part0013

What happens when you go to your doctor? Usually, you make an appointment some days ahead, then arrive at the appointed time and sit in a waiting room. When the doctor sees you—usually behind schedule—she or he makes a judgment about what your problem is likely to be. You are then routed to the appropriate specialist, quite possibly on another day, certainly after sitting in another waiting room. Your specialist will need to order tests using large, dedicated laboratory equipment, requiring another wait and then another visit to review the results. Then, if the nature of the problem is clear, it’s time for the appropriate treatment, perhaps involving a trip to the pharmacy (and another line), perhaps a trip back to the specialist for a complex procedure (complete with wait). If you are unlucky and require hospital treatment, you enter a whole new world of specialized functions, disconnected processes, and waiting.

If you take a moment to reflect on your experience, you discover that the amount of time actually spent on your treatment was a tiny fraction of the time you spent going through the “process.” Mostly you were sitting and waiting (“patient” is clearly the right word), or moving about to the next step in the diagnosis and treatment. You put up with this because you’ve been told that all this stopping and starting and being handed off to strangers is the price of “efficiency” in receiving the highest-quality care.

We’ve already looked briefly at another service, a trip involving an airline. And most of the time the experience is even worse than the Joneses’ family trip to Crete because rather than taking a direct flight you must go through a hub for sortation. In the end, the time you spend actually moving along the most direct route is likely to be little more than half the total time required to get from door to door. Yet most travelers put up with this system without dreaming of anything better. After all, it’s extremely safe, and travelers are told that it’s highly efficient because it fully utilizes expensive airplanes and airports.

Health care and travel are usually called “personal services,” in contrast with “products” like VCRs, washing machines, Wiremold’s wire guides, and Tesco’s beverages. Actually, the major difference is that in the case of health care and travel, you the customer are being acted upon—you are necessarily part of the production process. With goods, by contrast, you wait at the end of the process, seemingly beyond harm’s reach. However, there is no escaping the consequences of the way the job gets done even if you are not directly involved.

Let’s take just one example for a common good, the single-family home. Henry Ford dreamed about mass-producing homes using standard but modularized designs with the modules built in factories to slash design and production costs while still providing variety. A number of entrepreneurs actually created modular designs and briefly set up production lines in the United States to make the modules for prefabricated houses immediately after World War II. 1 And Toyota has had modest success in Japan since the 1960s in offering a wide range of floor plans and exterior appearances using a few basic modules fabricated on a production line and assembled almost instantly at the construction site.

Yet, almost all of the world’s new single-family homes are still built largely at the construction site by cutting and fastening a welter of materials to create the basic structure and then installing thousands of individual components, from plumbing fixtures to kitchen appliances to wall sockets.

If you go to your home builder and then to the construction site and take a seat to watch the action, you will mostly note inaction. For example, when Doyle Wilson started to measure what occurred in his office and at the work site as part of his TQM effort, he discovered that five-sixths of the typical construction schedule for a custom-built home was occupied with two activities: waiting for the next set of specialists (architects, cost estimators, bill-of-material drafters, landscape architects, roofers, sheetrockers, plumbers, electricians, landscapers) to work a particular job into their complex schedules, and rework to rip out and correct the work just done that was either incorrect from a technical standpoint or failed to meet the needs and expectations of the home buyer.

As the buyer at the end of the process, you pay for all the waiting and rework—grumbling, of course—but it is a custom product, after all, and you’ve heard many stories from your friends about even worse problems with their homes, so you tend to accept the predominant system and its problems as unavoidable and inherent to the nature of the activity.

In fact, all of these activities—the creation, ordering, and provision of any good or any service—can be made to flow. And when we start thinking about ways to line up all of the essential steps needed to get a job done into a steady, continuous flow, with no wasted motions, no interruptions, no batches, and no queues, it changes everything: how we work together, the kinds of tools we devise to help with our work, the organizations we create to facilitate the flow, the kinds of careers we pursue, the nature of business firms (including nonprofit service providers) and their linkages to each other and society.

Applying flow to the full range of human activities will not be easy or automatic. For starters, it’s hard for most managers to even see the flow of value and, therefore, to grasp the value of flow. Then, once managers begin to see, many practical problems must be overcome to fully introduce and sustain flow. However, we do insist that flow principles can be applied to any activity and that the consequences are always dramatic. Indeed, the amount of human effort, time, space, tools, and inventories needed to design and provide a given service or good can typically be cut in half very quickly, and steady progress can be maintained from this point onward to cut inputs in half again within a few years.

