How to identify the constraint of a system? Part 2

When trying to find the system’s constraint, why not simply asking the middle management? At least when Theory of Constraint was young, our world spinning slower and processes simpler, the foremen usually had a common sense understanding of their bottleneck. They knew what machine to look after, and what part of their process to give more attention.

If you haven’t read part 1, catch up: How to identify the constraint of a system? Part 1

Even so they may not have discovered all 9 rules about managing a bottleneck by themselves, they intuitively applied some of them.

Nowadays the picture is blurred with complexity and frequent changes. Nevertheless, asking middle management can still give precious hints about bottlenecks. Ask what the more troublesome spot of the process is and from where / whom the downstream process steps are waiting for something. Chances are that many managers will point to the same direction.

This works for project management or (software) development as well. In those cases I would also ask who the superstar (programmer) is, the one everyone wants on his/her project and in every meeting. Chances are that that person turned into a constraint without even noticing it.

Now if the tip can be useful, refrain from rushing to conclusions from these answers and check for yourself. Many managers may tell you the same just because they all heard the same complaints in a meeting. A meeting where all managers meet…

Go to the gemba, look for Work In Progress

Let’s start the shop floor investigation searching for the bottleneck like it is described in the early text books.

Go to the gemba, follow the flow (which is easier and somewhat more natural than walking upstreams, but up to you to choose the preferred way) visually assess the work in progress (WIP) and inventories in front of the machines or work cells.

Usually the highest piles of Inventories or work in progress are sitting in front of the bottleneck and the following downstream process steps are starved from material or parts.

Yet if it would be that easy it would be no fun. The above works well in simple processes which are neat and tidy. Most often the inventories are scattered wherever it is possible to store something, FIFO (First In First Out) rules are violated and downstream processes, incentivized on productivity, work on whatever they can work on for the sake of good looking KPIs. Finding the bottleneck in such a chaos needs more than a visual check.

It is also possible that excess inventory and work in progress may be temporarily stored in remote warehouses and not in full sight, thus not visible.

Another pitfall is confusing work waves, periodically releasing parts or information, and real bottlenecks. An example could be a slow process which is not a true bottleneck but needs more than the regular shifts to catch up with its workload.

Imagine a slow machine (sM) amidst a process. The process upstream (P1) works 8 hours with best possible productivity and WIP piles up in front of sM. The downstream process (P2) works at best possible productivity and has some WIP in front of it.

At the end of the shift P1 and P2 are shut down. They both fulfilled their daily scheduled work. sM goes on for a second shift, processing the WIP in front of it.

By the end of the second shift, no more WIP (or very few) in front of sM and what was waiting in front of sM is now waiting after it, in front of P2. This is the picture the next early morning:

An observer, depending when he/she looked at the process, could have come to wrong conclusions about a bottleneck. Early morning it looks like the first machine of P2 is holding back the flow. In mid afternoon it is sM that is the culprit, when in reality there is no true bottleneck. sM has enough capacity provided it can work more than one shift.

Some would mention wandering bottlenecks, jumping from one place to another. This is something I will elaborate on in a separate post. Or series…

We are not done now with our bottleneck safari. To learn more, proceed to part 3.


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How to identify the constraint of a system? Part 1

A very common question once people get familiar with Theory of Constraints and the notion of bottlenecks and constraints is how to find them in a process. Identifying the constraint is key as the constraint, by its nature, controls the performance of the whole system.

The trouble with examples given in textbooks or case studies is that they are rather simple compared to finding the constraint in real life. This difficulty grew over time as processes got more complex, adding new layers of rules, standards and regulations. This complexity grew to an extend that many constraints remain elusive to people searching them, leading many people to be wrong when identifying “their” constraint.

Facing this kind of difficulties, readers asked me if a formal procedure to identify the constraint exists. I am not aware of such a procedure and from my experience the search for the constraint is much more like a detective’s job requiring investigation skills than applying a recipe. Some common patterns and similarities may exist, but every organization has some specificities that make the search for the constraint a special case. Therefore intuition and experience are definitely of great help.

In this series of post, I propose to review such investigations, that may help readers to transpose in their own situation, and eventually try to wrap up guidelines to identify constraints.

The usual suspects

First let’s review common bottleneck resources, keeping in mind that being a bottleneck is not synonymous of being a constraint and, as a general rule, a constraint is (and should be) a resource too long or too expensive to get more of it, or put differently turn it in a non-constraint.

A constraint was long said to be a very expensive piece of machinery or equipment which is too expensive as an investment to afford another one for additional capacity or which is not currently available.

Big stamping machines or presses, painting booth, heat treatment, surface treatment or sophisticated machine tools made good candidates for being bottlenecks and ultimately constraints.

Bad news is that things evolved, as we will see, and even if those bulky expensive or scarce equipment still make good candidates for the constraint status, they are not always the constraint.

