Resilience

The rise in the use of the term “resilience” seems to mirror the sense of an accelerating pace of change. So, what does it mean? And is the meaning evolving over time?

One sense of the meaning implies a physical ability to handle stresses and shocks without breaking or failing. Flexible, robust and strong are synonyms; and opposites are rigid, fragile, and weak.

So, digging a bit deeper we know that strong implies an ability to withstand extreme stress while resilient implies the ability to withstanding variable stress. And the opposite of resilient is brittle because something can be both strong and brittle.

This is called passive resilience because it is an inherent property and cannot easily be changed. A ball is designed to be resilient – it will bounce back – and this inherent in the material and the structure. The implication of this is that to improve passive resilience we would need to remove and to replace with something better suited to the range of expected variation.

The concept of passive resilience applies to processes as well, and a common manifestation of a brittle process is one that has been designed using averages.

Processes imply flows. The flow into a process is called demand, while the flow out of the process is called activity. What goes in must come out, so if the demand exceeds the activity then a backlog will be growing inside the process. This growing queue creates a number of undesirable effects – first it takes up space, and second it increases the time for demand to be converted into activity. This conversion time is called the lead-time.

So, to avoid a growing queue and a growing wait, there must be sufficient flow-capacity at each and every step along the process. The obvious solution is to set the average flow-capacity equal to the average demand; and we do this because we know that more flow-capacity implies more cost – and to stay in business we must keep a lid on costs!

This sounds obvious and easy but does it actually work in practice?

The surprising answer is “No”. It doesn’t.

What happens in practice is that the measured average activity is always less than the funded flow-capacity, and so less than the demand. The backlogs will continue to grow; the lead-time will continue to grow; the waits will continue to grow; the internal congestion will continue to grow – until we run out of space. At that point everything can grind to a catastrophic halt. That is what we mean by a brittle process.

This fundamental and unexpected result can easily and quickly be demonstrated in a concrete way on a table top using ordinary dice and tokens. A credible game along these lines was described almost 40 years ago in The Goal by Eli Goldratt, originator of the school of improvement called Theory of Constraints. The emotional impact of gaining this insight can be profound and positive because it opens the door to a way forward which avoids the Flaw of Averages trap. There are countless success stories of using this understanding.


So, when we need to cope with variation and we choose a passive resilience approach then we have to plan to the extremes of the range of variation. Sometimes that is not possible and we are forced to accept the likelihood of failure. Or we can consider a different approach.

Reactive resilience is one that living systems have evolved to use extensively, and is illustrated by the simple reflex loop shown in the diagram.

A reactive system has three components linked together – a sensor (i.e. temperature sensitive nerves endings in the skin), a processor (i.e. the grey matter of the spinal chord) and an effector (i.e. the muscle, ligaments and bones). So, when a pre-defined limit of variation is reached (e.g. the flame) then the protective reaction withdraws the finger before it becomes damaged. The advantage this type of reactive resilience is that it is relatively simple and relatively fast. The disadvantage is that it is not addressing the cause of the problem.

This is called reactive, automatic and agnostic.

The automatic self-regulating systems that we see in biology, and that we have emulated in our machines, are evidence of the effectiveness of a combination of passive and reactive resilience. It is good enough for most scenarios – so long as the context remains stable. The problem comes when the context is evolving, and in that case the automatic/reflex/blind/agnostic approach will fail – at some point.


Survival in an evolving context requires more – it requires proactive resilience.

What that means is that the processor component of the feedback loop gains an extra feature – a memory. The advantage this brings is that past experience can be recalled, reflected upon and used to guide future expectation and future behaviour. We can listen and learn and become proactive. We can look ahead and we can keep up with our evolving context. One might call, this reactive adaptation or co-evolution and it is a widely observed phenomenon in nature.

The usual manifestation is this called competition.

Those who can reactively adapt faster and more effectively than others have a better chance of not failing – i.e. a better chance of survival. The traditional term for this is survival of the fittest but the trendier term for proactive resilience is agile.

And that is what successful organisations are learning to do. They are adding a layer of proactive resilience on top of their reactive resilience and their passive resilience.