So, how do you make value flow? The first step, once value is defined and the entire value stream is identified, is to focus on the actual object—the specific design, the specific order, and the product itself (a “cure,” a trip, a house, a bicycle)—and never let it out of sight from beginning to completion. The second step, which makes the first step possible, is to ignore the traditional boundaries of jobs, careers, functions (often organized into departments), and firms to form a lean enterprise removing all impediments to the continuous flow of the specific product or product family. The third step is to rethink specific work practices and tools to eliminate backflows, scrap, and stoppages of all sorts so that the design, order, and production of the specific product can proceed continuously.

In fact, these three steps must be taken together. Most managers imagine that the requirements of efficiency dictate that designs, orders, and products go “through the system” and that good management consists of avoiding variances in the performance of the complex system handling a wide variety of products. The real need is to get rid of the system and start over, on a new basis. To make this approach clear and specific, let’s take as a concrete example the design, ordering, and production of a bicycle .

We’ve chosen this example partly because the bicycle itself is simple and lacks glamour. You will not be distracted by novel product designs or exotic technologies. We’ve also chosen it because we happen to know something about the bicycle industry, one of us having resolved to test the methods we describe in this book by taking an ownership position in a real bicycle company. Finally, we have chosen bicycle manufacture because it is a deeply disintegrated industry, with most final-assembler firms making only the frame while buying the components—wheels, brakes, gears, seats, handle-bars, plus raw materials in the form of frame tubing—from a long list of supplier companies, many larger than the final assemblers themselves. The problems of value stream integration are present in abundance.

Product design in the bicycle industry was historically a classic batch-and-queue affair in which the marketing department determined a “need,” the product engineers then designed a product to serve the need, the prototype department built a prototype to test the design, the tooling department designed tools to make a high-volume version of the approved prototype, and the production engineering group in the manufacturing department figured out how to use the tools to fabricate the frame and then assemble the component parts into a completed bike. Meanwhile, the purchasing department, once the design was finalized, arranged to buy the necessary component parts for delivery to the assembly hall.

A design for a new product, usually only one of many under development at a given time, moved from department to department, waiting in the queue in each department. Frequently it went back for rework to a previous department or was secretly reengineered at a point downstream to deal with incompatibilities between the perspectives of, say, the tool designers and the product designers who handled the design in the previous step. There was no flow.

In the late 1980s and early 1990s, most firms switched to “heavyweight” program management with a strong team leader and a few dedicated team members, but without changing the rest of the system. The product “team” was really just a committee with a staff that sent the great bulk of the actual development work back to the departments, where it still waited in queues. What’s more, there was no effective methodology for carrying designs through the system without lots of rework and backflows. Even worse, no one was really responsible for the final results of development efforts because the accounting and reward systems never linked the success of a product through its production life with the original efforts of the design team. There was, therefore, a bias toward ingenious designs with admirable technical features which customers liked but which failed to return a profit due to excess costs and launch delays.

The lean approach is to create truly dedicated product teams with all the skills needed to conduct value specification, general design, detailed engineering, purchasing, tooling, and production planning in one room in a short period of time using a proved team decision-making methodology commonly called Quality Function Deployment (QFD). 2 This method permits development teams to standardize work so that a team follows the same approach every time. Because every team in a firm also follows this approach, it’s possible to accurately measure throughput time and to continually improve the design methodology itself.

With a truly dedicated team in place, rigorously using QFD to correctly specify value and then eliminate rework and backflows, the design never stops moving forward until it’s fully in production. The result, as we will demonstrate in the examples in Part II , is to reduce development time by more than half and the amount of effort needed by more than half while getting a much higher “hit rate” of products which actually speak to the needs of customers.

In our experience, dedicated product teams do not need to be nearly as large as traditional managers would predict, and the smaller they can be kept the better all around. A host of narrowly skilled specialists are not needed because most marketing, engineering, purchasing, and production professionals actually have much broader skills than they have (1) ever realized, (2) ever admitted, or (3) ever been allowed to use. When a small team is given the mandate to “just do it,” we always find that the professionals suddenly discover that each can successfully cover a much broader scope of tasks than they have ever been allowed to previously. They do the job well and they enjoy it.

