Knowledge and Understanding

Saturday, May 19, 2012

Knowledge is not the same as Understanding. We all know that the sun rises in the East and sets in the West; most of us know that the oceans have a twice-a-day tidal cycle and some of us know that these tides also have a monthly cycle that is associated with the phase of the moon. We know all of this just from taking notice; remembering what we see; and being able yo recognise the patterns. We use this knowledge to make reliable predictions of the future times and heights of the tides; and we can do all of this without any understanding of how tides are caused.

Our lack of understanding means that we can only describe what has happened. We cannot explain how it has happened.

People have observed and described the movements of the sun, sea, moon, and stars for millennia and a few could predict them with surprising accuracy but it was not until the 17th century that we understood how. Isaac Newton developed enough of an understanding explain what was known using a new concept called gravity and a new tool called calculus.

Understanding enables things that have not been observed or described to be predicted and explained. Understanding is necessary if we want to make rational decisions that will lead reliably to changes for the better.

So, how can we test if we only know what to do or if we actually understand what to do?

If we understand then we can demonstrate the application of knowledge by solving new problems effectively and explain how we will do it.  If we do not understand then we can still apply knowledge but we do not solve old problems effectively or efficiently and we are not able to explain why.

But we do not want to take the risk of making a mistake to find out if we have and understanding-gap so how can we find out? What we look for is the tell-tale sign of an excess of knowledge and a dearth of understanding - and it is called “bureaucracy”.

Suppose we have a system where the decisions-makers do not make effective decisions – whichs mean that their decisions lead to unintended adverse outcomes. It does not take long for the system to know that the decision process is ineffective – so to protect itself the system reacts by creating bureaucracy – a sort of organisational sand-bag that limits the damage created by the poor decisions. The bureaucratic firewall.

Unfortunately, the bureaucracy is non-specific and it slows everything down and reduces efficiency – so what we get is a system that costs more and appears to do less and that is resistant to any change. The do-less bit is important though; doing less bad stuff is actually a reasonable survival strategy – until the cost of the bureaucracy threatens the systems viability too. 

So what happens when a desperate “efficiency” drive is started and the “bureaucratic red tape” is cut away? The poor decisions that the red tape was ensnaring are released and implemented and they create a bigger unintended adverse consequence! The safety and quality performance of the system drops which triggers a reflex “we-told-you-so” and re-introduction of the safety red-tape, plus some extra.  The system learns from the experience, concludes that “higher quality always costs more” and “don’t trust our decision-makers” and “the only way to avoid a bad decision is not to make/or/implement any decisions” and to “the safest way to maintain quality is to add extra checks and pay the price”. The system then remembers this new knowledge for future reference; the bureaucratic concrete sets hard; and the whole cycle repats itself.   

With this insight into the role of bureaucracy and its root cause we can design an alternative strategy: to develop knowledge into understanding and by that route to increase our capability to make better decisions that lead to predictable, demonstrable and explainable improvements. When we do that the bureaucracy is clearly seen to impede progress so it makes sense to dismantle the just the bits that block improvement. We now get improved quality and lower costs at the same time, without taking a ny risks, and we can reinvest what we have saved in making making progress and developing more knowledge, a deeper understanding and further improvement.

The primary focus of Improvement Science is to expand understanding – the ability to decide what to do, and what not to; where and where not to; and when and when not to act – and to be able to explain and to demonstrate “how”.

One proven way to expand understanding is to See then to Do and then to Teach – and the person whose understanding increases the most is the teacher! 

Twitt

Posted in Reflections, Techniques, Theory, Training | No Comments »

Cause and Effect

Saturday, May 12, 2012

Breaking News: Scientists have discovered that people with yellow teeth are more likely to die of lung cancer. Patient-groups and dentists are now calling for tooth-whitening to be made freely available to everyone.”

Does anything about this statement strike you as illogical? Surely it is obvious. Having yellow teeth does not cause lung cancer – smoking causes both yellow teeth and lung cancer!  Providing a tax-funded tooth-whitening service will be futile – banning smoking is the way to reduce deaths from lung cancer!

What is wrong here? Do we have a problem with mad scientists, misuse of statistics or manipulative journalists? Or all three?

Unfortunately, while we may believe that smoking causes both yellow teeth and lung cancer it is surprisingly difficult to prove it – even when sane scientists use the correct statistics and their results are accurately reported by trustworthy journalists.  It id not easy to prove causality.

But we all do something very similar many times every day – we infer causality from our experience of interacting with the real world – and it is our innate ability to do that which allows us to say that the opening statement does not feel right.  And we do this trick effortlessly and unconsciously. 

We then use our inferred-causality for three purposes. Firstly, we use it to explain how past actions led to the present situation. The chain of cause-and-effect. Secondly, we use it to create options in the present – our choices of actions. Thirdly, we use it to predict the outcome of our chosen action – we set our expectation and then compare the outcome with our prediction. If outcome is better than we expected then we feel delighted, if it is worse then we feel disappointed.

What we are doing naturally and effortlessly is called “causal modelling”. And it is an amazing skill.

Unfortunately - the ability to build and use a causal model does not guarantee that our model is a valid, complete or accurate representation of reality. Our model may be imperfect – but we may not be aware of it.  And this raises two questions: “How could two people end up with different causal models when they are experiencing the same reality?” and “How do we prove if either is correct and if so, which it is?” 

The issue here is that no two people can perceive reality exactly the same way - we each have an unique perspective – and this inevitable difference is a form of variation.

We also tend to assume that what-we-perceive-is-the-truth so if someone expresses a different view of reality then we may jump to the conclusion that they are “wrong” and we are “right”.  This habitual assumption of our own rightness extends to our causal models as well. If someone else believes a different explanation of how we got to where we are, what our choices are and what effect we might expect from a particular action then there is almost endless opportunity for disagreement!

Fortunately our different perceptions agree enough to create common ground which allows us to co-exist reasonably amicably.  But, we then take the common ground for granted and magnify the molehills of disagreement into mountains of discontent.

So, if our goal is improvement, then we might consider a more effective approach: which might be to assume that all our causal models are approximate and that they are all works-in-progress. This implies that each of us has two challenges: first to develop a valid causal model by testing it against reality through experimentation; and second to assist the collective development of a common causal model by sharing our individual understanding through explanation and demonstration.

The problem we may then encounter is that statistical analysis of historical data cannot answer questions of causality – it is necessary to be sure but it is insufficient – and because it is insufficient it does not make common-sense.  For example, there may well be a statistically significant association between “yellow teeth” and ”lung cancer” and “premature death” but those knowing those facts is not enough to help us make a wiser choices of a more effective actions that cauase us to live longer.

Learning how to make wiser choices that lead to better outcomes is what Improvement Science is all about - and we need more than statistics – we need to learn how to collectively create, test and employ causal models.

And that is called common sense.

Twitt

Posted in Healthcare, Reflections, Techniques, Theory, Tools | No Comments »

Resistance to Change

Saturday, May 5, 2012

Many people who are passionate about improvement become frustrated when they encounter resistance-to-change. It does not matter what sort of improvement is desired – safety, quality, delivery, costs, revenue, productivity or all of them.

The natural and intuitive reaction to meeting resistance is to push harder – and our experience of the physical world has taught us that if we apply enough pressure at the right place then resistance will be overcome and we will move forward.

Unfortunately we sometimes discover that we are pushing against an immovable object and even our maximum effort is futile – so we give up and label it as “impossible”.

Much of Improvement Science appears counter-intuitive and even magical at first sight and the challenge of resistance is no different.  The counter-intuitive response to feeling resistance is to pull back, and that is exactly what works better. But why does it work better? Isn’t that just giving up and giving in? How can that be better?

To explain the rationale it is necessary to examine the nature of resistance more closely. Resistance to change is an emotional reaction to an unconsciously perceived threat that is translated into a conscious decision, action and justification: the response. The range of verbal responses is large, as illustated in the caption, and the range of non-verbal responses is just as large.  Attempting to deflect or defuse all of them is impractical, ineffective and leasds to a feeling of frustration and futility.

This negative emotional reaction we call resistance is non-specific because that is how our emotions work - and it is triggered as much by the way the change is presented as what the change is.  Many change “experts” recommend  the better method of “driving” change is selling-versus-telling and recommend learning psycho-manipulation techniques to achieve it – sales training for example. Unfortunately this strategy can create a psychological “arms race” which can escalate just as quickly and lead to the same outcome: an  emotional battle and psychological casualties. This inevitable outcome is often given the generic label of ”stress”.

An alternative approach is to regard resistance behaviour as multi-factorial and one model separates the non-specific resistance response into separate categories: Why Do – Don’t Do - Can’t Do – Won’t Do.

The Why Do response is valuable feedback because is says “we do not understand the purpose of the proposed change” and it is not unusual for proposals to be purposeless. This is sometimes called “meddling”.

