Tag: Kaizen

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Reducing Inventory

Yesterday’s post on vendor managed inventory touched on a couple of things about “lean” and reducing inventory that I’d like to explore further.

All too often “inventory reduction” has been a way to “sell” a lean manufacturing implementation. The reduction of inventory becomes the objective. While this isn’t inherently a bad thing, it is all to easy to get caught up in the trap of “management by measurement” and do it the wrong way.

Reduced inventory is a result of good kaizen, but it isn’t the justification for doing it. The purpose of kaizen is to solve problems, specifically the problems that disrupt the smooth flow of work and creation of value. Solving those problems saves time – worker’s time, customer’s time, leader’s time because everything runs more smoothly and predictably.

The primary reason that inventory is there is because things aren’t smooth and predictable. Once they are, you can take some of it out.

The necessity to have inventory at any given point in the system is evidence of a problem that has not yet been solved. (Including, sometimes, simply having poor inventory management, which is another way of saying “overproduction.”)

By asking “What must we do to live without this piece of inventory?” you can uncover the next problem to solve, and then make a decision to solve it.

If it is solved, then inventory can be reduced. But it doesn’t happen automatically, you have to actually take it out of the system and keep it from coming back.

But in any case, this is a lot different than just shoving the ownership of the inventory onto someone else.

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Without Standards There Can Be No Kaizen

The meaning of this famous quote, attributed to Taiichi Ohno, becomes much more clear in the context of “Chasing the Rabbit” and previous published research by Steven Spear.

Spear’s research goes beyond Toyota’s process and delves into a more general question about how any organization playing in an otherwise level field can continuously out perform similar organizations in similar circumstances. This makes Toyota is a subset or an instance of a very fundamental principle, rather than a special, complex, unique case.

I think that is important. Some critics say Spear is making a soft version of the TPS. I think quite the opposite. He is explaining why it works.

And why it works comes right back to Ohno’s quote.

To better understand Ohno’s quote, let’s compare Ohno’s context with Spear’s.

All of us have been taught Ohno’s three elements of standard work:

  1. Takt time
  2. Work sequence
  3. Standard inventory

In “Decoding the DNA of the Toyota Production System” (a summary of his PhD dissertation), Spear describes the first rule-in-use he observed:

All activities are highly specified in terms of content, sequence, timing and outcome.

Further, Spear’s research concluded that the process steps themselves include frequent, nearly continuous, built-in checks that are designed to call attention to any departure from the specification. It is those built in checks which, on an assembly line, trigger an andon call and start the escalation process.

It is the escalation process which, in turn, results in problem solving and improvement.

It is any departure from the standard which calls the standard itself into question and results in investigation to understand more about the process.

The elements of takt, sequence and standard inventory define not only standard work, but they define elements of the built-in checks.

Takt time is the standard. Cycle time is the actual.
Actual cycle time is compared to the takt every time the process is carried out. If it takes longer than expected – problem, andon, escalation, problem solving.

The defined work sequence is the standard. It is (or should be) checked against the actual work sequence every time it is carried out. If something knocks the worker off the standard sequence – problem, andon, escalation, problem solving.

The standard inventory is the minimum amount of inventory required for the process to be successful at takt. Just as the work cycle is timed against the takt time, actual inventory can be compared with the standard. Too little? The process gets halted. That is a problem. Andon, escalation, problem solving. How do you check for too much inventory? Inside a process, specified inventory locations (5S, folks!). Inventory out of place? That is a problem. Andon, escalation, problem solving.

In regular takt-based work, these things in combination are a very effective set of cross checks of actual vs. specified work. BUT these are only tools that set up the system for kaizen.

It is the problem solving – the seeking to understand why the exception occurred that is true kaizen. This should must happen rapidly and every day. Not just during special “events,” every day.

It is part of the work, just like putting on protective equipment, just like maintaining the machines, just like cleaning up. Only this part of the work actually improves the operation.