Moving most of the employees formerly in marketing, engineering, and production groups into dedicated teams for specific products does create problems for the functional needs of each firm along the value stream, a point we will address in Part III . Similarly, the need to include employees of key component and material supply firms as dedicated members of the product team raises difficult questions of where one firm stops and the next begins, the second major topic of Part III .

The historic practice in the bicycle industry has been to task the Sales Department with obtaining orders from retailers. In the United States, these range from the giant mass-marketers like Wal-Mart at one extreme to thousands of tiny independent bicycle shops at the other. When the orders are fully processed—to make sure that they are internally consistent and that the buyer is credit-worthy—they are sent to the Scheduling Department in Operations or Manufacturing to work into the complex production algorithm for a firm’s many products. A shipment date is then set for communication back to Sales and on to the customer.

To check on the progress of orders, particularly in the event of late delivery, the customer calls Sales, which then calls Scheduling. When orders are really late and important customers threaten to cancel, Sales and Scheduling undertake some form of expediting by going directly into the physical production system in both the assembler firm and the supply base to move laggard orders forward. This is done by jumping them to the head of each queue in physical production.

Under the influence of the reengineering movement in the early 1990s, a number of firms integrated Sales and Scheduling into a single department so that the orders themselves can be processed much more quickly—often by one person tied in to the firm’s electronic information management system so that orders never need to be handed off, placed in waiting lines, or put down. (They now flow.) As a result, orders can be scheduled for production in a few minutes rather than the days or even weeks previously required; at the same time, order information can be transmitted electronically to suppliers. Similarly, expediting procedures are tightened up to eliminate the confusion which often arose between Sales and Scheduling.

These innovations certainly helped, but a fully implemented lean approach can go much further. In the lean enterprise, Sales and Production Scheduling are core members of the product team, in a position to plan the sales campaign as the product design is being developed and to sell with a clear eye to the capabilities of the production system so that both orders and the product can flow smoothly from sale to delivery. And because there are no stoppages in the production system and products are built to order, with only a few hours elapsed between the first operation on raw materials and shipment of the finished item, orders can be sought and accepted with a clear and precise knowledge of the system’s capabilities. There is no expediting.

A key technique in implementing this approach is the concept of takt time, 3 which precisely synchronizes the rate of production to the rate of sales to customers. For example, for a bicycle firm’s high-end titanium-framed bike, let’s assume that customers are placing orders at the rate of forty-eight per day. Let’s also assume that the bike factory works a single eight-hour shift. Dividing the number of bikes by the available hours of production tells the production time per bicycle, the takt time, which is ten minutes. (Sixty minutes in an hour divided by demand of six bikes per hour.) Obviously, the aggregate volume of orders may increase or decrease over time and takt time will need to be adjusted so that production is always precisely synchronized with demand. The point is always to define takt time precisely at a given point in time in relation to demand and to run the whole production sequence precisely to takt time.

In the lean enterprise, the production slots created by the takt time calculation—perhaps ten per hour for high-end bicycles (for a takt time of six minutes) and one per minute for low-end models (for a takt time of sixty seconds)—are clearly posted. This can be done with a simple whiteboard in the product team area at the final assembler but will probably also involve electronic displays (often called andon boards) in the assembler firm and electronic transmission for display in supplier and customer facilities as well. Complete display, so everyone can see where production stands at every moment, is an excellent example of another critical lean technique, transparency or visual control. 4 Transparency facilitates consistently producing to takt time and alerts the whole team immediately to the need either for additional orders or to think of ways to remove waste if takt time needs to be reduced to accommodate an increase in orders. 5

Raising awareness of the tight connection between sales and production also helps guard against one of the great evils of traditional selling and order-taking systems, namely the resort to bonus systems to motivate a sales force working with no real knowledge of or concern about the capabilities of the production system. These methods produce periodic surges in orders at the end of each bonus period (even though underlying demand hasn’t changed) and an occasional “order of the century” drummed up by a bonus-hungry sales staff, which the production system can’t possibly accommodate. Both lead to late deliveries and bad will from the customer. In other words, they magically generate muda.

The historic practice in the bicycle industry was to differentiate production activities by type and to create departments for each type of activity: tube cutting, tube bending, mitering, welding, washing and painting for the frame and handle bars, and final assembly of the complete bike. Over time, higher-speed machines with higher levels of automation were developed for tasks ranging from cutting and bending to welding and painting. Assembly lines were also installed to assemble a mix of high-volume models in dedicated assembly halls.