The Don’t Do  is valuable feedback that is saying “there is a risk with this proposed change – an unintended negative consequence that may be greated than the intended positive outcome“.  Often it is very hard to explain this NooNoo reaction because it is the output of an unconscious thought process that operates out of awareness. It just doesn’t feel good. And some people are better at spotting the risks – they prefer to wear the Black Hat.

The Can’t Do is also valuable feedback that is saying ”we can see the problem and the benefit of a change – we cannot see the path that links the two because it is blocked by something.” This reaction is often triggered by an unconscious recognition that some form of collaborative working will be required combined with a low-trust context. It can also just be a manifestation of a knowledge, skill or experience gap – the “I don’t know how to do” gap. Some people habitually adopt the Victim Role.  

The Won’t Do response is also valuable feedback that is saying “we can see the problem, the benefit, and the path but we won’t do it because we don’t trust you“. This reaction is common in a low-trust culture where manipulation, bullying and game playing is the observed and expected behaviour. The role being adopted here is the Persecutor.

The common theme here is that all resistance-to-change responses represent valuable feedback and explains why the better reaction to resistance is to stop talking and start listening because to make progress will require using the feedback to diagnose what components are present. Managing each category requires a different approach.

For example Why Do requires making the both problem and the purpose explicit; Don’t Do requires exploring the fear and bringing to awareness what is fuelling it; Can’t Do requires searching for the skill gaps and filling them; and Won’t Do requires identifying the trust-eroding beliefs, attitudes and behaviours and challenging them.

Resistance-to-change is generalised as a threat to success, when in reality it represents an opportunity to learn and to improve - which is what Improvement Science is all about.

Twitt

Posted in 4N Chart, Techniques, Theory, Tools, Training | No Comments »

Building a Big Picture from the Small Bits

Saturday, April 28, 2012

We are all a small piece of a complex system that extends well beyond the boundaries of our individual experience. We all know this. We also know that seeing the big picture is very helpful because it gives us context, meaning and leads to better decisions more effective actions. We feel better when we know where we fit in the Big Picture – and we feel miserable when we do not.  And when our system is not working as well as we would like then we need to improve it; and to do that we need to understand how it works so that we change only what we need to. To do that we need to see the Big Picture and to understand it.  

So how do we build the Big Picture from the individual pieces? Solving a jigsaw puzzle is a good metaphor for the collective challenge we face. Each of us holds a piece which we know very well because it is what we see, hear, touch, smell and taste every day. But how do we assemble the pieces so that we can all see and appreciate the whole rather than dimly perceive a dysfunctional heap of bits?

One strategy is to look for tell-tale features that indicate where a piece might fit – irrespective of the unique picture on it. Such as the four corners. We also use this method to group pieces that belong on the sides – but this is not enough  to tell us which side and where on which side each piece fits. So far all we have are some groups of bits - rough parts of the whole - but no clear view of the picture. To see that we need to look at the detail – the uniqueness of each piece.

Our next strategy is to look at the shapes of the edges to find the pieces that are complementary – that leave no gaps when fitted together – these are our potential neighbours. Sometimes there is only one that fits, sometimes there are many that fit well enough. Our third strategy is to look at the pictures on potential neighbours and to check for continuity because the picture should flow across the boundary – and a mismatch means we have made an error.  

 What we have now is the edges of the picture and a heap of bits that go somewhere in the middle. By connecting the edge-pieces we can see that there are gaps and this is an important insight. It is not until we have a framework that spans the whole picture that the gaps become obvious. But we do not know yet if our missing pieces are in the heap or not - we will not know that until we have solved the jigsaw puzzle.

Throughout the problem-dissolving process we are using three levels of content: data that we gain through our senses, in this case our visual system; information which is the result of using rules to classify the data - shape and colour for example; and knowlege which we derive from past experience to help us make decisions - “That is a top-left corner so it goes there; that is an edge so it goes in that group; that edge matches that one so they might be neighbours and I will try fitting them together; the picture does not flow so they cannot be neighbours and I must separate them”.

The important point is that we do not need to understand the picture to do this – we can just use dumb pattern-matching techniques, simple logic and brute force to decide which bits go together and which do not. A computer could do it – and we or the computer can solve the puzzle and still not recognise, understand or be able to use what we are looking at.

To do that we need to look for meaning – and that usually means looking for and recognising symbols that are labels for concepts and using the picture to reveal how they relate to each other.

As we scan the pieces and fit the neighbours together we see words and phrases that we may recognise – “Legend” and “cycle” for example (click the picture to enlarge)  - and we can use these labels to start to build a conceptual framework and from that to create an expectation. Just as we did with the corners and edges. The word “cycle” implies a circle, which is often drawn as a curved line, so we can use this expectation to look for pieces of a circle and lay them out – just as we did with the edges. We may not recognise all the symbols – “citric acid“ for example – and that finding means that there is new knowledge hidden in the picture. By the end we may understand what those new symbols mean from the context that the big picture creates.

By searching for meaning we are doing more than mechanically completing a task - we are learning - we are expanding our knowledge and we are deepening our understanding. But to do this we need to separate the heap of bits so they do not obscure each other and we can see each clearly. When it is a mess the new learning and deeper understanding will elude us.

OK – we have found some pieces with lines on that look like parts of a circle and we can arrange them into an approximate sequence - and when we do that we are delighted to find that the pieces fit together, the pictures flow from one to the other, and there is a sense of order and structure starting to emerge from within the picture itself.  Until now the only structure we saw was the artificial and meaningless boundary.  We now see a new and unfamiliar phrase “citric acid cycle” – what is that? Our curiosity is building.

 

As we progress we find repeated symbols that we recognise but do not understand - red and gray circles linked together. In the top right under the word “Legend” we see the same symbols together with some we do recognise – “hydrogen, carbon and oxygen”.

Ah ha! Now we can translate the unfamiliar symbols into familiar concepts and now we know that this is something to do with chemistry. But what?

 

We are nearly there – almost all the pieces are in place and we have identified where the last few fit. Now we can see that all the pieces are from the same jigsaw, there are none missing and there are no damaged, distorted, or duplicated pieces. The big picture looks complete. 

We can see that the lines between the pieces are not part of the picture – they are artificial boundaries created when the picture was broken into parts – and useful only for helping use re-assemble the big picture. Now they are getting in the way – they are distracting us from seeing the picture as clearly as we could – so we can dispense with them – they have served their purpose.  We can also see that the pieces appear to be arranged in columns and rows – and we could view our picture as a set of interlocked vertical stripes or as a set of interlocked horizontal strips – but that this would be an artificial structure created by our artifical boundaries. The picture we are seeing transcends our artificial linear decomposition.

We erase all the artificial boundaries and the full picture emerges. Now we can see that we have a chemical system where a series of reactions are linked in a cycle – and we can see something called pyruvate coming in top left and we recognise the symbols water and CO2 and conclude that this might be part of the complex biochemical system that is called cellular respiration – the process by which the food that we eat and the oxygen we breathe is converted into energy and the CO2 that we breathe out. Wow!

And we can see that this is just part of a bigger map – the edges were also artificial and arbitrary! But where does the oxygen fit? And which bit is the energy? And what is the link between the carbohydrate that we eat and this new thing called pyruvate. Our bigger picture and deeper understanding has generated a lot of new questions, there is so much more to explore, to learn and to understand!!  

So what have we learned? We have learned that our piece was not just one of a random heap of unconnected jigsaw bits; we have learned where our piece fits into a bigger picture; we have learned how our piece is an essential part of that picture; we have learned that there is a design in the picture and how we are part of that design. And when we all know and we all understand the whole design and how it works then we all have a much better chance of being able to improve it in a rational, sensible and explainable way.

Building the big picture of a system from the disorganised heap of pieces is one of the key skills of an Improvement Science Practitioner - and the more practice we get the quicker we recognise what we are looking at – because there are a relatively few effective designs.  This is insight is important because most of the unsolved probelms are system problems – and the sooner we can diagnose the design flaw that is a root cause of a system problem then the sooner we can propose, test and implement a solution and experience an improvement.

And that is a win-win-win strategy.

Twitt

Posted in Design, Information, Reflections, Techniques, Tools | 1 Comment »

The Bucket Brigade Fire Fighting Service

Saturday, April 21, 2012

Fire-fighting is a behaviour that has a long history and before Fireman Sam arrived on the scene we had the Bucket Brigade.  This was a people-intensive process designed to deliver water from the nearest pump, pond or river with as little risk, delay and effort as possible. The principle of a bucket-brigade is that a chain of people forms between the pump and the fire and they pass buckets in two directions – full ones from the pump to the fire and empty ones from the fire back to the pump.

