When he compared the manual vs. automated measures for his audit, he found the automated system was off (actually way off). Lesson learned – just because numbers come out of a computer, it does not guarantee they are accurate.

It can be just as bad with “subjective” measurements. In a 1973 experiment, psychologist David Rosenhan sent sane volunteers to mental institutions and every single one was diagnosed with a psychiatric disorder. One institution complained about the experiment and challenged him to send more volunteers to see if they would be detected. Rosenhan then claimed to send in 193 additional sane volunteers, of which the hospital “caught” 41 that they identified as sane. It wasn’t until the results were in that Rosenhan revealed that he had lied – he had not sent in a single sane volunteer. Not only did the hospital misidentify sane people in round one, they failed to identify disorders in round two!

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