The Goal by Eliyahu M. Goldratt, Jeff Cox, and David Whitford
I tried to deliver the message contained in the book in the Socratic way. Jonah, in spite of his knowledge of the solutions, provoked Alex to derive them by supplying the question marks instead of the exclamation marks. I believe that because of this method, you the reader will deduce the answers well before Alex Rogo succeeds in doing so. If you find the book entertaining maybe you will agree with me that this is the way to educate, this is the way we should attempt to write our textbooks. Our textbooks should not present us with a series of end results but rather a plot that enables the reader to go through the deduction process himself.
And he’s saying, “Alex, I have come to the conclusion that productivity is the act of bringing a company closer to its goal. Every action that brings a company closer to its goal is productive. Every action that does not bring a company closer to its goal is not productive. Do you follow me?”
I reach for my briefcase, take out a yellow legal pad and take a pen from my coat pocket. Then I make a list of all the items people think of as being goals: cost-effective purchasing, employing good people, high technology, producing products, producing quality products, selling quality products, capturing market share. I even add some others like communications and customer satisfaction. All of those are essential to running the business successfully. What do they all do? They enable the company to make money. But they are not the goals themselves; they’re just the means of achieving the goal. How do I know for sure? Well, I don’t. Not absolutely. But adopting “making money” as the goal of a manufacturing organization looks like a pretty good assumption. Because, for one thing, there isn’t one item on that list that’s worth a damn if the company isn’t making money.
If the goal is to make money, then (putting it in terms Jonah might have used), an action that moves us toward making money is productive. And an action that takes away from making money is non-productive.
“Well, you’d have to have some kind of absolute measurement,” he says. “Something to tell you in dollars or yen or whatever just how much money you’ve made.” “Something like net profit, right?” I ask. “Yeah, net profit,” he says. “But you’d need more than just that. Because an absolute measurement isn’t going to tell you much.”
“Oh yeah?” I say. “If I know how much money I’ve made, why do I need to know anything else? You follow me? If I add up what I’ve made, and I subtract my expenses, and I get my net profit—what else do I need to know? I’ve made, say, $10 million, or $20 million, or whatever.” For a fraction of a second, Lou gets a glint in his eye like I’m real dumb.
“All right,” he says. “Let’s say you figure it out and you come up with $10 million net profit . . . an absolute measurement. Offhand, that sounds like a lot of money, like you really raked it in. But how much did you start with?” He pauses for effect. “You see? How much did it take to make that $10 million? Was it just a million dollars? Then you made ten times more money than you invested. Ten to one. That’s pretty goddamned good. But let’s say you invested a billion dollars. And you only made a lousy ten million bucks? That’s pretty bad.”
“So you need a relative measurement, too,” Lou continues. “You need something like return on investment . . . ROI, some comparison of the money made relative to the money invested.”
“You know,” he says, “it is possible for a company to show net profit and a good ROI and still go bankrupt.” “You mean if it runs out of cash,” I say. “Exactly,” he says. “Bad cash flow is what kills most of the businesses that go under.” “So you have to count cash flow as a third measurement?”
To make money by increasing net profit, while simultaneously increasing return on investment, and simultaneously increasing cash flow.
“They’re measurements which express the goal of making money perfectly well, but which also permit you to develop operational rules for running your plant,” he says. “There are three of them. Their names are throughput, inventory and operational expense.”
“Throughput,” he says, “is the rate at which the system generates money through sales.”
Then I ask, “But what about production? Wouldn’t it be more correct to say—” “No,” he says. “Through sales—not production. If you produce something, but don’t sell it, it’s not throughput. Got it?”
“The next measurement is inventory,” he says. “Inventory is all the money that the system has invested in purchasing things which it intends to sell.”
“And the last measurement?” I ask. “Operational expense,” he says. “Operational expense is all the money the system spends in order to turn inventory into throughput.”
One of them, I remember as I’m driving, was whether we had been able to sell any more products as a result of having the robots. Another one was whether we had reduced the number of people on the payroll. Then he had wanted to know if inventories had gone down. Three basic questions.