A bucket brigade is useful metaphor for many processes and an Improvement Scientist can learn a lot from exploring its behaviour.  First of all the number of steps in the process or stream is fixed because it is determined by the distance between the pump and the fire. The time it takes for a Bucket Passer to pass a bucket to the next person is predictable  too and it is this cycle time that determines the rate at which a bucket will move along the line. The fixed length and fixed cycle time implies that the time it takes for a bucket to pass from one end of the line to the other is fixed too. It does not matter if the bucket is empty, half empty or full – the delivery time per bucket is consistent from bucket to bucket. The outflow however is not fixed – it is determined by how full each bucket is when it reaches the end of the line: empty bucket means zero flow, full bucket means maximum flow.    

This means that the process is behaving like a time-trap because the delivery time and the delivery volume (i.e. flow) are independent. Having bigger buckets or fuller buckets makes no difference to the time it takes to traverse the line but it does influence the out flow.

Most systems have many processes that are structured just like a bucket brigade: each step in the process contributes to completing the task before handing the part-completed task on to the next step.

The three dimensions of Improvement are Quality, Delivery and Productivity and we can see that, if we are not dropping buckets, then the quality and delivery are fixed by the design of the process. So what can we do to improve productivity?

Well, it is evident that the time it takes to do the handoff adds to the cycle time of each step. So along comes the Fire Service Finance Department who sees time-as-money and they work out that the unit cost of each step of the process could be reduced by accumulating the jobs at each stage and then handing them off as a batch – because the time-is-money and the cost of the handoff can now be shared across several buckets. They conclude that the unit cost for the steps will come down and productivity will go up - simple maths and intuitively obvious in theory – but does it actually work in reality?

Q1: Does it reduce the number of Bucket Passers? No. We need just as many as we did before. What we are doing is replacing the smaller buckets with bigger ones – and that will require capital investment.  So when our Finance Department use the lower unit cost as justification then the bigger, more expensive buckets start to look like a good financial option - on paper. But looking at the wage bills we can see that they are the same as before so this raises a question: have the bigger buckets increased the flow or reduced the delivery time? We will need a tangible, positive and measurable  improvement in productivity to justify our capital investment. 

To summarise: we have the same number of Bucket Passers working at the same cycle time so there is no improvement in how long it takes for the water to reach the fire from the pump! The delivery time is unchanged. And using bigger buckets implies that the pump needs to be able to work faster to fill them in one cycle of the process – but to minimise cost when we created the Fire Service we bought a pump with just enough average flow capacity and it cannot be made to increase its flow. So, equipped with a bigger bucket the first Bucket Passer has to wait longer for their bigger bucket to be filled before passing it on down the line.  This implies a longer cycle time for the first step, and therefore also for every step in the chain. So the delivery-time will actually get longer and the flow will stay the same – on average. All we have appear to have achieved is a higher cost and longer delivery time – which is precisely the opposite of what we intended. Productivity has actually fallen!

In a state of  near-panic the Fire Service Finance Department decide to measure the utilisation of the Bucket Passers and discover that it has fallen which must mean that they have become lazy! So a Push Policy is imposed to make them work faster – the Service cannot afford financial inducements – and threats cost nothing. The result is that in their haste to avoid penalties the bigger, fuller, heavier buckets get fumbled and some of the precious water is lost - so less reaches the fire.  The yield of the process falls and now we have a more expensive, longer delivery time, lower flow process. Productivity has fallen even further and now the Bucket Passers and Accountants are at war. How much worse can it get?

Where did we go wrong?

We made an error of omission. We omitted to learn the basics of process design before attempting to improve the productivity of our time-trap dominated process!  Our error of omission led us to confuse the step, stage, stream and system and we incorrectly used stage metrics (unit cost and utilisation) in an attempt to improve system performance (productivity). The outcome was the exact oppposite of what we intended; a line of unhappy Bucket Passers; a frustated Finance Department and an angry Customer whose house burned down because our Fire Service did not deliver enough water on time. Lose -Lose-Lose.

Is it possible to improve the productivity of a time-trap design? Yes, it is. How do we avoid making the same error? The FISH know how.

Twitt

Posted in Examples, Finance, Operations, Theory, Tools | 1 Comment »

Targets, Tyranny and Traps.

Saturday, April 14, 2012

If we are required to place a sensitive part of our anatomy into a device that is designed to apply significant and sustained pressure, then the person controlling the handle would have our complete attention!  Our sole objective would be to avoid the crushing and relentless pain and this would most definitely bias our behaviour – we might say or do things that ordinarily we would not – just to escape from the pain.

The requirement to meet well-intentioned but poorly-designed performance targets can create the organisational equivalent of a medieval thumbscrew and the distorting effect on behaviour is the same.  And some people seem to derive pleasure from turning the screw.

But what if we do not know how to achieve the performance target? We might then act to deflect the pain onto others – we might become tyrants too – and we might start to apply our own thumbscrews further along the chain of command.  Those unfortunate enough to be at the end of the pecking order have nowhere to hide – and that is a deeply distressing place to be – hapless, helpless and hopeless.

Fortunately there is a way out of the corporate torture chamber: It is to learn how to design systems to deliver the required performance specification – and learning how to do this is much easier than most believe.

For example, most assume without question that big queues and long waits are always caused by inefficient use of available capacity - because that is what their monitoring systems report. So out come thumbscrews heralded by the chanted mantra ”increase utilisation, increase utilisation”.  Unfortunately, this belief is only partially correct: low utilisation of available capacity can and does lead to big queues and long waits but there is a much more prevalent and insidious cause of long waits that has nothing to do with capacity or utilisation. These little beasties are are called time-traps.

The essential feature of a time trap is that it is independent of both flow and time – it adds the same amount of delay irrespective of whether the flow is low or high and irrespective of when the work arrives. In contrast waits caused by insufficient capacity are flow and time dependent – the higher the flow the longer the wait - and the effect is cumulative over time.

Many confuse the time-trap with its close relative the batch - but they are not the same thing at all – and most confuse both of these with capacity-constraints which are a completely different delay generating beast altogether. 

The distinction is critical because the treatments for time-traps, batches and capacity-constraints are different - and if we get the diagnosis wrong then we will make the wrong decision, choose the wrong action, and our system will get sicker, or at least no better. The corporate pain will continue and possibly get worse – leading to even more bad behaviour and more desperate a self-destructive strategies.

So when we want to reduce lead times by reducing waiting-in-queues then the first thing we need to do is to search for the time-traps – and to do that we need to be able to recognise their characteristic footprint on our time-series charts; the vital signs of our system.

We need to learn how to create and interpret the charts – and to do that quickly we need guidance from someone who can explain what to look for and how to interpret the picture. If we lack insight and humiliaty and choose not to learn then we are choosing to stay in the target-tyranny-trap and our pain will continue. 

Twitt

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The Power of the Positive Deviants

Saturday, April 7, 2012

It is neither reasonable nor sensible to expect anyone to be a font of all knowledge and guroid thinking and behaviour is dangerous.

So where does an Improvement Scientist seek inspiration?

Guessing is a poor guide; gut-instinct can seriously mislead; and mind-altering substances are illegal, unreliable and usually both!

So who are the sources of fresh ideas and where do we find them?

They are called Positive Deviants and they are everywhere.

But, the phrase doesn’t sound quite feel right does it? The word “deviant” has a strong negative emotional association. We are socially programmed from birth to treat deviations from the norm with distrust and for good reason: social animals view conformity and similarity as security – it is our herd instinct – and anyone who looks or behaves too far from the norm is perceived as odd and therefore shunned.

So why consider deviants at all? Well, because anyone who behaves significantly differently from the majority is a potential source of new insight – so long as we know how to separate the positive deviants from the negative ones.

Negative deviants display behaviours that we could all benefit from by actively discouraging!  The thou-shalt-not behaviours that are usually embodied in Law – killing, stealing, lying, speeding, dropping litter. That sort of anti-social trust-eroding behaviour.

Positive deviants display behaviours that we could all benefit from actively encouraging – the nice-if behaviours. But we are habitually focussed more on self-protection than self-development and we gneralise and treat all deviants the same - we are wary of them. By so doing we miss valuable opportunities to learn and improve.    

How then do we identify the Positive Deviants?

The first step is to decide the dimension we want to improve and choose a suitable metric to measure it.

The second step is to measure the metric for everyone but do it over time – not just at a point in time – single point measurements are almost useless – we can be tricked by the noise. 

The third step is to plot our measure-for-improvement as a time-series chart and look at it.  Are there points at the positive end of the scale that deviate significantly from the average? If so – where and who do they come from? Is there a pattern? Is there anythbing we might use as a predictor? 

Now we separate the data into groups guided by our proposed predictors and compare the groups – do the positive deviants now stick out like a sore thumb? 

If so we next go and investigate – we need to compare and contrast the Positive Deviants with the Norms. We need to compare and contrast both their context and their content. We need to know what is similar and what is different. There is something that is causing the deviation and we need to search until we find it – and then we need know how and why it is happening. We need to separate associations from causations … we need to understand the chains of events and the outcomes. 

Only then will a new door materialise in our wall of ignorance – a door that leads to a potential path of improvement. A path that has been trodden before by a positive deviant.

And only we can choose to open the door and explore the path.