So – without first specifying what is supposed to happen, there is no way to determine if what actually happened is routine or cause for investigation, learning and improvement. Then the exceptions become the routine because there is no expectation of otherwise. Look up the term “normalizing of deviance” and get an idea what the ultimate consequences can be.

That is why the first step in improving a process is often to attack ambiguity itself. This is especially true in administrative processes, and it is critical at the points where one process step turns over work to another.

If a defect-free outcome has not been specified, people are left with the leadership cop-out of “do the best you can” and that results in continuous erosion of morale, quality, delivery, cost. It is anti-kaizen. It is what is very much like kaizan – faking it.

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Why Doesn’t Daily Kaizen Happen?

More than one organization gets stuck in kaizen events. By "stuck" I mean that kaizen events are the only mechanism for improvement. A good indicator of this is "waiting for a kaizen event" to make an improvement that everyone agrees should be made.

At the same time, I see leaders who understand that these kinds of improvements should be made on a daily basis, but those leaders are frustrated because that doesn’t happen.

So why does this happen?

There are a few things that have to be in place, but even with a workforce that understands improvement and where this is going, even with shop floor leaders who understand how to do it, that doesn’t seem to be enough.

So here are some things to think about.

You block out time during the day for your start-up meeting, end-of-shift cleanup (a different topic). You block out time for preventative maintenance (you do, right?). You block out time and resources for the things you expect to get done.

Do the low-level work groups capture, in real time, the little issues that disrupt smooth work? Those are your daily kaizen opportunities.

Do you block out time for daily kaizen? If you don’t, then you are saying "Do kaizen when there is nothing else to do. Your daily kaizen time should not count as "available minutes" when calculating your takt time.

Do the Team Leaders and Supervisors expect the work teams to work on those problems during the kaizen time?

The bottom line: Don’t just wish it would happen. Look at what is necessary for success (skill, time, leadership, tools, expectations), make sure those things are available. If actual events are not what you planned, then study and understand why not and fix it. Daily kaizen is no different than production. You have to plan for it.

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Bloodletting: Why Controlled Experiments are Important

Bloodletting: Why Controlled Experiments are Important

I want to start this post with the last paragraph of this article:

Next time someone tells you that they are sure their idea will work, consider running a prototype in a controlled experiment, and make a data driven decision!

Now – the article itself is in the context of Microsoft software development, but this is what "lean thinking" is all about.

In the Toyota Production System, processes and the organization are deliberately constructed so that a kaizen experiment in one area is unlikely to affect another – at least not before there is ample warning and opportunity to reverse the change.

Every production cycle itself is conducted as a controlled experiment testing the hypothesis that the process:

  • Can be conducted as specified.
  • Delivers the specified results.

Of course – and here is the key point – it is only an experiment if someone actually examines what really happens. And this is the fundamental difference that is captured in the quote at the top.

A truly lean process has built in checks that check, each and every time, whether the idea works. Any time an idea doesn’t work, there is an expectation that the process will be stopped and understood.

Continuing to blindly produce, without knowing if each and every process is working as planned, without knowing if the result is as planed each and every time is being sure it will work. It is bloodletting.

Don’t bleed your process, or your company, to death with things you "know will work."

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Costs and Kaizen

How does kaizen actually show up on the bottom line?
This is a question that gets asked a lot, and honestly, we owe the asker a better answer than “it just does, trust us.” (Even though this is true.)

Here’s my thinking – it shows up two ways.
One is intangible. By that I mean it is incredibly difficult to quantify, even afterwards. But it is there.

IF the organization manages to get the continuous improvement engine running – meaning they understand that “pursue perfection” is not a “step in implementation” but rather the thing that gets it going in the first place – then, over time, everything starts running more smoothly.