All three layers of resilience are required to survive in an evolving context.

One manifestation of this is the concept of design which is where we create things with the required resilience before they are needed. This is illustrated by the design squiggle which has time running left to right and shows the design evolving adaptively until there is sufficient clarity to implement and possibly automate.

And one interesting thing about design is that it can be done without an understanding of how something works – just knowing what works is enough. The elegant and durable medieval cathedrals were designed and built by Master builders who had no formal education. They learned the heuristics as apprentices and through experience.


And if we project the word game forwards we might anticipate a form of resilience called proactive adaptation. However, we sense that is a novel thing because there is no proadaptive word in the dictionary.

PS. We might also use the term Anti-Fragile, which is the name of a thought-provoking book that explores this very topic.

The A.B.C.D.E. of Improvement

In medicine we use checklists as aide memoirs because they help us to avoid errors of omission, especially in an emergency when we are stressed and less able to think logically.

One that everyone learns if they do a First Aid course is A.B.C. and it stands for Airway, Breathing, Circulation.  It is designed to remind us what to do first because everything that follows depends on it, and then what to do next, and so on.  Avoiding the errors of omission improves outcomes.


In the world of improvement we are interested in change-for-the-better and there are many models of change that we can use to remind us not to omit necessary steps.

One of these is called the Six Steps model (or trans-theoretical model to use the academic title) and it is usually presented as a cycle starting with a state called pre-contemplation.

This change model arose from an empirical study of people who displayed addictive behaviours (e.g. smoking, drinking, drugs etc) and specifically, those who had overcome them without any professional assistance.

The researchers compared the stories from the successful self-healers with the accepted dogma for the management of addictions, and they found something very interesting.  The dogma advocated action, but the stories showed that there were some essential steps before action; steps that should not be omitted.  Specifically, the contemplation and determination steps.

If corrective actions were started too early then the success rate was low.  When the pre-action steps were added the success rate went up … a lot!


The first step is to raise awareness which facilitates a shift from pre-contemplation to contemplation.  The second step is to provide information that gradually increases the pros for change and at the same time gradually decreases the cons for change.

If those phases are managed skillfully then a tipping point is reached where the individual decides to make the change and moves themselves to the third step, the determination or planning phase.

Patience and persistence is required.  The contemplation phase can last a long time.  It is the phase of exploration, evidence and explanation. It is preparing the ground for change and can be summed up in one word: Study.

Often the trigger for determination (i.e. Plan) and then action (i.e. Do) is relatively small because when we are close to the tipping point it does not take much to nudge us to step across the line.


And there is an aide memoir we can use for this change cycle … one that is a bit easier to remember:

A = Awareness
B = Belief
C = Capability
D = Delivery
E = Excellence (+enjoyment, +evidence, +excitement, +engagement)

First we raise awareness of the issue.
Then we learn a solution is possible and that we can learn the know-how.
Then we plan the work.
Then we work the plan.
Then we celebrate what worked and learn from what did and what did not.

Experience shows that the process is not discrete and sequential and it cannot be project managed into defined time boxes.  Instead, it is a continuum and the phases overlap and blend from one to the next in a more fluid and adaptive way.


Raising awareness requires both empathy and courage because this issue is often treated as undiscussable, and even the idea of discussing it is undiscussable too. Taboo.

But for effective change we need to grasp the nettle, explore the current reality, and start the conversation.

Cognitive Traps for Hefalumps

One of the really, really cool things about the 1.3 kg of “ChimpWare” between our ears is the way it learns.

We have evolved the ability to predict the likely near-future based on just a small number of past experiences.

And we do that by creating stored mental models.

Not even the most powerful computers can do it as well as we do – and we do it without thinking. Literally. It is an unconscious process.

This ability to pro-gnose (=before-know) gave our ancestors a major survival advantage when we were wandering about on the savanna over 10 million years ago.  And we have used this amazing ability to build societies, mega-cities and spaceships.


But this capability is not perfect.  It has a flaw.  Our “ChimpOS” does not store a picture of reality like a digital camera; it stores a patchy and distorted perception of reality, and then fills in the gaps with guesses (i.e. gaffes).  And we do not notice – consciously.