And remember that when our system is designed to identify the positive deviants then the negative deviates will be identified too!   

For more about PDs click here: http://en.wikipedia.org/wiki/Positive_Deviance

Twitt

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Seeing Is Believing or Is It?

Saturday, March 31, 2012

Do we believe what we see or do we see what we believe?  It sounds like a chicken-and-egg question – so what is the answer? One, the other or both?

Before we explore further we need to be clear about what we mean by the concept “see”.  I objectively see with my real eyes but I subjectively see with my mind’s eye. So to use the word see for both is likely to result in confusion and conflict and to side-step this we will use the word perceive for seeing-with-our-minds-eye.   

When we are sure of our belief then we perceive what we believe. This may sound incorrect but psychologists know better – they have studied sensation and perception in great depth and they have proved that we are all susceptible to “perceptual bias”. What we believe we will see distorts what we actually perceive – and we do it unconsciously. Our expectation acts like a bit of ancient stained glass that obscures and distorts some things and paints in a false picture of the rest.  And that is just during the perception process: when we recall what we perceived we can add a whole extra layer of distortion and can can actually modify our original memory! If we do that often enough we can become 100% sure we saw something that never actually happened. This is why eye-witness accounts are notoriously inaccurate! 

But we do not do this all of the time.  Sometimes we are open-minded, we have no expectation of what we will see or we actually expect to be surprised by what we will see. We like the feeling of anticipation and excitement – of not knowing what will happen next.   That is the psychological basis of entertainment, of exploration, of discovery, of learning, and of improvement science.

An experienced improvement facilitator knows this – and knows how to create a context where deeply held beliefs can be explored with sensitivity and respect; how to celebrate what works and how and why it does; how to challenge what does not; and how to create novel experiences; foster creativity and release new ideas that enhance what is already known, understood and believed.

Through this exploration process our perception broadens, sharpens and becomes more attuned with reality. We achieve both greater clarity and deeper understanding - and it is these that enable us to make wiser decisions and commit to more effective action.

Sometimes we have an opportunity to see for real what we would like to believe is possible – and that can be the pivotal event that releases our passion and generates our commitment to act. It is called the Black Swan effect because seeing just one black swan dispels our belief that all swans are white.

A practical manifestation of this principle is in the rational design of effective team communication – and one of the most effective I have seen is the Communication Cell – a standardised layout of visual information that is easy-to-see and that creates an undistorted perception of reality.  I first saw it many years ago as a trainee pilot when we used it as the focus for briefings and debriefings; I saw it again a few years ago at Unipart where it is used for daily communication; and I have seen it again this week in the NHS where it is being used as part of a service improvement programme.

So if you do not believe then come and see for yourself.

Twitt

Posted in Design, Information, Reflections, Stories, Techniques, Theory, Tools, Training | 2 Comments »

March Madness

Saturday, March 24, 2012

Whether we like it or not we are driven by a triumvirate of celestial clocks. Our daily cycle is the result of the rotation of the Earth; the ebb and flow of the tides is caused by the interaction of the orbiting Moon and the spinning Earth; and the annual sequence of seasons is the outcome of the tilted Earth circling the Sun.  The other planets, stars and galaxies appear not to have much physical influence – despite what astrologists would have us believe. 

Hares are said to behave oddly in the month of March – as popularised by Lewis Carroll in Alice’s Adentures in Wonderland - but there is another form of March Madness that affects people – one that is not celestial and seasonal in origin – its cause is fiscal and financial. The madness that accompanies the end of the tax year.

This fiscal cycle is man-made and is arbitrary - it could just as well be any other month and does indeed differ from country to country – and the reason it is April 6th in the UK is because it is based on the ecclesiastical year which starts on March 25th but was shifted to April 6th when 11 days were lost on the adoption of the Gregorian calendar in 1752.  The driver of the fiscal cycle is taxation and the embodiment in Law of the requirement to present standard annual financial statements for the purpose of personal taxation.

The problem is that this system was designed for a time when the bean-counting bureaucracy was people-pen-paper based and to perform this onerous task more often than annually would have been counter-productive.  That is the upside. The downside is that an annual fiscal cycle shackled to a single date creates a feast-and-famine cash flow effect. The public coffers would have a shark-fin shaped wonga-in-progress chart!  And preparing for the end of the financial year creates multi-faceted March madness: annual cash hoarding leads to delayed investment decisions and underspent budgets being disposed of carelessly; short term tax minimisation strategies distort long term investment decisions and financial targets take precident over quality and delivery goals. Success or failure hinges on the the financial equivalent of threading the eye of a long needle with a bargepole. The annual fiscal policy distorts the behaviour of system and benefits nobody. 

It would be a better design for everyone if fiscal feedback was continuous – especially as the pace of change is quickening to the point that an annual financial planning cycle is painfully long . The good news is that there are elements of fiscal load levelling aleady: companies can choose a date for their annual returns; sales tax is charged continuosuly and collected quarterly; income tax is collected monthly or weekly. But with the ubiquitous digital computer the cost of the bureaucracy is now so low that the annual fiscal fiasco is technically unnecessary and it has become more of a liability than an asset.

What would be the advantages of scrapping it? Individuals could change their tax review date and interval to one that better suits them and this would spread the bureaucratic burden on the inland revenue over the year; the country would have a smoother tax revenue flow and less ]need to  borrow to fund public expenses; and publically funded organisations could budget on a trimester or even monthly basis and become more responsive to financial fluxes and changes in the system. It could be better for everyone - but it would require radical redesign. We are not equipped to do that – we would need to understand the principles of improvement science that relate to elimination of variation.

And what about the other annual cycle that plagues the population - the Education Niggle? This is the one that requires everyone with children of school age to be forced to take family holidays at the same time: Easter, Summer and Christmas – creating another batch-and-queue feast-and-famine cycle. This fiasco originated in the early 1800′s when educational reformers believed that continuous schooling was unhealthy and institutionalised when the Forster Elementary Education Act of 1870 provided partially state funded schools – especially for the poor – to provide a sufficient supply of educated workers for the burgeoning Industrial Revolution. Once the expectation of a long summer vacation was established it has been difficult to change.  More recent evidence shows that the loss of learning momentum has a detrimental effect on children not to mention the logistical problems created if both parents are working. Children are born all year round and have wide variation in their abilities and rate of learning and to impose an arbitrary educational cycle is clearly more for the convenience of the schools and teachers than aligned to the needs of children, their families or society.  As our required skills become more generic and knowledge focussed the need for effective and efficient continuous education has never been greater. Digital communication technology is revolutionising this whole sector and individually-tailored, integrated, life-long  learning and continuous assessment is now both feasible and more affordable.

And then there is healthcare!  Where do we start?

It is time to challenge and change our out-of-date no-longer-fit-for-purpose bureaucratic establishment designs – so there will be no shortage of opportunties or work for every competent and capable Improvement Scientist!

Twitt

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Never Events, Near Misses and Nailing Niggles

Saturday, March 17, 2012

Some events should NEVER happen – such as removing the wrong kidney; or injecting an anti-cancer drug designed for a vein into the spine instead; or sailing a cruise ship over a charted underwater reef; or driving a bus full of sleeping school children into a concrete wall.

 

But  these catastrophic irreversible and tragic Never Events do keep happening - rarely perhaps – but persistently. At the Never-Event investigation the Finger-of-Blame goes looking for the incompetent culprit while the innocent victims call for compensation.

And after the smoke has cleared and the pain of loss has dimmed another Never-Again-Event happens – and then another, and then another. Rarely perhaps – but not never.

Never Events are so awful that we remember them and we come to believe that they are not rare and we develop a constant nagging feeling of fear for the future. It is our fear that erodes our trust which leads to the paralysis that prevents us from acting.

The metaphor that is often used for this behaviour is the Swiss Cheese - the one on cartoons with lots of holes in it. The cheese represents a quality check - a barrier that catches and corrects mistakes before they cause irreversible damage. But the cheesy check-list is not perfect - it has holes in it – mistakes slip through unnoticed.

So multiple layers of cheesy checks are added in the hope that the holes in the earlier slices will be covered by the cheese in the later ones - and our experience shows that this multi-check design does reduce the number of mistakes that get through. But not completely. And when, by rare chance, holes in each slice line up then the error penetrates all the way through and a Never Event becomes a Real Catastrophe.  So, the typical recommendation from the after-the-never-event investigation is to add another layer of cheese to the stack - another check on the list on top of all the others.

But the cheese is not durable: it deteriorates over time with the incessant barrage of work and the pressure of increasing demand. The holes get bigger, the cheese gets thinner, and new holes appear. The inevitable outcome is the opening up of unpredictable, new paths through the cheese to a Never Event; more Never Events; more after-the-never-event investigation; and more slices of increasingly expensive and complex cheese added to the tottering, rotting heap.