All bike makers produced a wide range of models using the same production equipment, and part fabrication tools typically ran at much higher speeds (expressed as pieces per minute) than the final assembly line. Because changing over part fabrication tools to make a different part was typically quite time-consuming, it made sense to make large batches of each part before changing over to run the next part. The typical final assembly plant layout and materials flow looked as shown in Figure 3.1 .

As batches of parts were created, an obvious problem arose: how to keep track of the inventory and make sure that the right parts were sent to the right operation at the right time. In the early days of the bicycle industry—an activity dating back to the 1880s and a key precursor to the auto industry—scheduling was handled by means of a master schedule and daily handwritten orders to each department to make the parts final assembly would need.

After nearly a hundred years, these manual scheduling methods were replaced in the 1970s by computerized Material Requirements Planning systems, or MRPs. A good MRP system was at least 99 percent accurate in keeping track of inventory, ordering materials, and sending instructions to each department on what to make next. As a group, these systems were a clear improvement on older manual systems for controlling batch-and-queue operations and became progressively more complex over time. Eventually capacity planning tools were added to evaluate the capacity of machines at every step in the production process and to guard against the emergence of bottlenecks and capacity constraints.

MRP, however, had a number of problems. If even one part was not properly logged into the system as it proceeded from one production stage to the next, errors began to accumulate that played havoc with the reorder “triggers” telling a department when to switch over to the next type of part. As a result, downstream manufacturing operations often had too many parts (the muda of overproduction) or too few parts to meet the production schedule (producing the muda of waiting).

A worse problem was that total lead times in batch-and-queue systems were usually quite lengthy—typically a few weeks to a few months between the point in time when the earliest upstream part was produced and the moment when a bike containing that part was shipped to the retailer. This would have been fine if orders had been perfectly smooth, but in fact orders received by the bike manufacturer changed all the time, partly due to the bonus-driven selling system, partly due to the substantial inventories in the retail channel, and partly due to seasonal demand patterns, particularly for low-end bikes. What’s more, there were often engineering changes in bicycle designs, even for mature products, meaning that a considerable fraction of the parts piled up alongside the value stream were suddenly either completely obsolete or in need of rework. 6

MRP systems which were very simple in concept therefore became exceedingly complex in practice. In the bicycle industry, every firm’s MRP system was supplemented by a backup system of expediters moving through the production system to move parts in urgent shortage downstream to the head of the queue in every department and at every machine. Their efforts, while essential to avoiding cancellations or large penalties on overdue orders, played havoc with the internal logic of the MRP system—often causing it to generate absurd orders—and with inventory accuracy as well. In the end, most MRP applications were better than manual systems, but they operated day to day at a level of performance far below what was theoretically possible and what had been widely expected when MRP was first introduced.

Just-in-Time, an innovation pioneered at Toyota in the 1950s and first embraced by Western firms in the early 1980s, was designed to deal with many of these problems. This technique was envisioned by Taiichi Ohno as a method for facilitating smooth flow, but JIT can only work effectively if machine changeovers are dramatically slashed so that upstream manufacturing operations produce tiny amounts of each part and then produce another tiny amount as soon as the amount already produced is summoned by the next process downstream. JIT is also helpless unless downstream production steps practice level scheduling (heijunka in Toyota-speak) to smooth out the perturbations in day-to-day order flow unrelated to actual customer demand. Otherwise, bottlenecks will quickly emerge upstream and buffers (“safety stocks”) will be introduced everywhere to prevent them .

The actual application of JIT in the bicycle industry largely ignored the need to reduce setup times and smooth the schedule. Instead, it concentrated on suppliers, making sure that they only delivered parts to the final assemblers “just in time” to meet the erratic production schedule. In practice, most suppliers did this by shipping small amounts daily or even several times a day from a vast inventory of finished goods they kept near their shipping docks. Some final assemblers even specified the existence of these safety stocks and periodically sent around their purchasing staffs to inspect them. In the end, “just in time” was little more than a once-and-for-all shift of massive amounts of work-in-process from the final assembler to the first-tier supplier and, in turn, from first-tier supplier to firms farther upstream.

