Tag Archives: guest post

Remembering Peter Scholtes

Guest Post by Fazel Hayati

Fall always reminds me of my friend Peter Scholtes. It was during 2008 annual Deming Institute fall conference in Madison, Wisconsin when Peter said farewell to his friends and colleagues. He gave a keynote titled Deming 101 (that full speech can be watched online). Although inactive for many years and managing numerous health challenges, he was sharp, witty and very happy to be talking about Dr. Deming, systems thinking, problems with performance appraisal, talking to his old friends and reminiscing. Anticipating this event had really energized him. He told me numerous times he was very grateful for the opportunity. He passed away in July 11, 2009.

Peter Scholtes, 2008

Peter Scholtes at Deming Conference in Madison, Wisconsin, 2008

Peter wrote two seminal books, both remain relevant years after their publication. The Team Handbook remains one of the best in developing teams and it has helped many organizations to improve quality and productivity through team building. The Leader’s Handbook is one of the best elaborations on Dr. Deming’s System of Profound Knowledge.

Peter articulated Dr. Deming’s teaching and incorporated his own experience in six competencies for leaders:

  1. The ability to think in terms of systems and knowing how to lead systems,
  2. the ability to understand the variability of work in planning and problem solving,
  3. understanding how we learn, develop, and improve; leading true learning and improvement,
  4. understanding people and why they behave as they do,
  5. understanding the interaction and interdependence between systems, variability, learning, and human behavior; knowing how each affects others (Figure 2-16, Page 44, Leader’s Handbook),
  6. giving vision, meaning, direction, and focus to the organization.

No one has done a better job of operationalizing Dr. Deming’s teachings.

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Your Purpose Must Be About You

Guest post by Jurgen Appelo

I’m a writer. It’s the one thing that I intend to do for the rest of my life. That means, when I focus on writing, I cannot focus on knitting. Somebody else will have to do the knitting, so I can focus on the writing. And maybe later, I can trade my wonderful book for someone’s beautiful sweater. This concept applies to all other professionals too. Everyone is entangled in a web of economic dependencies, and therefore, the purpose you choose for yourself should somehow generate value for the others around you. Or else nobody will give you a knitted sweater.

This all makes perfect sense to complexity scientists, who have known for a while that complex adaptive systems find a global optimum through local optimizations and interdependencies. (At Home in the Universe by Stuart Kauffman) The parts in a complex system all try to optimize performance for themselves, but their efforts depend on the dependencies imposed on them by the parts around them. With a mix of competition and collaboration, the parts interact with each other without any focus on a global purpose. Nevertheless, the end result is often an optimized system. Biologists call it an ecosystem. Economists call it an economy. I call it common sense.

Putting the “Why” in Your Mission Statement

Most management scholars and experts have ignored the insights from the complexity sciences (or are unaware of them) and some have suggested goals for teams, and purposes for businesses, that are too narrow. There are many corporate mission statements in the world expressing ideas such as, “Make money for shareholders”, “Put customers first”, and “Achieve superior financial results” (The Leader’s Guide to Radical Management by Stephen Denning). In each of these cases, the purpose of the organization is (too) narrowly defined as providing value to one type of client or stakeholder.

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Analysis Must be Implemented by People to Provide Value

Guest Post by Bill Scherkenbach

photo of W. Edwards Deming with a cat

Every time I look at this picture, I think of Dr. Deming’s words to drive out fear and take joy in your work. We were talking in my home office when Sylvester saw a good lap and took it. Our conversation immediately shifted when both Dr. Deming and Sylvester started purring.

The greatest statistical analysis is nothing if it can’t be implemented by people. But people learn in different ways. Some like good stories, others like pictures. Only a few like equations. Dr. Deming always liked a good laugh; and a good purr.

By what method do you get your analyses implemented?

Bill Scherkenbach taught with Dr. Deming at the Deming 2 day seminars and received the Deming Medal and the author of several books on Deming management principles.