A drawback of the Swiss Cheese metaphor is that it gives the impression that the slices are static and each cheesy check has a consistent position and persistent set of flaws in it. In reality this is not the case – the system behaves as if the slices are moving about: variation is jiggling , jostling and wobbling the whole cheesy edifice. This may not increase the risk of a Never Event  but it prevents the subsequent after-the-event investigation from discovering the specific conjunction of holes that caused it. The Finger of Blame cannot find a culprit and the cause is labelled a ”system failure” or an unlucky individual is implicated and is named, shamed, blamed and sacrificed to the Gods of Chance on the Alter of Hope! More often new slices of KneeJerk Cheese are added in the desperate hope of improvement – and creating an even greater burden of bureaucy than before – and paradoxically increasing the number of holes!  

Improvement Science offers a more rational, logical, effective and efficient approach to dissolving this messy, inefficient and ineffective design.

First it recognises that to prevent a Never Event then no errors should reach the last layer of cheese checking – the last opportunity to block the error path. Any errors that penetrate that far is a Near Miss and these will happen much more often than Never Events so they are the key to understanding and dissolving the problem.

Every Near Miss that is detected should be reported and investigated immediately – because that is the best time to identify the hole in the previous slice – before it slips out of sight. The goal of the investigation is understanding not accountability. Failure to report a near miss; failure to investigate it; failure to learn from it; failure to act on it; and failure to monitor the effect of the action are all errors of omission and are the greater management crimes.

The question to ask is “What error happened immediately before the Near Miss?”.  This event is called a Niggle. Focussing attention on this Niggle and understanding what, where, when, who and how it happened is the path to preventing the Niggle, the Near Miss and the Never Event.  Why is not the question to ask – especially when trust is low and cynicism and fear are high – the question to ask is “how”.  

The first action after Naming the Niggle is to design a counter-measure for the specific Niggle – to plug the hole to block the Niggle – to Nail the Niggle – and NOT to add another slice of KneeJerk cheese! The second necessary action is to treat that Niggle as a Near-Miss and to monitor it so when it happens again the preceeding Niggle can be named; and so on – working up the causal chain until the first Niggle in the chain is named and nailed!  Niggle naming and nailing is everyone’s responsibility – it is part of business-as-usual – and if leaders do not demonstrate the behaviour then followers will not do it.

So what effect would we expect?

To answer that question we need a better metaphor than our static stack of Swiss cheese slices: we need something more dynamic – something like a motorway!

Suppose you were to set out walking across a busy motorway with your eyes shut and your fingers in your ears – hoping to get to the other side without being run over. What is the chance that you will make it across safely?  It depends on how busy the traffic is and how fast you walk – but say you have a 50:50 chance of getting across one lane safely (which is the same chance as tossing a fair coin and getting a head) - what is the chance that you will get across all six lanes safely? The answer is the same chance as tossing six heads in a row: a 1-in-2 chance of surviving the first lane (50%), a 1 in 4 chance of getting across two lanes (25%), a 1 in 8 chance of making it across three (12.5%) …. to a 1 in 64 chance of getting across all six (1.6%). Said another way that is a 63 out of 64 chance of being run over somewhere which is a 98.4% chance of failure – near certain death! Hardly a Never Event.

What happens to our risk of being run over if the traffic in just one lane is stopped and that lane is now 100% safe to cross? Well you might think that it depends on which lane it is but it doesn’t – the risk of failure is now 31/32 or 96.8% irresepective of which lane it is – so not much improvement!

Is there a better improvement strategy?

What if we work collectively to just reduce the flow of Niggles in all the lanes at the same time - and suppose we are all able to reduce the risk of a Niggles in our lane-of-influence from 1-in-2 to 1-in-6. How we do it is up to us. To illustrate the benefit we replace our coin with a six-sided die (no pun intended) and we only “die” if we throw a 1.  What happens to our pedestrian’s probability of survival? The chance of surviving the first lane is now 5/6 (83.3%), and both first and second 5/6 x 5/6 = 25/36 (69%.4) and so on to all six lanes which is 5/6 x 5/6 x 5/6 x 5/6 x 5/6 x 5/6 = 15625/46656 = 33.3% which is a lot better than our previous 1.6%!  And what if we keep plugging the holes in our bits of the cheese and we increase our individual lane success rate to 95% – our pedestrian probability of survival is now 73.5%. The chance of a catastropic event becomes less and less. 

The arithmetic may be a bit scary but the message is clear: to prevent the Never Events we must reduce the Near Misses and to to do that we investigate every Near Miss and Nail all the Niggles that are exposed.

This strategy will improve the safety of our system and it has another positive benefit – it will free up our Near Miss investigation team to do something else: it frees them to re-design the system so that Niggles cannot happen at all - they become Never Events too - and the earlier in the path that safety-design happens the better – because it renders the other layers of cheesocracy irrelevant.

Just imagine what would happen in a real system if we did that …

And now try to justify not doing it …

And now consider what an individual, team and organisation would need to learn to do this …

And if you seek guidance then look no further than the FISH …

Twitt

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The Journal Of Improvement Science

Saturday, March 10, 2012

Improvement Science encompasses research, improvement and audit and includes both subjective and objective dimensions. An essential part of collective improvement is sharing our questions and learning with others.

From the perspective of the learner it is necessary to be able to trust that what is shared is valid and from the perspective of the questioner it is necessary to be able to challenge with respect.

Sharing new knowledge is not the only purpose of publication: for academic organisations it is also a measure of performance so there is a academic peer pressure to publish both quantity and quality - an academic’s career progression depends on it.  This pressure has created a whole industry of its own – the academic journal - and to ensure quality is maintained it has created the scholastic peer review process. The  intention is to filter submitted papers and to only publish those that are deemed worthy – those that are believed by the experts to be of most value and of highest quality.  There are several criteria that editors instruct their volunteer ”independent reviewers” to apply such as originality, relevance, study design, data presentation and balanced discussion. The purpose is to weed out the unworthy – but this process was designed over a hundred years ago. It has stood the test of time - but – it was designed specifically for research and before the invention of the Internet, of social media and the emergence of Improvement Science.

So fast-forward to the present and to a world where improvement is now seen to  be complementary to research and audit; where time-series statistics is viewed as a valid and complementary data analysis method; and where we are all able to globally share information with each other and learn from each other in seconds through the medium of modern electronic communication. Given these changes is the traditonal academic peer review journal system still fit for purpose?

One way to approach this question is from the perspective of the customers of the system - the people who read the published papers and the people who write them.  What niggles do they have that might point to opportunities for improvement?

Well, as a reader:

My first niggle is to have to pay a large fee to download an electronic copy of a published paper before I can read it. All I can see is the abstract which does not tell me what I really want to know – I want to see the details of the method and the data not just the authors editied highlights and conclusions.

My second niggle is the long lead time between the work being done and the paper being published – often measured in years! This means that the published news is old news  useful for reference maybe but useless for stimulating conversation and innovation.

My third niggle is what is not published – the well-designed and well-conducted studies that have negative outcomes; lessons that offer as much opportunity for learning as the positive ones.  This is not all - many studies are never done or never published because the outcome might be perceived to adversely affect a commercial or “political” interest.

My fourth niggle is the almost complete insistence on the use of empirical data and comparative statistics – data from simulation studies being treated as “low-grade” and the use of time-series statistics as “low-rigour”.  Sometimes simulations and uncontrolled experiments are the only feasible way to answer real-world questions and there is more to improvement than a RCT (randomised controlled trial). 

From the perspective of an author of papers I have some additional niggles – the secrecy that surrounds the review process (you are not allowed to know who has reviewed the paper); the lack of constructive feedback that could help an inexperienced author to improve their studies and submissions; and the insistence on assignment of copyright to the publisher - as an author you have to give up ownership of your creative output.

That all said there are many more nuggets to the peer review process than niggles and to a very large extent what is published can be trusted – which cannot be said for the more popular media of news, newspapers, blogs, tweets, and the continuous cacophony of partially informed prejudice, opinion and gossip that goes for “information”.

So, how do we keep the publication baby and lose the process bath water? How do we keep the nuggets and dump the niggles?

What about a Journal of Improvement Science with a design specification along the lines of:

1. Fully electronic, online and free to download – no printed material.
2. Community of sponsors - who publically volunteer to support and assist authors.
3. Continuously updated ranking system – where readers vote for the most useful papers.
4. Authors can revise previously published papers – using feedback from peers and readers.
5. Authors retain the copyright – they can copy and distribute their own papers as much as they like.
6. Expected use of both time-series and comparative statistics where appropriate.
7. Short publication lead times – typically days.
8. All outcomes are publishable – the warts and all stories.
9. Published authors are automatically eligible to be sponsors for future submissions.
10. No commercial sponsorship or advertising.

So, all we need to get the ball rolling is to publish one paper - here we go then …

Dodds SR, Silvester KM. The Emergency Pathway Horned Gaussian. J Improvement Science 2012:1;1-14. 

STOP PRESS: JOIS web portal launched: Click here to enter. 