Increase throughput while simultaneously reducing both inventory and operating expense.
“Interesting, isn’t it, that each one of those definitions contains the word money,” he says. “Throughput is the money coming in. Inventory is the money currently inside the system. And operational expense is the money we have to pay out to make throughput happen. One measurement for the incoming money, one for the money still stuck inside, and one for the money going out.”
Then Stacey says, “Maybe Jonah feels direct labor shouldn’t be a part of inventory because the time of the employees isn’t what we’re really selling. We ‘buy’ time from our employees, in a sense, but we don’t sell that time to a customer—unless we’re talking about service.”
“First of all, the market determines the value of the product,” says Lou. “And in order for the corporation to make money, the value of the product—and the price we’re charging—has to be greater than the combination of the investment in inventory and the total operational expense per unit of what we sell.”
“Any money we’ve lost is operational expense; any investment that we can sell is inventory.” “The carrying costs have to be operational expense, don’t they?” asks Stacey.
Then we decide it depends, quite simply, upon what the knowledge is used for. If it’s knowledge, say, which gives us a new manufacturing process, something that helps turn inventory into throughput, then the knowledge is operational expense. If we intend to sell the knowledge, as in the case of a patent or a technology license, then it’s inventory. But if the knowledge pertains to a product which UniCo itself will build, it’s like a machine—an investment to make money which will depreciate in value as time goes on. And, again, the investment that can be sold is inventory; the depreciation is operational expense.
He says, “A balanced plant is essentially what every manufacturing manager in the whole western world has struggled to achieve. It’s a plant where the capacity of each and every resource is balanced exactly with demand from the market. Do you know why managers try to do this?”
“For one thing, there is a mathematical proof which could clearly show that when capacity is trimmed exactly to marketing demands, no more and no less, throughput goes down, while inventory goes through the roof,” he says. “And because inventory goes up, the carrying cost of inventory—which is operational expense—goes up. So it’s questionable whether you can even fulfill the intended reduction in your total operational expense, the one measurement you expected to improve.” “How can that be?” “Because of the combinations of two phenomena which are found in every plant,” he says. “One phenomenon is called ‘dependent events.’ Do you know what I mean by that term? I mean that an event, or a series of events, must take place before another can begin . . . the subsequent event depends upon the ones prior to it.
“The big deal occurs when dependent events are in combination with another phenomenon called ‘statistical fluctuations,’ ” he says. “Do you know what those are?” I shrug. “Fluctuations in statistics, right?” “Let me put it this way,” he says. “You know that some types of information can be determined precisely. For instance, if we need to know the seating capacity in this restaurant, we can determine it precisely by counting the number of chairs at each table.” He points around the room. “But there are other kinds of information we cannot precisely predict. Like how long it will take the waiter to bring us our check. Or how long it will take the chef to make an omelet. Or how many eggs the kitchen will need today. These types of information vary from one instance to the next. They are subject to statistical fluctuations.” “Yeah, but you can generally get an idea of what all those are going to be based on experience,” I say. “But only within a range. Last time, the waiter brought the check in five minutes and 42 seconds. The time before it only took two minutes. And today? Who knows? Could be three, four hours,” he says, looking around. “Where the hell is he?”
I’m the last operation. Only after I have walked the trail is the product “sold,” so to speak. And that would have to be our throughput—not the rate at which Ron walks the trail, but the rate at which I do. What about the amount of trail between Ron and me? It has to be inventory. Ron is consuming raw materials, so the trail the rest of us are walking is inventory until it passes behind me. And what is operational expense? It’s whatever lets us turn inventory into throughput, which in our case would be the energy the boys need to walk. I can’t really quantify that for the model, except that I know when I’m getting tired.
Then a long-lost memory from way back in some math class in school comes to mind. It has to do with something called a covariance, the impact of one variable upon others in the same group. A mathematical principle says that in a linear dependency of two or more variables, the fluctuations of the variables down the line will fluctuate around the maximum deviation established by any preceding variables. That explains what happened in the balanced model.