To get manufactured goods to flow, the lean enterprise takes the critical concepts of JIT and level scheduling and carries them all the way to their logical conclusion by putting products into continuous flow wherever possible. For example, in the case of the bicycle plant shown in Figure 3.1 , flow thinking calls for the creation of production areas by product family, which includes every fabrication and assembly step. (Product families can be defined in various ways, but in this industry they would logically be defined by the base material used for the frame, specifically titanium, aluminum, steel, or carbon-fiber. This classification makes sense because the fabrication steps and processing techniques are quite different in each case.)

Better yet, if noise problems can be managed, the lean enterprise groups the product manager, the parts buyer, the manufacturing engineer, and the production scheduler in the team area immediately next to the actual production equipment and in close contact with the product and tool engineers in the nearby design area dedicated to that product family. The old-fashioned and destructive distinction between the office (where people work with their minds) and the plant (where people work with their hands) is eliminated.

(We’re often struck that in the old world of mass production, the factory workforce really had no need to talk to each other. They were supposed to keep their heads down and keep working and professionals rarely went near the scene of the action. So production machinery could make a lot of noise. The isolated workers simply donned their ear protection and shut out the world. In the lean enterprise, however, the workforce on the plant floor needs to talk constantly to solve production problems and implement improvements in the process. What’s more, they need to have their professional support staff right by their side and everyone needs to be able to see the status of the entire production system. Many machine builders are still oblivious to the fact that a lean machine needs to be a quiet machine. )

In the continuous-flow layout, the production steps are arranged in a sequence, usually within a single cell, and the product moves from one step to the next, one bike at a time, with no buffer of work-in-process in between, using a range of techniques generically labeled “single-piece flow.” To achieve single-piece flow in the normal situation when each product family includes many product variants—in this case, touring and mountain bike designs in a wide range of sizes—it is essential that each machine can be converted almost instantly from one product specification to the next. It’s also essential that many traditionally massive machines—paint systems being the most critical in the bike case—be “right-sized” to fit directly into the production process. This, in turn, often means using machines which are simpler, less automated, and slower (but perhaps even more accurate and “repeatable”) than traditional designs. We will look in detail in Chapter 8 at the Pratt & Whitney example of simplified blade grinding machinery that we mentioned in the Introduction.

This approach seems completely backward to traditional managers who have been told all their lives that competitive advantage in manufacture is obtained from automating, linking, and speeding up massive machinery to increase throughput and remove direct labor. It also seems like common sense that good production management involves keeping every employee busy and every machine fully utilized, to justify the capital invested in the expensive machines. What traditional managers fail to grasp is the cost of maintaining and coordinating a complicated network of high-speed machines making batches. This is the muda of complexity.

Because conventional “standard-cost” accounting systems make machine utilization and employee utilization their key performance measures while treating in-process inventories as an asset—even if no one will ever want them—it’s not surprising that managers also fail to grasp that machines rapidly making unwanted parts during 100 percent of their available hours and employees earnestly performing unneeded tasks during every available minute are only producing muda.

To get continuous-flow systems to flow for more than a minute or two at a time, every machine and every worker must be completely “capable.” That is, they must always be in proper condition to run precisely when needed and every part made must be exactly right. By design, flow systems have an everything-works-or-nothing-works quality which must be respected and anticipated. This means that the production team must be cross-skilled in every task (in case someone is absent or needed for another task) and that the machinery must be made 100 percent available and accurate through a series of techniques called Total Productive Maintenance (TPM). It also means that work must be rigorously standardized (by the work team, not by some remote industrial engineering group) and that employees and machines must be taught to monitor their own work through a series of techniques commonly called poka-yoke, or mistake-proofing, which make it impossible for even one defective part to be sent ahead to the next step. 7

A simple example of a poka-yoke is installing photo cells across the opening of each parts bin at a workstation. When a product of a given description enters the area the worker must reach into the boxes to get parts, breaking the light beam from the photo cells on each box. If the worker attempts to move the product on to the next station without obtaining the right parts, a light flashes to indicate that a part has been left out.

These techniques need to be coupled with visual controls, as mentioned earlier, ranging from the 5Ss 8 (where all debris and unnecessary items are removed and every tool has a clearly marked storage place visible from the work area) to status indicators (often in the form of andon boards), and from clearly posted, up-to-date standard work charts to displays of key measurables and financial information on the costs of the process. The precise techniques will vary with the application, but the key principle does not: Everyone involved must be able to see and must understand every aspect of the operation and its status at all times.