The cognitive trap is set and sits waiting to be sprung.  And to trip us up.


Here is an example:

“Improvement implies change”

Yes. That is a valid statement because we can show that whenever improvement has been the effect, then some time before that a change happened.  And we can show that when there are no changes, the system continues to behave as it always has.  Status quo.

The cognitive trap is that our ChimpOS is very good at remembering temporal associations – for example an association between “improvement” and “change” because we remember in the present.  So, if two concepts are presented at the same time, and we spice-the-pie with a bit of strong emotion, then we are more likely to associate them. Which is OK.

The problem comes when we play back the memory … it can come back as …

“change implies improvement” which is not valid.  And we do not notice.

To prove it is not valid we just need to find one example where a change led to a deterioration; an unintended negative consequence, a surprising, confusing and disappointing failure to achieve our intended improvement.

An embarrassing gap between our intent and our impact.

And finding that evidence is not hard.  Failures and disappointments in the world of improvement are all too common.


And then we can fall into the same cognitive trap because we generalise from a single, bad experience and the lesson our ChimpOS stores for future reference is “change is bad”.

And forever afterwards we feel anxious whenever the idea of change is suggested.

It is a very effective survival tactic – for a hominid living on the African savanna 10 million years ago, and at risk of falling prey to sharp-fanged, hungry predators.  It is a less useful tactic in the modern world where the risk of being eaten-for-lunch is minimal, and where the pace of change is accelerating.  We must learn to innovate and improve to survive in the social jungle … and we are not well equipped!


Here is another common cognitive trap:

Excellence implies no failures.

Yes. If we are delivering a consistently excellent service then the absence of failures will be a noticeable feature.

No failures implies excellence.

This is not a valid inference.  If quality-of-service is measured on a continuum from Excrement-to-Excellent, then we can be delivering a consistently mediocre service, one that is barely adequate, and also have no failures.


The design flaw here is that our ChimpWare/ChimpOS memory system is lossy.

We do not remember all the information required to reconstruct an accurate memory of reality – because there is too much information.  So we distort, we delete and we generalise.  And we do that because when we evolved it was a good enough solution, and it enabled us to survive as a species, so the ChimpWare/ChimpOS genes were passed on.

We cannot reverse millions of years of evolution.  We cannot get a wetware or a software upgrade.  We need to learn to manage with the limitations of what we have between our ears.

And to avoid the cognitive traps we need to practice the discipline of bringing our unconscious assumptions up to conscious awareness … and we do that by asking carefully framed questions.

Here is another example:

A high-efficiency design implies high-utilisation of resources.

Yes, that is valid. Idle resources means wasted resources which means lower efficiency.

Q1: Is the converse also valid?
Q2: Is there any evidence that disproves the converse is valid?

If high-utilisation does not imply high-efficiency, what are the implications of falling into this cognitive trap?  What is the value of measuring utilisation? Does it have a value?

These are useful questions.

The Turkeys Voting For Xmas Trap

One of the quickest and easiest ways to kill an improvement initiative stone dead is to label it as a “cost improvement program” or C.I.P.

Everyone knows that the biggest single contributor to cost is salaries.

So cost reduction means head count reduction which mean people lose their jobs and their livelihood.

Who is going to sign up to that?

It would be like turkeys voting for Xmas.

There must be a better approach?

Yes. There is.


Over the last few weeks, groups of curious skeptics have experienced the immediate impact of systems engineering theory, techniques and tools in a health care context.

They experienced queues, delays and chaos evaporate in front of their eyes … and it cost nothing to achieve. No extra resources. No extra capacity. No extra cash.

Their reaction was “surprise and delight”.

But … it also exposed a problem.  An undiscussable problem.


Queues and chaos require expensive resources to manage.

We call them triagers, progress-chasers, and fire-fighters.  And when the queues and chaos evaporate then their jobs do too.

The problem is that the very people who are needed to make the change happen are the ones who become surplus-to-requirement as a result of the change.