And I say, “The idea of this hike is not to see who can get there the fastest. The idea is to get there together. We’re not a bunch of individuals out here. We’re a team. And the team does not arrive in camp until all of us arrive in camp.”
“A bottleneck,” Jonah continues, “is any resource whose capacity is equal to or less than the demand placed upon it. And a non-bottleneck is any resource whose capacity is greater than the demand placed on it. Got that?”
“Oh, I see,” says Stacey. “The idea is to make the flow through the bottleneck equal to demand from the market.”
“But you’re not saying we should ignore quality, are you?” asks Bob. “Absolutely not. You can’t make money for long without a quality product,” says Jonah. “But I am suggesting you use quality control in a different way.” I ask, “You mean we should put Q.C. in front of the bottlenecks?” Jonah raises a finger and says, “Very perceptive of you. Make sure the bottleneck works only on good parts by weeding out the ones that are defective. If you scrap a part before it reaches the bottleneck, all you have lost is a scrapped part. But if you scrap the part after it’s passed the bottleneck, you have lost time that cannot be recovered.”
“Of course it does,” says Jonah. “And with that in mind, how do we optimize the use of the bottlenecks? There are two principal themes on which you need to concentrate . . . “First, make sure the bottlenecks’ time is not wasted,” he says. “How is the time of a bottleneck wasted? One way is for it to be sitting idle during a lunch break. Another is for it to be processing parts which are already defective—or which will become defective through a careless worker or poor process control. A third way to waste a bottleneck’s time is to make it work on parts you don’t need.” “You mean spare parts?” asks Bob. “I mean anything that isn’t within the current demand,” he says. “Because what happens when you build inventory now that you won’t sell for months in the future? You are sacrificing present money for future money; the question is, can your cash flow sustain it? In your case, absolutely not.” “He’s right,” admits Lou. “Then make the bottlenecks work only on what will contribute to throughput today . . . not nine months from now,” says Jonah. “That’s one way to increase the capacity of the bottlenecks. The other way you increase bottleneck capacity is to take some of the load off the bottlenecks and give it to non-bottlenecks.”
“That’s why I was asking those questions when we were out in the plant,” he says. “Do all of the parts have to be processed by the bottleneck? If not, the ones which don’t can be shifted to nonbottlenecks for processing. And the result is you gain capacity on your bottleneck. A second question: do you have other machines to do the same process? If you have the machines, or if you have a vendor with the right equipment, you can offload from the bottleneck. And, again, you gain capacity which enables you to increase throughput.”
“By the end of today, all work-in-process on the floor will be marked by a tag with a number on it,” he says and holds up some samples. “The tag will be one of two colors: red or green. “A red marker means the work attached to it has first priority. The red tags go on any materials needing to be processed by a bottleneck. When a batch of parts with that color marker arrives at your work station, you are to work on them right away.” Bob explains what we mean by “right away.” If the employee is working on a different job, it’s okay to finish what he’s doing, as long as it doesn’t take more than half an hour. Before an hour has passed, certainly, the red-tagged parts should be getting attention. “If you are in the middle of a setup, break the setup immediately and get ready for the red parts. When you’ve finished the bottleneck parts, you can go back to what you were doing before. “The second color is green. When there is a choice between working on parts with a red marker and parts with a green marker, you work on the parts with the red marker first. So far, most of the work-in-process out there will be marked by green. Even so, you work on green orders only if you don’t have any red ones in queue. “That explains the priority of the colors. But what happens when you’ve got two batches of the same color? Each tag will have a number marked on it. You should always work on the materials with the lowest number.”
the level of utilization of a non-bottleneck is not determined by its own potential, but by some other constraint in the system.”