Once the commitment is made to convert to a flow system, striking progress can be made very quickly in the initial kaikaku exercise. However, some tools (for example, massive paint booths with elaborate emission control equipment) will be unsuited for continuous-flow production and won’t be easy to modify quickly. It will be necessary to operate them for an extended period in a batch mode, with intermediate buffers of parts between the previous and the next production step. The key technique here is to think through tool changes to reduce changeover times and batch sizes to the absolute minimum that existing machinery will permit. 9 This typically can be done very quickly and almost never requires major capital investments. Indeed, if you think you need to spend large sums to convert equipment from large batches to small batches or single pieces, you don’t yet understand lean thinking.

The original small-lot, quick-change techniques pioneered at Toyota in the 1960s are a striking achievement, but we caution readers not to take quick-change machines still producing batches, however small, as an end in themselves. Any changeover requiring any loss in production time and any machine which must run at a rate far out of step with the rest of the production sequence can still create muda. The end objective of flow thinking is to totally eliminate all stoppages in an entire production process and not to rest in the area of tool design until this has been achieved.

Let’s tie all of these techniques together by showing what a lean bicycle production process looks like, as shown in Figure 3.2 . First, note that the same number of bikes are being produced but that the plant is more than half empty, in large part because all of the in-process storage areas have disappeared. Although the diagram cannot show this, the human effort needed to produce a bicycle has been cut in half as well, and time through the system has been reduced from four weeks to four hours. (We’ll talk in Part II about what to do with people no longer needed for their traditional tasks as muda is eliminated. Protecting their jobs by finding them other productive tasks is a central part of any successful lean transition.)

The diagram does show that single large machines have been broken down into multiple small machines, in particular the washing systems and paint booths, so that bikes can proceed continuously, one at a time, from tube cutting to mitering to bending to welding to washing to painting to final assembly without ever stopping. In this arrangement the inventory between workstations can be zero and the size of the work team can be geared to the production volume of the cell, with high-volume cells having more workers than low-volume cells. Finally, note that the track assembly operations have been eliminated. When production is broken into product families, it is often the case that no family accounts for the kind of volume needed for track assembly. Remarkably, manual advancing of the product through assembly is often cheaper .

Because the work flow has been so drastically simplified, the MRP system and the accompanying expediters are no longer needed to get parts from step to step. (MRP still has a use for long-term capacity planning for the assembler firm and its suppliers.) When the sequence is initiated at the end of final assembly, work progresses from each station to the next in accordance with takt time and at the same rate as final assembly.

The entire product team including the team leader, the production engineer, the planner/buyer, the TPM/maintenance expert, and the operators (collectively the heart of the lean enterprise) can be located immediately adjacent to the machinery for each product cell. Because the process machinery currently available for these operations in the bicycle industry either makes very little noise inherently—for example, paint—or can be shielded so that very little noise escapes into the team area—the mitering step—it’s possible to lay out activities so everyone can see the whole operation and its status at a quick glance.

A final point about the cells which is hard to illustrate with a diagram is that the work in each step has been very carefully balanced with the work in every other step so that everyone is working to a cycle time equal to takt time. When it’s necessary to speed up or slow down production, the size of the team may be increased or shrunk (contracting or expanding job scope), but the actual pace of physical effort is never changed. And when the specification of the product changes, the right-sized machines can be added or subtracted and adjusted or rearranged so that continuous flow is always maintained.

Only one more flow technique needs mentioning, which is to locate both design and physical production in the appropriate place to serve the customer. Just as many manufacturers have concentrated on installing larger and faster machines to eliminate direct labor, they’ve also gone toward massive centralized facilities for product families (sometimes called “focused factories”) while outsourcing more and more of the actual component part making to other centralized facilities serving many final assemblers. To make matters worse, these are often located on the wrong side of the world from both their engineering operations and their customers (Taiwan in the bicycle case) to reduce the cost per hour of labor.

The production process in these remotely located, high-scale facilities may even be in some form of flow, but launching products and improving the process machinery is much harder (because the core engineering skills are on the other side of the world), and the flow of the product stops at the end of the plant. In the case of bikes, it’s a matter of letting the finished product sit while a whole sea container for a given final assembler’s warehouse in North America is filled, then sending the filled containers to the port, where they sit some more while waiting for a giant container ship. After a few weeks on the ocean, the containers go by truck to one of the bike firm’s regional warehouses, where the bikes wait until a specific customer order needs filling, often followed by shipment to the customer’s warehouse for more waiting. In other words, there’s no flow except along a tiny stretch of the total value stream inside one isolated plant.