So change does not happen.

It would like turkeys voting for Xmas.


The way around this impasse is to anticipate the effect and to proactively plan to re-invest the resource that is released.  And to re-invest it doing a more interesting and more worthwhile jobs than queue-and-chaos management.

One opportunity for re-investment is called time-buffering which is an effective way to improve resilience to variation, especially in an unscheduled care context.

Another opportunity for re-investment is tail-gunning the chronic backlogs until they are down to a safe and sensible size.

And many complain that they do not have time to learn about improvement because they are too busy managing the current chaos.

So, another opportunity for re-investment is training – oneself first and then others.


R.I.P.    C.I.P.

Ability minus Awareness equals Engagement

It is always rewarding when separate but related ideas come together and go “click”.

And this week I had one of those “ah ha” moments while attempting to explain how the process of engagement works.

Many years ago I was introduced to the conscious-competence model of learning which I found really insightful.  Sometime later I renamed it as the awareness-ability model because the term competence felt too judgemental.

The idea is that when we learn we all start from a position of being unaware of our inability.

A state called blissful ignorance.

And it is only when we try to do something that we become aware of what we cannot do; which can lead to temper tantrums!

As we concentrate and practice our ability improves and we enter the zone of know how.  We become able to demonstrate what we can do, and explain how we are doing it.

The final phase comes when it becomes so habitual that we forget how we learned our skill – it has become second nature.


Some years later I was introduced to the Nerve Curve which is the emotional roller-coaster ride that accompanies change.  Any form of change.

A five-step model was described in the context of bereavement by psychiatrist Elisabeth Kübler-Ross in her 1969 book “On Death & Dying: What the Dying Have to Teach Doctors, Nurses, Clergy and their Families.

More recently this has been extended and applied by authors such as William Bridges and John Fisher in the less emotionally traumatic contexts called transitions.

The characteristic sequence of emotions are triggered by external events are:

  • shock
  • denial
  • frustration
  • blame
  • guilt
  • depression
  • acceptance
  • engagement
  • excitement.

The important messages in both of these models is that we can get stuck along the path of transition, and we can disengage at several points, signalling to others that we have come off the track.  When we do that we exhibit behaviours such as denial, disillusionment and hostility.


More recently I was introduced to the work of the late Chris Argyris and specifically the concept of “defensive reasoning“.

The essence of the concept:  As we start to become aware of a gap between our intentions and our impact, then we feel threatened and our natural reaction is defensive.  This is the essence of the behaviour called “resistance to change”, and it is interesting to note that “smart” people are particularly adept at it.


These three concepts are clearly related in some way … but how?


As a systems engineer I am used to cyclical processes and the concepts of wavelength, amplitude, phase and offset, and I found myself looking at the Awareness-Ability cycle and asking:

“How could that cycle generate the characteristic shape of the transition curve?”

Then the Argyris idea of the gap between intent and impact popped up and triggered another question:

“What if we look at the gap between our ability and our awareness?”

So, I conducted a thought experiment and imagined myself going around the cycle – and charting my ability, awareness and emotional state along the way … and this sketch emerged. Ah ha!

When my awareness exceeded my ability I felt disheartened. That is the defensive reasoning that Chris Argyris talks about, the emotional barrier to self-improvement.


Ability – Awareness = Engagement


This suggested to me that the process of building self-engagement requires opening the ability-versus-awareness gap a little-bit-at-a-time, sensing the emotional discomfort, and then actively releasing the tension by learning a new concept, principle, technique or tool (and usually all four).

Eureka!

I wonder if the same strategy would work elsewhere?

The Pathology of Variation I

In medical training we have to learn about lots of things. That is one reason why it takes a long time to train a competent and confident clinician.

First, we learn the anatomy (structure) and the physiology (function) of the normal, healthy human.

Then we learn about how this amazingly complicated system can go wrong.  We learn about pathology.  And we do that so that we understand the relationship between the cause (disease) and the effect (symptoms and signs).

Then we learn about diagnostics – which is how to work backwards from the effects to the most likely cause(s).

