Currently browsing the Process improvement Category

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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Build Systems That Allow Quick Action – Don’t Just Try and Run Faster

This month Paul Borawski (CEO of ASQ) has asked the ASQ Influential Voices to share their thoughts on the cries for “faster, faster, faster” that so often is a refrain heard today.

I have long said that the measure of management improvement isn’t only about improving. It is the speed at which the management system and internal processes are being improved. Improvement is a given. If an organization is not improving every year the odds of long term success is low.

One of the common objections to a need for improvement is that we are doing fine and we are improving (so leave us alone we are already improving). That is better than not doing fine and not improving but it isn’t a reason to be complacent. Managers should be continually pushing the improvement acceleration higher.

The biggest problems I see with a focus on being faster are attempting move faster than the capability of the organization and falling back on working harder as a method to achieve the faster action. Really these are the same issue – working harder is just a tactic to cope with attempting to achieve better results than the system is capable of.

Agile software development has a principle, sustainable development, which is a reaction to the far too common attitude of management to just have software developers work longer and longer hours to meet targets. Any attempt to be faster internally or respond to a faster marketplace should first put the principle of sustainable workload as a requirement. And next build the capability of the enterprise to respond quickly and keep increasing how quickly it can respond effectively.

The well know management improvement concepts, practices and tools will lead an organization to improve that capability reliably, sustainable and continuously.

My new book, Management Matters: Building Enterprise Capability, delves into how to manage an enterprise based on the ideas needed to apply management improvement concepts, practices and tools to achieve results, including, but not limited to, faster.

Related: Process Improvement and InnovationFind the best methods to produce the best results over the long termThink Long Term Act Daily

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.

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?

Agile Story Point Estimation

In agile software development tasks are documented as user stories. Then the level of effort for those stores can be estimated by assigning each story points. The velocity that can be produced in a period (called a sprint, for us 2 weeks) can be estimated. Thus you can predict what can be delivered in the next sprint (which can help business managers make priority decisions).

I have found estimation to be worthwhile. In doing so, we accept there is a great amount of variation but points give a hint to scale. They can help prioritize (if you have 5 things you want but 1 is much harder you may well drop that to the bottom). I have always accepted a great amount of variation in the velocity, worry about the variation I don’t find worthwhile. I do think trying to act as though the velocity is precise can lead to problems. At the same time having a measure of velocity, even accepting understanding variation was present, was useful.

Over time reducing variation (probably largely through better estimation and perhaps a few better tools, reduced technical debt, better documentation, testing…) is helpful and laudable. We made improvement but still lots of variation existed. The biggest help in reducing the measured velocity was breaking down large stories to more manageable sizes. The challenge of estimating user stories, I suspect, has some fairly high variation (even with good system improvements that can help reduce variation).

Large stories just can hide huge variation in what is really required once getting into implementing it.

The way we did estimation (discussing in a sprint planning meeting) did take some time (but not a huge amount). It was agreed by those involved that the time spent was worthwhile. Sometimes we did slip and spend too much time on this, that was an area we had to pay attention to. The discussions were educational and helped provide guidance on how to approach the story. The value of discussions around estimations was probably the biggest surprise I have had in implementing any agile ideas. The value of those discussion was much higher than I imagined (I basically anticipated them just as non-value added time to get the result of an estimate, but they were a source of learning and consensus building).

Related: Assigning Story Points to Bug FixesMistake Proofing the Deployment of Software CodeChecklists in Software Development

These thoughts were prompted by: Story Points Considered Harmful – Or why the future of estimation is really in our past…

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Eliminate the Waste of Waiting in Line with Queuing Theory

One thing that frustrates me is how managers fail to adopt proven strategies for decades. One very obvious example is using queuing theory to setup lines.

Yes it may be even better to adopt strategies to eliminate as much waiting in line as possible, but if there is still waiting in line occurring and you are not having one queue served by multiple representatives shame on you and your company.

Related: Customer Focus and Internet Travel SearchYouTube Uses Multivariate Experiment To Improve Sign-ups 15%Making Life Difficult for Customers

Rethinking or Moving Beyond Deming Often Just Means Applying More of What Dr. Deming Actually Said

Don Reinertsen – Is It Time to Rethink Deming? from AGILEMinds on Vimeo.

I feel very strongly about the value of Deming’s ideas. I am glad people challenge those ideas and try to push forward management thinking. Helping us manage organizations better (to get better results and allow people to better enjoy their jobs and lives) is why I value Deming’s ideas. To the extent we find better ideas I am very happy. I understand I will disagree with others on the best ways to manage, and believe healthy debate can be productive.

What Don Reinertsen discusses in the video, about special and common cause is not the best way to look at those ideas, in my opinion (though I would imagine it is the most common view). For data points that are common cause (within the control limits and not a special cause pattern) it is most effective to use common cause tools/thinking to improve. For indications of special cause (points outside the control limits or patterns in the data, such as continually increasing results that indicate a special cause) it is most effective to use special cause tools to improve.

This does not mean that a point outside the control limits is caused by a special cause (also know as assignable cause). It is just best to use special cause tools and thinking to address those data points (and the reason this is true is because it is most likely there is an assignable cause). The control limits do not define the nature of the point, they define the type of improvement strategy that should be used.

Don also says repeatedly that you don’t “respond to random variation” in Deming’s view. That is accurate. But then he implies this means you don’t address system performance, which is not. You work on improving systems (that are in control) by improving the system, not by responding to individual common cause data points (random variation) as if it were assignable cause variation.

The purpose of the control chart (that Shewhart developed) was to help you most effectively take action (knowing if special cause thinking, or system improvement, was the best improvement strategy). The control chart shows if the results are in control and tells you that the system is preforming consistently (and identifies a special cause so special cause tools can be used immediately, this is important because special cause improvement strategies are time sensitive). It tells you nothing about if the results are acceptable.

Continual improvement was also central to Deming’s management philosophy (based on the business value of the many improvement options available in every organization). For Deming this meant working on improving the system, if the results are in control, instead of trying to deal with finding a specific assignable cause for one data point and acting on that. If the issue is one of the system performance (no indication it is a special cause) the most effective strategy to get better results is to improve the system, rather than approach it as a special cause issue (examining individual data points, to find special items in that event to be improved). You can use special cause thinking, even where system improvement thinking would be better. It will work. It is just not very effective (improvement will be much slower) compared to focusing on system improvement.

I agree with Don that the United States mentality, not only in nuclear plants but everywhere, is to apply special cause thinking as the strategy for process improvement. This is one the areas Deming was trying to change. Deming, and I, think that setting your improvement strategy based on a common cause (system improvement) or assignable/special cause (learn what is special about that one instance) is the most effective way to achieve the best results. We believe in continual improvement. We believe that the effective way to improve, when a system is in statistical control, is by focusing on the whole systems (all the data) not assignable cause (special cause) thinking where you look at what is special about that bad (or good) individual result.

The economic consideration of whether the costs of improvements are worth the benefit is sensible (and I do not see Dr. Deming arguing against that). That is separate from the best method to improve. For Deming the best method to improve means using special cause thinking for assignable cause issues and common cause thinking for systems issues.

The idea of where to focus improvement efforts is not something Dr. Deming made as clear as he could have, in my opinion. So I see the argument of Deming not prioritizing where improvement should occur voiced occasionally. This is a weakness in Deming’s content, I believe, more than his philosophy (but I can understand it causing some confusion).
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Interviewing: I and We

In response to: say “I” — not “we” — in your interviews

If you are a manager you need to lead teams, lead projects and improve work systems. In an interview I believe you need to say specifically what you did but also talk about what the team accomplished. A manager needs to have successful project and make other people successful. To me the important thing is getting great long term results, not doing lots of tasks themselves. Often figuring out the right leverage points to work on is difficult but it doesn’t have to be a large volume of work, just the right decisions on where to make improvements.

Sometimes (often, for me, but maybe I have more difficulty explaining it than I should) these ideas are hard to convey to others. It is similar to answering hypothetical questions where, the way to “handle” the issue raised is to avoid getting into that mess in the first place. We were able to success not because of 3 specific actions I took during the project but because of the system I put in place and cultivated for years that allowed the team to succeed. But some people have trouble connecting long term system improvements to current project results.

As a manager my main focus is on building capacity of my organization to succeed over the long term. That greatly reduced any fire-fighting I have to do. Of course for many interviewers great tales of fire-fighting play better than I didn’t really have to do much to make x,y and z projects successful because I set the stage over years creating a system that works well.

Creating systems that work well often isn’t tremendously exciting and tales of creating systems that avoid disasters seem boring. I didn’t have to be heroic isn’t as sexy as and I was a hero in this way 3 months ago and then last month I saved us from disaster when… If I am interviewing, I would want to ask why you have to keep being a hero, but I don’t think most people think that way.

If you just talk about what I did it also can confuse interviewers, I think. Those things are often not directly tied to accomplishing some business need. Creating the right systems which allow great results to be attained often isn’t obvious why it matters. It is indirect and not nearing as obvious as fire-fighting behavior what the benefit is. Most organizations are not used to the value of creating well performing systems so they just think of management doublespeak that accomplishing nothing (since most such talk, respect for people, for example, is just talk and not of much value).

To show that the improvements made have real results I think you then have to switch follow “I did x,y,z’ with “which allowed our team to accomplish a,b, c.” Unless you really did have to do most things yourself instead of creating the systems that allow others to perform well. In which case it makes it easier to say what I did, but should cause those doing the interviewing to ask why you hadn’t set up better systems (at least it would if I were the one conducting the interview).

Related: How to Get a New Management Strategy, Tool or Concept AdoptedWhy work doesn’t happen at workBuild an Environment Where Intrinsic Motivation FlourishesCircle of Influence

When Companies Can Treat You Like an ATM, Many Will Do So

The End of Refrigeration

One small custom chip, some relays, a transformer, a couple of heat sinks, and a bunch of passive parts. Maybe a build cost of $20-30 or so? But GE’s price to me was $250, plus $150 for the 20 minutes it took to pull out the old one and swap in the new one.

Paying $400 for a big piece of physical gear plus a couple hours of labor didn’t bother me. Paying $400 for a primitive circuit board and a few minutes to plug it in does.

Bottom line: $400 because a $2.02 Song Chuan 832 Series 30 A SPDT 12 VDC Through Hole General Purpose Heavy Duty Power Relay burned out.

This is a combination of companies 1) not being customer focused, 2) short term thinking, 3) very ologopolistic markets (very little competition). So when you are looking at this from the view of providing the best system, for in this case refrigeration, it is not a very difficult solution. You would want to minimize loss (have parts last) and in case they don’t minimize replacement cost. You would design the entire system so the parts that do burn out are easily replaceable and cheap and ideally notify you which part is broken (without the need for expensive contractor visits).

However, if your goal is to maximize company profit it is easy to see how you would develop a system that rips off the customer (very expensive part replacement, huge text messaging fees…) and attempts to capitalize on very little competition in the marketplace and customers that cannot reasonable analyze the system to see how they will be penalized by choosing your very expensive to maintain equipment. It is what they seem to teach in business school – take as much advantage of your customers as you can get away with. I prefer the Jeff Bezos school of thinking

There are two kinds of companies, those that work to try to charge more and those that work to charge less

It is a vastly different mentality to try to charge customers less as Amazon does (rather than say the practices of: Verizon, Bank of America, AT&T or Comcast). Your organization has to focused not on your quarterly profit (and if you are think kind of company, probably your personal bonus targets) but in serving your customers well, and in continually improve the value you provide to customers. And the company takes a share of the value just as all other stakeholders do (customer, employees [not just those in the c-suite)], suppliers, society…). Not only do I want to be a customer of this kind of company, I want to be a stockholder.

Related: Drug Prices in the USAWorse Hotel Service the More You PayCustomer Service is Important$8,000 per gallon printer inknew deadly diseases (often companies rely on bad “intellectual property” policies to restrict customer options)

Factorial Designed Experiment Aim

Multivariate experiments are a very powerful management tool to learn and improve performance. Experiments in general, and designed factorial experiments in particular, are dramatically underused by managers. A question on LinkedIn asks?

When doing a DOE we select factors with levels to induce purposely changes in the response variable. Do we want the response variable to move within the specs of the customers? Or it doesn’t matter since we are learning about the process?

The aim needs to consider what you are trying to learn, costs and potential rewards. Weighing the various factors will determine if you want to aim to keep results within specification or can try options that are likely to return results that are outside of specs.

If the effort was looking for breakthrough improvement and costs of running experiments that might produce results outside of spec were low then specs wouldn’t matter much. If the costs of running experiments are very high (compared with expectations of results) then you may well want to try designed experiment values that you anticipate will still produce results within specs.

There are various ways costs come into play. Here I am mainly looking at the costs as (costs – revenue). For example the case where if the results are withing spec and can be used the costs (net costs, including revenue) of the experiment run are substantially lower.
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Why Lean is Different


Why Lean is different by Operae_Partners

Short webcast by Michael Ballé discusses what makes lean manufacturing different: going to where the work is done, standardize processes (from the gemba view), practice respect for people and continually improve. Lean thinking focuses on achieving better results and through that process improves trust and teamwork internally, as well as better supplier and customer relationships.

Related: Non-technical Control Chart WebcastMihaly Csikszentmihalyi: Creativity, Fulfillment and Flowlean management, books, articles…

Innovation in Thinking and the Web

Investing time and effort to attract “the right kind” of contributors to a news site

He thought we needed to make the same shift with our users – instead of seeing having to engage with them digitally as a time-consuming and resource eating problem, we should be seeing our audience as an asset to the brand. Any online organisation that doesn’t include readers in the production chain is inherently inefficient.

I agree. And I think this is a good example of an organization needing to adapt to the changing environment. I thought about what I would do if I ran a news site and how I would try to take advantage of the possibilities to increase engagement using internet technology.

I do think if I was trying to increase engagement I would try to figure out how to highlight thoughtful commenters. I would probably try to look into something like the commenting system on Reddit (with Karma) and also the ability to follow commenters (like you can follow article contributers on Seeking Alpha). I would look at giving value back to good comments (maybe something like commentluv). I would definitely have a pages where you could view more comments by a commenter. I would try to set up categories and then list top commenters on local politics, local sports, health care… I would display in the order of popular comments (like Reddit) not just list in order made. There are lots of ideas I don’t see used (but I haven’t really thought about it until 5 minutes ago – maybe these are already widespread, or maybe I haven’t really though out why they wouldn’t work well).

I just remember a post here previously about a newspaper in Kansas that was taking some sensible actions, and seemed to get the value chain they were serving. I would also take a look at them if I were really going to do this for a news organization.

This blog has a failure miserable, engagement with readers. Hopefully I can work on improving that in the next year. My last post, Customer Focus and Internet Travel Search (is the effort of one of the 4 founders of Reddit).

Related: Joel Spolsky Webcast on Creating Social Web ResourcesJohn Hunter online (Reddit comments…)Delighting CustomersPrice Discrimination in the Internet Age

Customer Focus and Internet Travel Search

The internet should make finding airline flight information easy. Instead it is a huge pain. Hipmunk has taken on the challenge of doing this well, and I think they have done a great job. This video provides an excellent view of both web usability and customer focus. This is a great example of focusing on providing customer value and using technology to make things easy – which is done far to little at most companies.

Related: Innovation Example (Farecast – which seems to have been bought by Microsoft and broken)Making Life Difficult for CustomersConfusing Customer FocusJoel Spolsky Webcast on Creating Social Web ResourcesCEO Flight Attendant

Productivity Improvement for Entrepreneurs (and Everybody Else Really)

The 3 Factors That are Limiting Your Productivity by Evan Carmichael

Elimination is at the core of every successful business. You have to focus on what you’re really good [at], what drives your business forward, and what you’re legally required to do in order to stay in business. Everything else should be eliminated.

Just because everyone else does it or because you’ve always done it that way, it doesn’t mean you have to continue doing it.

The order of Eliminate, Automate, Delegate is very important.

Eliminate is first. You don’t want to automate or delegate something that can be eliminated because it’s a non-productive task. Automate is next. You don’t want to delegate something that can be automated because it is more expensive and more prone to error.

I agree that eliminating non-value/low-value work should be done much more often. Automating makes a great deal of sense, though I would generalize it to process improvement. Automation is great: I think that is a specific form of process improvement – automation is wise, but maybe limiting. You improve productivity both by taking less time and by producing more effectively. If you produce something of more value to customers in the same time that improves productivity.

I also think there is another important area for people to think about – new ideas. Spending more time on something might seem counter-productive to productivity improvement. It takes time after all. Going and seeing what is really going on with your own eyes takes time, but trying to save time by acting based on reports results in ineffective and therefore unproductive action.

One of the things I first when looking at using internet technology to improve performance was that the technology opens new opportunities that were not feasible previously. People often focused just on how to improve what was done. People forget to look at things that were not pursued before that are now possible. With the time you save by eliminating, improving and delegating maybe you would get a big productivity improvement by coaching someone – or by being coached yourself. Or by reading about how to apply successful management improvement strategies that are too often ignored. Or you can learn about a new strategy that is more effective such as, combinatorial testing. Or learn to eliminate ineffective strategies such as: multitasking .

A number of “new ideas” are round about ways to eliminate work, in some form, though in a bit less direct way than people normally would consider elimination. For example, if you focus on reducing turnover, you can eliminate time spent bringing new people up to speed. If you make a process more reliable you can reduce the time spent dealing with the problems from a less reliable process.
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Learn by Seeking Knowledge – Not Just from Mistakes

Being open to new ideas and new knowledge is what is needed to learn. Experimenting, seeking out new knowledge is even better.

You can be successful and see an even better way to do things and learn from it. This seems the best way to learn to me – not to just learn from mistakes. Of course this means your goal has to be improvement not just avoiding more mistakes than before.

Your actions are based on theories (often unconsciously): and learning involves improving those theories. Learning requires updating faulty ideas (or learning new ideas – in which case ignorance rather than a faulty theory may have lead to the mistake). Encouraging people to learn from mistakes is useful when it is about freeing them to make errors and learn from them. But you should be learning all the time – not just when you make mistakes.

You can be also be wrong and not learn (lots of people seem to do this). This is by far the biggest state I see. It isn’t an absence of people making mistakes (including carrying out processes based on faulty theories) that is slowing learning. People are very reluctant to make errors of commission (and errors of commission due to a change is avoided even more). This reluctance obviously makes learning (and improvement) more difficult. And the reluctance is often enhanced by fear created by the management system.

It is best to be open and seek out new knowledge and learn that way as much as possible. Now, you should also not be scared to be wrong. Taking the right risks is important to improving – encouraging creativity and innovation and risk taking is wise.

Experiment and be open to learn from what could be better and improve (PDSA is a great way to try things and evaluate how they work). And the idea is not to be so conservative that every turn of the PDSA cycle has no failures. In order to get significant successes it is likely you will try things that don’t always work.

The desire to improve understanding (and the desire to improve results provides focus to the learning) is what is valuable in learning – not being wrong. Creating a culture where being wrong needs to be avoided harms learning because people avoid risk and seek to distance themselves from failure instead of experimenting and digging into the details when something goes wrong. Instead of learning from mistakes people try to stay as far away from them and hide them from others. That is not helpful. But what is needed is more desire to continually learn – learning from mistakes is wise but hardly the only way to learn.

Related: The Illusion of Knowledgeconfirmation biasManagement is Prediction

How to Get a New Management Strategy, Tool or Concept Adopted

Often when learning about Deming’s ideas on management, lean manufacturing, design of experiments, PDSA… people become excited. They discover new ideas that show great promise to alleviate the troubles they have in their workplace and lead them to better results. But how to actually get their organization to adopt the ideas often confounds them. In fact, I believe most potential improvements efforts may well fail even before they start because people can’t get past this problem.

I believe the way to encourage adoption of management improvement tools, methods and ideas is to solve people’s problems (or give them new opportunities). Instead of trying to convince people by talking about why they need to adopt some new ideas, I think it is much better to show them. To encourage the adoption of whatever it is (a philosophy like Deming or a new tool) try to find projects that would be good candidates for visible success. And then build on those successes.

For adopting whole new ways of working (like lean thinking) you go through this process many times, adding more and more new ideas to the accepted way of doing things. It is a bit easier if you are the CEO, but I think the strategy is very similar whoever you are. For smaller efforts a boss can often just mandate it. But for something like a large improvement in the way work is done (adopting a lean management system, for example), the challenge is the same. You have to convince people that the new methods and ideas are valuable and that they can use the ideas to help improve results.

Start small, it is very helpful if initial efforts are fairly small and straight forward. You often will have limited resources (and limited time people are willing to invest) at first. so start by picking projects that can be accomplished easily and once people have seen success more resources (including what is normally the most important one – people’s time) should be available. Though, honestly getting people to commit will likely be a challenge for a long time.

It is a rare organization that adopts a continual improvement, long term focus, system thinking mindset initially. The tendency is often strong to focus on fire fighting, fear (am I taking a risk by doing x, if I spend time improving y – what about the monthly target my boss is measuring me on…) and maintaining the status quo. It is baffling to many hoping for improvement, when you have huge successes, and yet the old way of doing things retains a great hold. The inertia of organizations is huge.
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Good Process Improvement Practices

Good process improvement practices include:

  • standardized improvement process (pdsa, or whatever)
  • Going to the gemba – improvement is done where the work is done. You must go to the where the action is. Sitting in meeting rooms, or offices, reading reports and making decisions is not the way to improve effectively.
  • evidence based decision making, data guides decision making rather than HiPPO
  • broad participation (those working on the process should be the ones working on improving it and everyone in the organization should be improving their processes)
  • measurable results that are used to measure effectiveness
  • pilot improvement on a small scale, after results are shown to be improvements deploy standardized solutions more broadly
  • visual management
  • Standardized work instructions are used for processes
  • one of the aims of the improvement process should be improving peoples ability to improve over the long term (one outcome of the process should be a better process another should be that people learned and can apply what they learned in future improvements)
  • quality tools should be used, people should be trained on such tools. The tools are essentially standardized methods that have been shown to be effective. And most organization just ignore them and struggle to reinvent methods to achieve results instead of just applying methods already shown to be very effective.
  • the improvements are sustained. Changes are made to the system and they are adopted: this seems obvious but far too often process improvements are really just band-aids that fall off a few weeks later and nothing is done to sustain it.
  • goals, bonuses and extrinsic motivation are not part of the process
  • The improvement process itself should be continually improved

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