Twitt

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Resetting Our Systems

Saturday, March 3, 2012

 Our bodies are amazing self-monitoring and self-maintaining systems – and we take them completely for granted! The fact that it is all automatic is good news for us because it frees us up to concentrate on other things - BUT – it has a sinister side too.  Our automatic monitor-and-maintain design does not imply what is maintained is healthy - the system is just designed to keep itself stable.

Take our blood pressure as an example. We all have two monitor-and-maintain systems that work together – one that stablises short-term changes in blood pressure (such as when you recline, stand, run, fight, and flee) and the other that stablises long-term changes. The image above is a very simplified version of the long-term regulation system!

 Around one quarter of all adults are classified as having high blood pressure – which means that it is consistently higher than is healthy - and billions of £ are spent every year on drugs to reduce blood pressure in millions of people.  Why is this an issue? How does it happen? What lessons are there for the student of Improvement Science?

High blood pressure (or hypertension) is dangerous – and the higher it is the more dangerous it is. It is called the silent killer and the reason is that it is called silent is because there are no symptoms. The reason it called a killer is because over time it causes irreversible damage to vital organs – the heart, kidneys and arteries.

The vast majority of hypertensives have what is called essential hypertension – which means that there is no obvious single cause and it is believed that this is the result of their system gradually becoming reset so that it actively maintains the high blood pressure.  This is just like gradually increasing the setting on the thermostat in our house – say by just 0.01 degree per week – not much and not even measurable – but over time the cumulative effect would have a big impact on our heating bills!

So, what resets our long-term blood pressure regulation system? It is believed that the main culprit is stress because when we feel stressed our bodies react in the short-term by pushing our blood pressure up – it is called the fright-fight-flight response. If the stress is repeated time and time again our pressure-o-stat becomes gradually reset and the high blood pressure is then maintained, even when we do not feel stressed. And we do not notice – until something catastrophic happens! And that is too late.

The same effect happens in organisations except that the pressure is emotional and is created by the stress of continually fighting to meeting performance targets. The result is a gradual resetting of our expectations and behaviours and the organisation develops emotional hypertension which leads to irreversible damage to the organisations culture. This emotional creep goes largely unnoticed until a catastrophic event happens – and if severe enough the organisation will be crippled and may not survive. The Mid Staffs Hospital catastrophe is a real and recent example of cultural creep in a healthcare organisation and is a stark lesson to us all. 

So what is the solution?

The first step is to realise that we cannot just rely on hope, ignore the risk and wait for the early warning  symptoms – by that time the damage may be irreversible; or the catastrophe may get us without warning. We have to actively look for the signs of the creeping cultural change - and we have to do that over a long period of time because it is gradual. So, if we have just be jolted out of denial by a too-close-for-comfort expereince then we need to adopt a different strategy and use an external absolute reference – an emotionally and culturally healthy organisation.

The second step is to adopt a method that will tell us reliably if there is a significant shift in our emotional pressure and a method that is sensitive eneough to alert  us before it goes outside a safe range – because we want to intervene as early as possible and only when necessary;  masterly inactivity and cat-like observation according to one wise medical mentor.  

The third step is to actively remove as many of the stressors as possible – and for an organisation this means replacing DRATs (Delusional Ratios and Arbitrary Targets) with well-designed specification limits; and replacing reactive firefighting with proactive feedback. This is the role of the organisations leaders - they must walk the talk.

The fourth step is to actively reduce the emotional pressure but to do it gradually because the whole system needs to adjust – dropping the emotional pressure too quickly is as dangerous as discounting its importance.

The key to all of this is the appropriate use of data and statistics because the small long-term shifts are hidden in the large short-term variation – and this is where many get stuck because they are not aware that there two different sorts of statistics. The  correct sort for monitoring systems is called time-series statistics and it not the same as the statistics that we learn at school and university. This is a shame really because time-series statistics is much more applicable to every day life problems such as managing our blood pressure, our weight, our finances, and the cultural health of our organisations.

Fortunately time-series statistics is easier to learn and use than school statistics so to get started on resetting your personal and organisational emot-o-stat please help yourself to the complimentary guide by clicking here.

Twitt

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Renewal

Saturday, February 25, 2012

“Old habits die hard” so the saying goes – but not all habits are bad. Most are good. And in our quest for improvement sometimes we have to challenge a good habit and replace it with an even better one. And doing that is tough – much tougher than challenging a bad habit.

Sometimes the challenge to our comfort zone comes from Reality – and we suddenly lose something very dear to us that has become such an integral and important part of our lives that when it is taken away we feel the acute pain of loss. We are left with an open emotional wound – and we have to give ourselves time and space to recover and to heal.

With the clarity of hindsight we can see that we knew all along what would happen – we just did not know when it would happen - and we were in a state of hope-for-the-best-for-now. After all, why suffer the perpetual pain of worry when the outcome is inevitable? Well, it may be inevitable but it does not mean it needs to be imminent! So a healthy dose of anxiety is OK. Complacency is the precursor to a catastrophe and most of our catastrophes are preventable – so keeping busy doing what we have always done is not an effective strategy for warding off a preventable catastrophe.

A more effective strategy is to worry just enough to keep our complacency level low and to keep us alert to threats because in averting these we are forced to challenge ourselves and in doing that we discover hidden opportunities.

The outcome is renewal.

Sometimes though we have to learn the lesson the hard way.

Twitt

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Tilt-Nudge-Poke

Saturday, February 18, 2012

Improvement requires change and change requires learning – so knowing how to guide learning is an essential skill for an improvement scientist. There is a common belief that we learn by watching and listening – and therefore that we can teach by showing and talking. This belief is incorrect. We all learn by doing something different and comparing what we perceived with what we predicted. So what prompts us to do something different?  The answer is we are nudged.

We learn and change over time as a result of a series of small nudges – the effects of which add up. We can simulate this behaviour easily.

Find a tray and a piece of kitchen paper and draw two circles on the paper. Put the paper on the tray and then put a heap of granulated sugar on the leftmost circle. It will stay where it is placed. Hold the tray horizontal and nudge the tray repeatedly by tapping on its edge with a finger. The heap of sugar will spread out in all directions – and only a small proportion goes to wards the second circle – the intended direction of improvement.

Now repeat the simulation but this time tilt the tray slightly in the direction of improvement so that the heap stays put – and then nudge the tray. The heap of sugar will spread out and more will move in the direction of the second circle – the improvement goal.  The nudging is necessary but it is not sufficient - a tilt in the intended direction of improvement is also necessary but not sufficient. Actual improvement requires both.

Life provides a continuous series of random nudges – so in reality all that is needed to improve is to set the direction of tilt – which implies making it easier to move in the direction of improvement than away from it. Setting the direction of tilt is one facet of leadership – and it requires aligning the reward with the improvement. Very often this is not done and improvement becomes an uphill struggle that is unsustainable and unmaintainable.

Even when the reward is aligned with the improvement we cannot guarantee success – there is another factor.

Now repeat the sugar flow simulation and this time create a physical barrier between the heap and the goal – such as a row of sugar cubes or a fold in the kitchen paper –  to create a barrier that the tilting and nudging is not enough to move. Now the sugar flow will be blocked by the barrier and our temptation is to increase the tilt and apply bigger nudges – but this increase-the-pressure-by-pushing-harder strategy has a risk because when the barrier eventially breaks the backlog of sugar lurches forward in an uncontrolled surge. Uncontrolled behaviour is not what we want.

So the second role of the improvement scientist is to help to remove the barriers – and this requires a more focussed action than a tilt or a nudge. It requires a poke.

Pokes are uncomfortable for the poker and for the pokee – and the skill to master the art of the positive poke. Negative pokes are surprising, emotionally painful and result in an angry reaction which damages the pokee. Positive pokes are surprising, emotionally uncomfortable and result in an excited proaction which develops the pokee.

So now poke the barrier where it crosses the line that joins the two circles so that it is reduced or removed at that point - and then tilt and nudge as before. The backlog of sugar will funnel through the gap in the barrier in a well-focussed stream in the direction of improvement. The barrier actually helps to direct the the flow so a precise poke is necessary.

The effective improvement scientist needs to know how to tilt, when to nudge and where to poke.

 

Twitt

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Homeostasis

Saturday, February 11, 2012

Improvement Science is not just about removing the barriers that block improvement and building barriers to prevent deterioration – it is also about maintaining acceptable, stable and predictable performance.

In fact most of the time this is what we need our systems to do so that we can focus our attention on the areas for improvement rather than running around keeping all the plates spinning.  Improving the ability of a system to maintain itself is a worthwhile and necessary objective.

Long term stability cannot be achieved by assuming a stable context and creating a rigid solution because the World is always changing. Long term stability is achieved by creating resilient solutions that can adjust their behaviour, within limits, to their ever-changing context.

This self-adjusting behaviour of a system is called homeostasis.

The foundation for the concept of homeostasis was first proposed by Claude Bernard (1813-1878) who unlike most of his contemporaries, believed that all living creatures were bound by the same physical laws as inanimate matter.  In his words: ”La fixité du milieu intérieur est la condition d’une vie libre et indépendante” (“The constancy of the internal environment is the condition for a free and independent life”).

The term homeostasis is attributed to Walter Bradford Cannon (1871 – 1945) who was a professor of physiology at Harvard medical school and who popularized his theories in a book called The Wisdom of the Body (1932). Cannon described four principles of homeostasis:

  1. Constancy in an open system requires mechanisms that act to maintain this constancy.
  2. Steady-state conditions require that any tendency toward change automatically meets with factors that resist change.
  3. The regulating system that determines the homeostatic state consists of a number of cooperating mechanisms acting simultaneously or successively.
  4. Homeostasis does not occur by chance, but is the result of organised self-government.

Homeostasis is therefore an emergent behaviour of a system and is the result of organised, cooperating, automatic mechanisms. We know this by another name – feedback control - which is passing data from one part of a system to guide the actions of another part. Any system that does not have homeostatic feedback loops as part of its design will be inherently unstable - especially in a changing environment.  And unstable means untrustworthy.

Take driving for example. Our vehicle and its trusting passengers want to get to their desired destination on time and in one piece. To achieve this we will need to keep our vehicle within the boundaries of the road – the white lines – in order to avoid “disappointment”.

As their trusted driver our feedback loop consists of a view of the road ahead via the front windscreen; our vision connected through a working nervous system to the muscles in ours arms and legs; to the steering wheel, accelerator and brakes; then to the engine, transmission, wheels and tyres and finally to the road underneath the wheels. It is quite a complicated multi-step feedback system – but an effective one. The road can change direction and unpredictable things can happen and we can adapt, adjust and remain in control.  An inferior feedback design would be to use only the rear-view mirror and to steer by looking at the whites lines emerging from behind us. This design is just as complicated but it is much less effective and much less safe because it is entirely reactive.  We get no early warning of what we are approaching.  So, any system that uses the output performance as the feedback loop to the input decision step is like driving with just a rear view mirror.  Complex, expensive, unstable, ineffective and unsafe.     

As the number of steps in a process increases the more important the design of  the feedback stabilisation becomes - as does the number of ways we can get it wrong:  Wrong feedback signal, or from the wrong place, or to the wrong place, or at the wrong time, or with the wrong interpretation – any of which result in the wrong decision, the wrong action and the wrong outcome. Getting it right means getting all of it right all of the time - not just some of it right some of the time. We can’t leave it to chance – we have to design it to work.

Let us consider a real example. The NHS 18-week performance requirement.

The stream map shows a simple system with two parallel streams: A and B that each has two steps 1 and 2. A typical example would be generic referral of patients for investigations and treatment to one of a number of consultants who offer that service. The two streams do the same thing so the first step of the system is to decide which way to direct new tasks - to Step A1 or to Step B1. The whole system is required to deliver completed tasks in less than 18 weeks (18/52) - irrespective of which stream we direct work into.   What feedback data do we use to decide where to direct the next referral?

The do nothing option is to just allocate work without using any feedback. We might do that randomly, alternately or by some other means that are independent of the system.  This is called a push design and is equivalent to driving with your eyes shut but relying on hope and luck for a favourable outcome. We will know when we have got it wrong – but it is too late then – we have crashed the system! 

A more plausible option is to use the waiting time for the first step as the feedback signal – streaming work to the first step with the shortest waiting time. This makes sense because the time waiting for the first step is part of the lead time for the whole stream so minimising this first wait feels reasonable - and it is - BUT only in one situation: when the first steps are the constraint steps in both streams [the constraint step is one one that defines the maximum stream flow].  If this condition is not met then we heading for trouble and the map above illustrates why. In this case Stream A is just failing the 18-week performance target but because the waiting time for Step A1 is the shorter we would continue to load more work onto the failing  stream – and literally push it over the edge. In contrast Stream B is not failing and because the waiting time for Step B1 is the longer it is not being overloaded – it may even be underloaded.  So this “plausible” feedback design can actually make the system less stable. Oops!

In our transport metaphor – this is like driving too fast at night or in fog – only being able to see what is immediately ahead – and then braking and swerving to get around corners when they “suddenly” appear and running off the road unintentionally! Dangerous and expensive.

With this new insight we might now reasonably suggest using the actual output performance to decide which way to direct new work – but this is back to driving by watching the rear-view mirror!  So what is the answer?

The solution is to design the system to use the most appropriate feedback signal to guide the streaming decision. That feedback signal needs to be forward looking, responsive and to lead to stable and equitable performance of the whole system – and it may orginate from inside the system. The diagram above holds the hint: the predicted waiting time for the second step would be a better choice.  Please note that I said the predicted waiting time – which is estimated when the task leaves Step 1 and joins the back of the queue between Step 1 and Step 2. It is not the actual time the most recent task came off the queue: that is rear-view mirror gazing again.

When driving we look as far ahead as we can, for what we are heading towards, and we combine that feedback with our present speed to predict how much time we have before we need to slow down, when to turn, in which direction, by how much, and for how long. With effective feedback we can behave proactively, avoid surprises, and eliminate sudden braking and swerving! Our passengers will have a more comfortable ride and are more likely to survive the journey! And the better we can do all that the faster we can travel in both comfort and safety – even on an unfamiliar road.  It may be less exciting but excitement is not our objective. On time delivery is our goal.

Excitement comes from anticipating improvement – maintaining what we have already improved is rewarding.  We need both to sustain us and to free us to focus on the improvement work! 

 

Twitt

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The Safety Line in the Quality Sand

Saturday, February 4, 2012

Improvement Science is about getting better - and it is also about not getting worse. These are not the same thing. Getting better requires dismantling barriers that block improvement. Not getting worse requires building barriers to block deterioration.

When things get tough and people start to panic it is common to see corners being cut and short-term quick fixes taking priority over long-term common sense.  The best defense against this self-defeating behaviour is the courage and discipline to say “This is our safety line in the quality sand and we do not cross it”.  This is not dogma it is discipline. Dogma is blindness; discipline is wisdom.

Leaders show their mettle when times are difficult not when times are easy.  A leader who abandons their espoused principles when under pressure is a liability to themselves and to their teams.

The barrier that prevents descent into chaos is not the leader – it is the principle that there is a minimum level of acceptable quality – the line that will not be crossed. So when a decision needs to be made between safety and money the choice is not open to debate. Safety and quality come first.  

Only those who believe that higher quality always costs more will argue for compromise. So when the going gets tough those who question the Safety Line in the Quality Sand are the ones to challenge by respectfully reminding them of their own principles. This will require courage because they might well be the ones in the seats of power – but when leaders compromise their own principles they have sacrificed their credibility and abdicated their power.

Twitt

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Is Our System Constipated?

Saturday, January 28, 2012

There are some very common system ailments that we do not talk about in public – they are not socially acceptable topics of conversation.  We all know they exist because we all suffer from them at sometime or other - and some more than others.

Our problem is “how do we solve sometheng that no one wants to own up to and talk about?”  Grin-and-bear it? Trial-and-error? Or seek competent, confidential, professional assistance?

One such ailment is chronic system constipation. Yes – I said it.

The usual symptoms are recurrent, severe pains in the middle management area associated with ominous rumblings, intermittent eruptions of unpleasant hot ”air” and accompanied by infrequent, unpredictable and often inconsequential output.

The signs are also characterstic: bloated budgets, capital distention and a strained and pained appearance of the executive visage.

The commonest finding on further investigation is accumulation of work in progress inside the organisation that is caused by functional bottlenecks, accumulation of undigestable red-tape, and process paralysis.  This finding confirms the diagnosis.

The more desperate organisations may seek help from corporate quacks who confidently prescribe untested yet expensive remedies such as mangement purges and corporate restructure.  These drastic actions only serve to impoverish the patient and exacerbate the problem. They are also sometimes fatal. 

The patient who avoids or survives the quacks may seek competent help – and reluctantly submit themselves to a more intimate examination of their orifices.  This proceeds in a back-office to front-of-house order looking for accumulations of work-in-progress (WIP) and their associated causes.  The usual finding is apathetic and demoralised staff burned out by over-complicated, error-prone processes and pushing against turgid bureaucracy. 

The first stage of treatment is to relieve the obstruction that is closest to the discharge orifice first. Often the intimate examination itself is sufficient to stimulate spontaneous ejection of the offending obstruction; sometimes a corporate-level enema is required to facilitate the process.  Either way the relief is welcome, dramatic and immediate; and is usually followed by vigorous expulsion of the remaining offensive material and restoration of both regular flow and disspiation of the gaseous bloating.

The timid or inexperienced corporoproctologist may be tempted to try exogenous stimulants instead – an inspiring podcast or an executive awayday perhaps.  The palliative attempt may distract attention and sooth the discomfort but the effect is short-lived and the symptoms soon return; often with a vengeance.

