Posts Tagged ‘knowledge’

If you put an ear to someones chest you can hear their heart “lub-dub lub-dub lub-dub”. The sound is caused by the valves in the heart closing, like softly slamming doors, as part of the wonderfully orchestrated process of pumping blood around the lungs and body. The heart is an impressive example of bioengineering but it was not designed – it evolved over time – its elegance and efficiency emerged over a long journey of emergent evolution.  The lub-dub is a comforting sound – it signals regularity, predictability, and stabilty; and was probably the first and most familiar sound each of heard in the womb. Our hearts are sensitive to our emotional state – and it is no accident that the beat of music mirrors the beat of the heart: slow means relaxed and fast means aroused.

Systems and processes have a heart beat too – but it is not usually audible. It can been seen though if the measures of a process are plotted as time series charts. Only artificial systems show constant and unwavering behaviour – rigidity –  natural systems have cycles.  The charts from natural systems show the “vital signs” of the system.  One chart tells us something of value – several charts considered together tell us much more.

We can measure and display the electrical activity of the heart over time – it is called an electrocardiogram (ECG) -literally “electric-heart-picture”; we can measure and display the movement of muscles, valves and blood by beaming ultrasound at the heart – an echocardiogram; we can visualise the pressure of the blood over time – a plethysmocardiogram; and we can visualise the sound the heart makes – a phonocardiogram. When we display the various cardiograms on the same time scale one above the other we get a much better understanding of how the heart is behaving  as a system. And if we have learned what to expect to see with in a normal heart we can look for deviations from healthy behaviour and use those to help us diagnose the cause.  With experience the task of diagnosis becomes a simple, effective and efficient pattern matching exercise.

The same is true of systems and processes – plotting the system metrics as time-series charts and searching for the tell-tale patterns of process disease can be a simple, quick and accurate technique: when you have learned what a “healthy” process looks like and which patterns are caused by which process “diseases”.  This skill is gained through Operations Management training and lots of practice with the guidance of an experienced practitioner. Without this investment in developing knowlewdge and understanding there is a high risk of making a wrong diagnosis and instituting an ineffective or even dangerous treatment.  Confidence is good – competence is even better.

The objective of process diagnostics is to identify where and when the LUBs and HUBs appear are in the system: a LUB is a “low utilisation bottleneck” and a HUB is a “high utilisation bottleneck”.  Both restrict flow but they do it in different ways and therefore require different management. If we confuse a LUB for a HUB and choose the wrong treatent we can unintentionally make the process sicker – or even kill the system completely. The intention is OK but if we are not competent the implementation will not be OK.

Improvement Science rests on two foundations stones – Operations Management and Human Factors – and managers of any process or system need an understanding of both and to be able to apply their knowledge in practice with competence and confidence.  Just as a doctor needs to understand how the heart works and how to apply this knowledge in clinical practice. Both technical and emotional capability is needed – the Head and the Heart need each other.                          

I love history – not the dry boring history of learning lists of dates – the inspiring history of how leaps in understanding happen after decades of apparently fruitless search.  One of the patterns that stands out for me in recent history is how the growth of the human population has mirrored the changes in our understanding of the Universe.  This pattern struck me as curious – given that this has happened only in the last 10,000 years – and it cannot be genetic evolution because the timescale is to short. So what has fuelled this population growth? On further investigation I discovered that the population growth is exponential rather than linear – and very recent – within the last 1000 years.  Exponential growth is a characteristic feature of a system that has a positive feedback loop in it that is not balanced by an equal and opposite negative feedback loop. So, what is being fed back into the system that is creating this unbalanced behaviour? My conclusion so far is “collective improvement in understanding”.