You have created this mountain of inventory with your own decisions. And why? Because of the wrong assumption that you must make the workers produce one hundred percent of the time, or else get rid of them to ‘save’ money.” Lou says, “Well, granted that maybe one hundred percent is unrealistic. We just ask for some acceptable percentage, say, ninety percent.” “Why is ninety percent acceptable?” asks Jonah. “Why not sixty percent, or twenty-five? The numbers are meaningless unless they are based upon the constraints of the system. With enough raw materials, you can keep one worker busy from now until retirement. But should you do it? Not if you want to make money.”
Then Ralph suggests, “What you’re saying is that making an employee work and profiting from that work are two different things.” “Yes, and that’s a very close approximation of the second rule we can logically derive from the four combinations of X and Y we talked about,” says Jonah. “Putting it precisely, activating a resource and utilizing a resource are not synonymous.”
He explains that in both rules, “utilizing” a resource means making use of the resource in a way that moves the system toward the goal. “Activating” a resource is like pressing the ON switch of a machine; it runs whether or not there is any benefit to be derived from the work it’s doing. So, really, activating a non-bottleneck to its maximum is an act of maximum stupidity.
“And the implication of these rules is that we must not seek to optimize every resource in the system,” says Jonah. “A system of local optimums is not an optimum system at all; it is a very inefficient system.”
“No, it isn’t,” I tell him. “Since we began withholding materials from the floor until the bottlenecks are ready for them, the non-bottlenecks now have idle time. It’s perfectly okay to have more setups on non-bottlenecks, because all we’re doing is cutting into time the machines would spend being idle. Saving setups at a non-bottleneck doesn’t make the system one bit more productive. The time and money saved is an illusion. Even if we double the number of setups, it won’t consume all the idle time.”
“According to the cost-accounting rules that everybody has used in the past, we’re supposed to balance capacity with demand first, then try to maintain the flow,” I say. “But instead we shouldn’t be trying to balance capacity at all; we need excess capacity. The rule we should be following is to balance the flow with demand, not the capacity.
assumption that the level of utilization of any worker is determined by his own potential,” I tell them. “That’s totally false because of dependency. For any resource that is not a bottleneck, the level of activity from which the system is able to profit is not determined by its individual potential but by some other constraint within the system.”
“No, and that’s a third assumption that’s wrong,” I say. “We’ve assumed that utilization and activation are the same. Activating a resource and utilizing a resource are not synonymous.”
say an hour lost at a bottleneck is an hour out of the entire system. Hilton says an hour lost at a bottleneck is just an hour lost of that resource. I say an hour saved at a non-bottleneck is worthless. Hilton says an hour saved at a non-bottleneck is an hour saved at that resource.
Probably Mark Twain was right saying that ‘common sense is not common at all’ or something similar.”
Then it dawns on me. Here’s the answer. This is the technique that I should ask Jonah to teach me: how to persuade other people, how to peel away the layers of common practice, how to overcome the resistance to change.
“Alex, we blamed the distorted way in which product costs are calculated for giving the appearance that our net profit was only twelve point eight percent, rather than over seventeen percent as we believed was the case. I know that you were furious about it, but what I’ve found out is that there’s an even bigger accounting distortion. It’s tied to the way that we evaluate inventory, but it’s hard for me to explain. Maybe I’ll try to do it through the balance sheet.” He pauses again. This time I wait patiently. “Maybe I should start with a question,” he says. “Do you agree that inventory is a liability?”
“Of course, everybody knows that. And even if we didn’t know it, the last few months have shown to what extent inventory is a liability. Do you think we could have pulled off this fast response to orders if the floor had been as jammed up as before? And haven’t you noticed that quality has improved, and overtime has gone down—not to mention that we hardly ever have to expedite today!” “Yeah,” he says, still looking at his papers. “Inventory is definitely a liability, but under what heading are we forced to report it on the balance sheet?” “Holy cow, Lou!” I jump to my feet. “I knew that the financial measurements were remote from reality, but to that extent— to report liabilities under the heading of assets? I never realized the full implications . . . Tell me, what are the bottom line ramifications?” “Bigger than you think, Alex. I’ve checked and rechecked it, but the numbers do talk. You see, we’re evaluating inventory according to the cost to produce the goods. These costs include not only the money we pay for the raw materials, but also the value added in production.