Related: How to Get a New Management Strategy, Tool or Concept Adopted part 1 and part 2Getting Known Good Ideas AdoptedRespect People by Creating a Climate for Joy in WorkPlaying Dice and Children’s Numeracy

You are a Fool if You Do What I Say

Guest post from Mark Graban

There’s an interesting quote from Taiichi Ohno in “Taiichi Ohno’s Workplace Management,” which I was re-reading today…

“You are a fool if you do what I say. You are a greater fool if you don’t do as I say. You should think for yourself and come up with better ideas than mine.”

The best examples of Lean in healthcare are examples where leaders and organizations learned, but did not blindly copy. Sami Bahri DDS (the “lean dentist”) read Deming, Shingo, Ohno, etc. and had to figure this out himself, rather than copying some other dentist.

ThedaCare is the first to say “don’t directly copy what we do.”

We can learn from others, run our own experiments to see what works, and keep improving to make it better than even Ohno or Shingo would have imagined.

Related: Two resources, largely untapped in American organizations, are potential information and employee creativityRespect People by Creating a Climate for Joy in Work

Value Stream Mapping for Fun and Profit

Guest post by Evan Durant, author of the Kaizen Notebook blog.

I tend to get a little preachy about the importance of value stream maps, but they really can be useful tools not only to plan an improvement effort but also to monitor your progress going forward. In particular they provide a way to quantify the impact of changes to your process. Here’s a real life example as a case in point.

For a particular value stream a team went to gemba, followed the flow of material and information, collected process cycle times, and counted inventory. When everything was mapped and all the data tallied, here was the current state that they came up with:

Total Lead Time:
   
16.8 days
Process Lead Time: 2.2 days
Process Time: 1.9 days
Operator Cycle Time: 8.2 minutes

So what does all this mean? First of all the Total Lead Time represents the amount of time that a new piece of raw material would take to enter the value stream, be worked on, wait around with all the rest of the material in process, and then finally make its way to the customer. This number is usually driven higher by large amounts of in-process inventory caused by pushing between operations.

Second, the Process Lead Time is the amount of time it would take to process a single batch through the process, if it didn’t have to wait behind any other batches. Note that even though parts are processed one at a time through all of the manual operations, a certain amount of batching is required to overcome long machine cycle times in automatic operations. Also we do not ship parts to the customer one at a time, but rather in standard package sizes.

Third, we have the Process Time. This is the total amount of value added time, manual and automatic processing, that a part sees in the value stream.

Finally the Operator Cycle Time (also called manual time) is the amount of actual “touch” time required to make a part. The difference between the Process Time and the Operator Cycle Time is the Machine Cycle Time (also called automatic time). This is when a batch of parts is on a machine that does not require any operator intervention during a cycle. (We have a lot of machine cycle time in this value stream.)

Then the team applied the concepts of flow and pull to reduce overproduction and pace the value stream to the rate of customer demand. The results of the future state map were as follows:

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The Impact of Leadership on Business Outcomes

photo of Joe Folkman

Joe Folkman

Guest post by Joe Folkman

Have you ever been part of an organization where things were proceeding smoothly, where goals were achieved, people were busy and the organization was doing well? Then, a new leader came and everything suddenly changed for the better. The energy level of employees went up substantially, pride in the organization increased, the effort and dedication of individuals jumped, bold objectives were enthusiastically accepted and even greater results were achieved. The differences were not only measurable by the accountants, but everyone could feel it.

Perhaps you had the opposite experience where things were things were going along smoothly and a new leader was introduced and things quickly began to fall apart. High performers quit, conflicts became more apparent, work seemed much less important and there was no fun. Colleagues skulked into corners, not wanting to be engaged. Overall satisfaction decreased. Grousing and carping criticism of the leaders became rampant. People receiving promotions were chosen because of politics, not performance. Management decisions felt arbitrary and unfair. Results began to slide, and employees became the cause of the problems as much as the economy or market conditions. Key employees were laid off while the remaining people were asked to carry a bigger load. Results continued to decline, and your job felt increasingly harder and you found yourself beginning to think about quitting.

Those who have experienced great leadership or poor leadership have felt the difference. Could these changes have been predicted? Are there clear correlations between the effectiveness of a leader and the success of an organization?

Case Study on the Impact of Leadership on Customer Satisfaction
A large telecommunication company was focused on an effort to improve customer satisfaction ratings. The company wanted to know which factors impacted the customer satisfaction. A group of 81 leaders received 360 feedback from their immediate managers, peers, direct reports and others. The leadership effectiveness of each manager was evaluated by a 49 item assessment. Based on the overall rating from the 49 items, managers were divided into five groups, from leaders at the bottom 10th percentile (the worst leaders) to those at the top 10% (the best leaders).

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One factor at a time (OFAT) Versus Factorial Designs

Guest post by Bradley Jones

Almost a hundred years ago R. A. Fisher‘s boss published an article espousing OFAT (one factor at a time). Fisher responded with an article of his own laying out his justification for factorial design. I admire the courage it took to contradict his boss in print!

Fisher’s argument was mainly about efficiency – that you could learn as much about many factors as you learned about one in the same number of trials. Saving money and effort is a powerful and positive motivator.

The most common argument I read against OFAT these days has to do with inability to detect interactions and the possibility of finding suboptimal factor settings at the end of the investigation. I admit to using these arguments myself in print.

I don’t think these arguments are as effective as Fisher’s original argument.

To play the devil’s advocate for a moment consider this thought experiment. You have to climb a hill that runs on a line going from southwest to northeast but you are only allowed to make steps that are due north or south or due east or west. Though you will have to make many zig zags you will eventually make it to the top. If you noted your altitude at each step, you would have enough data to fit a response surface.

Obviously this approach is very inefficient but it is not impossible. Don’t mistake my intent here. I am definitely not an advocate of OFAT. Rather I would like to find more convincing arguments to persuade experimenters to move to multi-factor design.

Related: The Purpose of Factorial Designed ExperimentsUsing Design of Experimentsarticles by R.A. Fisherarticles on using factorial design of experimentsDoes good experimental design require changing only one factor at a time (OFAT)?Statistics for Experimenters

The Achilles’ Heel of Agile

Guest post by Jurgen Appelo

When I wrote this, I was working in a big open office space in the Van Nelle Factory in Rotterdam (see photo). About 100 people work in an office that was the first of its kind in Europe, when it was built in 1929. And more than 80 years later, architecture lovers from all over the world still come to admire it, take pictures, and make drawings. I sometimes waved at them.

photo of open office style at Van Nelle Office
Van Nelle office, reprinted by permission of Stephan Meijer

A big open office space has advantages and disadvantages. Advantages are flexibility and easy communication. The main disadvantage is that it is a shared resource for all who work there. Climate, sound, and light are hard to manage in a space like that, and the optimal configuration for the whole is never optimal for all. But our office manager did the best she could in trying to maximize pleasant working conditions, while maintaining tight rules to keep things under control. A shared open office is not the ideal environment to give people full responsibility over their own working space.

Self-organization is usually promoted in agile software development. But when shared resources are not managed by a central authority, self-organization often results in the Tragedy of the Commons. The name refers to a situation in which multiple self-organizing systems, all acting in their own self-interest, overexploit a shared limited resource, even when they all know it is not in anyone’s interest for this to happen. The impact that humanity has on CO2 levels in the air, trees in the forests, and fish in the sea, is right now the most debated and intensively researched case of the Tragedy of the Commons. Organizations also have shared resources, like budgets, office space, and system administrators. We could see them as the business-equivalent of the air we breathe, the landscape we change, and the fish we eat.

