When enough is… enough

cho-in-azoneThis is a behavior I’ve noticed quite often in food industry, in chemical or pharmaceutical plants: cleaning and sanitation processes (mainly their duration) are extended beyond the standard procedures at the expense of costs and production capacity.

Fear of harming

In the regulatory-constraint industries like food, chemical or pharma, people on shopfloor are trained and qualified to perform cleaning and sanitation operations. They follow procedures and work instructions, based on standards.

They usually also have frequent training about the importance of sanitation or sterilization and the possible consequences if badly done. Working in food, healthcare or pharma is embracing the sacred mission to bring something good, to cure or relieve customers and/or patients and do everything to prevent hurting them in any way.

They are also reminded what consequences for the organization in case of problem beyond failing to: losing the customers’/patients trust, losing the licence to produce, being sued, being exposed to scandals…scary enough for shopfloor people to take things seriously.

Yet the people on shopfloor seldom have the scientific background to fully understand what is required for good sanitation or sterilization, when doing more is useless or even counterproductive. They also are often left on their own, without expert supervisors to reassure them, answer possible question or take decisions in case of doubt.

Furthermore, the results of sanitation/sterilization is most often only known after a sample of rinsing water or the swabbing of the tool/equipment has been analyzed by some remote lab.

Fearing to harm the organization, or worse the customers / patients or possibly to have to go over the whole lengthy sanitation process again if it is not satisfactory, the sanitation is performed longer than procedures require it. This is base on the belief the more the better.

This seemingly logical and well-intentioned assumption is never challenged, leading to waste detergents, acids, water… and time, simply because over-sanitation is not noticed by management.

Changeovers are even longer

Changeovers in such environments can be long and painstaking due to regulatory constraints and all the paperwork associated. Ignoring the over-sanitation habits can extend the changeover duration even more.

Besides adding costs for no additional value, the additional time spent on sanitation may be needed on critical equipment (bottlenecks) and the time lost will not only never be recovered but the true cost is to be counted in minutes of turnover. And this one can be skyrocketing!

Conclusion

When looking for additional productive capacity or a way to get more out of the current process, check the changeovers’ content and take a closer look on sanitation.

Give the shopfloor personnel clear indication when enough is enough, without risk to harm anybody nor to endanger quality. If necessary, have a real qualified subject matter expert attending these critical phases, ready to support the team and answer any question.

Not only will it take some concerns off the team, but may be a great payback in terms of additional yield.


Feel free to share your thoughts and experience in the comments and share the post if you liked it.

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The man-machine system performance

When looking for performance improvement of a man-machine system, too often management puts emphasis onto machine or technology at large, ignoring the fact that humans associated with equipment, machines or technology form an interrelated system and consequently humans are the discriminating factor.

The fallacy of trusting the latest technology

There is a strong belief, backed up by vendor’s marketing, that the latest state-of-the-art high-tech equipment will bring a breakthrough in performance. This is welcome news for executives struggling to keep their organization up with competition and seeking a significant performance uplift.

Production managers, industrial engineers or system designers are big kids loving high-tech expensive toys, geeks of their own kind and dreaming to get the latest, biggest, fastest piece of equipment.

Once investment made, performance does not skyrocket though.

What happened?

Management blindness

Management ignored the human factor, i.e. people put in front or in charge of the new machine, the latest technology. An operator and his machine for instance are a system.

The overall performance of this system is determined by the human-machine pair, and guess what, the most variable and hardest to control is the human factor.

Unlike machines, humans have their moods, their worries, variable health and morale, private concerns and motivation issues. One day fine, the other day down.

Humans are not equal in competencies and skills. Some learn fast, some learn slow and some never really get it.

So what’s the point giving the latest top-notch technology to someone not competent or not motivated?

Yet this is most often what happens. Management assumes that the best of machines will make the difference, totally ignoring the influence of the people in charge.

The irresistible appeal of technology

Most decision makers and managers have some kind of hard-science background, got their degrees in engineering or business management. They were taught the robustness of math, the beauty of straightforward logic and to trust only facts and data.

When puzzled facing in real-life the highly variable and elusive nature of humans, they have a natural tendency to prefer hardware. This is something that can be put into equations and eventually controlled. This is what they are most familiar with or at least the most at ease with.