For instance, I worked in a engineer-to-order company designing and manufacturing heavy mechanical equipment. The heat treatment was said to be the constraint and was managed by-the-book as a constraint.

After a short diagnostic, it turned out that heat treatment was not the constraint. It wasn’t because the true constraint was elsewhere in the process and those heat treatment operations could be subcontracted nearby at short notice and reasonable price. The subcontracting gave sprint capacity and provided relief whenever necessary. So heat treatment, even with long cycle times, was nothing really scarce nor excessively expensive.

Why was the heat treatment mistakenly thought to be the constraint? Because literature on the subject point this kind of process as usually being a bottleneck (remember: not enough capacity with regard to average demand placed on it). If indeed the workload often exceeded the capacity, the heat treatment was not the constraint. Failing to understand the difference between bottleneck and constraint led to a wrong conclusion.

Where was the real constraint? In engineering department where equipment are designed: people with specific skills that are long to learn.

More usual suspects

Very slow processes are usually also good candidates as bottlenecks: drying, curing, maturation, chemical or biological reactions, etc.

People with specific skills (as we have seen), knowledge, abilities, expertise, etc. that cannot easily be hired can also become constraints. So are some raw materials that are rare or dependent on harvest, climate, embargo, shortage, etc.

In some areas it is difficult to find some qualified workforce like welders, forklift drivers or specialists in some trade, which makes them constraints even so their profession is not so scarce at a larger scale.

When the constraint is not obvious nor easy to find, its identification becomes a matter of investigation. Investigation will start in part 2.


About the author, Chris HOHMANN

About the author, Chris HOHMANN

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You are entering unclear territory

This post is inspired by some pictures* in Mike Rother’s book “Toyota Kata”, very relevant in our actual changing times and complex situations. I really like the figures that remind that the journey towards a goal requires entering unclear territory at some point.

Unclear territory

Adapted from “Toyota Kata”, Mike Rother

Experience from the military tells that no plan, regardless how carefully it was planned, will survive contact with the enemy.

No plan survives contact with the enemy.
Helmuth von Moltke
https://en.wikiquote.org/wiki/Helmuth_von_Moltke_the_Elder

What this means is that unknown facts, unexpected events and dynamic complex interrelated relationships will interfere with the plan based on partial knowledge, biased perception and simplified hypotheses.

Plans are important because they allow to explore hypotheses and be prepared accordingly but most plans are useless as reality often unfolds differently as expected.

This is why, when starting a journey toward a significant change or a Lean transformation for example, the plan will probably last only for the few first steps, but barely further. Once the journey started, unexpected circumstances will reveal themselves and require adjustment.

This is similar to exploring a dark room with a flashlight**. Only a part of the room is visible and every move is done accordingly to visibility and noticed obstacles. As one moves forward the line of sight extends and the vision clears further one step at a time. New obstacles appear, requiring new adjustment, and so on. The path across the dark room is probably not straight, but must get past several obstacles.

The same happens while hiking. The goal is set, the map shows the terrain and the compass helps for the bearing. Yet the map may show the canyon, the river and the forest, but none of the boulders, the fallen trees across the path neither the recently flooded areas. Those obstacles will appear once the hikers come close. In this case too, the hikers have to adjust to circumstances and find alternate routes to reach their goal. The one they had in mind while planning the hike is no more relevant.

Leaders must be able to lead through unclear territories

Unclear territories of all sorts are more and more common. Even what we believed familiar ground can be disrupted overnight. Everything is going “VUCA”, meaning being increasingly Volatile, Uncertain, Complex and Ambiguous. More decisions must be taken, more frequently and often with incomplete data and only partial understanding of the situation.

Among all decisions, some – and hopefully few – will show unadapted, requiring new adjustments. Wandering in unclear territories is a new fate. Being able to make quick and good decisions in unclear territories is a necessary aptitude for aspiring leaders.

What are good decisions? Those enabling the organization to achieve its goal despite the obstacles and unexpected difficulties, those solving the problems to clear the way towards the goal or choosing alternate routes to get closer to the goal.
Therefore, having a clear Goal onto which aligning actions, projects and initiatives when going through unclear territory is mandatory.

Followers too must understand “unclear territories”

Unclear territory is not a concept for leaders only, the followers must understand it too. What does it mean? It means that once entering unclear territories:

  • leaders (managers, people in charge…) may get surprised by unexpected events and this does not make them bad leaders
  • leaders, managers, etc. don’t have all the answers to all difficulties and problems that arise along the journey
  • plans and projects sometimes have to be reoriented, which may look like poor management or a fantasy but isn’t
  • some invested efforts and actions must be abandoned due to new circumstances, it’s disappointing, but that’s life

One may wonder how to distinguish poor leadership from the necessities to adapt to new circumstances? I would suggest to prevent the question from arising by establishing a clear communication upfront, giving frequent and transparent updates and have everyone exploring the unclear territory by teamwork.