However, exponential growth has a dark side – it is not sustainable. At some point a negative feedback loop will exert itself – and there are two extremes to how fast this can happen: gradual or sudden. Sudden negative feedback is a shock is the one to avoid because it is usually followed by a dramatic reversal of growth which if catastrophic enough is fatal to the system.  When it is less sudden and less severe it can lead into repeating cycles  of growth and decline – boom and bust – which is just a more painful path to the same end.  This somewhat disquieting conclusion led me to conduct the thought experiment that is illustrated by the diagram: If our growth is fuelled by our ability to learn, to use and to maintain our collective knowledge what changes in how we do this must have happened over the last 1000 years?  Biologically we are social animals and using our genetic inheritance we seem only able to maintain about 100 active relationships – which explains the natural size of family groups where face-to-face communication is paramount.  To support a stable group that is larger than 100 we must have developed learned behaviours and social structures. History tells us that we created communities by differentiating into specialised functions and to be stable these were cooperative rather than competitive and the natural multiplier seems to be about 100.  A community with more than 10,000 people is difficult to sustain with an ad hoc power structure with a powerful leader and we develop collective “rules” and a more democratic design – which fuels another 100 fold expansion to 1 million – the order of magnitide of a country or city. Multiply by 100 again and we get the size that is typical of a country and the social structures required to achieve stablity on this scale are different again – we needed to develop a way of actively seeking new knowledge, continuously re-writing the rule books, and industrialising our knowkedge. This has only happened over the last 300 years.  The next multipler takes us to Ten Billion – the order of magnitude of the current global population – and it is at this stage that  our current systems seem to be struggling again.

From this geometric perspective we appear to be approaching a natural human system barrier that our current knowledge management methods seem inadequate to dismantle – and if we press on in denial then we face the prospect of a sudden and catastrophic change – for the worse. Regression to a bygone age would have the same effect because those systems are not designed to suport the global economy.

So, what would have to change in the way we manage our collective knowledge that would avoid a Big Crunch and would steer us to a stable and sustainable future?

W. Edwards Deming (1900-1993) is sometimes referred to as the Father of Quality. He made such a significant contribution to Japan’s burgeoning post-war reputation for innovative high-quality products, and the rapid development of their economic power, that he is regarded as having made more of a difference than any other individual not of Japanese heritage.

Though best known as a statistician and economist, he was initially educated as an electrical engineer and mathematical physicist. To me however he was more of a social scientist – interested in the science of improvement and the creation of value for customers. A lifelong learner, in his later years (1) he became fascinated by epistemology – the processes by which knowledge is created – and this led him into wanting to know more about the psychology of human behaviour and its underlying motivations.

In his nineties he put his whole life of learning into one model – his System of Profound Knowledge (SoPK). What follows is my brief take on each of the four elements of the SoPK and how they fit together.

THE PSYCHOLOGY OF HUMAN BEHAVIOUR
Everyone is different, and we all SEE things differently. We then DO things based on how we see things – and we GET results – of some kind. Over time we shore up our own particular view of the world – some call this a “paradigm” – our own particular world view – multiple loops of DO-GET-SEE (2) are self-reinforcing and as our sense making becomes increasingly fixed we BEHAVE – BECOME – BELIEVE. The trouble is we each to some extent get divorced from reality, or at least how most others see it – in extreme cases we might even get classified by some people as “insane” – indeed the clinical definition of insanity is doing the same things whilst expecting different results.

THE ACQUISITION OF KNOWLEDGE
So when we DO things it would be helpful if we could do them as little experiments that test our sense of what works and what is real. Even better we might get others to help us interpret the results from the benefit of their particular world view/ paradigm. Did you study science at school? If so you might recognize that learning in this way by experimentation is the “scientific method” in action. Through these cycles of learning knowledge gets continually refined and builds. It is also where improvement comes from and how reality evolves. Deming referred to this as the PLAN-DO-STUDY-ACT Cycle (1) – personally i prefer the words in this adjacent diagram. For me the cycle is as much about good mental health as acquiring knowledge, because effective learning (3) keeps individuals and organizations connected to reality and in control of their lives.

