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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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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So many wasted data

In many organizations people capture a lot of data and… just ignore them, wasting their potential value.
The latest case, at the moment I write this post, is with an aircraft MRO company.

This post echoes a previous one: Trouble with manual data capture

Every aircraft undergoing MRO requires a lot of mandatory paperwork for the sake of traceability. The required information is either directly captured in an IT system, either written on paper and later input into the IT systems.

As this company wants to drastically reduce the duration of the aircrafts’ grounding for MRO and improve the reliability of its planning, the primary source of information to understand the causes of the problems is the data logbook.

I could easily figure out what kind of analysis to do and the correlation to look for, as adherence to planning for example.
Alas, as I was presented the database my enthusiasm quickly faded.

Some of the data supposed to be entered into the system simply wasn’t. Of course it happen to be the most interesting data for my analysis.

Work Breakdown is not always consistent across the portfolio, which makes comparisons challenging.
Mechanics would not always report their work on the appropriate work order. Thus work order lead time to workload correlation would be flawed.

It didn’t seem to worry management as much as it worried me, not because it could compromise my analysis but because the clients would not be charged the right amount (hours spent on an aircraft are billed).

According to data some aircrafts departed the MRO facility before they flew in. An indication of the lack of rigorous tracking as well as a lack in the software’s input trustworthiness checking.

And the list of flaws goes on.

A bit troublesome in a business boasting about safety by the way.

The pity is, as so often, that companies allocate resources to capture data and just ignore them. It would just require a little extra energy and rigor to exploit the data and use them to monitor, drive and improve their business.

Instead of that, just accumulating the data without exploitation is nothing more than wasting its value.

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Four good reasons to take a break if you are to remain efficient

Deep involvement in a project, problem solving or coaching really drains one’s energy. A periodic break is therefore mandatory in order to remain efficient. Here are four good reasons for it.

1. Recharge

Everyone needs a breather now and then. The tenser the situation, the more the break is needed.

Getting away some time from a project or an assignment helps recharging, gathering new energy and keeping fresh and motivated.

It does not have to be long but long enough to get the feeling of a real break. An extra day or two right before or immediately after a weekend for example can be good.

Taking a break doesn’t mean take holidays. Working on something else or seeing something else for a short period is usually enough.

2. Get rid of mental clutter

Taking a break is also an opportunity to get rid of mental clutter accumulated during the deep dive into the project or problem solving.

Often one just gets caught in a vicious circle, spinning around with a problem and not finding out.

Take a break.

When coming back, the brain is like reset and the mental cache emptied, ready to process new data or analyze differently.

3. Avoid complacency

Staying too long on the same subject may end up with complacency. After a while, abnormal conditions seem less shocking, ways are found to work around blockades rather than removing them and so on.

A breather helps to stay sharp, critical and to avoid complacency.

4. Look at the broader picture

Finally, stepping back simply helps to look at the broader picture. It’s easy to get drawn down into details and losing Sight of the Goal, of what is important.

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Measurement is the first improvement step

Chris HOHMANNIt’s a kind of magic and it works every time: setup some indicators to measure something and this very something will automatically start improving, without any other action.

Well, it looks a kind of magic but is a very human trait. People pay attention, stick to the rules and behave from the moment they can be spotted not doing it.

Indicators, dashboards, measurement systems are such means used to surface and analyze problems down to their root cause, including behaviors and deviations.

As nobody wants to be singled out as an ugly outlaw, those who did not always stick to the rules or behave, inclined to be messy or sloppy will straighten their behaviors and adjust to the rules.

If they don’t do it wholeheartedly, they do it to avoid (personal) problems.

People generally choose the easiest path; if sticking to the rules and behaving is “easier” than trying to get around, they’ll stick and behave.

Setting up some measurement means keeping an eye on something and as soon as it is known, behaviors change and things improve. I have witnessed this often.

  • Spare parts inventories are not accurate ? Setup measurement of inputs and outputs and by whom or at least when, the latter often being enough to focus on (a group of) individuals, and the inventory will instantly be kept better. Everybody will sign for the parts issued and won’t take more than really needed. Those still “forgetting” to book parts will soon be discovered and they’ll learn it’s faster and easier to book parts than to give explanations to the boss.
  • OEE (Overall Equipment Effectiveness) is low? Set Up a poster with OEE value per shift and the split of productivity losses and OEE will improve without even starting any other action. Most of the time, the first thing team members do (if applies) is stop taking more rest time than allowed. Thus having more run time, OEE improves.

Installing proper measurement is simple and yields quick results. A trick known by seasoned practitioners.


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Benchmarking is only trouble!