It is hard to put a hard-monetary return on things like:

  • Everybody is working together, as a team, toward the organization’s overall goals.
  • Everybody understands who the customer is, and keeps their focus there.
  • Every instance of a problem causes the organization to improve and learn.
  • Everybody comes to work knowing what they must do to succeed; knowing they can do it; knowing that, if there is a problem, they will find out right away; knowing that they will get support in resolving it.

In short, the organiztion performs, and that performance is getting better and better.
What is that worth? Is it better to have a superbly performing organization, or one which requires continuous micro-management of every detail? (Hint: It isn’t about hiring better people, it is about creating working conditions and processes where regular, competent people can create superb performance.)

But it is possible to understand some direct, tangible returns as well. In fact it is possible to set solid targets, understand what must be done to reach them, and track progress on activities and results.

Any organization that is self-funding (including a non-profit) must offer some kind of value to its paying customers. If “value” is what the customer is willing to pay, then it is easy to determine the, ah, value of the value.

“Value add” defines the economic result of a transformation process. We buy some stuff at some cost (value), transform it into something that is worth more to the customer, and sell it. The difference between what we paid for the stuff we bought, and what the customer paid for the product or service we sold is the “value add.”

Note that this has absolutely nothing to do with what it cost to make that transformation. Nothing at all. It is possible to add value and lose money at the same time. It happens every day.

It does cost something to run the operation that adds the value. When those costs are less than the total value added (over some period), then the organization gets to keep some of the money as profit.

When those costs are more than the amount of value added, then someone has to fund the gap – the owners / shareholders, debt, the money has to come from somewhere.

When it comes to costs, I like to keep things really simple and easy to understand.

Costs are incurred two ways, and in the details, they intermix.

  1. In order to operate, we spend money every day on things like payroll, rent, utilities. This is cash burn.
  2. We have stuff needed to operate. This is cash tied up in the business, capital, inventory, etc. Just having that stuff costs money, and a lot of this stuff depreciates. That depreciation can, in turn, be counted the same as cash burn, but real life is more abstract than that because, while payroll must be paid, “depreciation” is something we can hold our breath about.

I have not included the cost for materials that are transformed into finished product here. That cost is captured in “value add.” The above two things add up to the cost to add that value, and those costs are largely fixed (in the classic sense of the word), whether we make anything or not.

Aside from the actual materials that are bought, transformed, and sold, there are very few truly “variable costs.”

“Continuous improvement” means to continuously increase value add, and continuously decrease what it costs to add that value.

There are fundamentally four ways in increase value-add.

  1. Improve the product offering so that customers will pay more. Ideally this is done without increasing any costs. This is really the only leverage point of purely service businesses.
  2. Pay less for the raw materials and parts – push your suppliers for lower prices.
  3. Change the engineering design to one that is less expensive to source.
  4. Examine your make / buy. Look for high-leverage items that your currently purchase. These are items which:
    1. We could make if we wanted to.
    2. Have a very high differential between the cost of the pieces and what we pay for them. (i.e. the supplier has a very high value-add to us.)

    Now, here’s the rub (and where this ties in to kaizen). If you have been doing a good job at kaizen, you have made some people available. If you know how to make these high leverage parts, can you put those people to work making them? A lot of this depends on the capital required, etc. but, as a general rule, the further up the supply chain you reach, the higher your value add. It comes down to capability and cost. And if you are using labor made available through kaizen, it does not matter what this labor costs. If you are adding more value today than you were yesterday, and incurring exactly the same costs to do so, your profit is higher. And the last time I checked, that was the name of the game.

Aside from increasing value-add, the other objective is to do so at the lowest possible cost, and there is a bit of a circular reference here.

Good kaizen can free up a lot of time. I suppose, if you wanted to do scorched-earth kaizen, you could immediately lay those people off. (Don’t expect much help with further improvements after that.) Aside from the ethical issues, these kinds of actions are really disruptive to the organization, in ways that are difficult to quantify.