Humans are only trouble. No equation helps to understand their intrinsic drivers nor to reduce their variabilities. This is all about soft skills and psychological factors. Nothing for engineers and hard science-minded people.

Instead, they put a strong hope that the best and latest technology will trump the human factor, reduce it to a neglectable pain. But this never happens.

So again: what’s the point giving the latest top-notch technology to someone not competent or not motivated?

Leveraging performance

In order to improve a man-machine system, it is key to first have a look on the human factor, the most important one. Make sure competency is granted. If someone lacks the necessary competencies, performance is nothing than a matter of luck.

Beware of incompetent but highly motivated people though. In their desire to do well, they may have unknowingly potentially dangerous behaviours and/or take bad decisions. These motivated ones are likely to learn, do thing right but need training and guidance.

Not motivated incompetents are not likely to take any initiatives. They are the manager’s pain and burden and giving them better, faster machines won’t help. What’s worse with not motivated incompetents is passive aggressive behaviors that can lead to potentially dangerous situations as well.

Competent but not motivated people need and probably deserve management’s attention in order to get them into the winning quadrant of the competency-motivation matrix, aka skill-will matrix (top right).

There are the competent and motivated people who do their job effectively, often efficiently and without bothering anybody.

Competent Find a driver or a whip No worries
Incompetent Long way to go… Potentially dangerous good will
Not motivated Motivated

Competency-motivation matrix from a supervisor perspective

It is with these competent and motivated people that the limits of machines or technology can be found, as they will use them properly and purposely. Even when these performance limits are reached, it’s not certain that better planning and/or better organization cannot get more performance out of the system.

Think about quick changeovers and all capacity that can be regained applying SMED methodology, or rethinking maintenance in Total Productive Maintenance (TPM) style.

Wrapping up

When facing the challenge for improving performance, considering the way operations are done should be the first step. The second is to remember than investing in people is usually cheaper and more effective than investing in technology in first place, because a well utilized outdated machine will have better yield and be way cheaper than a poorly utilized state-of-the-art new one.

“Unfortunately” for tech-lovers who would prefer new “toys”, this investment in humans has to be a substantial part of their manager’s daily routine.


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What data for changeover monitoring and improvement?

CapacityMaximizing the exploitation of critical Capacity Constraint Resources (CCRs), so called bottlenecks, is crucial for maximizing revenue. Changeovers usually have a significant impact on productive capacity, reducing it with every new change made on those resources that already have too few of it.

Yet changeovers are a necessary evil, and the trend is going for more frequent, shorter production runs of different products, so called high mix / low volume. Consequently, changeovers must be kept as short as possible in order to avoid wasting the precious limited productive capacity of Capacity Constrained Resources (CCRs).

Monitoring changeover durations at bottlenecks is a means to:

  • reinforce management’s attention to the appropriate CCR management
  • analyze current ways of changing over
  • improving and reducing changeovers duration

Management’s obsession should be about maximizing Throughput of the constraints.

To learn more about this, read my post “If making money is your Goal, Throughput is your obsession”.

What data for changeover monitoring?

When starting to have a closer look at how capacity is lost during changeovers, the question is: besides direct periodic observations, what data are necessary and meaningful for such monitoring?

Before rushing into a data collecting craze, here are a few things to take into account:

In the era of big data, it is admitted now that one never has enough data. Yet data must be collected somewhere and possibly by someone. The pitfall here is to overburden operators with data collection at the expense of their normal tasks.

I remember a workshop manager so passionate with data analysis that he had his teams spent more time collecting data than to run their business.

Chances are that your data collection will be manual, by people on shop floor. Keep it as simple and as short as possible.

This a matter of respect for people and a way to insure data capture will be done properly and consistently. The more complicated and boring the chore, the more chances people will find ways to escape it.

Take time to think about the future use of data, which will give you hints about the kind of information you need to collect.

Don’t go for collecting everything. Essential fews are better than trivial many!

Be smart: don’t ask for data that can be computed from other data, e.g. the day of the week can be computed from the date, no need to capture it.