It happens periodically. When managers are faced with improvement challenge, they ask for benchmarks. Not because they’re eager to take it on competition but to check if by chance they’re not already better or at least good enough, thus escape the challenge.

And this is only the beginning with trouble about Benchmarking.


It is legitimate to measure one’s performance against a standard – and it makes sense to measure relatively to the best, not the average or the worst – and to define a strategy according to the gap.

The problem is once benchmark data are given, people generally get shocked by the amplitude of the gap and start to argue about the figures, content, calculation, conditions and a long list of other items in order to demonstrate the benchmark cannot be taken as a reference for them/ the organization.

All energy is wasted to reject the evidence instead of trying to fill the gap or even challenge to leap ahead of competition.

The second kind of common problem is that benchmark is often understood as a target. But being just as good as the best is limiting the ambition to being a follower, a me-too, a substitute. Is this really what the organization’s management wants?

Besides, all the efforts paid to catch up with the best can be ruined if the leader moves further ahead.

We can assume the leader has some reserves the challenger may not have anymore or never had first hand.

Benchmark is therefore only a reference, not a target. The organization’s target should go beyond the benchmark and the way to achieve it should (probably) be different than the leader’s.

Third problem is that finding relevant benchmarking data is sometimes difficult, impossible or out of reach.

Some people/organizations may grant access to some data but refuse to give any details, pretending they are proprietary.

Some people/organizations don’t hesitate to invent such data and generally do not share details which might uncover the trick.

The problem within this problem is that data may be real and accurate, but refusing to share details – what can be understandable for the sake of data protection – leads immediately to distrust:

  • are data trustworthy?
  • what methodology was used?
  • are data relevant, accurate?
  • and so on.

Fourth problem is that top management is generally pleased with the revealed potential. Closing the gap with the leader means more sales, more profit, more productivity, less waste, less costs, etc.

How-to is not top management’s concern, that’s why middle management is often puzzled with the objectives assigned after the “big” strategy consultants made their recommendations based on benchmarks. Squeeze out 25% more productivity or boost sales 20% is easier set (sic) than done.

Middle management tend to react as described in the beginning of this post, with shock and denial.

But here I think the problem is not about trustworthiness of data. Even so figures are just fantasy, the assigned objectives are to be taken for what they are: objectives.

The proper reaction of all the organization should therefore be to find a way to achieve them. It probably will require to think outside the box, be creative, search for breakthroughs.

Doing so will most probably help the organization to leap forward, maybe even beyond the goal.

Alas, the latter is seldom seen and it takes a lot of energy to explain this challenge to scared managers.

Therefore, from my experience, benchmarking is only trouble!

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How Lean are you? Part 4

This is the fourth post in the How Lean are you? series.

Measuring leanness

Author, Chris HOHMANN

In previous posts of this series I explained the advantage and necessity to assess leanness on two dimensions, one being primarily depicting how familiar with Lean tools and concepts people in the organization are, the second to measure tangible results: performance.

In part 2 we have seen that “awareness” is tricky when it means “knowledgeable”, as good Lean awareness can lead to no tangible outcome. To avoid this potential mismatching, I will refer from now to “maturity” which in my definition means familiarity not only by knowing but also using.

The matrix therefore looks like this:

The question is how to put a figure next to each dimension in order to plot the organization’s leanness?

Lean maturity

For assessing Lean maturity one way is to define what principles, methods and tools as well as activities routinely or at least frequently done would characterize a Lean organization?

Doing this for a European-wide study in the automotive industry, we defined no less than 21 items for this list, ranging from basic 5S to cyclical materials supplier in production (Milk run, water spider, etc.), from kaizen workshops to Value Stream Mapping or Visual Management and Poka-Yoke error proofing to production levelling (heijunka).

Each of these items had to be ticked in either categories: not implemented, pilot, halfway, extensively, completely, giving a grade on a five-levels scale.

The more items ticked in the category of widest coverage, the higher the maturity.

This way may not be perfect, in regard to frequency, consistency and so on. Furthermore, this being done via a questionnaire, the answers may of course be biased, but as explained in a previous post, the accurate benchmark the participants expected as feedback invited them to answer as faithfully as possible.

The final grade for Lean maturity has to be a single number, so the 21 grades were used to compute a Lean deployment index, what I refer to as maturity.

Lean performance

In order to appraise performance vs. Lean maturity, we selected 7 measurable Key Performance Indicators (KPIs) that are common to any company and likely to be positively correlated to lean maturity: Raw material inventory, finished goods inventory, customer’s satisfaction, customers’ claim rate, OEE on bottleneck and pace of A product production (known as EPEI or Every Part Every Interval, which is a marker for production levelling).

As for maturity, the different items making Lean performance were used to compute a Value Stream Performance Index, which I refer to as “performance”.

