Tag Archives: Quality tools

Stated Versus Revealed Preference

My father provided me a good example of the flawed thinking of relying on stated preference when I was growing up. Stated preference is, as you might deduce, the preferences voiced by customers when you ask. This is certainly useful but people’s stated preference often do not match there actions. And for a business, actions that lead to customers are more important than claims potential customers make about what will make them customers.

His example was that if you ask people if clean bathrooms in a restroom is required for a restaurant they will say yes. Potential customers will say this is non-negotiable, it is required. But if you eat at many “ethnic restaurants,” as we always did growing up, you would see many popular restaurants did not have clean restrooms. If the food at atmosphere was good enough clean restrooms were negotiable, even if customers stated they were not.

Now I think clean restrooms is a wise move for restaurants to make; it matters to people. Instead of creating a barrier to repeat customers that has to be overcome with much better food and atmosphere it is wiser to give yourself every advantage by giving the customers what they want. But I think the example is a simple example of stated versus revealed preferences.

McDonald’s gets a great deal of success by doing certain things well, including clean bathrooms, even if they miss on things some people think are important for a restaurant. McDonald’s really gets a fair amount of business for people driving a long distance that really want a clean bathroom and a quick stretch of their legs and quick food. This is a small percentage of McDonald’s customer visits but still a very large number of visits each day I am sure. Understanding, and catering to, the problem your customers are trying to solve is important.

The point to remember is what your potential customers say they will do is different than what they do. It is sensible to listen to stated preferences of customers just understand them for what they are.

We need to pay more attention to revealed preferences. Doing so can require putting in a bit more thinking than just asking customers to fill out a questionnaire. But it is worth the effort. A simple restaurant based example would be to have wait staff pay attention to what people leave on their plate. If you notice certain side dishes are not eaten more often, look into that and see what can be done (improving how it is prepared, substituting something else…).

Related: Voice of the CustomerThe Customer is the Purpose of Our WorkCustomers Are Often IrrationalPackaging Affects Our Perception of TasteBe Careful What You Measure

Management Blog Review 2012: Gemba Walkabout

This is my second, of two, 2012 management blog review posts. In this post I look back at the last year on Mike Stoecklein’s Gemba Walkabout blog. Mike is the Director of Network Operations at Thedacare Center for Healthcare Value.

photo of Mike Stoecklein
  • In a very long post, Some thoughts on guiding principles, values & behaviors, he provides a sensibly explanation for one the real difficulties organization have making progress beyond a certain point (project success but failure to succeed in transforming the management system). “I’m not saying this approach (focus on tools, teams, events) is wrong, but I do think it is incomplete. I think we also need to work from right to left – to help people understand the guiding principles, to think about the kinds of systems they want and to use tools to design and redesign those systems. Dr. Shigeo Shingo said, ‘people need to know more than how, they need to know why’.

    Most managers view their organization like an org chart, managed vertically. They assume that the organization can be divided into parts and the parts can be managed separately

    It’s what they believe, and what they don’t know is that is is wrong – especially for a complex organization.
    If their thinking was based on the guiding principles (for instance “think systemically”) they would manage their organization differently. They would see their organization as as set up interdependent components working together toward a common aim.”
  • Reflections on My (Brief) Time with Dr. Deming – “The executives thought he was pleased. When they were done with their ‘show’ he thanked them for their time, but he wanted to know what ‘top management’ was doing. He pointed out that they were talking about improvements on the shop floor, which accounted for only about 3 percent of what was important.” When executives start to radical change what they work on the organization is starting to practice what Dr. Deming taught. Mike recorded a podcast with Mark Graban on working with Dr. Deming.
  • Standard Work and PDSA – “What I have noticed is that sometimes people insert another wedge (shown as black) in the diagram below. So, progress gets stopped because some seem to believe that standard work doesn’t get adjusted as you make improvement.” This is a brilliant graphic including the text standard work misued. The 2 biggest problem with “standard work” in practice is ignoring the standards and treating them as barriers to improvement. Standard work should be practiced and if that is a problem the standard work guidance should be changed.
image showing how failure to adjust standard work can block progress

During the year stay current with great posts twice a month via the Curious Cat Management Improvement Carnival.

Related: Management Blog Review 2012: Not Running a Hospital2011 Management Blog Roundup: Stats Made EasyStandardized Work InstructionsAnnual Management Blog Review: Software, Manufacturing and Leadership

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.

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5s at NASA

NASA did some amazing things culminating with landing on Moon. Much of what they did was doing many small things very well. They used 5s, checklists, gemba thinking, usability, simplicity, testing out on a small scale and much more.

Here are a few photos from the Smithsonian Air and Space museum in Washington DC. I also have some nicer NASA 5s photos from the new Annex near Dulles Airport, but, ironically, I can’t find them.

photo of container labeled with many compartments for NASA

These kits were used by NASA astronauts on the Apollo 11 mission to the moon. Obviously NASA had to have everything that might be needed where it was needed (picking up something from the supply closet in building 2 wasn’t an option).

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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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Moving Beyond Product Quality

This month Paul Borawski (CEO of ASQ) has asked the ASQ Influential Voices to share their thoughts on moving beyond product quality.

The opening paragraph of the Quality Council’s perspective is, “For some organizations, ‘quality’ remains a set of tools and techniques associated almost exclusively with quality control. For others, quality has evolved into a critical partner, closely linked with business model development and the enterprise-wide execution of long-term strategy to achieve results.

The way to move beyond just the set-of-tools mindset is very similar to the March topic on selling quality improvement.

What is needed to move beyond quality tools into a new management system is to make changes to the system that allow for that management system to be continually improved. Using the tools helps improve product quality a great deal. Much more can be done (both for product quality and overall effectiveness) if we don’t limit the use of modern improvement efforts to the manufacturing line.

At first it is often difficult to get managers and executives to accept the kind of change to their work that they will direct others to make. But once the process of improving the management system gets started, it takes a life of its own and is a very strong force to move beyond product quality.

Here are some previous posts on methods and strategies to move forward the organization into adopting a customer focused systemic effort to continuously improve every aspect of the organization – including the management system:

Related: Dr. Deming in 1980 on Product Quality in Japan and the USA

Richard Feynman Explains the PDSA Cycle

Ok, really Richard Feynman Explains the scientific method. But his thoughts make the similarity between the PDSA cycle and the scientific method obvious.

1) Plan, hypothesis.
You make a guess about a theory (in using the PDSA cycle this step is often missed, while in the scientific method this is of the highest priority). You make a prediction based on that theory.

2) Do the experiment

3) Study the results

If the results disprove the theory you were wrong. If they results don’t disprove the theory you may have a useful theory (it can also be that your theory is still wrong, but this experiment happened not to provide results that disprove it).

Step 4, Act, only exists for PDSA. In science the aim is to learn and confirm laws. While the PDSA cycle has an aim to learn and adopt methods that achieve the desired results.

Richard Feynman: “If it disagrees with experiment it is wrong, in that simple statement is the key to science, it doesn’t make any difference how beautiful your guess is, it doesn’t make a difference how smart you are (who made the guess), or what his name is, if it disagrees with experiment it is wrong.”

Actually far to often “PDSA” fails to adopt this understanding. Instead it become PA: no study of the results, just implement and we all already agree it is going to work so don’t bother wasting time testing that it actually does. Some organization do remember to study results of the pilot experiments but then forget to study the results when the new ideas are adopted on a broader scale.

Related: Does the Data Deluge Make the Scientific Method Obsolete?Video of Young Richard Feynman Talking About Scientific ThinkingHow to Use of the PDSA Improvement Cycle Most EffectivelyUsing Design of Experiments

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 prediction of the results are important. 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.

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 – 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.

Study should not take much time. The plan should have already have laid out what data is important and an expectation of what results will be achieved and provide a good idea on next steps. Only if you are surprised (or in the not very common case that you really have no idea what should come next until you experiment) will the study phase take long.

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Why Use Lean if So Many Fail To Do So Effectively

If less than 1% of companies are successful with Lean, why are we doing it?

Lots of us are not. I would say the efforts I see “fail” are because they don’t do it. They have something they call TQM, six sigma, lean management or whatever and try out 10-30% of it in some half-measures, with big doses of Dilbert’s pointy haired boss methods and then don’t get great results. Wow.

The biggest complaint (with some merit) I see is why is lean/Deming/six sigma… so hard to actually do. If companies constantly fail to do it at all (even when they use the name) isn’t that an issue. Isn’t that a weakness of the “solution.” My answer is: yes. The caveat is, until someone comes up with the management system that both gets the results using Deming’s management ideas can, and is super easy for organizations to actually fully adopt (and have the great success that doing so provides) I know of nothing better than trying to do these things.

Certainly I believe you are much better off attempting to use Deming, lean or six sigma than listen to someone that tells you they have management instant pudding that will give you great results with no effort.

My belief is that a partial success rate is much higher than 1%. While many organization never go beyond slapping a few good tools on a outdated management system those few tools actually have good results. Maybe 50% of the implementations are so lame they have almost no positive results (not even getting improvement worth the time and effort). They could be seen as “failures,” to me. Those that actually have a right to say they are practicing “lean” I would say is a pretty small number but still above 1%?

There is also an advantage to this stuff being hard to do. You really don’t have to invent anything new. If you just have persistence and keep continually improving along the path applying ideas proven over decades from Deming, Ohno, McGregor, Christensen, Drucker, Scholtes, Womack, Roger Hoerl (six sigma)… you have a great advantage over all those organizations that ignored the ideas or made a bit of effort and then gave up.

Related: Engage in Improving the Management SystemRethinking or Moving Beyond Deming Often Just Means Applying More of What Dr. Deming Actually SaidManagement Advice FailuresManagement Improvement FlavorsHas Six Sigma Been a Success?