Example of data (collected and computed)

  • Line or machine number
  • Date (computed)
  • Week number (computed)
  • Changeover starting date and hour
  • Changeover ending date and hour
  • Changeover duration (computed)
  • Changeover type
  • Shift (team) id.

Explain why you need these data, what for and how long presumably you will ask for data capture. Make yourself a note to give data collectors regular feedback in order to keep people interested or at least informed about the use of the data.

Data relative to resources with significant excess productive capacity can be ignored for the sake of simplicity and avoid overburdening data collectors. Yet chances are that some day you’ll regret not having captured those data as well, and soon enough. Make your own mind about this.

Monitoring: what kind of surveys and analyses?

There are roughly two types of analyses you should be looking for: trends and correlations. Trends are timely evolutions and correlations are patterns involving several parameters.

Trends

One key trend to follow-up is changeover duration over time.

Monitoring by itself usually leads to some improvement, as nobody wants to take blame for poor performance i.e. excessive duration. As frequently things tend to improve spontaneously as soon as measurement is put in place, I use to say measurement is the first improvement step.

The first measurements set the crime scene, or original benchmark if you will. Progress will be appraised by comparing actual data against the original ones, and later the reference will shift to the best sustained performance.

In order to compare meaningful data, make sure the data sets are comparable. For instance certain changeovers may require additional specific tasks and operations. You may therefore have to define categories of changeovers, like “simple”, “complex”, “light”, “heavy”, etc.

Over time the trendline must show a steady decrease of changeover durations, as improvement efforts pay off. The trendline should fall quickly, then slow down and finally reach a plateau* as a result of improvements being increasingly difficult (and costly) to achieve, until a breakthrough opens new perspectives: a new tool, simplified tightenings, another organisation…

Changeover duration

*See my post Improving 50% is easy, improving 5% is difficult

>Consider SMED techniques to recover capacity

Correlations

Looking for correlations is looking for some patterns. Here are some examples of what to check:

Is there a more favorable or unfavorable day of the week? If yes, understanding the cause(s) behind this good or poor performance can lead to a solution to improve everyday performance.

Does one team outperform underperform? Is one team especially (un)successful? The successful team may have better practices than the lower performing ones. Can those be shared and standardized?

For instance if one team consistently outperforms, it could be this team found a way to better organize and control the changeover.

If it is the case, this good practice should be shared or even become the standard as it proved more efficient.

I happen to see the performance data from a night shift in a pharma plant being significantly better than the day shifts. Fewer disturbances during the night was the alleged cause.

Be critical: an outstanding team may “cut corners” to save time. Make sure that all mandatory operations are executed. Bad habits or bad practices should be eradicated.

Conversely, poor performing teams may need to be retrained and/or need coaching.

Is one type of changeover more difficult to master? Search for causes and influencing factors. Some engineering may be required to help improving.

These are only some examples of patterns that can be checked. Take time to consider what factor can have some influence on changeover ease and speed, than check how to test it with data and how to collect these data.

Note that correlation is not causation. When finding a pattern, check in depth to validate or invalidate your assumptions!

Speak with data

All the data collection and analysing is meant to allow you and your teams to speak with data, conduct experiments in a scientific way and ultimately base your decisions on facts, not beliefs or vague intuitions.


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Why No One Talks About TPM Anymore?

Total Productive Maintenance (TPM) was a big thing in the late 1980s, got lot of attention, tried to go from “maintenance” to “management” and finally faded out into oblivion.

This analysis is my own, you may respond in comments.

Total Productive Maintenance (TPM) originated in Japan with Nippondenso in the 1960s and is an evolution from Preventive Maintenance principles introduces to Japan from the USA.

TPM grow popular in the west with other “Japanese methods” in the 1980s when Toyota Production System (TPS) was not known nor the word “Lean” used for manufacturing.

TPM in a nutshell

TPM proposed a framework of 8 pillars aiming at getting the most out of lines, machines and equipment especially by reducing machine downtime and increasing machine availability. The 8 pillars are:

  • Autonomous Maintenance
  • Planned Maintenance
  • Quality Maintenance
  • Focused Improvement
  • Early Equipment Maintenance
  • Education and Training
  • Health, Safety & Environment
  • TPM in Office

Their naming and order (may) vary according to sources. “Six big losses” were identified as obstacles to better machine effectiveness:

  1. Breakdown losses
  2. Setup and adjustment losses
  3. Idling and minor stoppage losses
  4. Speed losses
  5. Quality defects and rework losses
  6. Startup / yield losses

These six losses’ measurement were combined into a single KPI: Overall Equipment Effectiveness (OEE), still very popular and widespread in industry.

TPM was striving to improve OEE by developing the personnel’s maturity about the 8 pillars and reducing the 6 losses.

Early years till today

TPM brought tremendous improvements in operations and work conditions. Despite the machine-orientation TPM had also influence on operations management and at some point was supposed to translate into broader application, attempting to go Total Productive Management.

Alas, TPM was strongly machine shop and shopfloor connoted and never got much attention outside of these playgrounds. Furthermore, Lean became highly fashionable and easier to transpose in any activity, thus got all attention.

In my humble opinion TPM was bound to fail from the moment it was presented as a maturity-driven approach to improvement, requiring organizations to go through a multiyear program, step by step implementing every pillar. The pitch was that eventually performance will raise once personnel is trained and gets experienced with TPM. After some years of continuous effort, the organization will be mature enough to apply for one of the PM awards awarded by the Japan Institute of Plant Maintenance (JIPM) or local representative body.

Of course, the journey toward maturity would require consultants’ support, making it a long, costly and still risky one. With the competitive challenges getting tougher, few CEOs would commit to such a slow approach with questionable ROI, very much machine-effectiveness oriented.

Nowadays OEE, quick changeover and setup techniques like Single Minute Exchange of Die (SMED) are seen as part of the Lean Body of Knowledge and TPM very seldom mentioned.


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Critical Chain Project Management alone is not enough

Critical Chain Project Management (CCPM) alone is not enough to drastically reduce a project’s duration and improve the development process efficiency.

CCPM is a proven Project Management approach to ensure a project, any project, will meet its finishing date without compromising quality nor any of the requirements, and even though CCPM can lead to terminate projects earlier, CCPM alone will not squeeze out all improvement potential still hidden in the development process.

What CCPM does well is reconsider in a very smart way the project protection against delaying. Individual protective margins will be confiscated and mutualized in a project buffer, allowing everyone to benefit from this shared and common protection.

There is a bit more than this protective project buffer, but for the sake of simplicity let us just be that… simple.

The visual progress monitoring with a Fever Chart will provide early warning if the project completion date may be at risk and help spot where the trouble is.

Fever Chart

Fever Chart in a nutshell: x axis = project completion rate, y axis = protective buffer burn rate. Green zone = all ok, don’t worry, Amber zone = watch out, the project is drifting and finishing date may be jeopardized. Red zone = alert, project likely to be delayed if no action bring the plot into Amber and preferably Green zone.

After a while, with the proof that all projects can finish without burning up all the protective buffer, meaning ahead of estimated finish date, this arbitrary margin confiscation can be refined and some tasks durations trimmed down while fixing some of the common flaws in the process, like incomplete Work Breakdown Structures, poor linkage between tasks, ill-defined contents or missing requirements.

When done, the projects may be shorter because of lesser of the original protective margins and the other fixes, but the tasks themselves are seldom challenged about their value.

For instance, many of the project’s gate reviews have been set to monitor progress and give confidence to management. They were countermeasures to the drifts and tunnel effects, the period where management is blind about the progress, but with the early warning and easy visual monitoring through the Fever Chart, and more agility in the process, many of these reviews are now useless.

Thus, the time to prepare the documents, KPIs, presentations and attend meetings can be saved for value-creating activities or simply eliminated.

Other tasks may clutter the project, like legacies of fixes of older issues, long obsolete but still kept as the project template still carry them over. Evolution in technologies, unnecessary or suppressed downstream process steps, never fed back may also let unnecessary tasks in the project.

This is where a Lean Thinking approach completes CCPM, challenging the Added-Value of each task, questioning the resources required (both in qualification or competencies and in quantity) and even the linkage to preceding and following tasks.

When considering a development process, embracing Lean Engineering can even go further. Lean Engineering fosters learning and reuse of proven solutions. Libraries of such solutions and ready-for-use modules can save significant time, which can be reinvested in experimenting for the sake of further learning or to shorten projects and engage more development cycles with same resources and within the same time span.