Plotting onto the matrix

Now that each participating unit can provide data to compute a pair of coordinates, it’s easy to display them in the matrix.

The plots, about 150 of them, showed a nice scatter diagram with a positive linear correlation between maturity and performance, proving that the more lean-mature an organization is, the more performance it gets.

The beauty of this approach is that it is not sensitive to nature of activity or capital intensity, For instance, participants to this study had to be actors within automotive industry, but could be as dissimilar as OEMs, electric wire and harnesses provider, a tier two system maker or a stamping contractor as well as a plastic parts manufacturer. These activities use very different means, some of which extremely capital intensive, while others can operate with small facilities and simple equipment.

The indexes are common to any industrial company and therefore are welcome to compare very different companies.

About indexes

This approach has its biases. First of all it was designed for industry, so the metrics relate to manufacturing e.g. raw material inventories.

Another weakness is the dilution when computing the indexes, regardless how smart they’re calculated, they end up as some kind of averaging averages.

Yet, as every participant was assessed in the same way, the relative scores of all of them keep the result of great interest. As for any benchmarking, the most important is not to discuss the accuracy or reliability of the result but what can be done to improve the score.

>Next Post: how lean are you? part 5

How lean can help shaping the future ? Lean engineering

Before searching about new high-tech disruptive innovation* let us reflect how lean thinking and lean tools were used so far.

*read my ‘Technologies alone will not regain competitive advantage‘ post

Every time an organization was exposed to lean concepts, those were used to improve the actual situation, resulting from decisions, practices and behaviors prior to lean introduction. Improvements were numerous and impressive enough to accumulate success stories and prove the power of lean.

Yet many improvements were limited and many impossible to Cary out, letting improvement efforts lingering in the low hanging fruits zone.

The reasons are decisions and options taken in early design phases, which engaged the organization for longer periods. Many conversion costs from actual situation to improved one would be too high and won’t pay off.

Many factories in Europe are located in centennial buildings with layouts having to cope with architectural constraints. Machines and equipment were packed in the available space, sometimes spread over several floors and over different buildings.

  • Even more recent factories I’ve helped to improve we’re located in remote places, in former backyard of founder’s home, in mountain village, in the midst of the Black Forest…
  • One of the biggest French company’s headquarter is located in a very old former convent.
  • Hospitals have similar backgrounds, layouts too often are nightmare to everyone, from visitors, patients, to staff and logistics.

All those locations may be lovely places but most of them are unfit for seamless flows and efficient work. Despite this, many of those locations will be kept for number of reasons good or bad, and will continue to hinder significant improvements.

Greenfield recent factories are generally build with lean concepts and future efficiency in mind, giving them a tremendous competitive advantage over the elder non-lean designed facilities.

Brownfield companies may pay great efforts improving their operations, it will usually not suffice to catch-up with the greenfield competitor.

Henceforth, greenfields are usually smartly located in the heart of the market they serve and hired lean aware workforce and/or trained it intensively, without facing the resistance to change nor lean learning curve.

Process and product improvement face similar problems: many decisions and options taken in early design phases constrain their design and evolution for long periods, sometimes during their entire lifetime.

Problems that drive workers crazy or require extra work, poor ergonomics and quality issues just remain because conversion costs would not pay off. Think about a mold or die modification, shape redesign, material change with all qualification process to go through again, etc.

What is left to improve is fetching the tool to correct a defect faster instead of preventing the defect.

So how can Lean help shaping the future?

Lean engineering in one way. My understanding of Lean engineering is using lean concepts, methods and tools to both improve engineering performance AND embed lean into designed products and processes to ensure future efficiency in manufacturing, delivery, servicing, etc.

While the first part – improving engineering performance – strives to reduce the time-to-market and design and engineering costs, the second part strives to put latter phases like manufacturing in best possible conditions to be efficient.

Therefore, all painfully lessons learned in manufacturing should be taken into account for the next design, frontloading issues to be solved and problems to be prevented. In the early design phases, lean thinking should help to design and build-in future sustainable performance. Design for Manufacturing and Assembly (DFMA) is one way.

While many designers may claim doing it, in reality they face great pressure to design-to-cost and speed-up to deliver products fast. Design-to-cost is usually flawed because it ignores the cost of later problem solving, error correction, scrap, rework, inefficiency and so on.

Problem solving and preventing is often ignored for the sake of design and engineering local objectives. But remember, those without memory are committed to repeat the same mistakes.

> More about How Lean can help shaping the future


How lean are you? Part 2

In previous post I described the lean awareness assessment, a relatively simple but not very effective way for assessing leanness.

Its weak point is the assumption lean awareness and operational performance are correlated and this causation is taken for granted. While this assumption makes sense and may be true, experience shows that this cause-effect relationship is not systematic.

