Tag Archives: Strategy

CVTufteGraph for blog
May 11 2012

Metrics in Lean – Part 4 – Gaming and how to prevent it

As massively practiced today, Management-by-Objectives (MBO) boils down to management imposing  numerical targets on a few half-baked metrics, cascading this approach down the organization and giving individuals a strong incentive to spin their numbers. It is a caricature of the process Peter Drucker recommended almost 60 years ago, and he deserves no more of the blame for it than Toyota does for what passes as Lean in most companies that claim to implement it.

A non-manufacturing example of decadent MBO is the French police under former president Sarkozy, which was tasked by the government to decrease the crime rate by 3%/year while increasing the proportion of solved cases. According to the French press, this was achieved by gaming the numbers. The journalists first latched on to a reported yearly decrease in identity theft, which seemed unlikely. They found that police stations routinely refused to register complaints about identity theft on the grounds that the victims were the banks and not the individuals whose identities were stolen. A retired officer also explained how crimes were systematically downgraded with, for example, an attempted break-in recorded as the less severe “vandalism.”

The fastest way the police had found to boost the rate of case solutions was to focus on violations detected through their own actions, such as undocumented aliens found through identity checks. The solution rate for such crimes is 100%, because they are simultaneously discovered and solved. The challenge is to generate just enough of such cases to boost the solution rate without increasing the overall crime rate… To achieve this result, packs of police officers stalked train stations in search of offenders, as reported both by cops who felt this was not what they had joined up to do, and innocent citizens who complained about being harassed for their ethnicity.

In organizations affected by this kind of gaming, members work to make numbers look good rather than fulfill their missions. It is a widely held belief that you get what you measure and that people will always work to improve their performance metrics, but this is not a simplistic view of human nature. This behavior does not come naturally. On their own, schoolteachers focus on educating children, not boosting test scores, and production operators on making parts they can take pride in. It takes heavy-handed management to turn conscientious professionals into metrics-obsessed gamers, in the form, for example, of daily meetings focused entirely on the numbers, backed up by matching human resource policies on retention, promotion, raises and bonuses.

But enough about police work. Let us return to Manufacturing, and list a few of the most common ways of gaming metrics in our environment:

  1. Taking advantage of bad metrics. As discussed in The Staying Power of Bad Metrics, many metrics commonly used in manufacturing are poorly defined, providing gaming opportunities, such as outsourcing in order to increase sales per employee.
  2. Stealing from the future. In sports, nothing is more dramatic than the game won by points scored in the last seconds of a game. The bell rings right after the ball spirals into the basket and the Cinderella team wins the championship. In business, the end of an accounting period is the end of a game, and, as it approaches, sales scrambles to close last-minute deals and manufacturing to ship a few more orders. This is what Eli Goldratt called the “hockey stick effect.” Of course, this is done by moving up activities that would otherwise have taken place a few days later, during the beginning of the next accounting period. As a consequence, the beginning of the period is almost quiescent. Not much is going on, but it will be made up at the end…
  3. Redefining 100%. Many ratios, by definition, top out at 100%. A machine cannot run 25 hours/day, and a manufacturing process cannot produce more good parts than the total it makes. This is why ratios like equipment uptime and first-pass yield top out at 100%. Any result under 100%, however, invites questions on how it could be improved. A common way to fob off the questioners is to decree, for example, that a particular machine could not possibly be up more than 85% of the time, and redefine the scale so that 85% uptime is 100% performance. For production rates in manual operations, the ratio of an operator’s output to a work standard is often used instead of process times or piece rates. Such ratios have the advantage of being comparable across operations, and are not bounded in either direction. But their relevance depends on a work standard, and, when everybody in a shop performs at 140% of standard, chances are that the standards are engineered for this purpose.
  4. Leveraging ambiguity. Terms like availability, cycle time, or value added are used with different meanings in different organizations, creating many opportunities to game the metrics. If the product’s market share in the first quarter went for 1% to 2%, it doubled, but, if it went back to 1% in the second quarter, it went down by 1%.
  5. …

Why do people who, in other parts of their lives, may be model citizens, engage in such behaviors, ranging from spinning to cheating? One answer is that, with what MBO has degenerated into in many companies, management is co-opting metrics gamers into its ranks. It is not that gaming is human nature, but instead that you are actively weeding out those who don’t engage in it. Changing such habits in an organization is obviously not easy.

Assume, for example, that your goal is to be competitive by having a skilled work force, and that your analysis shows that it requires employees to stay for entire careers so that what they learn at the company stays in the company. You then apply a number of different methods to make it happen:

  • Communications. You make sure that all employees know what you are doing.
  • Career planning. You have human resources develop a plan with all employees so that each one knows what he or she can aspire to by staying with the company.
  • Organized professional development. You organize formal training, on-the-job training, and continuous improvement to provide opportunities for employees to develop the skills they need to execute their plans.
  • Job enrichment. You redesign the jobs themselves to make more effective use of each employee’s talents.

If employees appreciate their jobs and have long-term career perspectives within the company, few of them should quit or make excuses not to come to work today, and the results should be visible in lower employee turnover rates and absenteeism.

The metrics are there to validate the approaches taken to reach the goal, but the goal is not to improve the metrics. It is a subtle difference. If you have the flu, you have a fever, but your goal is to heal, not just to bring down the fever. Once you are healed, you fever will be gone, and the decrease in your temperature is therefore a relevant indicator of your healing process, but it is not the healing process. If bringing down the fever were the goal, you could “game” your temperature and bring it down without healing. This distinction existed in Drucker’s original writings about MBO, but got lost in implementation.

So, what can you do to prevent metrics gaming? Let us examine three strategies:

  1. Review the metrics themselves. Use the requirements listed in my first post on this subject. You may not be able to completely game-proof your metrics, but at least you could make sure that they make sense for your business and are not trivially easy to game.
  2. Decouple the metrics from immediate rewards. Piece rates used to be the most common form of payment for production work, but have almost entirely vanished in advanced manufacturing economies, and been replaced by hourly wages. Performance expectations are attached, but there is no direct link to the amount produced in a given hour of a given day. There are many reasons for this evolution:
    • The pace of work is often set by machines or by a moving line, rather than by the individual.
    • The best performance for the plant is not necessarily achieved by every individual maximizing output at all times.
    • More is expected of all individuals than just putting out work pieces, including training or participating in improvement activities.

    One consequence of this decoupling is that time studies are easier and more accurate than in a piece rate environment. The same logic applies in management: the more direct the link between metrics and individual evaluations, the more intense the gaming. Don’t make the metrics the key to promotions or to prizes representing a substantial part of a manager’s compensation. Use them only as indicators to inform discussions on plans and strategies.

  3. Increase the measurement frequency. The longer the reporting period, the more opportunities it offers for gaming the metrics by stealing from the future, and the more pronounced the hockey stick effect. Conversely, you can reduce it by measuring more often, and eliminate it by monitoring continuously, as is done, for example by the electronic production monitors that keep a running tally of planned versus actual production in a line during a shift. Periods exist in accounting because of the limitations of data processing technology at the time the accounting methods were developed. In the days of J.P. Morgan, closing the books was a major effort that a company could only be do every so often. In 2012, there is no technical impediment to the “anytime close,” but the publication of periodic reports continues by force of habit. Metrics in the language of things as well as the language of money can be monitored continuously.
  4. Have third parties calculate the metrics. In principle, counting chips should be done more accurately by agents with no stake in where they may fall. In practice, it is not only expensive but does not always produce the desired result. It is the approach used in Management Accounting. A plant’s accounting manager, or comptroller, is not chosen by the plant manager, he or she reports directly to corporate finance, and has no motivation to humor the plant manager. This is a double-edged sword because, with neutrality, comes a distance from the object of the measurement that may cause misunderstandings, and Management Accounting leaders like Robert Kaplan, Orrie Fiume, or Brian Maskell  have been struggling with the challenge of providing relevant, actionable information to managers for the past 30 years. Outside of Accounting, for metrics in the language of things, the closest you can come to having a 3rd party produce the measurements is to have a computer system do it, based on automatic data acquisition. There is no opportunity for gaming, but the issues of relevance are as acute as in Management Accounting.
Silos by Sheeler
Mar 22 2012

Improvement in a silo

In a discussion he recently started in the PEX Network discussion group on LinkedIn, Adi Gaskell asked whether process improvement worked in a silo. Most participants said no, but Steven Borris said yes, and I agree with him. Following is what I added:

I agree with Steven, and will even go further: your first pilot projects when you start Lean implementation have the best chance of success if they are contained within a department. The more departments, silos, or fiefdoms you involve, the more difficult you make it, and the less likely to succeed.

The scope does not have to include a complete process from raw materials to finished goods. It does not even have to be at the end or the beginning of the process. All his has to be is a process segment with a technical potential for improvement that is achievable with available skills, and enthusiastic local management.

There is a simple criterion to establish whether such a local project improves the plant as a whole: does it move its target operations in the direction of takt-driven production. If it does, and only if it does, the order-of-magnitude improvements you get locally translate to nibbling percentages globally. For example, the local WIP drops by 90% and that makes the global WIP drop by 4%.

Only once you have a few successful within-silo projects under your belt do you have the support in the organization and the skills base to take on cross-silo or silo-eliminating projects.

elephant
Dec 22 2011

The Lean Body of Knowledge

Efforts at implementing Lean have become pervasive in manufacturing, branching out from the automotive industry to electronics, aerospace, and even food and cosmetics, not to mention efforts to adapt it to construction, health care, or services. As a consequence, the knowledge of Lean, proficiency in its tools, and skills in its implementation are highly marketable in many industries.

There is, however, no consensus on a body of knowledge (BOK) for education in the field, and my review of existing BOKs and university courses confirms it.  A consensus is elusive because Lean emerged as the accumulation of point solutions developed at Toyota over time, rather than as the implementation of a coherent strategy.

As Takahiro Fujimoto explains, there was no individual thinker whose theories started the company down this path. Decades later, we are left with the task of reverse-engineering underlying principles from actual plant practices. Those who have attempted it produced inconsistent results because they have gone at it like the six blind men with the elephant: their personal backgrounds, mostly in business school education, management, or even psychology allowed them to see different slivers of the Toyota system but not the whole, giving, in particular, short shrift to its engineering dimension.

In the following paragraphs, first I explain what I think the Lean BOK should be. Then I review five programs offered in the US by universities and professional societies and highlight where they differ.

My view of the Lean BOK

A well-rounded program for manufacturing professionals would provide Lean skills to all the professionals involved in designing and operating manufacturing plants. Organizations that are successful at Lean do not rely on one department to “do Lean” for everybody else. Instead, Lean is part of everybody’s job. There are basics that everybody needs to know, and then there are different subsets of skills that are useful depending on where you work in the plant.

Beyond the common background, the knowledge should be organized around functions performed by people. In this way of thinking, Visual Management, for example, would not be a stand-alone subject, because factories don’t have “visibility managers.” On the other hand, plants have assembly lines, machining or fabrication shops, shipping and receiving departments all in need of visual management. As a consequence, visual management is part of the training of professionals in assembly, machining, fabrication, logistics, quality, maintenance, etc. And each one only needs to know visual management as it is relevant to his or her position.

Over time, Lean should  migrate into the mainstream of manufacturing and industrial engineering, and lose its separate identity, both in industrial practice and in engineering and management education. This has been the fate of successful innovations in manufacturing in the past. For example, the “American system of manufacture” to which we owe interchangeable parts is now only a subject for historians. It is not the object of a standard or certification, and nobody explicitly undertakes to implement it. That is because its components — engineering drawings, tolerances, allowances, routings, special-purpose machines, etc. — have all become an integral part of how we make things. Likewise, in Japan, TQC is no longer a topic, as its most useful components have just fused into the manufacturing culture 30 years ago. This is what must happen to Lean in the next 30 years.

Lean proficiency should be built around manufacturing functions, not Lean tools. From foundation to superstructure, we see the following hierarchy — originally defined by Crispin Vincenti-Brown — and structure the body of knowledge accordingly:

  1. Manufacturing and industrial engineering of production lines is the foundation, covering every aspect of the physical transformation of materials and components into finished goods. This is about the design and operation of a production lines using different technologies and working at different paces.
  2. Logistics and production control build on top of this foundation, covering both the physical distribution and the information processing required to make materials available to production and deliver finished goods.
  3. Organization and people covers both what an implementer needs to know in order to lead the Lean transformation of an organization, and to manage it once it is underway. The first part is about Lean project and program management; the second, about the alignment of operator team structures  to the production lines, continuous improvement and skills development, and support from production control, quality assurance, maintenance, engineering, and HR.
  4. Metrics and accountability. This is about appropriate metrics for quality, cost, delivery, safety, and morale. In routine operations, this also means collecting the data needed, computing the metrics, and communicating the results in a way that provides useful feedback. On projects, this means estimating improvements. In both cases, metrics in the language of things need to be translated into the language of money for top management.

A hypothetical participant who would master all  of the above  would understand both the philosophy and the tools of Lean, their range of applicability, and their implementation methods. He or she would possess the following skills:

  1. How to read a plant, assess its performance potential, set strategic directions, and start it moving in these directions. This entails the following:
    • Characterizing the demand the plant is expected to respond to.
    • Mapping its current, ideal and future value streams and processes and detect waste.
    • Assessing its technical and human capabilities.
    • Setting strategic directions for improvement.
    • Identifying appropriate improvement projects for current conditions and skill levels.
  2. How to generate or evaluate micro-level designs for takt-driven production lines or cells in assembly, fabrication, or machining by focusing on flows of materials and movements of people. The tools include spreadsheet calculations with Yamazumi and work-combination charts, jidoka, board game simulations, full-size mockups, and software simulations as needed.
  3. How to generate or evaluate macro-level designs for plants and supply chains, involving the organization of:
    • Internal and external logistics.
    • Milk runs.
    • Water spiders.
    • Heijunka and Kanbans.
    • Lean inventory management.
    • …
  4. How to apply the right tools for quality improvement, addressing:
    • Process capability issues with statistical methods/Six Sigma
    • Early detection and resolution of problems through one-piece flow and systematic problem-solving.
    • Human-error prevention through poka-yoke/mistake-proofing.
    • Planned responses to common problems through Change Point Management (CPM), embedded tests and other tools of JKK.
  5. How to organize people to execute and support takt-driven production, and in particular:
    • Set up a systems of small teams, team and group leaders, to carry out daily production as well as continuous improvement activities.
    • Set up a Lean daily management system with performance boards and management follow-up routines.
    • Generate and maintain a system of posted standard work instructions.
    • Apply Training-Within-Industry (TWI).
    • Set up and dimension appropriately a support structure for logistics/production control, maintenance, quality assurance, engineering, human resources, supply chain management and customer service.
  6. How to manage the Lean transformation of a plant from pilot projects to full deployment.
  7. How to select and deploy relevant metrics to monitor manufacturing performance and estimate the impact of improvement projects both in the language of things and in the language of money.

This BOK is dauntingly large, and new wrinkles are added daily.  Fortunately, you don’t need to master all of it in order to be effective.

Review of existing BOKs

I took a look at a few of the existing training programs offered by various institution, for the purpose of identifying the underlying BOKs. Table 1 shows the list. My comments follow.

Table 1: A few Lean training programs in the US
University of Kentucky Lean Systems Certification
University of Michigan Lean Manufacturing Training
SME Lean Certification
University of Dayton Get Lean
Auburn University Lean Certificate Series

The University of Kentucky program

The University of Kentucky’s program includes Core Courses — a train-the-trainer program — and Specialty Courses — for professionals outside of production operations. Some but not all the specialty courses are targeted at functions within the organization but others are abou tools. Just the core courses add up to three one-week training sessions, while each specialty course is typically a one- or two-day workshop.

From the University’s web site, however, I cannot tell when, or if, participants ever learn how to design a machining cell, or an assembly line, or how to reduce setup times. In the core courses, it’s great to talk about mindsets, culture, and transformational leadership, but where is the engineering red meat?

The specialty courses address planning, improvement methods, logistics, supplier development, and other unquestionably important topics, but offer nothing about manufacturing or industrial engineering.

The University of Michigan program

The University of Michigan has a program of two one-week sessions with three-week gaps between sessions. This program does cover cell design, materials handling and factory layout,  and even rapid plant assessment, that are certainly relevant engineering topics, but I didn’t see anything about the design of lines that are not cells, autonomation, or the Lean approach to quality. There is a module about integrating Six Sigma with Lean, but there is a lot to Lean Quality that has nothing to do with Six Sigma, such as mistake-proofing.

There is also some coverage of logistics, organization, and accountability, but not as much as in the University of Kentucky program.

The SME

The SME has published a document entitled Lean Certification Body of Knowledge, in which the major headers are:

  1. Cultural Enablers
  2. Continuous Process Improvement
  3. Consistent Lean Enterprise Culture
  4. Business Results

Organization and People issues are treated in 1. and 3. The first two line items under Cultural Enablers are “Respect for the individual” and “Humility.” I am not sure how you can teach this or test for it, particularly humility. It is followed by techniques that have to do with implementation. The topics  in 3. have more to do with management once Lean is started, but it doesn’t say it in so many words.

All Engineering and Logistics is lumped under Continuous Improvement, which is clearly a misnomer because many of the Lean techniques in these areas are radical innovations that have nothing to do with continuous improvement. Inside this section, the choice of topics and their structure is surprising. For example, the only method of data collection considered is the check sheet, and it ranks as high in the hierarchy of topics as poka-yoke or one-piece flow.

As the name suggests, Business Results covers metrics and accountability.

The weight of the different areas varies with the level of certification. At the Bronze level, for example, Continuous Improvement counts for 60%; at the Gold level, only for 15%.

The University of Dayton

I have ties with this institution from having taught courses there  for many years, and I am still listed among their Experts. But I am not involved with their GetLean Certification program. It is an 8 to 10-day curriculum with a core of 5 days on the following topics:

  • Introduction to the Lean Tools
  • How to Develop New Metrics in a Lean Culture
  • Human Error Reduction: Root Cause Analysis
  • Fundamentals of Negotiation
  • Strengthening Your Business Services using LEAN Tools
  • Managing Projects in a LEAN or Six Sigma Environment
  • Managing an Efficient Supply Chain

The choice of topics may seem odd. For example, you might wonder what Fundamentals of Negotiation is doing in a Lean training program, or why Root Cause Analysis only appears under Human Error Reduction. What about root cause analysis of process capability problems?

Auburn University

Of all the Lean programs reviewed here, Auburn University’s probably has the deepest roots, through the influence of JT Black, whose passion for Lean goes back to the late 1970s.

The list of subjects they cover is as follows:

  • Principles of Lean
  • Value Stream Mapping
  • 5s
  • Total Productive Maintenance (TPM)
  • Quick Changeover
  • Pull / Kanban / Cellular Flow
  • Sustaining Continuous Improvement
  • Lean Office
  • Lean Accounting
  • Rapid Improvement Event
  • Problem Solving

If anything, this program has too much of the red meat that is lacking in some of the others. It could, without harm, emphasize Logistics and Management a bit more.

Conclusion: no consensus

Even when considering the programs solely on the basis of their published syllabi, it is clear that their graduates will have received vastly different instruction, and that the designers of these programs have no common view of what the Lean Body of Knowledge is.

Greek temple diagram
Nov 17 2011

Jidoka versus automation

Toyota’s jidoka isn’t just about stopping production when something goes wrong. It is an automation strategy that works because it is incremental and centered on human-machine interactions. It is essential to the strength of manufacturing in high-wage economies and should command more attention than it has so far among Lean implementers.

The most striking characteristic of automation in manufacturing is that, while making progress, it has consistently fallen short of expectations. In Player Piano, Kurt Vonnegut articulated the 1950s vision of automated factories: integrated machines produce everything while their former operators are unemployed and the managers spend their time playing silly team-building games at offsite meetings. 60 years on, the most consistently implemented part of Vonnegut’s vision is the silly team-building games…

Nippon Steel’s Yawata Steel Works in Kitakyushu, Japan, produce as much today with 3,000 employees as they did with 40,000 in 1964, and this transition was accomplished without generating massive unemployment. There are other such limited areas of automation success, like the welding and painting of car bodies. When manufacturing jobs are lost today, it is almost never to automation and almost always to cheaper human competition elsewhere. In the words of an experienced operator in a plant making household goods in the US, “When I joined 25 years ago, I expected these jobs to be automated soon, but we’re still doing them the same way.”

What is holding up automation today is not technology  but the lack of consideration for people. There are entire books on automation without a paragraph on what their roles should be. Of course, a fully automatic, “lights-out” factory has nobody working inside, so why bother? There are at least two reasons. First, even an automatic plant needs people, to program its processes, tell it what work to do, maintain it, monitor its operations and respond to emergencies. Second, successful automation is incremental and cannot be developed without the help of the people working in the plants throughout the migration.

Enter autonomation, or jidoka, which is sometimes also called “automation with a human touch” but really should be called human-centered automation. Instead of systems of machines and controls, it is about human-machine interactions. In the classical House of Lean model, the two pillars holding up the roof at Just-In-Time and Autonomation, or Jidoka. Figure 1 is lifted from the introduction to Working with Machines, and shows what happens when the jidoka pillar is ignored.

Figure 1. Just-in-Time and Jidoka

More and more, the Lean literature in English uses the japanese word jidoka rather than autonomation, but with its scope reduced to the idea of stopping production whenever anything goes wrong, and the concept is tucked away under the umbrella of Quality Management.

Toyota’s jidoka is a tricky term, because it is an untranslatable pun. Originally,  the Japanese word for automation　is　jidoka (自動化) , literally meaning “transformation into something that moves by itself.” What Toyota did is add the  human radical 人　to the character　動　 for “move,” turning it into the character 働　for “work,” which is still pronounced “do” but changes the meaning to “transformation into something that works by itself.” It”s automation with the human radical added, but it is still automation, with all the technical issues the term implies.

The discussion of automation in the first draft of Working with Machines started with the following historical background, which was edited out like the chapter on locomotives and typewriters, on the ground that it contained no actionable recommendations. In this blog, I can let you be the judge of its value.

From tea-serving wind-up dolls to autonomation

The word automation was first used by Ford manufacturing Vice President Delmar Harder in 1947 for devices transferring materials between operations. He set as targets a payback period of at most one year in labor savings, which meant in practice that each device should not cost more than 15% above an operator’s average yearly wages and eliminate at least one operator. While this kind of economic analysis is still used, from the perspective of Toyota’s system, Ford’s focus on materials handling was putting the integration cart before the unit operation horse. Toyota’s approach focuses on individual operations first, and only then addresses movements of parts between them. In 1952, John Diebold broadened the meaning of automation to what has become the common usage, and painted a picture of the near future that was consistent with Kurt Vonnegut’s.

At that time, automatic feedback control was perceived to be the key enabling technology for automation, to be applied to ever larger and more complex systems. It was not a new concept, having been applied since 1788 in the centrifugal governor regulating pressure in a steam engine (See Figure 2)

Figure 2. James Watt’s 1788 centrifugal governor

Applying electronics to feedback control in World War II had made it possible, for example, to move a tank’s gun turret to a target angle just by turning a knob. Postwar progress in the theory and application of feedback control both caused many contemporary thinkers, like Norbert Wiener,  to see in the concept a philosophical depth that is truly not there, and to underestimate what else would need to be done in order to achieve automation. Of course, if you cannot tell a machine to take a simple step and expect it to be executed accurately and precisely, then not much else matters. Once you can, however, you are still faced with the problem of sequencing these steps to get a manufacturing job done.

While automatic feedback control was historically central to the development of automatic systems, it is not at center stage in manufacturing automation today. With sufficiently stable processes, open-loop systems work fine, or feedback control is buried deep inside such off-the-shelf components as mass flow controllers, thermostats, or humidity controllers. Manufacturing engineers are occasionally aware of it in the form of variable-speed drives or adaptive control for machine tools, but other issues dominate.

Fixed-sequence and even logic programming also have a history that is as long as that of feedback control and are by no means easier to achieve. Figure 2 shows two examples of 18th century automata moved by gears, levers and cams through sequences that are elaborate but fixed.

Figure 2. 18th century automata from France and Japan

These concepts found their way into practical applications in manufacturing as soon as 1784, with Oliver Evans’s continuous flour mill that integrated five water-powered machines through bucket elevators, conveyors and chutes (See Figure 3). The same kind of thinking later led to James Bonsack’s cigarette making machine in 1881, and to the kind of automatic systems that have dominated high-volume processing and bottling or cartonning plants for 100 years, and to the transfer lines that have been used in automotive machining since World War II.

Figure 3. Oliver Evans’ continuous flour mill (1784)

Fixed-sequence automation works, but only in dedicated lines for products with takt times under 1 second, where the investment is justifiable and flexibility unnecessary. Rube Goldberg machines parody this type of automation.

Figure 3. Winner of the 2008 Penn State Rube Goldberg machine contest

Automation with flexibility is of course a different goal, and one that has been pursued almost as long, through programmable machines. The earliest example used in production is the Jacquard loom from 1801, shown in Figure 4. It is also considered a precursor to the computer, but it was not possible to make a wide variety of machines programmable until the actual computer was not only invented but made sufficiently small, cheap and easy to use, which didn’t occur until decades after Vonnegut and Diebold were writing.

Figure 4. Jacquard loom from museum in Manchester, UK

By the mid 1980’s, the needed technology existed, but the vision of automation remained unfulfilled. In fact, more technology was available than the human beings on the shop floor, in engineering, and in management knew what to do with. As discussed in the post on Opinels and Swiss knives, the computer as a game changer. In manufacturing, this was not widely recognized when it became true, and it still is not today.

Writing in 1952, John Diebold saw nothing wrong with the way manufacturing was done in the best US plants, nor did he have any reason to, as the entire world was looking at the US as a model for management in general and manufacturing in particular. In the 1980’s, however, when GM invested $40B in factory automation, it was automating processes that were no longer competitive and, by automating them, making them more difficult to improve.

Whether the automation pioneers’ vision will ever come true is in question. So far, every time one obstacle has been overcome, another one has taken its place. Once feedback control issues were resolved came the challenge of machine programming. Next is the need to have a manufacturing concept that is worth automating, as opposed to an obsolete approach to flow and unit processes. And finally, the human interface issues discussed must be addressed.

21st century manufacturers do not make automation their overall strategy. Instead, automation is a tool. In a particular cell, for example, one operator is used only 20% of the time, and a targeted automation retrofit to one of the machines in the cell may be the key to eliminating this 20% and pulling the operator out of the cell.

Nov 17 2011

Why people don’t learn Lean management

Nicolas Stampf, from BNP Paribas, posted the following question on LinkedIn: “How come that despite being showed and coached into doing continuous improvement the Lean way, people don’t learn. I mean that when you stop coaching them and come back some months later, although they’re doing performance management and problem solving, improvements are absent? When you re-show them, they say they forgot having done that previously.”

Following is my response:

  1. You might as well ask why people keep behaving in self-destructive ways when they know better, for example overeating and not exercising. The rewards of changing behavior are obvious and they know them, yet they don’t do it until a significant event happens. Getting seriously ill will do it, but so will running for president.
  2. In  your question, you also treat the adoption of Lean as an personal choice. It’s not. Organizations choose to implement Lean, not individuals. It is a decision made by top managers, and they must communicate to all levels why they are doing it and that they are dead serious, which means that participation in the effort is a condition for continued membership in the organization.
  3. Also, as Tom Berghan put it “Lean isn’t Feng Shui on the business, it is the business.” In other words, if you want to be successful in implementing Lean, you cannot cherry-pick elements of it. Your question is centered on continuous improvement, performance management, and problem-solving, , which won’t make much of a difference if they are all you do. In manufacturing, the core of Lean includes specific approaches to production line design, operator job design, production control and logistics, quality assurance, maintenance, human resources, accounting, strategy deployment, etc.  I understand your work in Banking, where many of these approaches are not directly relevant, which means that you have to invent their equivalent for banking operations.
Lean implementation survey
Nov 9 2011

More Flak on Lean Based on the Same Survey

Managing Automation published another response to the same study that claims to show that Lean does not work: Lean Manufacturing and Operation Excellence: Not Worth Their Weight? 

As described in the press and their own press release, the AlixPartners study commingles Lean with “Six Sigma and other productivity programs,” which raises the following issues:

  1. Lean Manufacturing is based on the Toyota Production System, which includes neither Six Sigma nor Operation Excellence nor  “other productivity programs,” whatever those may be.
  2. Lean Manufacturing is not a “productivity program,” but the pursuit of concurrent improvement in quality, productivity, delivery, safety, and morale. I  know I am repeating myself, but it needs to be said until the leaders of manufacturing companies hear it.

If these press accounts are correct, the survey confuses Lean with other approaches in an open-ended list, misstates its purpose, and considers exclusively metrics of cost reduction.

The effectiveness of Lean is not an easy subject to study. Should we survey all the companies that claim to be Lean, have a Lean program in place, have been certified Lean by some external authority, or are top performers in their industry? Once we agree on this, we still need yardsticks to quantify both  the effort they put into Lean and the rewards from it.

I took a stab at it a few years ago, and did my own analysis, the results of which were published as a Viewpoint in Manufacturing Engineering in 2006. I chose 40 winners of the Shingo Prize and searched Hoovers Online, for comparative performance data with their 400 top competitors. On the average, the data did not show that the Shingo Prize predicted any advantage in profitability, market share or employment growth. The AlixPartner press release says roughly the same thing, but I see it as reflecting on the Shingo Prize itself, not Lean.

The Shingo Prize is supposed to be the “Nobel Prize for Manufacturing,” but what are the criteria used to award it? You can download the Shingo Prize Guidelines and see for yourself. A team of Shingo Prize auditors visits the plants and awards points  to measure “the degree to which the behaviors in an organization are aligned with the principles of operational excellence.” In other words, the plants are measured on process compliance. They score points for practices they have in place. It is like measuring chess players on the number of pawns they move, and is correlated to victory like the Shingo Prize to business performance.

Toyota did not grow based on a compliance checklist. When I visit a plant, based on what I see and what people tell me, I can form an opinion as to whether they are among the few that have the spirit of Lean or the many that are going through the motions. But I don’t know how to generate a checklist that could be systematically applied to arrive at such a conclusion, and, desirable though it may be, I don’t believe a real survey is feasible.

Jamie Flinchbaugh doesn’t like sports metaphors, but I can’t resist one here. Usain Bolt  is the fastest man alive. Let us assume somebody publishes a book entitled “The Running Secrets of Usain Bolt.” How Usain Bolt actually trains is probably not trivial and certainly involves sustained effort and ferocious discipline. The author of the book, however, is concerned that a stern, eat-your-vegetables message would hurt sales, and focuses instead on easier topics, like shoes. As a result, kids flock to shoe stores thinking that wearing these shoes will make them fast, but the real ones are too expensive, so they buy cheap imitations instead. Six months later, based on their responses, a survey concludes that Usain Bolt’s methods don’t work.

Most Lean programs today are to serious implementations as cheap imitation shoes are to the training of Usain Bolt. Where they may succeed is in ruining the reputation of Lean. It is bound to happen sooner or later. As a brand, Lean has had a 22-year run so far, already longer than I expected.

Orgchart - end of lean program
Nov 4 2011

Should a lean transformation program ever end?

On LinkedIn, Patrick Courtney asked the following question: “In your experience, with a Lean transformation program when can the program become a waste? Is there a tipping point? Please share your experiences and wins.”

Let us assume we are talking about a successful Lean transformation with a program office, headed by a lean champion and including a small group of project facilitators. The question then is whether there is a point beyond which this organization is unnecessary.

That a Lean transformation is successful means that practices from daily operations on  the shop floor to strategic planning in the board room are more effective and efficient as a result of Lean, as evidence in business performance. At that point, people in the organization no longer refer to “Lean tools,” but simply to “the way we do things.” What was a change requiring adaptation is the new normal.

In principle, once Lean practices are assimilated into the company’s standard mode of operations, a program office is no longer necessary. In reality, there are some functions for which continued, organized support is necessary, such as the following:

  1. Continuous improvement. If continuous improvement is carried out through a system of circles or individual suggestions, then a structure will be needed to manage it and organize periodic conferences and award ceremonies.
  2. External certification. If the company is a part supplier, it may need to maintain its status as a “certified Lean” with some OEMs, and resources are needed to host audits and make sure that actions are taken as needed to ensure compliance.
  3. Supplier support. Companies that are successful at Lean commonly endeavor to pass their skills on to suppliers in exchange for price breaks, which requires a team of engineers.

Some people will remain involved with Lean, but in other roles than during the initial implementation, and often elsewhere on the organization chart. More generally, a successful change program should eventually fade away. For example, the pursuit of Total Quality Control (TQC) was a program in major Japanese manufacturing companies until the mid 1970′s, when all of them had received a Deming Prize. Then it  gradually lost visibility, as everything they had learned from this program was integrated in normal operations and its principles had become part of the culture.

Jun 14 2011

Management Whack-a-Mole and the Value of Lean

On 5/24/2011, NWLEAN moderator Bill Kluck launched the richest, most vigorous debate in the 13-year history of that forum by asking members whether they were cost cutters or capacity enhancers. Over the following three weeks, 29 authors posted 68 spirited, yet courteous messages accessible from NWLEAN to anyone with Yahoo! ID.  The contributors included several well-know authors and some of my favorite sparring partners. In alphabetical order, they were  Dan Barch, William Bowman, Robert Byrd, Abhijit Deshpande, Mark Graban, Jim Harrington, Jonathan Harrison, Rob Herhold, Blair Hogg, Gangadhar Joshi, Bill Kluck, Joachim Knuf, Ed Larmore, Paul Layton, Ted Mayeshiba, Jim McKechnie, Larry Miller, Joe Murli, John Nelson, Stephen P. O’Brien, Anthony Reardon, Tom Robinson, Sunita Sangra, Dale Savage, Patrick D. Smith, Tom Stogsdill, Mike Thelen, Chuck Woods, plus a few others who did not use their real names.

The message that started the thread was as follows:

“It seems more and more (especially in this recession!) that lean professionals fall into 2 camps:
- Cost cutters
- Capacity enhancers
There are some out there that are saying that you HAVE to cut costs, or you’re not getting lean.
There are others that say lean is about improving capacity, so you can enhance the customer experience.
Which are you, and why? Is this driven by the top of your organization, people who may not understand what lean is? Do we risk becoming cost cutters, or smoke-and-mirror guys?
Just askin’!

Bill”

Although I didn’t participate initially, it was clear to me that the effect of a successful Lean implementation was limited neither to cost cutting nor to capacity enhancement. Instead, I see Lean as the pursuit of concurrent improvement in all dimensions of manufacturing performance, but I had already shared my thoughts on this matter in Lean as the End of Management Whack-a-Mole. Management Whack-a-Mole is the game illustrated in Figure 1, in which managers  boost performance in one dimension at the expense of the others, shifting focus every few months without ever achieving a genuine overall improvement.

Figure 1. Management Whack-a-Mole

Several of the early posts, however, prompted me to  jump into the fray and respond on a variety of topics, initially as follows:

  1. People trained in Finance and Management Accounting have had their shot at running US Manufacturing from the 1950s to the 1970s, with outcomes that should make them modest about the value of their approaches.
  2. Companies that have grown through Lean include Toyota since 1950, Wiremold from 1991 to 2000, and many others that are not publicized. A successful Lean effort helps Sales in specific ways, as, for example, when more flexibility enables Manufacturing to accept a sample order for a new component by a customer, who then designs it into his own products and becomes a major OEM.
  3. Cost reductions are a by-product of Lean but not its primary purpose. Manufacturing is a competitive sport, and Lean a strategy that makes you a stronger player, and not just right now but in the long run as well. When you hire a top coach for a sports team it’s not to cut costs but to win games.
  4. ROI is just one ratio, invented at DuPont 100 years ago to report in a common form the activities of multiple business units. There is nothing magic about it, and, by itself, it certainly does not give a complete picture of the health of a business, as even finance people recognize.

This caused further exchanges with Robert Byrd, who wrote: “…The most basic concept is Profit = Price – Cost. The market dictates price, so we have the best leverage for maximizing profit through controlling our cost structure…”  My response:

Is this always true? What about situations in which time to market is of the essence? I remember a client that was introducing a new frozen food product. On one of our visits they had us taste the R&D prototype, which was delicious. Three months later, they had a jury-rigged production line making 900 units/minute. The line left much to be desired, but we could not argue with their focus on getting the product to market. During all that time, their focus was not on getting it done cheaply but on getting it done at all. Then they could go back and improve the line.

He also wrote: “…Which is best accomplished through the elimination of waste and problem solving…”  My response:

This is the key point. We have yet to encounter a manufacturing or service organization in which the details of how work is being done contains no improvement opportunity, and this is what most managers simply do not believe. They are trained to think in terms of “big pictures,” and look for cost cutting opportunities like eliminating entire departments or reducing every department’s budget by 5%.

And finally: “If the aim is only to increase profit by reducing cost, without focus to grow the business, then the culture will never take root and only a short-term improvement will be realized. Or the company will never achieve it’s true potential.”

Your point does not fit in a 30-sec sound-bite or tag line. Good managers are able to monitor all aspects of performance at the same time, from growth to costs. But communication is tricky. For example, if you showcase ” Profit = Price – Cost,” what behaviors do you expect to stimulate, other than cost cutting?

In his second response, he added: “However, what was their business objective once they focused on improvement? I would venture to guess that it was focused on cost reduction.” My response:

I don’t recall them mentioning cost reduction explicitly. When the line first started, about 20% of the units were defective, and that was a focus of concern. Of course, quality improvements reduce costs as a side effect, but they also have other effects: quality problems have an impact on customer perceptions of the product because of variability among the units that are not defective.

In their other production lines, improvement was driven by marketing concerns. This was in Europe, and, in spite of the existence of the EU, frozen food packages had a different sizes by country, in addition to having labels in different languages. Based in Italy, they pursued quick changeovers in package sizes in order to be able to export to Germany, France, the UK, etc.

Their Lean program fit within their business strategy, but it is a stretch to say that this strategy was centered on cost reduction.