Problem solving: what was the last change?

This post could be a sequel of “Yeah, problem solving” in which I used Peter Senge’s quote: “Today’s problems come from yesterday’s solutions”.

Quite often people we consultants meet are puzzled by a problem they can’t understand:

  • a reliable process or machine suddenly seems out of control,
  • steady performance dropped unexpectedly and with no apparent reason,
  • sudden quality issues with trusted supplies,
  • etc.

Our experience lead us to investigate the last change made, precisely because of the “wisdom” of Peter Senge’s quote: chances are that a modification (fixing a problem) led to unexpected Undesirable Effects and causing new a problem to appear.

Of course, the modification to look for is seldom the worried person’s ones, which he/she would most probably remember and perceive the possible cause-to-effect relationship.

No, the modification more likely happened outside the span of control and without the knowledge of the impacted people.

A modification leading to a problem in a lengthy process can happen far away (both in process steps and location) from the point the problem appears, letting the people perplexed about this reliable process now out of control.

Purchasing and procurement choices are unfortunately often the unintentional culprits, buying a slightly different grade of material, changing a supplier or accepting a low quality batch with the best intentions: cut costs or ensure timely deliveries.

When facing a puzzling problem the investigation should follow “the last modification path”.

This isn’t always easy though. The Undesirable Effects brought up by the change may be minimized or even neutralized for a while, long enough for everybody to forget about the nature of the change, when it happened and its consequences then.

That’s precisely why some industries with strong safety and regulatory constraints like aeronautics or pharmaceutical have to be cautious about any modification (needs approval after thorough risk assessment) and capture every information about virtually anything (dates, manufacturing conditions, persons in charge, certificates…), in case an investigation must find the root causes of a deviation (or worse), long time after the triggering action occurred.

When the problem cannot longer be neutralized by the former forgotten fix, it looks like a new problem.

Searching for the last change is often a good guess, yet not always leading to the root cause. Keep in mind that some modification correlate nicely with the apparition of the problem, but correlation isn’t causation.

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Yeah, problem solving

Most people love to solve problems and feel the satisfaction of getting rid of some nasty tricky problem. It’s an outdated but still lasting belief that management is about problem solving. Problem solving turned in some cases into the managers’ and engineers’ holly mission and in some minds, the more problems the manager/engineer solves, the better manager/engineer he/she is. This kind of problem solving can be addictive, hence the Arsonist Fireman Syndrome.

On the other hand, thanks to Lean Management, enlightened managers understand it is crucial to refrain from solving problems and develop their subordinates’ ability to solve problems themselves instead.

Note that all the above is about problem solving, not problem avoidance or problem prevention. And if today’s problems come from yesterday’s solutions, as stated in Peter Senge’s “The 11 Laws of the Fifth Discipline”, in a world requiring increasingly fast decisions (read solutions), we’ll never run out of new problems to solve.

So what’s wrong with problem solving?

There are at least 2 major issues with actual problem solving practices.

1. Quick fixes

Solutions to problems are most often quick fixes made of the first “best” idea that popped up. Problem solving is not very often a robust and standardized process, systematically rolled out. In fact formal problem solving processes seldom exist even if everybody is claiming solving problems.

If known, simple structured approaches like PDCA are disregarded and ignored, pretending the situation requires quick reaction and not “unnecessary paperwork!”

Often, the problem seem to be fixed, giving credit to the firefighters and reinforcing their belief in their “way” of handling.

It is not really surprising that the same problem keeps showing up as the fixes did not eradicate the problem’s root cause, and the problem itself was never really studied, hence understood.

2. No risk assessment / risk mitigation

If formal and structured processes to tackle problems are seldom, the solutions’ risk assessment is even more seldom. And if the rush to quick fixes leaves no time for properly analyzing the possible problem root causes, no need to mention non-existing attempts to figure out the possible risks these quick fixes bring with them.

Chances are that the ill-prepared and hastily put in place solutions generate unexpected Undesirable Effects. What may fix one problem may well cause one or several others to appear.

That’s how quick and dirty troubleshooting usually come at the expense of later longer efforts to cope with a situation that possibly grew worse, and how Peter Senge’s quote: “Today’s problems come from yesterday’s solutions” makes the most sense.

What solutions?

  • Choose yourself a structured problem solving approach, there are several available. Try it and if proven suitable for your purpose make it your standard way of approaching a problem.
  • Make sure the implemented solutions will really kill the problem by measuring on a long time horizon if the trouble has disappeared for good. The Quality Operating System is perfect for that.
  • Explore the Logical Thinking Process, the sole complex problem solving methodology I know which includes a systematic “Negative Branch” check to avoid or mitigate Undesirable Effects as by-products of the implemented solution.

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The benefits of failing fast

In a recent conversation with a friend of mine, CEO of a small Consulting firm, he explained me how he energized his small company using Lean Startup principles and tools.

Especially when it comes to answer calls for tender or a request for a proposal, Frederic (his name) has gotten pickier.

My test, he said, is to ask when I can come and present my proposal. If the person asks to receive it by e-mail or tries to escape the presentation, chances are there is no genuine interest. I can save myself precious time for something doomed from the beginning. I won’t inflict pain to myself starting to answer. Fail fast, save time.”

Being still somewhat old school, educated in a system and at a time when failing was not fashionable, I realized that “failing fast” is not only about physical widgets or apps not working (even if called Minimum Viable Products) or services nobody care about except their creators, but also about the more mundane and lukewarm requests from prospects.

I recalled how many proposals I wrote myself, for which I got stupid excuses to turn them down, if any answer ever came. I could have failed fast and saved myself a lot of time!

Indeed, some prospects are asking for proposals to gather some intelligence on a subject, fuel their own creativity, get a free guideline to roll out the proposed program by themselves or just to please the purchasing department with more than their favorite proposal because the procedure requires at least three.

In a time of harsh competition it’s sometimes hard to discard an opportunity for business, but here one has to remember that every inquiry and call for tender is not a true opportunity.

And failing fast has real benefits, it saves time!

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The Executive Guide to Breakthrough Project Management – Book Review

The Executive Guide to Breakthrough Project Management is about combining Critical Chain Project Management and “alliancing” or collaborative contracting for a win-win efficient way to manage huge (or small) construction projects.

Soon when reading the guide, it becomes obvious that what the authors describe as efficient in construction and capex projects can be used in many other trades.

Watch the author’s conference

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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