If you are trying to simply increase production volume (the right kind of problem to have), then dealing with this issue is fairly simple, you just avoid hiring more people. You increase output without increasing payroll.

But also take a look at the in-sourcing option mentioned above. A lot of organizations overlook these kinds of opportunities today.

Like I said, this model is very simple. It is essentially the “throughput accounting” model offered by the Theory of Constraints folks. (Believe me, I don’t just make this stuff up.) Traditional cost accounting models can be mapped directly into this model. I just find it a lot easier to understand, and more importantly, to explain to the people who actually have to make all of these things happen.

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The Value of People

How can some companies not only survive, but thrive when operating in “high cost labor” areas, while others are struggling even as they are busy chasing the lowest possible costs?

I would like to suggest that one key difference is the attitude toward people. On the one hand is the “people as cost” model. This model usually has a couple of built-in assumptions.

  • The number of people required to do a particular task is fixed, often against some kind of earned-hours standard.
  • The cost driver is wages, salaries and benefits.

On the other hand is the (seemingly) rare organization that truly believes that people are their strength, or the well worn out “our greatest asset.”

The assumptions which are required for this belief are:

  1. People’s net productivity can always be improved.
  2. The cost driver is the amount of time wasted coping with all of the small problems that keep things from going perfectly.

The above assumptions, of course, are anchored in a faith-based position that perfection is possible. (see “Chatter as Signal“)

So… what kinds of actions to each of these two models drive?

The first one – people are cost – says to find the cheapest possible labor and hire it. Since factory wages in China are (right now) running about 1/12 or less of those in the USA or Europe, that seems a logical choice. Here’s the rub.

You can outsource the entire job to another company – give the work to the lowest bidder. Now, if you truly believe that the amount of labor is fixed, and that only lower wages can change cost, then this is the obvious choice. You are relying on your superior supply chain management system to ensure you select a supplier that can maintain, and maybe even improve, the quality they deliver, plus hold the line against increases in materials, energy, and their own labor costs. In short, you are looking for a supplier who believes the opposite of what you do. Your ideal supplier knows they can bid aggressively, get your work, and then improve their profit position by applying continuous improvement.

Or you can export the production and set up your own operation in a “low wage area.” You are shifting your core beliefs about people to another culture, and another language. Communication (believe me!!) is a major issue, even if the managers work for you.

AND.. if “labor is cheap” then the solution to problems is to throw people at them. The cost differential you actually get almost NEVER reaches the advantage of a 1:1 substitution. Oh – and you just added 3-4 weeks to your lead / response times.

If, on the other hand, you take the attitude that the most precious resource in your operation is people’s time – no matter what you pay them, and take the attitude that to deliberately waste anyone’s time is to show great disrespect, then I would suggest that even in high-wage areas you can drive levels of improvement in productivity, quality and response to your customers that would be difficult to beat anywhere.

So – before you reflexively outsource or relocate to a “low wage area” please check your attitude about people. What are your expectations, and why is it that you don’t believe your own people are capable of delivering a 10x improvement?

Who are your competitors? What do they do?
What would you do if you had to compete with Toyota? or Komatsu? (to name two that come to mind) They are building product in your back yard, why can’t you?

Afterthought: Some companies end up outsourcing the skills they need to improve their own products and systems. They no longer understand the technology they sell, they no longer know how to make what they sell. I remember a time when I reminded an (arrogant) procurement executive that it was possible to outsource the entire procurement process just as easily. Another team had outsourced all of their direct labor management… they contracted the labor and the first level supervisors into their factory. Where did they really believe this was leading?

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Shingijutsu Kaizen Seminar – Day 2

The day today ended about 10 pm. It is 11 pm now as I write this, which translates to 7 am Pacific Time. I will leave the remaining time zones as an exercise for my European readers. (Hello, Corrie!)