And only then can we learn about therapeutics – the design and delivery of a treatment plan that we are confident will relieve the symptoms by curing the disease.

And we learn about prevention – how to avoid some illnesses (and delay others) by addressing the root causes earlier.  Much of the increase in life expectancy over the last 200 years has come from prevention, not from cure.


The NHS is an amazingly complicated system, and it too can go wrong.  It can exhibit a wide spectrum of symptoms and signs; medical errors, long delays, unhappy patients, burned-out staff, and overspent budgets.

But, there is no equivalent training in how to diagnose and treat a sick health care system.  And this is not acceptable, especially given that the knowledge of how to do this is already available.

It is called complex adaptive systems engineering (CASE).


Before the Renaissance, the understanding of how the body works was primitive and it was believed that illness was “God’s Will” so we had to just grin-and-bear (and pray).

The Scientific Revolution brought us new insights, profound theories, innovative techniques and capability-extending tools.  And the impact has been dramatic.  Those who do have access to this knowledge live better and longer than ever.  Those who do not … do not.

Our current understanding of how health care systems work is, to be blunt, medieval.  The current approaches amount to little more than rune reading, incantations and the prescription of purgatives and leeches.  And the impact is about as effective.

So we need to study the anatomy, physiology, pathology, diagnostics and therapeutics of complex adaptive systems like healthcare.  And most of all we need to understand how to prevent catastrophes happening in the first place.  We need the NHS to be immortal.


And this week a prototype complex adaptive pathology training system was tested … and it employed cutting-edge 21st Century technology: Pasta Twizzles.

The specific topic under scrutiny was variation.  A brain-bending concept that is usually relegated to the mystical smoke-and-mirrors world called “Sadistics”.

But no longer!

The Mists-of-Jargon and Fog-of-Formulae were blown away as we switched on the Fan-of-Facilitation and the Light-of-Simulation and went exploring.

Empirically. Pragmatically.


And what we discovered was jaw-dropping.

A disease called the “Flaw of Averages” and its malignant manifestation “Carveoutosis“.


And with our new knowledge we opened the door to a previously hidden world of opportunity and improvement.

Then we activated the Laser-of-Insight and evaporated the queues and chaos that, before our new understanding, we had accepted as inevitable and beyond our understanding or control.

They were neither. And never had been. We were deluding ourselves.

Welcome to the Resilient Design – Practical Skills – One Day Workshop.

Validation Test: Passed.

Dr Hyde and Mr Jekyll

Dr Bill Hyde was already at the bar when Bob Jekyll arrived.

Bill and  Bob had first met at university and had become firm friends, but their careers had diverged and it was only by pure chance that their paths had crossed again recently.

They had arranged to meet up for a beer and to catch up on what had happened in the 25 years since they had enjoyed the “good old times” in the university bar.

<Dr Bill> Hi Bob, what can I get you? If I remember correctly it was anything resembling real ale. Will this “Black Sheep” do?

<Bob> Hi Bill, Perfect! I’ll get the nibbles. Plain nuts OK for you?

<Dr Bill> My favourite! So what are you up to now? What doors did your engineering degree open?

<Bob> Lots!  I’ve done all sorts – mechanical, electrical, software, hardware, process, all except civil engineering. And I love it. What I do now is a sort of synthesis of all of them.  And you? Where did your medical degree lead?

<Dr Bill> To my hearts desire, the wonderful Mrs Hyde, and of course to primary care. I am a GP. I always wanted to be a GP since I was knee-high to a grasshopper.

<Bob> Yes, you always had that “I’m going to save the world one patient at a time!” passion. That must be so rewarding! Helping people who are scared witless by the health horror stories that the media pump out.  I had a fright last year when I found a lump.  My GP was great, she confidently diagnosed a “hernia” and I was all sorted in a matter of weeks with a bit of nifty day case surgery. I was convinced my time had come. It just shows how damaging the fear of the unknown can be!

<Dr Bill> Being a GP is amazingly rewarding. I love my job. But …

<Bob> But what? Are you alright Bill? You suddenly look really depressed.