The result is high logistics costs and massive finished unit inventories in transit and at retailer warehouses. Another consequence is obsolete goods, eventually sold at large discounts, created by the need to place orders based on forecasts months in advance of demonstrated demand. When carefully analyzed, these costs and revenue losses are often found to more than offset the savings in production costs from low wages, savings which can be obtained in any case by locating smaller flow facilities incorporating more of the total production steps much closer to the customer. (We’ll return to this point in Chapter 10 on Japan, because wrong location, rather than high wages, lies at the heart of Japan’s current competitive dilemma.)

Flow thinking is easiest to see in conventional, discrete-product manufacturing, which is where flow techniques were pioneered. However, once managers learn to see it, it’s possible to introduce flow in any activity and the principles are in every case the same: Concentrate on managing the value stream for the specific service or good, eliminate organizational barriers by creating a lean enterprise, relocate and right-size tools, and apply the full complement of lean techniques so that value can flow continuously. At the end of this volume, in Chapter 13 , we’ll apply lean thinking to a wide range of activities besides traditional manufacturing.

So far, we have been talking about the flow of value as if the needs of the customer and the investor are the only ones which count. However, we all know from our daily lives that our experience as producers (that is, as employees and workers) is often far more significant than our activities as consumers or investors. What does the transition to flow mean for the experience of work ?

Let’s begin with a brief look at the recent research findings of the Polish-born psychologist Mihaly Csikszentmihalyi, now at the University of Chicago. He has spent the last twenty-five years reversing the usual focus of psychology. Instead of asking what makes people feel bad (and how to change it) he has explored what makes people feel good, so that positive attributes of experience can be built into daily life.

His method has been to attach beepers, which sound at random intervals, to his research subjects. When the beeper sounds, the subject is asked to record in a notebook what she or he was doing and how they were feeling. After sifting decades of notebook data from thousands of subjects around the world, he has reached some very simple conclusions.

The types of activities which people all over the world consistently report as most rewarding—that is, which make them feel best—involve a clear objective, a need for concentration so intense that no attention is left over, a lack of interruptions and distractions, clear and immediate feedback on progress toward the objective, and a sense of challenge—the perception that one’s skills are adequate, but just adequate, to cope with the task at hand.

When people find themselves in these conditions they lose their self-consciousness and sense of time. They report that the task itself becomes the end rather than a means to something more satisfying, like money or prestige. Indeed, and very conveniently for us, Csikszentmihalyi reports that people experiencing these conditions are in a highly satisfying psychological state of flow. 10

Csikszentmihalyi’s classic flow experience is rock climbing, where the need for concentration is obvious and the task itself is clearly the end, not a means. Participation sports less dangerous than rock climbing, interactive games, and focused intellectual tasks (such as writing books!) are often mentioned by Csikszentmihalyi’s respondents as flow experiences. However, traditional work-related tasks are only rarely mentioned despite the fact that work is rated the most important overall life activity. This is for a good reason. Classic batch-and-queue work conditions are hardly conducive to psychological flow. The worker can see only a small part of the task, there is often no feedback (much less immediate feedback), the task requires only a small portion of one’s concentration and skills, and there are constant interruptions to deal with other tasks in one’s area of responsibility.

By contrast, work in an organization where value is made to flow continuously also creates the conditions for psychological flow. Every employee has immediate knowledge of whether the job has been done right and can see the status of the entire system. Keeping the system flowing smoothly with no interruptions is a constant challenge, and a very difficult one, but the product team has the skills and a way of thinking which is equal to the challenge. And because of the focus on perfection, to be further explored in Chapter 5 , the whole system is maintained in a permanent creative tension which demands concentration.

We’ve now seen striking examples of what happens when the value stream flows smoothly. What’s more, there is absolutely no magic involved. Any organization can introduce flow in any activity. However, if an organization uses lean techniques only to make unwanted goods flow faster, nothing but muda results. How can you be sure you are providing the services and goods people really want when they really want them? And how can you tie all the parts of a whole value stream together when they can’t be conducted in one continuous-flow cell in one room? Next you need to learn how to pull.