“You know what we have done in the last few months. Donovan has worked only on things that we have orders for. Stacey has released material accordingly. We’ve drained about fifty percent of the work in process from the plant, and about twenty-five percent from finished goods. We’ve saved a lot by not purchasing new materials to replace this excess inventory, and the cash figures show it clearly. But on our books, the assets represented by inventory went down, since they were only partially compensated for by the cash we didn’t have to pay out. In this period, when we were reducing inventory, all the difference between the product cost and the material cost of the reduced inventory showed up as a net loss.”
I swallow hard. “Lou, you’re telling me that we were penalized for doing the right thing? That reducing the excess inventory was interpreted by our books as a loss?”
“What my people and I have done is to examine daily the queues in front of the assembly and in front of the bottlenecks— we call them ‘buffers.’ We check just to be sure that everything that’s scheduled to be worked on is there—that there are no ‘holes.’ We thought that if a new bottleneck pops up it would immediately show up as a hole in at least one of these buffers. It took us some time to perfect this technique, but now it’s working smoothly.
“Yeah. And it became even more interesting when we realized that we were visiting the same six or seven work centers every time. They’re not bottlenecks, but the sequence in which they perform their jobs became very important. We call them ‘capacity constraint resources,’ CCR for short.”
“I’m coming to it. See, these holes have become more and more dangerous lately—sometimes to the extent that assembly has to deviate significantly from their scheduled sequence. And it’s become apparent that the foremen of the CCRs have more and more difficulty supplying on time. Ralph was telling me that these work centers still have enough capacity, and maybe on the average he’s right, but I’m afraid that any additional increase in sales will throw us into chaos.”
“Don’t you realize that we’ve concentrated our improvement efforts too narrowly? We tried so hard to improve our bottlenecks, when what we should do is improve the CCRs as well. Otherwise we’ll run into an ‘inter-active’ bottleneck situation.
“The key is in the hands of production. These techniques to manage the buffers should not be used just to track missing parts while there is still time, they should be used mainly to focus our local improvement efforts. We must guarantee that the improvements on the CCRs will always be sufficient to prevent them from becoming bottlenecks. “Alex, Bob, that’s why I want this job so badly. I want to make sure that the material manager’s job will continue to be boring. I want to demonstrate how local improvements should be managed. And I want to show all of you how much more throughput we can squeeze from the same resources.”
After that it was easy. Relatively easy. It wasn’t too long before the process was written clearly on the board: STEP 1. Identify the system’s bottlenecks. (After all it wasn’t too difficult to identify the oven and the NCX10 as the bottlenecks of the plant.) STEP 2. Decide how to exploit the bottlenecks. (That was fun. Realizing that those machines should not take a lunch break, etc.) STEP 3. Subordinate everything else to the above decision. (Making sure that everything marches to the tune of the constraints. The red and green tags.) STEP 4. Elevate the system’s bottlenecks. (Bringing back the old Zmegma, switching back to old, less “effective” routings. . . .) STEP 5. If, in a previous step, a bottleneck has been broken go back to step 1.
“You’re right,” I say. And then, “It’s a little odd to call the market or the system of material release a bottleneck. Why don’t we change the word, to . . .” “Constraint?” Stacey suggests.
“It’s how physicists approach a subject; it’s so vastly different from what we do in business. They don’t start by collecting as much data as possible. On the contrary, they start with one phenomenon, some fact of life, almost randomly chosen, and then they raise a hypothesis: a speculation of a plausible cause for the existence of that fact. And here’s the interesting part. It all seems to be based on one key relationship: IF . . . THEN.”
“What they actually do is to derive the unavoidable results logically from their hypothesis. They say: IF the hypothesis is right THEN logically another fact must also exist. With these logical derivations they open up a whole spectrum of other effects. Of course the major effort is to verify whether or not the predicted effects do exist. As more and more predictions are verified, it becomes more obvious that the underlying hypothesis is correct. To read, for example, how Newton did it for the law of gravity is fascinating.”