The more courageous and experienced Improvement Science practitioner knows that ”if you don’t put your finger in it you will put your foot in it“ and they come prepared with the organisational equivalent of rubber gloves and lubrication: flip charts and hot coffee.

So to avoid the squirming discomfort of the probing questions it is better to seek advice well before this stage. And you may not be surprised to hear that it is all common-sense:

  • avoid all high-bureaucracy diets or high-technology quick-fixes,
  • stimulate the flow of creativity with regular service improvement exercises,
  • monitor continuously for corporate expansion and treat early with a high-challenge dialog.

But we know all this already – don’t we?

Twitt

Posted in Reflections, Stories | 2 Comments »

Eureka!

Saturday, January 21, 2012

This exclamation is most famously attributed to the ancient Greek scholar Archimedes who reportedly proclaimed “Eureka!” when he stepped into a bath and noticed that the water level rose. He suddenly realised that the volume of water displaced must be equal to the volume of the part of his body he had submerged but this was not why he was allegedly so delighted: he had been trying to solve a problem posed by Hiero of Syracuse who needed to know the purity of gold in an irregular shaped votive crown. Hiero suspected that his goldsmith was diluting the pure gold with silver and Archimedes  knew that the density of pure gold was different from gold-silver alloy and he suddenly realised that he could now measure the volume of the crown and with the weight he could calculate the density – without damaging the crown.

The story may or may not be true, but the message is important – new understanding often  appears in a “flash of insight” when a conscious experience unblocks an unconscious conflict. Reality provides the nudge.

Improvement means change, change means learning, and learning means new understanding.  So facilitating improvement boils down to us a series of reality nudges that change our understanding step-by-step.

The problem is that reality is messy and complicated and noisy. There are reality nudges coming at us from all directions and all the time - and to avoid being overwhelmed we filter most of them out – the ones we do not understand.  This unconscious habit of discounting the unknown creates the state of blissful ignorance but has the downside of preventing us from learning and therefore preventing us from improving.

Occasionally a REALLY BIG REALITY NUDGE comes along and we are forced to take notice - this is called a smack – and it is painful and has the downside of creating an angry backlash.

The famous scientist Louis Pasteur is reported to have said “Chance favours the prepared mind” which means that when conditions are right (the prepared mind) a small, random nudge (chance) can trigger a Eureka effect.  What he is saying is that to rely on chance to improve we must prepare the context first.

The way of doing this is called structured reality – deliberately creating a context so the reality nudge has maximum effect.  So to learn and improve and at the same time avoid painful smacks we need to structure the reality so that small nudges are effective – and that is done using carefully designed reality immersion experiences.

The effect is remarkable – it is called the Eureka effect – and it is a repeatable and predictable phenomenon.

This is how the skills of Improvement Science are spread. Facilitators do not do it by delivering a lecture; or by distributing the theory in papers and books; or by demonstrating their results as case studies; or by dictating the actions of others.  Instead they create the context for learning and, if reality does not oblige, at just the right time and place they apply the nudge and …. Eureka!

The critical-to-success factor is creating the context – and that requires an effective design – it cannot be left to chance. 

Twitt

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The Hierarchy of Constraints

Saturday, January 14, 2012

Improvements need to be sustained - but not forever. They should be worthwhile on their own and provide a foundation for future improvement. Improvement flows and it does so down the path of least resistance. Improvement will not flow easily up the path of most resistance. Resistance to flow is the result of a constraint.

 Many things flow - water, energy, money, data, ideas, knowledge, influence - the list is endless - so the list of possible constraints is similarly endless.  But not all constraints are the same: a constraint that limits the flow of water – a dam for instance – does not limit the flow of ideas.

The flows and their constraints can be arranged on a contiuum with one end labelled ”Physics” and the other end labelled “Paradigms”.  Physical flows are constrained by the Laws of the Universe which are absolute and stable. Philosophical flows are constrained by beliefs which are arbitrary and mutable.

This spectrum is often viewed as a hierarchy – with Paradigms at the top and Physics at the bottom – and between these limits there is a contiuum of constraints.  The Paradigm is completely abstract and intangible and is made actual through Policy, guided by Politics, and enforced by Police.  The root of all these words is ”poli” which means “many” and implies the collective of people. So, a Policy is an arbitrary constraint that limits what is and what is not allowed. It is the social white line that indicates what behaviours the collective expect from the individual.  A Policy is implemented as a Process.

What actually happens is constrained by the Physics. Irrespective of the Paradigm, Policy and Process – if the Laws of Physics say something is impossible then it does not happen. It is impossible to squeeze, store or reverse time. It is impossible to do something that requires 30 mins of time in 5 minutes; it is impossible to store time to use later; it is impossible to rewind time go back to a previous point in time.

From the perspective of reality our hierarchy of constraints is upside down – Physics dictates what is possible irrespective of what the Paradigm indicates is believable.  What is believable may not be possible; and what is possible may not be believed.

Improvement Science is the art of the possible – of what the Laws of Physics do not forbid – a wide vista of opportunity.  It is now that our Paradigm acts as the constraint – and Improvement Science is the ability to challenge our Paradigm.  Only then can we create the Policy and the Process that will deliver actual, valuable and sustainable improvement.

Some parts of our Paradigm are necessary to provide explanation and meaning. Other parts are not needed – they are our “belief baggage” – the assumptions that we have picked up along the way; the mumbo-jumbo that obscures the true message. When we focus on the mumbo-jumbo we miss the message and we open the door to cynicism and distrust.

Our challenge is to separate the two – the wheat from the chaff; the diamond from the dross and the pearl-of-wisdom hidden in the ocean-of-data.  What do we actively include? What do we actively exclude? What do we actively remove? What do we actively improve?  We need to monitor all four parts of our Paradigm and that task is what The 4N Chart® was designed to help us do.

Click here get The 4N Chart template and here to get The 4N Chart instructions.

Twitt

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Steps, Streams, Silos and Swamps.

Saturday, January 7, 2012

The late Steve Jobs created a world class company called Apple – which is now the largest and most successful technology company – eclipsing Microsoft.  The secret of the success of Apple is laid out in Steve Jobs biography – and can be stated in one word. Design.

Apple designs, develops and delivers great products and services  - ones that people want to own and to use.  That makes them cool. What is even more impressive is that Steve Jobs has done this in more than once and has reinvented more than one market: Apple Computers and the graphical personal computer;  Pixar and animated films; and Apple again with digital music, electronic publishing; and mobile phones.

The common themes are digital technology and end-to-end seamless integrated design of chips, devices, software, services and shops. Full vertical integration rather like Henry Ford’s verically integrated iron-ore to finished cars production line.  The Steve Jobs design paradigm is simplicity. It is much more difficult to design simplicity than to evolve complexity and his reputation was formidable. He was a uncompromising perfectionist who sacrificed feelings on the alter of design perfection. His view of the world was binary – it was either great or crap – meaning it was either moving towards perfection or away from it.

What Steve Jobs created was a design stream out of which must-have products and services flowed – and he did it by seeing all the steps as part of one system and aligned with one purpose.  He did not allow physical or psychological silos to form and he did this by challenging anything and everything.  Many could not work in this environment and left, many others thrived and delivered far beyond what they believed they could do.

Other companies were swamps. Toxic emotional waste swamps of silos, politics and turf wars.  Apple computers itself when through a phase when Steve Jobs was “ejected” and without its spiritual leader the company slipped downhill. He was enticed back and Apple was reborn and went on to create the iMac, iPod, iTunes, iPhone, iPad and now iCloud. Revolutioning the world of digital commnication.

The image above is a satellite view of a delta – a complex network of interconnected streams created by a river making its way to the sea through a swamp.  The structure of the delta is constantly changing and evolving so it is easy to get lost it in, to get caught in a dead-end, or stuck in the mud. Only travel by small boat is possible and that is often both ineffective and inefficient.  

Many organistions are improvement science swamps. The stream of innovative ideas gets fragmented by the myriad of everchanging channels; caught in political dead-ends; and stuck in the mud of bureaucracy.  Only small, skillfully steered ideas will trickle  through – but this trickle is not enough to keep the swamp from silting up. Eventually the resistance to change reaches a critical level and the improvement stream is forced to change course – diverting the flow of change away from the swamp – and marooning the stick-in-the-muds to slowly sink and expire in the bureaucratic gloop that they spawned.

Steve Jobs’ legacy to us is a lesson. To create a system that continues to deliver and delight we need to start by learning how to design the steps, then to design the streams of steps to link seamlessly, and finally to design the system of streams to synergise as sophisticated simplicity.

Improvement cannot be left to chance in the blind hope that excellence will evolve spontaneously. Evolution is both ineffective and inefficient and is more likely to lead to dissipated and extravagant complexity than aligned and elegant simplicity.

Improvement is a science that sits at the cross-roads of humanity and technology.

 

Twitt

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