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Performance improvement: simple things can earn big results

Silly things can cost a lot in terms of productivity and output.  In this video interview, Philip Marris  asks me about lessons learnt while helping a pharmaceutical plant to improve productivity and deliver drugs to patients faster.

It is about how simple actions solve those silly small problems and bring big results at literally no cost.


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Stuck with continuous improvement?

This post is a kind of post scriptum to “Improving  50% is easy, improving 5% is difficult” in which I described 3 stages of improvement and ended stuck with continuous improvement as the Return On Investment (ROI) in C stage was not worth going on.

Continuous Improvement

Now assume it is not possible to radically change the process (kaikaku), because for instance it has been approved by some authority (customer, regulatory…), being on the verge of C stage does not necessarily mean this is permanent.

If the limitation to improve further are skills or experience, the situation may change over time as trainings are delivered, experience is accumulated or necessary skills hired.

If the limitation is the cost of some solution, like changing material or buying some equipment, this too may change over time and become affordable / change the ROI, thus providing opportunities to improve further without changing everything.

What wasn’t possible or reasonable at some point may become possible and meaningful.

It is therefore important to revisit the assumptions and conclusions of the improvement workshops /projects periodically and check if some conditions have changed in a favorable manner.

This is also why, after a Value Stream Mapping and/or some diagnostic was done, designing the future state should first attempt to design a perfect process. This frees the designers from actual constraints and limitations and can lead to interesting solutions.

In a second step, the constraints and limitations are brought back in and the ideal solution trimmed down to what is possible given the limitations, e.g. state of industry vs. state of art, technological or economical limitations, limited know-how, etc.

But all brainstorming ideas and drafts of a perfect process/ideal state should be kept in a kind of think tank and periodically checked. It may happen that one of the ideas, impossible at a given moment can now be envisioned, thanks to some evolution.


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TOC, Lean and aviation MRO

In a previous post, “CCPM helps shorten aircrafts MRO”, I explained the benefits of Critical Chain Project Management (CCPM) for reducing the aircraft downtime during their mandatory and scheduled MRO.

If CCPM is great and helps a lot meeting the challenge, it will not squeeze out every potential improvement, thus time reduction, on its own.

As I explained in my post Critical Chain and Lean Engineering, a promising pair, “What CCPM per se does not is discriminate added-value tasks and non added value, the wasteful tasks listed in a project in a Lean thinking way.

Conversely, if wasteful tasks remain in the project network, chance are they will be scheduled and add their load (and duration) to the project.

That’s why in aviation MRO (as well as in other businesses), Critical Chain Project Management will not be used as a stand alone but in conjunction with other approaches, like Lean and Six Sigma.

Lean mainly will help to discriminate value-added from non value-added tasks, especially those on the Critical Chain, making them high priorities to optimize, reduce or eliminate.

We did not differently when we started with our client Embraer and while in their service center, I placed Philip Marris in front of the camcorders to present, in situ, two books related to TOC, Critical Chain and Lean in aviation MRO (aircraft Maintenance, Repair and Overhaul).


Note: Critical Chain Project Management is part of the Theory of Constraints Body of Knowledge, hence the title of this post where “TOC” is referring to CCPM.


Chris Hohmann

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CCPM helps shorten aircraft MRO

Facts

Aircrafts have to undergo periodic Maintenance, Repair and Overhaul (MRO). This is mandatory in order to insure the aircraft’s airworthiness and overall safety. During these inspections and repairs, the aircrafts are grounded.

For the owners and operators, the shorter the turnaround time*, the better. An aircraft is a huge investment and the ROI is only when it can be used in service.

*the time the aircraft is grounded, usually counted in weeks for longer in-depth inspections.

Yet aircraft operational availability is not only a question of Return On Investment, think about relief and the lives saved by medivacs or military forces brought closer to their spot during a crisis.

When an aircraft comes in for its scheduled maintenance, according to the type of inspection (ranging from Check A to Check D, according the depth and importance of inspection, the amount of time or usage…  (see Wikipedia)

The process is scheduled like a project as many tasks can’t be done prior to some others, e.g. access some hydraulic pipes before stripping the surrounding frame.

It is therefore common to use Project Management tools and techniques to organize, carry-out and monitor the whole process.

The challenge

Shortening the turnaround time is therefore a challenge for the service centers, not only to please and retain their customers, but also to attract new ones in order to grow their business and improve their profitability.

Of course the challenge is to be met while remaining compliant to the severe regulations and specific constraints, taking no chances with quality nor safety.

Furthermore, “findings” – unexpected defects of potential issues found once the aircraft is under inspection – or sudden customers requirements may add unscheduled workload.

In the traditional project management way, each task is estimated for its duration and a cautious (and generous) margin of time added. The service centers want to keep their committed due date, even if findings or any other random events (parts shortages, supplies problems…) arise.

It is therefore no surprise that major Checks ground an aircraft for weeks.

The new approach

It wasn’t long before some service centers spotted the improvement potential (turnaround time reduction) with Critical Chain Project Management (CCPM). Delta TechOps, Lufthansa Technik, US Navy and Air Force, French SiAé are cases I’m aware of.

Compared to traditional Critical Path Method (CPM), Critical Chain Project Management takes the resources’ limited capacities into account at once and has a completely different approach regarding margin of time. In short, all margins are shortened based on a statistical rationale and a share of it put into a global protective time buffer.

Chris Hohmann

CCPM provides also a simple but very effective visual indicator to monitor both project’s achievement and protective buffer consumption, thus indicating instantly when the project may be late. This robust and early warning allows project managers to focus on a very limited number of issues instead of trying to control every single task.

This allows also the mechanics to work in a quieter atmosphere, an important additional benefit in a trade that considers human stress as a major risk for quality.

CCPM has proven great for consistently meeting due dates and often shortening a whole project duration compared to its original estimations.

Our client testimony

I was fortunate to be involved in Embraer’s Business Jets Service Center’s project to reduce turnaround time in Paris (Le-Bourget) and pleased to produce a series of videos of their testimonies about their achievement.

In this video, Sébastien Albouy, Director of Embraer Executive Jets Services center in Paris Le Bourget executive airport, explains how Critical Chain Project Management helped to drastically shorten the aircraft turnaround time, thus increasing aircraft availability and the center’s capacity.


>Related: TOC, Lean and aviation MRO


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Improving  50% is easy, improving 5% is difficult

It is with this enigmatic sentence that one of my Japanese mentors introduced the growing difficulty with continuous improvement.

What it means is that at the beginning of an improvement program or when starting in a new area, the first and usually the easiest actions bring big improvement, hence the “easy” 50%.

This is also known as “reaping the low hanging fruits“, another metaphor for earning easy results with very reasonable effort.

Once these easy and quick wins are done, what is left to improve requires more effort, more time or more investment.

The improvement curve is therefore asymptotic and it is increasingly difficult and expensive to squeeze out the last improvement potential, hence the “difficulty to improve (the last) 5%”

The graph shows the 3 stages of improvement

Continuous ImprovementA: quick and easy, few actions, visible results, big leverage, usually a leap in performance. Excellent Return On Investment (ROI).

B: second stage in continuous improvement, more effort and investment is necessary, but the ROI is still worth it

C: “chasing the decimals” : huge efforts and investment are required to squeeze out the last potential. The ROI is not worth it.

At some point, the Return On Investment (ROI) is not worth going on. This means that improving further what exists and/or the way it has been done until now is no more meaningful. What is required is a breakthrough, a radical change.

This is where kaizen (continuous incremental improvement) must give way to kaikaku (radical change), or in other words: as the old process or usual way cannot be further reasonably improved, it must be totally reconsidered.

Yet in many cases this is the upper limit of improvement as the process cannot be changed. Too often redesigning the product or process is not possible:

  • Design has to be approved or the new product/process has to undergo lengthy and costly qualification (pharma, automotive, aerospace…)
  • Remaining life is not long enough to pay for
  • Facilities are not flexible, can’t be modified
  • The modification would break some contract

The continuous improvement is often limited by options and decision made in early design and development stages, a fact I discuss in >this post<


Related: Stuck with continuous improvement?


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