“Yes, you probably can, but look at the conclusion that we can derive already. If any organization was built for a purpose and any organization is composed of more than one person, then we must conclude that the purpose of the organization requires the synchronized efforts of more than one person.” “That makes sense,” he says. “Otherwise we wouldn’t need to create an organization; the efforts of individuals would suffice. So?” “If we need synchronized efforts,” I continue, “Then the contribution of any single person to the organization’s purpose is strongly dependent upon the performance of others.”
“If synchronized efforts are required and the contribution of one link is strongly dependent on the performance of the other links, we cannot ignore the fact that organizations are not just a pile of different links, they should be regarded as chains.”
“Or at least a grid,” he corrects me. “Yes, but you see, every grid can be viewed as composed of several independent chains. The more complex the organization—the more interdependencies between the various links—the smaller number of independent chains it’s composed of.”
The important thing is you’ve just proven that any organization should be viewed as a chain. I can take it from here. Since the strength of the chain is determined by the weakest link, then the first step to improve an organization must be to identify the weakest link.”
stop and look at him. “What are we asking for? For the ability to answer three simple questions: ‘what to change?’, ‘what to change to?’, and ‘how to cause the change?’ Basically what we are asking for is the most fundamental abilities one would expect from a manager. Think about it. If a manager doesn’t know how to answer those three questions, is he or she entitled to be called manager?”
We should learn to be able to do it without any external help. I must learn these thinking processes, only then will I know that I’m doing my job.” “We should and can be our own Jonahs,” Lou says and stands up. Then this reserved person surprises me. He puts his arm around my shoulder and says, “I’m proud to work for you.”
The manufacturing industry has been shaped by two great thinkers, Henry Ford and Taiichi Ohno. Ford revolutionized mass production by introducing the flow lines. Ohno took Ford’s ideas to the next level in his TPS, a system that forced the entire industry to change its grasp of inventory from an asset to a liability.
Ford’s starting point was that the key for effective production is to concentrate on improving the overall flow of products through the operations. His efforts to improve flow were so successful that, by 1926, the lead time from mining the iron ore to having a completed car composed of more than 5,000 parts, on the train ready for delivery, was 81 hours!3 Eighty years later, no car manufacturer in the world has been able to achieve, or even come close, to such a short lead time.
Flow means that inventories in the operation are moving. When inventory is not moving, inventory accumulates. Accumulation of inventory takes up space. Therefore, an intuitive way to achieve better flow is to limit the space allowed for inventory to accumulate. To achieve better flow, Ford limited the space allotted for work-in-process between each two work centers. That is the essence of the flow lines, as can be verified by the fact that the…
The daring nature of Ford’s method is revealed when one realizes that a direct consequence of limiting the space is that when the allotted space is full, the workers feeding it must stop producing. Therefore, in order to achieve flow, Ford had to abolish local efficiencies. In other words, flow lines are flying in the face of conventional wisdom; the convention…
One might think that preventing resources from working continuously will decrease throughput (output) of the operation. That undesirable effect might have been the result if Ford would have been satisfied with just limiting the space. But, there is another effect that stems from restricting the accumulation of inventory. It makes it very visible to spot the real problems that jeopardize the flow—when one work center in a line stops producing for more than a short while, soon the whole line stops. Ford took advantage of the resulting clear visibility to better balance the flow by addressing and eliminating the apparent stoppages.4 The end result of abolishing local…
In summary, Ford’s flow lines are based on the following four concepts: 1. Improving flow (or equivalently lead time) is a primary objective of operations. 2. This primary objective should be translated into a practical mechanism that guides the operation when not to produce (prevents overproduction). 3. Local…
Like Ford, Ohno’s primary objective was improving flow—decreasing lead time—as indicated in his response to the question about what Toyota is doing: All we are doing is looking at the time line from the moment the customer gives us an order to the…