UNDERSTANDING VARIATION
The origins of PDSA lie with Walter Shewhart (4) who in 1925 – invented it to help people in organizations methodically and continually inquire into what is happening. He observed that when workers or managers make changes in their working practices so that their processes run better, the results vary, and that this variation often fools them. So he invented a tool for collecting numbers in real time so that each process can be listened in to as a “system” – much like a doctor uses a stethoscope to collect data and interpret how their patient’s system is behaving, by asking what might be contributing to – actually causing – the system’s outcomes. Shewhart named the tool Statistical Process Control – three words, each of which for many people are an instant turn-off. This means they miss his critical insight that there are two distinct types of variation – noise and signal, and that whilst all systems contain noise, only some contain signals – which if present can be taken to be assignable causes of systemic behaviour. Indeed to make it more palatable the tool might better be referred to as a “system behaviour chart”. It is meant to be interpreted like a doctor or nurse interprets the vital sign graph on the end of a patient’s bed i.e. to decide what action if any to take and when. Here is an example that has been created in BaseLine© which is specifically designed to offer the agnostic direct access to the power of Shewhart’s thinking. (5).

THINKING SYSTEMICALLY
What is meant by the word “system”? It means all the parts connected and interrelated as a whole (3). It is often helpful to get representatives of the various stakeholder groups to map the system – with its parts, the flows and the connections – so they can see how different people make sense of say.. their family system, their work system, a particular process of interest.. indeed any system of any kind that feels important to them. The map shown here is one used that might be used generically by manufacturers to help them investigate the separate causal sources of systemic variation – from the Suppliers of Inputs received, to the Processes that convert those inputs into Outputs, which can then be received by Customers – all made possible by vital support processes. This map (1) was taught by Deming in 1950 to Japan’s leaders. When making sense of their own particular systemic context others may prefer a different kind of map, but why? How come others prefer to make sense of things in their own way? To answer this Peter Senge (3) in his own equivalent to the SoPK says you need 5 distinct disciplines: the ability to think systemically, to learn as a team, to create a shared vision, to understand how our mental models get ingrained, and lastly “personal mastery” … which takes me back to where I started.

Aware that he was at the end of his life of learning, Deming bequeathed his System of Profound Knowledge to us so that we might continue his work. Personally, I love the SoPK because it is so complete. It is hard however to keep such a model, complete and as a whole, continually in the front of our minds – such that everything we think and do can be viewed as a fractal of that elegant whole. Indeed as a system, the system of profound knowledge is seriously – even fatally – undermined if any single part is missing ..

• Without understanding the causes of human behaviour we have no empathy for other people’s worldviews, other value systems. Without empathy our ability to manage change is fundamentally impaired.

• Without being good at experimentation and turning our experience into Knowledge – the very essence of science – we threaten our very mental health.

• Without understanding variation we are all too easily deluded – ask any magician (6). We spin our own reality. In ignoring or falsely interpreting data we are even “wilfully blind” (7). Baseline© for example is designed to help people make more of their time-series data – a window onto the system that their data is representing – using its inherent variation to gain an enhanced sense of what’s actually happened, as well as what’s really happening, and what if things stay the same is most likely to happen.

• Without being able to see how things are connected – as a whole system – and seeing the uniqueness of our own particular context, moment to moment, we miss the importance of our maps – and those of others – for good sense-making. We therefore miss the sharing of our individual realities, and with it the potential to spot what really causes outcomes – which neatly takes us back to the need for empathy and for understanding the psychology of human behaviour.

For me the challenge is to be continually striving for that sense of the SoPK – as a complete whole – and by doing this to see how I might grow my influence in the world.

Julian Simcox

References

1. Deming W.E – The New Economics – 1993
2. Covey S.R. – The 7 habits of Highly Effective People – 1989
3. Senge P. M. – The Fifth Discipline: the art and practice of the learning organization – 1990
4. Wheeler D.J. & Poling S.R.– Building Continual Improvement – 1998
5. BaseLine© is available via www.threewinsacademy.co.uk.
6. Macknik S, et al – Sleights of Mind – What the neuroscience of magic reveals about our brains – 2011.
7. Heffernan M. – Wilfully Blind – 2011