*Mike Rother “Toyota Kata: Managing People For Improvement, Adaptiveness, and Superior Results”, McGraw-Hill Professional, 2010. Pictures mentioned are page 8; 120; 124; 133; 163

**Flashlight metaphor, page 133


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What is autonomous maintenance (TPM)?

Autonomous maintenance is one of the 8 Total Productive Maintenance (TPM) pillars, it aims to give both competence and responsibility for routine maintenance, such as cleaning, lubricating, and inspection to operators.

The aims and targeted benefits of autonomous maintenance

The ultimate goal of Total Productive Maintenance is to enhance machines’ effectiveness. TPM is a participative approach, involving all stakeholders and taking into account all aspects of maintenance. In order to achieve this goal, TPM is split in 8 pillars or topics. Autonomous maintenance is one of the 8 and is about simple mundane tasks, but having their importance nevertheless. The expected outcomes are:

  • Operators’ greater “ownership” of their equipment
  • Increased operators’ knowledge of their equipment
  • Ensuring equipment is well-cleaned and lubricated
  • Identification of emergent issues before they become serious failures
  • Freeing maintenance personnel for higher-level tasks

Operators’ ownership

Operator’s ownership of their equipment is meant to close the divide between Production and Maintenance in cases where the first claim “my job is to produce” and the second “my job is to repair”. This is mainly the case when production staff is incentivized on production output and maintenance is jealous about keeping its technical skills and prerogatives.

What happens then is that production operators do not usually care much about the equipment and machines they use and are prone to trespass speed limits, for example.

As they are not supposed to do anything about the machine breaking down, they soon find out that breakdowns are opportunities for an extra break, hence an extra smoke, one more coffee and so on.

As a result, machines stops last longer as they should: waiting for maintenance staff to come, discover the cause of the trouble, fix it, waiting for the operators to come back and resume production.

It can go the other way when production is strongly incentivized on units produced: any stoppage or breakdown jeopardizes the bonus and is immediately resented when maintenance doesn’t fix the problem fast enough.

What TPM is trying to do: give operators a sense of ownership of their equipment in order for them to take care, use it well, help maintenance technicians to find the causes of breakdowns by summarizing what happened before, and so on.

In order to achieve this, training must be delivered to both production and maintenance staff, focusing on the required cooperation for the sake of overall performance improvement. It will be a win-win cooperation: operators enriching their jobs with technical aspects and maintenance technicians being freed of low-qualification tasks for a better use of their real technical expertise. However, this must be done step by step.

Increasing operators’ knowledge of their equipment

Operator will use their equipment and machines correctly if they are trained not only for the use, but also a bit further into technical details. When operators have a basic understanding of how a machine works, they may be able to discover some causes of malfunction by themselves and give precious indication to maintenance team. With this focus, downtime can be reduced as maintenance does not have to go through a full investigation. If operators show interest and abilities, they may be trained further, to a point they can help maintenance with repairs, preventive maintenance tasks, adjustments, etc.

In my years as production manager with Yamaha, we brought teams of ladies to take care of the maintenance of automatic electronic components insertion machines. These ladies started as operators without any technical background, only feeding the machines. Step by step we trained them to take care of simple cleaning tasks, then adjustments, later exchanging more and more complicated mechanisms and finally be involved in major repairs.

Ensuring equipment is well-cleaned and lubricated

Before dreaming of repairing complex equipment, the journey starts with more mundane but important tasks: cleaning and lubrication.

But it’s more than that. Autonomous maintenance is about passing over  to operators the basic cleaning of the machines, lubricating and oiling, tightening of nuts and bolts, etc.

With these new tasks, operators will soon be able to take over daily inspection, diagnosis of potential problems and other actions that increase the productive life of machines or equipment. With appropriate prior training, of course.

Identification of emergent issues before they become serious failures

Cleaning and lubrication by operators is not a trick to reduce manpower costs by pushing tasks to lesser qualified people. On the contrary: TPM considers daily cleaning as an inspection and operators as subject matter experts. Indeed, operators using the machines and equipment daily are the best qualified detectors of early signs of problems. While cleaning they can detect: wear, unusual noises, vibrations, heat, smell, leakage, change of color, etc.

Using the machines frequently, they know best what is “as usual” and what is unusual. Someone hired only to clean and lubricate machines without using them would not be able to notice the forerunning signs of potential big trouble.

This daily inspection is key to reduce breakdowns by keeping the machine in good condition and by warning early – before breakdown – in order to remedy swiftly to unusual forerunning signs.

Freeing maintenance personnel for higher-level tasks

Putting skilled professionals in charge of challenges matching their expertise is certainly more attractive than asking them “to clean up other’s mess”, as maintenance staff frequently complain. Therefore the reluctance to train production operators for simple tasks and hand those over should not be a big deal for maintenance techs.

Production management should also see the opportunity to have better technical support for improvement and repairs, as skilled technicians are made more available. Of course, this comes at the expense of some daily minutes devoted to take care about machines instead of producing parts. In the long run, this should be a good deal, because less breakdowns, less scrap, fewer minor stops and faster changeovers thanks to technical improvements will pay back in productive capacity.

Finally, for production operators, the deal is to enrich their job with more technical content. For those immediately claiming acquisition of new skills deserve a pay raise, they should first consider that taking care of machines and equipment they are in charge is a basic expectation, not an extra requirement. Time will be given to do the daily maintenance routine. For operators it’s a shift of occupation content a few minutes a day.

Now this said, the question of a raise is to be considered in the context.

About the author, Chris HOHMANN

About the author, Chris HOHMANN

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Can Industry 4.0 rejuvenate Total Productive Maintenance?

In this post:

The youngest among my blog readers may not understand what I mean with Total Productive Maintenance, this pre-Lean management approach to maximize machines and equipment effectiveness and aiming to improve companies’ performances.

TPM in a nutshell

In a nutshell, Total Productive Maintenance or TPM in short, originated in Japan, 1971. It was a participative spin-off of the american Productive Maintenance (a mix of maintenance policies to maximize machines’ availability and effectiveness), aiming to minimize all kind of losses by involving every department and everyone.

TPM had its heyday in the 1985-1995s in the western companies and failed to get mainstream despite the efforts to rebrand it Total Productive Management. The original name and much of the content, even so transposable to almost any activity, was too much linked to industrial machinery maintenance.

Total Productive Maintenance gave way to Lean Manufacturing and somehow got absorbed by Lean. TPM brought Overall Equipment Effectiveness (OEE) indicator to the world, a still very popular KPI nowadays.

Industry 4.0 and Total Productive Maintenance 2.0?

My basic assumption for this prospective thinking is that industry 4.0 environments will be highly automated so that the human factor will have lesser impact on the machines / cells / lines /workshops performance. Conversely machines’ utilization will regain focus.

Performance is determined by market requirements, but it will continue to be a mix of responsiveness, speed (time to market, lead time… ) and quality, with a higher expectation for agility than today. Costs may come second when dealing with high customization.

Performance will be mainly driven by machines’ availability, speed and yield, the latter being roughly the right first time rate. In other words OEE.

Availability is key for agility and responsiveness. This stresses the need of preventive maintenance and quick changeovers. Preventive maintenance starts with daily cleaning and inspection in order to keep all equipment in operational state and detect any wear or damage early. Some equipment will probably also need periodic calibration and geometry checks to ensure accuracy e.g 3D printing.

These tasks may be passed to former operators now converted into level one maintenance technicians. Further more in-depth periodic inspection will also be required by more expert staff that can be either company’s own or third-party. This reminds of the ‘autonomous maintenance’ pillar of TPM.

TPM autonomous maintenance in 4.0 environment

Autonomous maintenance intent was/is to give operators greater “ownership” of their equipment in order for them to take care and use responsibly. By increasing operators’ technical knowledge of the equipment they use and entitle them to do the simple daily maintenance tasks, autonomous maintenance aim was/is to:

  • ensure equipment is constantly well-cleaned and lubricated
  • maintenance experts’ time is freed for higher-level tasks
  • emergent issues are noticed and identified before they become failures
  • enrich the job of production operators.

if operators showed interest and demonstrated capacities, they could be trained further and assist maintenance experts for more complex maintenance tasks and even take part in repairs and overhauls.

In a industry 4.0 environment, the content of this ‘autonomous maintenance’ pillar of TPM must be adapted to the new technologies. It could encompass data management, using the digital twin, simulate… and require digital literacy.

In a industry 4.0 environment the role of operators as machine feeder, unloader and tool fitter may be marginalized thanks to automation. The jobs for production operators as we knew them may diminish and new jobs will be created requiring different skills and abilities, but not as many.

I could imagine recycling some of the former production operators into ‘autonomous maintenance’ operators, but my guestimate is that one operator could take care of 5 to 20 3D printers. The operator-to-equipment rate compared to traditional manufacturing will surely shrink. Besides, everyone will not show the necessary capacity to evolve.

Can Industry 4.0 rejuvenate Total Productive Maintenance?

As for the autonomous maintenance my guess is that chances are good, even so it may need to be updated in a new 2.0 version fitting the new technical environment.

Focus will be on equipment because of the investment, because of managers in love with tech, because equipment performance will be the main driver for (a production) company’s performance, and for probably more reasons.

For the other 7 traditional pillars I am not sure. You’re welcome to share your own thoughts.

About the author, Chris HOHMANN

About the author, Chris HOHMANN

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Industry 4.0 promoter’s flaw of logic and Categories of Legitimate Reservation

Promoters of any solution or change agents of are usually in love with the object of their promotion. Love is said to be blind and oblivious of any negative aspect of the loved thing. That is why so often promoters of change highlight all the benefits of the change, regardless of any Undesirable side Effects for the people they try to convince to change. They usually also complain about resistance to change when skeptic listeners do not show enthusiasm for the promoted brilliant solution.

But promoters may also forget to adapt their communication to the targeted audience. They may know well their subject and cut corners, leaving the audience with doubts and questions about a logic they can’t completely follow.

In this post I will address:

For that I pick two sentences from an Industry 4.0 promoter’s blog post which does not seem logically sound.

The statement

“Brave companies who adopt new approaches (e.i. Industry 4.0) and adapt how they manufacture and run their businesses will be rewarded with success. While those who drag their feet and avoid risk will get left behind.”

There is no further explanation in the blog to backup these two sentences.

The first sentence, rephrased in logical cause-and-relationship reads: “if companies adopt new approaches (e.i. Industry 4.0) AND if companies adapt how they manufacture and run their businesses THEN companies will be rewarded by success.”

The AND here suggest that the two conditions must be fulfilled simultaneously in order to cause the success.

Necessity-based logic versus sufficiency-based logic

The statement is made with sufficiency-based logic, because it suggest that the adoption of new approaches and adaptation are sufficient to cause the companies to be successful.

Sufficiency is base on “if…then” or cause-and-effect relationship.

If the article was about listing all the conditions necessary to make the companies successful, it would have been necessity-based logic. In this case the relationship would have been: “in order to… the companies must…”.

The logical structure that Logical Thinking Process aware people “see” in the statement is either a Communication Current Reality Tree or a Future Reality Tree.

To learn more about necessity-based logic versus sufficiency-based logic, check my post: Goal Tree Chronicles – Enablers vs.triggers

Reservations

1 – Clarity

The first reservation about this statement is a clarity reservation about the meaning of “success”. What is “success”? How can we measure it? How can we know whether the company is “successful” or not?

Unfortunately there is no way to ask the author for clarification. One could understand that deployment of industry 4.0 technologie(s) together with adaptation of the work procedures is a success. A project manager in charge of such a program would surely agree about this definition of success.

The CEO and the board are probably looking for more than having the latest technologies installed, even it probably helps the image of the company to have a nice techno-showcase. In their view, success is more likely increase of sales, profit and market share. Let’s assume this one is meant by “success”.

We could go on and challenge the meaning of “new approaches”, “industry 4.0” or even what is exactly meant by “how they manufacture”. In case someone really need clarification, the question could be raised, otherwise let’s not go for unnecessary wordsmithing.

2 – Entity existence

An entity in the Logical Thinking Process parlance is a statement that conveys an idea. An entity is also the logical box holding the statement in the various logic trees.

An entity must only convey a single idea, therefore when building a logic tree on this statement we must have 3 entities combining their effects to produce one outcome: the success of the companies (read figure from bottom to top).

3 – Causality existence

Causality existence is checking the existence of the causal connection between entities.

“if companies adopt Industry 4.0 AND if companies adapt how they manufacture AND if companies adapt how they run their businesses THEN companies will be rewarded by success.”

Does it exist? One example would be enough to demonstrate it exists, but, in absence of hard evidence, the likeliness of the causality existence must be evaluated. We assume it’s ok.

4 – Cause sufficiency

Are the 3 proposed causes sufficient alone to produce the effect “successful companies”? I would intuitively say no. There is a lot more necessary. We are here facing a typical “long arrow” which is a leap of logic from some causes directly to the outcome, ignoring intermediate steps and conditions in between.

This is typical when people discuss matters they know well because they don’t have to detail everything, they know what is missing and is implicit. But here it is about promoting something which is quite new (in 2017), relatively complicated and not very well known by laymen. Effort should be paid to elaborate on the message in order to favor buy-in.

5 – Additional cause

This check is looking for other causes that can independently produce the same effect. There are indeed other ways for companies to be successful than going for industry 4.0, but the statement suggests there is only one, as it warns: “those who drag their feet and avoid risk will get left behind.”

Conclusion

With these two last reservations we uncover the major flaw in the statement:

  • The proposed “logic” is not likely to be enough to produce the expected effect
  • There are other ways to be successful

From the audience point of view, the argumentation is weak. This is more likely to raise suspicion about the promoter’s expertise and trustworthiness, thus distrust and reservation than frantic enthusiasm about the proposed idea.

Such a weak argumentation can have devastating effects, making decision makers to turn their backs, refusing a good plan or a clever strategy which was ill-prepared and badly presented.

The Categories of Legitimate Reservation are 8 formal “rules” or “tests” used to check the logical soundness of a reasoning or an argumentation. They are part of the Logical Thinking Process corpus.


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Jim Womack’s hansei on where lean has failed

Lean leading figure Jim Womack posted a sincere and critical reflection (hansei) on where Lean has failed and why not to give up. I was impressed when reading it and it reinforced my respect and admiration for the author.

You can read the August 29th, 2017 post on planet lean (http://planet-lean.com/jim-womack-on-where-lean-has-failed-and-why-not-to-give-up)

>Lisez-moi en français

Jim Womack is someone to take seriously when he expresses himself about Lean, so when he posts an article titled “where lean has failed” it is probably not just a clickbait nor a questionable joke. Indeed, the critical reflection Jim shares is truly about failure from his point of view. And his point of view with regards to Lean is one that really matters.

Where lean has failed

The failure is, in Mr Womack’s opinion, manyfold:

  • It is the failure to get big organizations to transform themselves in a Lean way and have, at least, “another Toyota” emerging.
  • It is the failure to reverse offshoring, despite the rational proof that companies would be better off keeping operations close instead of trading labor costs for logistics and quality costs.
  • It is the failure to see disaffection among the workers and the growing acceptance of things as they are, without attempt to resist or change them in the Lean Community itself.

This hurts.

I am impressed by the courage to analyze and acknowledge that situation of someone who dedicated his life to promote Lean and share the knowledge. After all the enthusiasm, hype, hope and successes, this must be bitter.

Many people in Mr Womack’s position would deny the situation and keep going on, their ego not allowing them to acknowledge failure. Jim Womack not only has the courage to do it, but refuses to give up and want to avoid the “muda of denial about the situation”.

What I see from my narrower and European (mainly in France) perspective is consistent with Mr Womack’s analysis: the number of lean managers and continuous improvement champions soared in the last years but no company advertises or gets attention because of drastic improvement of its performances.

Furthermore, when called for assistance in companies, I am most of the time appalled by the (very) limited competences of the people in charge of Lean or operational excellence, a fact also reported by Karen Martin in a post on the Lean Edge https://www.theleanedge.org/256088-karen-martin-technical-proficiency-and-leadership-acumen-can-you-nail-the-problem-statement-first-time-right/

So yes, “doing Lean” is reduced to running small kaizen workshops here and there without consistency nor link to a strategic intent. It is merely about patching broken processes,solving local problems at best, or opportunistic muda hunting.

This keeps the additional layer of “Lean” bureaucracy busy and living easy with a lot of complacency about local qualitative results. Once a 5S workshop went through the first 3Ss, they’re done and feel “Lean” now. This is how Lean looks like too often.

No wonder the questions about “what’s next” or “is lean dead?” arise.

Considering Lean transformations, like many armchair generals giving strategic advice in hindsight, I would say that Jim Womack and people around him did well  addressing the diagonal of the 2×2 change matrix: promoting the “pot of gold”, metaphor for reward and benefits of the change, as well as warning about the “alligator”, symbol of the danger of the status quo. I remember well Jim recommending to have a burning platform or even create a crisis to get the change done.

This was the rationale promoting the change, the Lean transformation.

What could have been underestimated was the other, emotional diagonal of the matrix. Many of the decision makers are in love with their “mermaid”. By definition, a mermaid cannot leave the sea and therefore the decision makers stay put, close to the object of love and happy with the current situation. A happiness, they believe, they can enjoy ONLY in their current situation.

Maybe the decision makers are risk averse and see nothing else than the frightening perspective of the “crutches”, the metaphor for risks and big efforts. Indeed, many decision makers may jeopardize their actual position if they dare going for a disruptive transformation with unforeseeable results. Leading a Lean transformation requires leadership, courage, confidence and the necessary freedom to act.

Why not to give up

Despite this bleak picture, Jim Womack is not ready to give up nor let “the muda of defeatism” get in his way. If no other Toyota is likely to emerge, other success stories can be reported. Successes may be experienced in and with start-ups for example.

Acknowledging the limits of the actual Lean promotion and Lean methods training ways, mainly through workshops and workbooks, Jim calls for “thinking hard about more effective ways to pass lean knowledge along to the next generation”.

The last paragraph of Jim Womack’s post sounds like a firm resolution “to rethink the (Lean community) tactics, stick to its purpose, and better understand the challenges preventing it from staying on course”.

I encourage everyone to read the original post as well as to have a look on the comments.

Personal conclusion

It is a sad read, but I can only agree. I empathize with Jim Womack and again, I am impressed by his courage and humility.

Even if Lean loses its shine, I still measure what it brought – and still brings – to me. I think that true Lean-understanding people, once “infected”, will not get away from Lean Thinking. I will continue to promote and use everything Lean at personal and professional level, wherever and whenever it’s meaningful, which should be pretty often. Fashionable or not.

My personal belief is that Lean (Thinking) will keep lingering in operations, but the emphasis will probably shift upstreams to Product and Process Development. I also think that the irresistible wave of digitalization and all the news techs around smart factories will reshuffle the cards on how to plan, organize, drive and strive. All new opportunities to reinvent business and the philosophy, methods and tools that must come with.

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The fallacy of maturity assessments

Maturity assessments are a kind of qualitative audit during which the current “maturity” of an organization is compared to a maturity reference model and ranked accordingly to its score.

As explained in the wikipedia article about maturity model (https://en.wikipedia.org/wiki/Maturity_model), the implementation is either top-down or bottom-up, but from my experience it is mostly top-down. The desired maturity score is set by the corporate top management in its desire to bring the organization to a minimum level of maturity about… Lean, Supply Chain practices, project management, digital… you name it.

The maturity assessment is usually quite simple: a questionnaire guides the assessment, each maturity level being characterized by a set of requirements. It is close to an audit.

The outcome of such an assessment is usually a graphic summary displaying the maturity profile or a radar chart, comments about the weak points / poor scores and maybe some recommendation for improvement.

The gap between the current maturity and the desired maturity state is to then to be closed by an action plan or by following a prescribed roadmap.

What’s wrong with maturity models/assessments?

1 – The fallacy of maturity assessments

A maturity assessment would be ok if it would be considered for what it is: a maturity assessment. But the one-dimensional assessment is too often used as a two-dimensional tool by assuming that the level of operational performance is positively correlated to maturity.

In other words: the better the maturity, the better the operational performance.

Indeed, such a correlation can frequently be found, but correlation isn’t causation, which means that there is no mechanical nor systematic link between the maturity and performance level.

Even so the high level of maturity matches a high level of performance and vice-versa, there is no guarantee that performance will raise if maturity is raised.

Furthermore, studies have shown that there are exceptions and organizations with low maturity perform better than some high maturity ones. You may be interested reading my post How lean are you part 2, about Awareness / performance matrix about this subject.

Therefore the belief in the positive correlation between maturity and performance that makes it a kind of law is flawed or is nothing more than wishful thinking.

Many organizations boast about their high maturity, the number of kaizen events, number of workshops, number of colored belts, the number of training sessions or worker’s suggestions but there is nothing impressive to be noticed on the gemba.

Now I can understand why most managers and improvement champions like the sole maturity assessment:

  • it is much easier to do
  • the assessment items can be common to very different units with different activities
  • the general roadmap and global target are easy to set
  • maturity objectives are qualitative

On the other hand:

  • measuring overall performance that can be compared can be more tricky, especially in an organization with several different core businesses
  • it is annoying to admit that all efforts to raise maturity are not paying-off in terms of performance and painful to explain why

2 – The one-fits all maturity targets

Another problem with maturity assessment is that some corporations dictate a minimum maturity level regardless to local realities.

That’s how some subsidiaries doing well with regards to performance get bad maturity scores because they do not apply SMED (Single Minute Exchange of Die, an approach to reduce the changeover duration). The point is these subsidiaries have more or less continuous production processes with huge batch sizes that barely change. Why would they go for SMED when they don’t need it? The same case can be told with one-piece flow or heijunka (load levelling) enacted as a must do.

Others are scoring poor because they didn’t Value Stream Map (VSM) their processes. The fact is that those units had no problems a VSM could help to solve. The example list can go on and probably, dear reader, you have faced such situations yourself (leave your testimony in the comments..!)

3 – Doing it to be compliant, not because it makes sense

This third point is a corollary to the previous one. Because the objectives have been set at higher level and in order to be compliant, most unit manager will pay lip service to the dictated targets, get the scores good enough and be left alone once the assessment is done.

The local staff recognizes the nonsense of the demanded score, yet goes for the least effort and instead of fighting against the extra unnecessary work, chose to display what top management wants.

This the typical “tell me how you’re measured, I tell you how you behave” syndrome inducing counterproductive behaviors or practices.

While top management will be pleased with the scores enforcing its flawed belief, the local units managers did not embrace at all the practices, tools or methods prescribed. They only camouflaged the reality.

Wrapping up

Maturity assessment are not a bad thing per se, but their practicality and simplicity are often misused to assess more than just maturity (or awareness). This is most often misleading because of the false underlying assumptions and promoting wrong behaviors and practices.


PS: You may be interested to read Michel Baudin’s comments on his own blog about this post: http://michelbaudin.com/2017/08/22/the-fallacy-of-maturity-assessments-chris-hohmann/


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Is Lean dead?

Is Lean dead? is the provocative title of a podcast hosted by Mark Graban with guest Karen Martin. The question, the podcast description says, is “easy to discuss, but hard to answer”.

The reason Karen proposed to discuss this question is because of hearing and reading about “what’s next”, “is it time for something new?” and what seems to be a waiting for a “post-Lean” world.

There is an invitation to share thoughts about this, but instead of leaving a comment on Mark’s podcast-related post, I add my two cents here. I hope Mark and Karen won’t mind this piggybacking.

Some takeaways from the podcast

From 4:35 Karen frames the topic and from 6:05 she shares her thoughts, especially two reasons for the “what’s next?” question (rephrased by me):

  1. people don’t get great results from Lean and quit too early with the conclusion Lean doesn’t work
  2. the attention span, especially in business, is (very) short

By 19:45, Karen reminds the listeners that Lean is made of layers of quite “meaty” subjects and is made for constant learners. Yet Lean teaching programs cannot (?) do not go very deep into Lean beyond chosen tools. So it’s up to everyone to go for a never-ending learning journey. At 43:00 listeners get the wrap-up.

My thoughts on this

Ironically, the introduction of new methods and tools was once mocked as “the flavor of the month” with the preconceived belief that it won’t last. Now that Lean has demonstrated a longer lifespan than other management ways, it seems to be precisely too lasting in a time where  fashions come and go very quickly.

The methodologies life cycle

However long Lean is around now, it follows the same life cycle curve than others, made of a slow takeoff as long as long as no organization publicized extraordinary achievements with this approach or no book draw wider attention to it. Once the word spread, the methodology gets hype and many organizations and consultants go for it. After the hype spike, there is a loss of interest and a final plateau. In this later stage the methodology does not totally disappear but does not get the attention it once had.

In that regard, the methodologies life cycles look very much like Gartner’s hype cycle for technologies.

I started my career in the midst of Total Quality Management (TQM) hype, in the mid-1980s. Who aged less than 40 knows about TQM? It is still around in some form, like in the various ISO standards, but it does not get the excitement of the all the problem solving tools deployment TQM once had.

Similarly what happened to Total Productive Maintenance (TPM)? Parts of it is embedded in Lean and some companies keep TPM alive, but I barely hear anything about it anymore.

My friend and mentor Bill Dettmer witnessed the same phenomenon with Theory of Constraints. Not totally gone now, but barely known and not likely to get its fame back again. Six Sigma is said to be dead or is reduced to SIPOCs and DMAIC.

So maybe time has come for Lean to lose attention of the mass and remain a thing for true believers?

Quick wins and newcomers

The impatience about the post-Lean next thing can also come from the younger staff that did not experience the first attempts with Lean, when the organization was so inefficient that almost any structured tool deployment and kaizen events demonstrated significant quick wins. After a while and continuous sustained efforts, the remaining pockets of gains are few and hard/long to address. Newcomers experience Lean from hearsay or don’t notice anything about Lean because they are amidst of a more or less Lean environment. It’s just part of the scenery and nothing to get excited about.

Furthermore, many people have been repeatedly exposed to Lean methods and tools, have been involved in Lean workshops, kaizen events, sketched Value Stream Maps and identified wastes, sorted out, cleaned up and rearranged stuff 5S style. They share the feeling of being Lean, of being done with Lean.

The startup praise of failing fast and pivoting

My last thought about the possible fading of Lean is the growing influence of the startup movement and the praise of failing fast and pivoting. It keeps surprising me that failure can be praised, even so I understand the value of learning from failures. One Undesirable side Effect though may be the spreading of the belief that anything that does not work quickly is a failure – ok, we learned something – and it’s time to move on with something else.

Pivoting is getting away from an original idea that does not prove good fast enough and go for something else that can be 90 or 180 degrees from the original intent. What can make sense in a startup venture, stopping the experiment before the scarce resources are burnt up, may not be the suitable option where long commitment to cultural change and constant learning is required.

With allusion to Kahneman’s work, I think that for business there is a fast way and a slow one, and Lean is definitely a slow one.

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Jargon doesn’t make an expert

In a blog post I read the warning about candidates exaggerating their insight by using lot of jargon. It was about Lean Management. The author stated that when recruiting, mastering enough Lean vocabulary is important in order to catch candidates exaggerating their insight by using jargon. Any talented Lean manager can explain the same concepts without Lean management specific language, the author wrote, but inexperienced or unskillful interviewees may lean (pun intended?) on “concept-dropping.

Even so I agree with everything above, the heavy use of peculiar lingo is not specific to Lean and Lean “experts” are not even the worst.

>Lisez-moi en français

I remember a recent (July 2017) conference in which a speaker delivered a pretty convincing presentation about a somewhat uncommon approach we are familiar of. One of my colleagues, intrigued, went to see the speaker and asked him a question on a specific aspect only a true experienced expert could answer. This very question reminded the speaker of an important call he had to make and he vanished. He was indeed only “concept-dropping”.

Nothing really new. Molière, our most famous (French) playwright and actor (1622 – 1673) used to ridicule the physicians of his time in several of his works. Those experts were depicted as pompous and disputing in fantasy latin about this or that just to impress their audience or others fellow “experts” with fake erudition, while their patients usually were bleeding away.

In French slang, a “faisan” (pheasant) is a crook, a good-looking but stupid pretender. I used to hear fake experts being called “faisans”. Nice feathers, but that’s barely all.

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