Ohno faced an almost insurmountable obstacle when he came to apply the second concept. When the demand for a single product is high, dedicating a line to producing each component, as Ford did, is justified. However, at that time in Japan, the market demand was for small quantities of a variety of cars. Therefore, Ohno could not dedicate lines at Toyota. As we already said, all other industries that faced this situation simply did not contemplate using lines. Ohno, however, was toying with the idea of using lines when the equipment is not dedicated, when each work center is producing a variety of components. The problem was that in this case using the mechanism of limited space…
Ohno writes that he realized the solution when he heard about supermarkets (much before he actually saw a supermarket during his visit to the U.S. in 1956). He realized that both supermarkets and the feeding lines at Toyota needed to manage a large variety of products. In the supermarkets, products were not jam packing the aisles, rather most merchandise was held in the backroom storage. In the store itself, each product was allocated a limited shelf space. Only after a product was taken by a shopper, was replenishment from the backroom storage triggered to refill that product’s allotted shelf space. What Ohno envisioned is the mechanism that would enable him to guide Toyota’s operation when not to produce. Rather than using a single limited space between work centers to restrict work-in-process production, he had to limit the amount allowed to accumulate of each component specifically. Based on that realization Ohno designed the Kanban system. The Kanban system has been described in numerous articles and books. In this article I’ll describe just the essence, to show how true Ohno was to the fundamental concepts. Between each two work centers,6 and for each component separately, the accumulation of inventory is limited by setting a certain number of containers and the number of units per container. These containers, like every container in every industry, also contain the relevant paperwork. But, one page of the paperwork—usually a card (kanban in Japanese)—a page that specifies only the component code name and the number of units per container, is treated in an unconventional way. When the succeeding work center withdraws a container for further processing that card is not moved with the container, rather it is passed back to the preceding work center. This is the notification to that work center that a container was withdrawn, that the allotted inventory is not full. Only in that…
Adhering to the flow concept mandates the abolishment of local efficiencies. Ohno addressed this issue again and again in his books, stressing that there is no point in encouraging people to produce if the products are not needed in the very short-term. This emphasis is probably the…
Ohno had to pave a new way to overcome the setup obstacle. At the time, and until TPS became famous worldwide, the traditional way to deal with setups was to increase the batch size— ‘economical batch quantity’ was the popular name on which thousands of articles were written.9 Ohno ignored all that body of knowledge since yielding to using ‘economical’ quantities would have doomed his quest to reduce the lead times. Rather, he insisted that the setups required are not cast in stone, that the processes can be modified to drastically reduce the setup time required. He led the efforts to develop and implement setup reduction techniques that eventually reduced all setup times in Toyota to be, at most, just a few minutes.10 It is no wonder that Lean is now strongly associated with small batches and setup reduction techniques.
When the flow was disturbed the Five Why’s method was used to pinpoint the root cause. It had to be fixed before the quantities could be further reduced. It took time but the end result was a remarkable improvement in productivity.
In summary, both Ford and Ohno followed four concepts (from now on we’ll refer to them as the concepts of flow): 1. Improving flow (or equivalently lead time) is a primary objective of operations. 2. This primary objective should be translated into a practical mechanism that guides the operation when not to produce (prevents over production). Ford used space; Ohno used inventory. 3. Local efficiencies must be abolished. 4. A focusing process to balance flow must be in place. Ford used direct observation. Ohno used the gradual reduction of the number of containers and then gradual reduction of parts per container.
The most demanding assumption that TPS makes about the production environment is that it is a stable environment. And it demands stability in three different aspects.
A second aspect of the stability required by TPS is stability in demand over time per product. Suppose that the lead time to produce a certain product is two weeks but the demand for that product is sporadic; on average there is just one order per quarter for that product. Currently, this product contributes to the work-in-process only during two weeks in a quarter; the rest of the time it is not present on the shop floor. But, that will not be the case under Lean, which mandates permanently holding containers for each product between each two work centers.