It soon becomes obvious that Lean awareness should be checked versus operations’ performance level. This adds a second dimension to the assessment and allows scoring within a two dimensional matrix.


Four basic cases

A simple four quadrants matrix is very helpful to categorize an organization among four basic types. Instead of naming each type and explaining it I invite you to read the explanation and guess the name.

Lean Assessement Matrix

1) high awareness low performance

As described in previous post, many organizations may have very lean aware executives, managers, techs and personnel but there is no evidence of lean benefits on shop floor nor in operation’s performance indicators.

While concepts, methods and tools are known, at least in executives’ level, there is little evidence of them in ops and performance is low in comparison of other competitors or similar companies.

I call these organizations “theoreticians”.

2) low awareness high performance

These organizations perform well but at the expenses of their resources. The products are manufactured and delivered at high costs and/or capacities as well as material are wasted. Manpower is sweating to achieve these results or staff is plenty, more than really necessary or staff is working overtime often.

I call these organizations “effective” as they deliver timely (when really required) the awaited products and hopefully make some profit despite all the wastes. Profit could be higher, costs lower or spent energy more reasonable.

Until recently pharma industry was in this category, as sales profits were so high it wasn’t meaningful to strive for leaner operations, any investment in additional capacity eventually paid off. In case of pharma, capacities have often been wasted, low OEE being compensated by investments in additional capacities. Quality is worshiped at a point that any doubt leads to product or material destruction rather than trying to master processes. Times are changing and pharma has to consider leanness.

3) high awareness high performance

This quadrant is the quadrant of best in class, of operational excellence. Knowledge of Lean principles, methods and tools translate into operational practices, yielding good results at lowest costs and resource consumption.

These organizations are “efficient”.

4) low awareness low performance

The last quadrant is the all-danger zone in which the organization shows no awareness about Lean principles, methods and tools nor good operational performance.

If this is a start-up, it is understandable (but no excuse, Lean start-ups do exist!) but in any case this company should react swiftly and jump out of this deadly corner of the matrix.

I found no suitable name for organizations in this quadrant, feel free to suggest one!

When facing such a case in my consultant job, I urge the top management to get out of this “endangered” position, my best naming so far.

What course?

From low/low to high/high, no interest to lose time getting theoretical knowledge first (quadrant “high awareness low performance”) as performance is more important for immediate survival than knowledge. In a pragmatic way, it’s okay to go for “low awareness high performance” first, and then working to get efficient, thus heading for high/high.

Another route, more ambitious, is to head straight for high/high, trying to both improve performance and lean maturity. This may be difficult and risky.

>The next post deals with how to plot the position point in the matrix.


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How lean are you? Part 1

This is the first post of the “Lean assessment series” dedicated as its name tells to organizations’ leaness assessment.

One common and easy way to assess leanness is to check the organization’s lean awareness. This is usually done using a five level scale ranging from “barely any knowledge” to “top awareness”.

Assessors use question grids and score awareness according to answers and sometimes proofs and evidence. In the example below, the grid is built on five levels reflecting the judo / Six Sigma belt hierarchy. A set of questions or statements faces each level. If the respondent meets the requirements enclosed in questions or statements, the level is checked.

Lean Assessment Grid

Lean Assessment Grid

These grid usually come with reminders of proofs and evidences the assessor can ask or seek.

The assessment uses several grids, one per theme, several topics per theme, several items per topic, structured like this for example:

 Assessment Grid structure

One common way to summarize the results of all grids is to display a radar chart. Each theme is shown on an axis, the leaner , the more the surface covers the graph. Indents in the graph show the fields candidate for improvement.

Radar Chart

This kind of assessment is rather basic and assumes lean awareness leads to better performance as lean-aware organizations are supposed to think and act according to lean principles and use lean tools and techniques, thus are more efficient.

In reality I haven’t seen many lean-aware organizations, rather some lean-aware executives and middle managers with waning souvenirs about this or that tool.

This leads to the illusion of top management and the clear cut in the pyramid.

Cut in pyramid

While the lean aware top management believes lean tools and principles they mentioned or even promoted have dripped down to the shop floor, the latter has no knowledge and does not use any of them.

As top managers seldom tour the gemba and don’t pay much attention to the shop floor trivialities, they keep sitting in their ivory tower believing Lean tools and principles are in place.

The correlation between lean awareness and operational performance is not questioned either.

In the next post, we’ll see how to improve Lean assessment adding one more dimension.

>How Lean are you? Part2

You may also like: The fallacy of maturity assessments

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The Lean Advancement Initiative (LAI) at MIT offers LAI Self Assessment Tool (LESAT) for free download: