Tag Archives: Data

Special Cause Signal Isn’t Proof A Special Cause Exists

One of my pet peeves is when people say that a point outside the control limits is a special cause. It is not. It is an indication that it likely a special cause exists, and that special cause thinking is the correct strategy to use to seek improvement. But that doesn’t mean there definitely was a special cause – it could be a false signal.

This post relies on an understand of control charts and common and special causes (review these links if you need some additional context).

Similarly, a result that doesn’t signal a special cause (inside the control limits without raising some other flag, say a run of continually increasing points) does not mean a special cause is not present.

The reason control charts are useful is to help us maximize our effectiveness. We are biased toward using special cause thinking when it is not the most effective approach. So the control chart is a good way to keep us focused on common cause thinking for improvement. It is also very useful in flagging when it is time to immediately start using special cause thinking (since timing is key to effective special cause thinking).

However, if there is result that is close to the control limit (but inside – so no special cause is indicated) and the person that works on the process everyday thinks, I noticed x (some special cause) earlier, they should not just ignore that. It very well could be a special cause that, because of other common cause variation, resulted in a data point that didn’t quite reach the special cause signal. Where the dot happened to land (just above or just below the control limit – does not determine if a special cause existed).

The signal is just to help us systemically make the best choice of common cause or special cause thinking. The signal does not define whether a special cause (an assignable cause) exists of not. The control chart tool helps guide us to use the correct type of improvement strategy (common cause or special cause). But it is just a signaling device, it isn’t some arbiter of whether a special cause actually exists.

Continue reading

My New Book: Management Matters

Image of the book cover of Management Matters by John Hunter

Management Matters by John Hunter is now available.

I have a new book in progress: Management Matters. It is now available in “pre-release format” via leanpub. The idea I am experimenting with (supported by leanpub) is pre-publishing the book online. The ebook is available for purchase now, and comes with free access to the updates.

My plan is to continue working on the book for the next few months and have it “release ready” by October, 2012. One of the advantages of this method is that I can incorporate ideas based on feedback from the early readers of the book.

There are several other interesting aspects to publishing in this way. Leanpub allows a suggested retail price, and a minimum price. So I can set a suggested price and a minimum price and the purchaser gets to decide what price to pay (they can even pay over suggested retail price – which does happen). The leanpub model provides nearly all the revenue to the author (unlike traditional models) – the author gets 90% of the price paid, less 50 cents per book (so $8.50 of a $10 purchase).

They provide the book in pdf, mobi (Kindle) and epub (iPad, Nook, etc.) formats. And the books do not have any Digital Rights Management (DRM) entanglements.

Management Matters covers topics familiar to those who have been reading this blog for years. It is an attempt to put in one place the overall management system that is most valuable (which as you know, based on the blog, is largely based upon Dr. Deming’s ideas – which means lean manufacturing are widely covered too).

I hope the book is now in a state where those who are interested would find it useful, but it is in what I consider draft format. I still have much editing to do and content to add.

Leanpub also provides a sample book (where a portion of the content can be downloaded to decide if you want to buy). If you are interested please give it a try and let me know your thoughts.

Introductory Videos on Using Design of Experiments to Improve Results

The video shows Stu Hunter discussing design of experiments in 1966. It might be a bit slow going at first but the full set of videos really does give you a quick overview of the many important aspects of design of experiments including factorial designed experiments, fractional factorial design, blocking and response surface design. It really is quite good, if you find the start too slow for you skip down to the second video and watch it.

My guess is, for those unfamiliar with even the most cursory understanding of design of experiments, the discussion may start moving faster than you can absorb the information. One of the great things about video is you can just pause and give yourself a chance to catch up or repeat a part that you didn’t quite understand. You can also take a look at articles on design of experiments.

I believe design of experiments is an extremely powerful methodology of improvement that is greatly underutilized. Six sigma is the only management improvement program that emphasizes factorial designed experiments.

Related: One factor at a time (OFAT) Versus Factorial DesignsThe purpose of Factorial Designed Experiments

Continue reading

Management Blog Posts From November 2006

I have selected a few great posts from the Curious Cat Management Blog back in November 2006.

  • What Could we do Better? – There are many important ideas to improve management. This is one of the most important tips to aid improvement that I know of: it is easy to do, brings huge benefits and most organizations fail to do it. Ask your customers: “What one thing could we do to improve?”
  • Ackoff’s F-laws: Common Sins of Management presents 13 common sins of management, such as: Managers who don’t know how to measure what they want settle for wanting what they can measure
  • Common Cause Variation – “Every system has variation. Common cause variation is the variation due to the current system. Dr. Deming increased his estimate of variation due to the system (common cause variation) to 97% (earlier in his life he cited figures as low as 80%). Special cause variation is that due to some special (not part of the system) cause.”
  • Sub-Optimize by Interrupting Knowledge Workers – “The general consensus is that the loss from interrupting [software] developers is much greater than for interrupting most other forms of work and therefor a great deal of effort is placed on improving the system to allow developers to focus.”
  • Amazon Innovation – “I believe Amazon uses technology very well. They have done many innovative things. They have been less successful at turning their technology into big profits. But I continue to believe they have a good shot at doing so going forward (and their core business is doing very well I think).” [Amazon announced great sales numbers today, continuing their long term tread. They are also continuing to be very slow to grow profits (CEO, Jeff Bezos remains willing to challenge common practices – such as his willingness to build business and sacrifice current profits)].

Keys to the Effective Use of the PDSA Improvement Cycle

The PDSA improvement cycle was created by Walter Shewhart where Dr. Deming learned about it. An improvement process is now part of many management improvement methods (A3 for lean manufacturing, DMAIC for six sigma and many other modifications). They are fairly similar in many ways. The PDSA cycle (Plan, Do, Study, Act) has a few key pieces that are either absent in most others processes of greatly de-emphasized which is why I prefer it (A3 is my second favorite).

The PDSA cycle is a learning cycle based on experiments. When using the PDSA cycle, it is important to predict the results. This is important for several reasons but most notably due to an understanding of the theory of knowledge. We will learn much more if we write down our prediction. Otherwise we often just think (after the fact); yeah that is pretty much what I expected (even if it wasn’t). Also we often fail to think specifically enough at the start to even have a prediction. Forcing yourself to make a prediction gets you to think more carefully up front and can help you set better experiments.

PDSA Improvement cycle graphic

PDSA Improvement cycle graphic from my book – Management Matters

An organization using PDSA well will turn the PDSA cycle several times on any topic and do so quickly. In a 3 month period turning it 5 times might be good. Often those organizations that struggle will only turn it once (if they are lucky and even reach the study stage). The biggest reason for effective PDSA cycles taking a bit longer is wanting more data than 2 weeks provides. Still it is better to turn it several times will less data – allowing yourself to learn and adjust than taking one long turn.

The plan stage may well take 80% (or even more) of the effort on the first turn of the PDSA cycle in a new series. The do stage may well take 80% of of the time (when you look at the whole process, multiple turns through the PDSA cycle) – it usually doesn’t take much effort (to just collect a bit of extra data) but it may take time for that data to be ready to collect. In the 2nd, 3rd… turns of the PDSA cycle the Plan stage often takes very little time. Basically you are just adjusting a bit from the first time and then moving forward to gather more data. Occasionally you may learn you missed some very important ideas up front; then the plan stage may again take some time (normally if you radically change your plans).

Remember to think of Do as doing-the-experiment. If you are “doing” a bunch of work (not running an experiment and collecting data) that probably isn’t “do” in the PDSA sense.

Continue reading

2011 Management Blog Roundup: Stats Made Easy

The 4th Annual Management blog roundup is coming to a close soon. This is my 3rd and final review post looking back at 2001, the previous two posts looked at: Gemba Panta Rei and the Lean Six Sigma Blog.

I have special affinity for the use of statistics to understand and improve. I imaging it is both genetic and psychological. My father was a statistician and I have found memories of applying statistical thinking to understand a result or system. I also am comfortable with numbers, and like most people enjoy working with things I have an affinity for.

photo of Mark Anderson

Mark Anderson

Mark Anderson’s Stats Made Easy blog brings statistical thinking to managers. And this is not an easy thing to do, as one of his posts shows, we have an ability to ignore data we don’t want to know. Wrong more often than right but never in doubt: “Kahneman examined the illusion of skill in a group of investment advisors who competed for annual performance bonuses. He found zero correlation on year-to-year rankings, thus the firm was simply rewarding luck. What I find most interesting is his observation that even when confronted with irrefutable evidence of misplaced confidence in one’s own ability to prognosticate, most people just carry on with the same level of self-assurance.”

That actually practice of experimentation (PDSA…) needs improvement. Too often the iteration component is entirely missing (only one experiment is done). That is likely partially a result another big problem: the experiments are not nearly short enough. Mark offered very wise advice on the Strategy of experimentation: Break it into a series of smaller stages. “The rule-of-thumb I worked from as a process development engineer is not to put more than 25% of your budget into the first experiment, thus allowing the chance to adapt as you work through the project (or abandon it altogether).” And note that, abandon it altogether option. Don’t just proceed with a plan if what you learn makes that option unwise: too often we act based on expectations rather than evidence.

In Why coaches regress to be mean, Mark explained the problem with reacting to common cause variation and “learning” that it helped to do so. “A case in point is the flight instructor who lavishes praise on a training-pilot who makes a lucky landing. Naturally the next result is not so good. Later the pilot bounces in very badly — again purely by chance (a gust of wind). The instructor roars disapproval. That seems to do the trick — the next landing is much smoother.” When you ascribe special causation to common cause variation you often confirm your own biases.

Mark’s blog doesn’t mention six sigma by name in his 2011 posts but the statistical thinking expressed throughout the year make this a must for those working in six sigma programs.

Related: 2009 Curious Cat Management Blog Carnival2010 Management Blog Review: Software, Manufacturing and Leadership

Steve Jobs Discussing Customer Focus at NeXT

Video from 1991 when Steve Jobs was at NeXT. Even with the customer focus however, NeXT failed. But this does show the difficulty in how to truly apply customer focus. You have to be creative. You have examine data. You have to really understand how your customers use your products or services (go to the gemba). You have to speculate about the future. The video is also great evidence of providing insight to all employees of the current thinking of executives.

Related: Sometimes Micro-managing Works (Jobs)Delighting CustomersWhat Job Does Your Product Do?

Annual Performance Reviews Are Obsolete

Sam Goodner, the CEO of Catapult Systems, wrote about his decision to eliminate the annual performance appraisal.

the most critical flaw of our old process was that the feedback itself was too infrequent and too far removed from the actual behavior to have any measurable impact on employee performance.

I decided to completely eliminate of our annual performance review process and replace it with a real-time performance feedback dashboard.”

I think this is a good move in the right direction. I personally think it is a mistake to make the measures focused on the person. There should be performance dashboards (with in-process and outcome measures) that provide insight into the state of the processes in the company. Let those working in those processes see, in real time, the situation, weaknesses, strengths… and take action as appropriate (short term quick fixes, longer term focus on areas for significant improvement…). It could be the company is doing this, the quick blog post is hardly a comprehensive look at their strategies. It does provide some interesting ideas.

I also worry about making too much of the feedback without an understanding of variation (and the “performance” results attributed to people due merely to variation) and systems thinking. I applaud the leadership to make a change and the creative attempt, I just also worry a bit about how this would work in many organizations. But that is not really what matters. What matters is how it works for their organization, and I certainly believe this could work well in the right organization.

Related: Righter Performance AppraisalWhen Performance-related Pay BackfiresThe Defect Black Marketarticles, books, posts on performance appraisal

A Theory of a System for Educators and Managers

Excerpts from The Deming Library Volume XXI, Dr. W. Edwards Deming, Dr. Russell Ackoff and David Langford demonstrate that educators can begin a quality transformation by developing an understanding of the properties and powers of systems-oriented thinking. You can order the entire video, as well as the rest of The Deming Library.

Great stuff! If you enjoy this blog (the Curious Cat Management Improvement Blog), you definitely should watch this webcast. This video has some great insight into education, learning and systems thinking. It also provides a good explanation of systems thinking compared to analysis. Dr. Ackoff: “You cannot explain the behavior of a system by analysis.” “The performance of the whole is never the sum of the performance of the parts taken separately: but it’s the product of their interactions. Therefore, the basic managerial idea introduced by systems thinking is that to manage a system effectively you must focus on the interactions of the parts rather than their behavior taken separately.”

Dr. Deming: “You may reduce defects to zero and go out of business.”

Dr. Ackoff: “Most discussion of education assume that the best way to learn a subject is to have it taught to you. That’s nonsense… Teaching is a wonderful way to learn. Therefore if we want people to learn we have to make them teach.” If you want more on this see David Langford’s work which provides great advice on how to improve learning and education.

Related: Dr. Deming Webcast on the 5 Deadly DiseasesAn Introduction to Deming’s Management Ideas by Peter ScholtesHow to Manage What You Can’t MeasureMarissa Mayer Webcast on Google InnovationTraffic Congestion and a Non-Solution

Managing Our Way to Economic Success

From Managing Our Way to Economic Success, Two Untapped Resources by William G. Hunter, my father. Written in 1986, but still plenty relevant. We have made some good progress, but there is much more to do: we have barely started adopting these ideas systemically.

there are two enormously valuable untapped resources in many companies: potential information and employee creativity. The two are connected. One of the best ways to generate potential information to turn it into kinetic information that can produce tangible results is to train all employees in some of the simple, effective ways to do this. Rely on their desire to do a good job, to contribute, to be recognized, to be a real part of the organization. They want to be treated like responsible human beings, not like unthinking automatons.

W. Edwards Deming has illustrated one of the troubles with U.S. industry in terms of making toast. He says, “Let’s play American industry. I’ll burn. You scrape.” Use of statistical tools, however, allows you to reduce waste, scrap, rework, and machine downtime. It costs just as much to make defective products as it does to make good products. Eliminate defects and other things that cause inefficiencies, and you reduce costs, increase quality, and raise productivity. Note that quality and productivity are not trade-offs. They increase together.

Potential information surrounds all industrial processes. Statistical techniques, many of which are simple yet powerful, are tools that employees can use to tap and exploit this potential information so that increasingly higher levels of productivity, quality, and innovation can be attained. Engaging the brains as well as the brawn of employees in this way improves morale and participation…and profits.

What is called for is constant, never-ending improvement of all processes in the organization. What management needs, too, is constant, never-ending improvement of ideas.

Related: William Hunter, articles and booksInvest in New Management Methods Not a Failing CompanyThe Importance of Management ImprovementStatistics for Experimenters