Research indicates that four ingredients (called the four I’s) are needed for sustainability of shared resources [Van Vugt 2009:42]:

  • Institutions [managers] who work on building trusting relationships between competing systems [teams] in order to increase acceptance of common rules;
  • Information that increases understanding of the physical and social environment, in order to reduce uncertainty (because uncertainty results in bias towards self-interest);
  • Identity, or a need for a social “belonging” that encompasses all participants, to improve and broaden one’s sense of community and reduce competition between teams;
  • Incentives that address the need to improve oneself, while punishing overuse and rewarding responsible use.

Research shows that it is imperative that there is some form of management (or governance) to protect these shared resources by working on these four I’s. (I realize that most modern day governments are not setting a good example of how to do that.) In the case of shared resources, whether it concerns money, space, or system administrators, someone outside of the development teams must keep an eye on long-term sustainability instead of short-term gains by individual teams.

The Tragedy of the Commons is the Achilles’ heel of Agile. It takes management to protect that heel, in order to prevent teams from depleting resources, and crippling the organization.

This article is an adaptation from Management 3.0: Leading Agile Developers, Developing Agile Leaders, by Jurgen Appelo. The book will be published by Addison-Wesley, in Mike Cohn’s Signature Series.

Related: Embrace Diversity, Erase Uniformitymanagement 3.0agile software development booksVW Phaeton assembly plant

Embrace Diversity, Erase Uniformity

Guest Post by Jurgen Appelo, author of the Managing Software Development blog.

Five years ago, when I started working for my current employer, the entire organization (about 30 people) consisted only of 20-something white straight single males. The atmosphere was what you would expect from such an environment: conversations on football/soccer, lewd jokes, the smell of beer, and trash in every corner. In short, the perfect place to work, if you were a 20-something white straight single male.

Then the organization started changing. The subculture of 20-something white straight single males in our region could not keep up with the rapid growth of our company. And so the women arrived. And the married guys. And people with kids. And people older than 40. And people from all sorts of ethnic, religious, sexual, and disabled minorities. Before we knew it, the organization had grown to 200 people, and the group of 20-something white straight single males had dwindled to just another minority. And it’s still a great place to work, particularly for the large majority of people representing one or two minorities.

Diversity is Important
In biological ecosystems, genetic diversity is one of the most important principles. Biodiversity (the variation of species) is the most obvious form of it, but there’s also diversity within species themselves. Did you know that honey bees are slightly different from each other? That’s how they regulate the temperature in their beehives. When a hive gets too cold, the bees start huddling together, buzzing their wings. And when it gets too hot, the bees spread out and they start fanning their wings. Now, when the bees would respond to the same specific temperatures, they would all start buzzing or fanning their wings at the same time, resulting in a wildly oscillating temperature in the hive. Therefore, to improve stability, nature has made sure that the bees respond to different temperature levels. When the temperature rises, one by one the bees will start fanning their wings. And the more bees join in, the slower the temperature will rise, until it stops completely. Diversity among bees smoothes and stabilizes the temperature in the beehive.

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Dr. Deming’s 15th Point

Guest post from John McConnell, Wysowl Pty Ltd

Dr. Deming opened his first Australian seminar in 1986 with the question, “What are we here to do”? After some discussion he answered his own question with, “To learn”, and “To have a good time”.

He repeated this opening at subsequent seminars.

The Fifteenth Point
Mr. Murray Mansfield of Melbourne has what I believe to be the only completely up to date version of Dr. Deming’s famous Obligations for Top Management. After a long discussion with Murray during his last Australian seminar, Dr. Deming agreed that there ought to be a fifteenth point. He took Murray’s notes turned to the page containing the fourteen points and at the foot of the page wrote:

15.     Have a good time!

Related: I Don’t KnowFind Joy and Success in Businessposts on respect for peopleDestroyed by Best EffortsLets Play WorkSeven (plus 2) Deadly Diseases of Western Management