Once we hit the shop floor today we were in “understand the current situation” mode. It turned out to be more difficult than I expected due to a high level of variation, some real, but most self-inflicted, on the line. Yesterday I mentioned my great plan to put the less experienced people on the front line of the cycle time study. Well, I ended up doing that, along with everyone else, since the area we are working is fairly spread out and has 11 people working in it.

After getting our heads around things, we have these areas of focus tomorrow.

  1. Establish an even and visual pitch on the moving conveyor. We need to know when work cycles are supposed to start and end so we have some kind of baseline about where the cycle time issues are. This will help.
  2. Basic 5S and parts presentation in the first position. This guy is responsible for setting the takt for everyone else since he is the one who launches the unit down the conveyor after his stationary build. We might try to move most of his build to the conveyor too. I think it has been on the conveyor in the past because the unit moves through the first pitch without anyone touching it.
  3. Start recording line stops. When, why, how often. Basic understanding of where the problems are.
  4. Detailed work combination analysis of a semi-automated testing operation at mid-line. We know there are disruptions there, but those disruptions cause major distortions to the actual (vs. planned) work cycle, so we need to understand whether the operation even has the theoretical capability to meet takt.
  5. Work on a sub-assembly operation and at least try the concept of building unit-by-unit instead of batching to the weekly published schedule. Stuff is late to the line. It is probably not a capacity issue but rather that capacity being used making stuff other than what is needed right now. This will be a little complicated because they actually feed parts to more than one line position. Thus if they get truly synchronized with their customer, they will not build a unit set of parts because this is a mixed line, and different positions have different products at any given time. Instead they will have to shift their focus from “unit” to their individual main-line customers and build what they need next.

The real overall challenge is that this is a two-day event, and we spent the first day just getting our heads wrapped around all of this. So tomorrow will be busy. But people are learning, and that is the whole point. It is important not to lose sight of the reason we are here. If the host company gains, so much the better, but it is really about the participants learning something we can take back.

And yes, I have been deliberately vague so as not to compromise the host company. They have been at this a long time, and done some very impressive things. This particular area, however, needs work, which I suppose is why we are in it.

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Waste

I guess four months into this, it kind of makes sense to talk about waste. But rather than repeat what everyone else says, maybe I can contribute to the dialog and toss out some things to think about.

Identifying / Seeing Waste.

Taiichi Ohno had 7 wastes, a few publications say 7+1. I have always disliked trying to put “types of waste” into buckets. I have seen long discussions, some of them fairly heated, about which list of wastes is “correct” and whether this waste or that waste should be included, or whether it is included in another one. None of this passes the “So What?” test. (A related military acronym is DILLIGAS, but I’ll leave it as an exercise for the reader to work out what it means.)

The problem, as I see it, with lists of categories isn’t the categories themselves. It is that we teach people using the categories. We make people memorize the categories. We create clever mnemonics like TIMWOOD and CLOSEDMITT. We send them on waste safari with cameras to collect “examples” of various types of waste. Well.. you can’t take a photo of overproduction because it is a verb. You can only photograph the result – excess inventory. So which is it? People end up in theological discussions that serve no purpose.

Like I mentioned in an earlier post, teach it by inverting the problem. The thing people need to understand is this: Anything that is not adding value is waste. If you understand what value is, then waste is easy to see. It is anything else. What category of waste is that? Who cares. That only matters when you are working on a countermeasure.

What about “necessary waste?” Even Ohno concedes there is some of that. OK – ask “does this work directly enable a task that does add value?” Then it is probably necessary – for now.

Let’s take a real-world example from my little corner of the world – welding. Welding is pretty easy. If there is an arc, it is very likely value is being added. Not always, but it is a good place to start. Now – watch a welder. What does he do when he is not “burning wire?” (the phrase “and producing a quality weld” has to be tacked onto the end of this because I can burn wire, but it doesn’t mean I am welding.)

What stops the welder from welding? When, and why, does he have to put down the gun and do something else? For that matter, what makes him let go of the trigger and stop the arc? Is he loading parts into the jig? Does he have to jiggle those parts into place? Does he have to adjust the jig?

Special Types of Waste

In spite of what I said above, there are two types of waste that merit special attention. Most everyone who can spell “J-I-T” knows that overproduction is one of them. I won’t go into it here – anyone who is reading this probably already gets that at some level. If I am wrong about that, leave a comment and I’ll expand.

The other is the “waste of waiting.” Of all of the categories, overproduction is clearly the worst, but the waste of waiting is the best. Why?

It is the only type of waste that can be translated directly into productivity. It is the waste you are creating as you are using kaizen to remove the others. That is because all of your kaizen is focused on saving time and time savings, in the short term, turn busy people into idle people.

Let me cite some examples:

  • The Team Member is overproducing. You put in a control mechanism to stop it. Now the team member must wait for the signal or work cycle to start again before resuming work.
  • You remove excess conveyance by moving operations closer together. The person doing the conveyance now has less to do. He is idle part of the time where he was busy.
  • Defects and rework – eliminate those and there is less to do. More idle people.
  • Overprocessing – eliminate that, less to do.
  • Materials – somebody has to bring those excess materials. Somebody has to count them, transport them, weigh them. Somebody has to dispose of the scrap.
  • Inconsistent work or disruptions: Eliminate those and people are done early more often than they were. More idle time.

If you look at a load chart, these are all things which push the cycle times down. You have converted the other wastes to the waste of waiting.

Now your challenge is how to convert that wait time to productivity. What you do depends on your circumstance. You can drop the takt time and increase output with the same people. Or you can to a major re-balance and free up people – do the same with fewer, and divert those resources to something productive elsewhere.

Does something stop you from doing that? Do you have two half-high bars that you can’t combine onto one person? Start asking “Why?” and you have your next kaizen project. Maybe you have to move those processes closer together, or untie a worker from a machine.

Summary:

  • Don’t worry too much about teaching categories of waste. Teach people to see what is truly value-adding, and to realize everything else is waste – something to streamline or eliminate.
  • In most cases your kaizen activity will result in more waste of waiting. This is good because wait-time is the only waste that converts directly to increased productivity.
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Be A Perfect Supplier; Be A Perfect Customer

Operations that work to the “push” are well known for complex and interdependent problems. What looks like a problem in one area often has causes, or parts of causes, in other areas. Quality problems, delivery problems (late, too much, too little, wrong stuff), sub-optimizing attempts to reduce local cost.. all of these things propagate unchecked through the plant. To fix one area means having to fix almost all of the others at once. This initial improvement gridlock is pretty common.

When you start talking about implementing JIT in an environment like that, the pushback is visceral and, to be honest, legitimate. The only reason they get anything done is because the system runs to sloppy tolerances and doesn’t expect much. JIT demands a degree of mutual vulnerability, at least it seems that way when it is first presented.

The other really big psychological issue is that lean is often presented as a solution to all of these problems. Quite correctly, the survivalist shop floor supervisors don’t see that. And they are right. The problems do not go away when you implement flow. I sometimes find it surprising how many people don’t get that. All they see is fewer problems in operations that have flow, and they mix up cause and effect. Good flow is the result of solving the problems. Not the other way round, but I digress.

If you are dealing with this problem gridlock, where do you start? The first step is to contain the problems as close as possible to their sources.

The objective is to apply what temporary countermeasures are necessary to appear as a perfect supplier to your downstream customers; and the appear as a perfect customer to your upstream suppliers.

So what is a “perfect supplier?” That is probably the easier of the two logical questions to answer. A perfect supplier is capable of supplying what you need; when you needed it; with perfect quality; one-by-one; at takt.

What is a “perfect customer?” This one is a little harder, but it is good to look back at what makes a perfect supplier. Ask yourself – what things does the customer do that makes it difficult to be a good supplier? What does a bad customer look like?

  • They order or demand things in batches.
  • They give no advance notice about what they need.
  • Their demand is unpredictable and inconsistent.

A lot of this seeming unpredictability actually originates in the supplying process. I recall a case where the manager of a fabrication shop swore that his customer’s demands were totally random. At the assembly plants, though, they operated to takt with a steady mixed-model schedule. There was very little change from one day to the next. Why the big disconnect? The fabrication ship ran things in big batches, and set up big batch pull signals. Naturally those big batch pull signals would go a long time between trigger points, so they would seem to come back at arbitrary times, for huge amounts. Self-inflicted gunshot wound. Once they took the simple step of shipping things in smaller containers, a lot of that seeming instability went away. Smaller containers meant more frequent releases of pull orders, which gave them a cleaner picture of the demand picture. Think of it this way: The smaller the pixels on your screen, the more resolution you have in the image.

So that does the perfect customer look like? Level, predictable demand at takt with no major fluctuations.

Think of the purpose of heijunka or leveling production. Because customer demand arrives in spikes, batches, lumps, the leveling process is necessary to make that demand appear to be arriving exactly at takt time.

Although the books, such as Learning To See say there is only one pacemaker process or scheduling point, non-trivial flows frequently require re-establishing the pulse.

This is especially true if orders are batched up either through the ordering process itself or the delivery process. An example of this is a manual kanban process between an assembler and the supplier. Even though there is a paced assembly line and good leveling, kanban cards are collected and delivered to the supplying process in transportation-interval “chunks.” The supplier needs to have their own heijunka board to re-level the demand and pick at takt from the supermarkets. The alternative is that the demand arrives at the production cells in those same batches, and the smooth takt image is lost.

In a Previous Company we were working a project to establish pull on a trans-continental value stream that had five major operations, all in different geographic locations. To use the word “monument” does not even begin to describe the capital infrastructure involved, and there were a lot of these assets shared with other value streams, so relocating and directly connecting flows was out of the question. There were unreliable processes, big batches, transportation batches, end-using customers’ orders in huge, sudden surges based on their surge based business cycle. Step by step we isolated inventory buffers and ended up putting in heijunka to re-level the demand at nearly every stage of the process. It was big, ugly, cumbersome, but it worked to isolate problems within a process vs. pass them up and down stream.

The objective was simple: Use inventory buffers and heijunka to make each process in the chain appear as a perfect customer to its suppliers – always pulling exactly at takt. The consuming process “owned” the inventory buffers necessary to do this. Reason: Simple. The problems that cause them to be a less-than-perfect customer are theirs, so they own the inventory that is necessary to protect their suppliers from those problems. Likewise, that process owned whatever inventory was necessary them to appear to be a perfect supplier. They had to enable their customer to pull one-by-one, exactly at takt, from them, even if their problems kept them from producing that way.

Never mind that the downstream process didn’t actually consume at takt. THEIR inventory buffer translated their spiky signal into one which reflected the takt time.

All of this was very sophisticated and complicated, but in the long haul it worked. Megabucks of inventory came out of the system. Megabucks remained, but we knew exactly why it was there, and who had to solve what problems to reduce it.

If you can’t be a perfect customer, create the illusion that you are.

If you can’t be a perfect supplier, create the illusion that you are.

Then you own the problems yourself, you own the inventory-consequences of having those problems, and you control your own destiny.

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Invert the Problem

One very good idea-creation tool is “inverting the problem” – developing ideas on how to cause the effect you are trying to prevent. This is a common approach for developing mistake-proofing, but I just saw a great use of the idea for general teaching.

Ask “How could we make this operation take as long as possible?” Then collect ideas from the team. Everything on the flip chart will be some form of waste that you are trying to avoid. In many cases, I think, even the most resistant minds would concede that nothing on this list is something we would do on purpose.

It follows, then, that if we see we are doing it that we ought to try to stop doing it. And that is what kaizen is all about.