<Dr Bill> Sorry Bob. I don’t want to be a damp squib. It is good to see you again, and chat about the old days when we were teased about our names.  And it is great to hear that you are enjoying your work so much. I admit I am feeling low, and frankly I welcome the opportunity to talk to someone I know and trust who is not part of the health care system. If you know what I mean?

<Bob> I know exactly what you mean.  Well, I can certainly offer an ear, “a problem shared is a problem halved” as they say. I can’t promise to do any more than that, but feel free to tell me the story, from the beginning. No blood-and-guts gory details though please!

<Dr Bill> Ha! “Tell me the story from the beginning” is what I say to my patients. OK, here goes. I feel increasingly overwhelmed and I feel like I am drowning under a deluge of patients who are banging on the practice door for appointments to see me. My intuition tells me that the problem is not the people, it is the process, but I can’t seem to see through the fog of frustration and chaos to a clear way forward.

<Bob> OK. I confess I know nothing about how your system works, so can you give me a bit more context.

<Dr Bill> Sorry. Yes, of course. I am what is called a single-handed GP and I have a list of about 1500 registered patients and I am contracted to provide primary care for them. I don’t have to do that 24 x 7, the urgent stuff that happens in the evenings and weekends is diverted to services that are designed for that. I work Monday to Friday from 9 AM to 5 PM, and I am contracted to provide what is needed for my patients, and that means face-to-face appointments.

<Bob> OK. When you say “contracted” what does that mean exactly?

<Dr Bill> Basically, the St. Elsewhere’s® Practice is like a small business. It’s annual income is a fixed amount per year for each patient on the registration list, and I have to provide the primary care service for them from that pot of cash. And that includes all the costs, including my income, our practice nurse, and the amazing Mrs H. She is the practice receptionist, manager, administrator and all-round fixer-of-anything.

<Bob> Wow! What a great design. No need to spend money on marketing, research, new product development, or advertising! Just 100% pure service delivery of tried-and-tested medical know-how to a captive audience for a guaranteed income. I have commercial customers who would cut off their right arms for an offer like that!

<Dr Bill> Really? It doesn’t feel like that to me. It feels like the more I offer, the more the patients expect. The demand is a bottomless well of wants, but the income is capped and my time is finite!

<Bob> H’mm. Tell me more about the details of how the process works.

<Dr Bill> Basically, I am a problem-solving engine. Patients phone for an appointment, Mrs H books one, the patient comes at the appointed time, I see them, and I diagnose and treat the problem, or I refer on to a specialist if it’s more complicated. That’s basically it.

<Bob> OK. Sounds a lot simpler than 99% of the processes that I’m usually involved with. So what’s the problem?

<Dr Bill> I don’t have enough capacity! After all the appointments for the day are booked Mrs H has to say “Sorry, please try again tomorrow” to every patient who phones in after that.  The patients who can’t get an appointment are not very happy and some can get quite angry. They are anxious and frustrated and I fully understand how they feel. I feel the same.

<Bob> We will come back to what you mean by “capacity”. Can you outline for me exactly how a patient is expected to get an appointment?

<Dr Bill> We tell them to phone at 8 AM for an appointment, there is a fixed number of bookable appointments, and it is first-come-first-served.  That is the only way I can protect myself from being swamped and is the fairest solution for patients.  It wasn’t my idea; it is called Advanced Access. Each morning at 8 AM we switch on the phones and brace ourselves for the daily deluge.

<Bob> You must be pulling my leg! This design is a batch-and-queue phone-in appointment booking lottery!  I guess that is one definition of “fair”.  How many patients get an appointment on the first attempt?

<Dr Bill> Not many.  The appointments are usually all gone by 9 AM and a lot are to people who have been trying to get one for several days. When they do eventually get to see me they are usually grumpy and then spring the trump card “And while I’m here doctor I have a few other things that I’ve been saving up to ask you about“. I help if I can but more often than not I have to say, “I’m sorry, you’ll have to book another appointment!“.

<Bob> I’m not surprised you patients are grumpy. I would be too. And my recollection of seeing my GP with my scary lump wasn’t like that at all. I phoned at lunch time and got an appointment the same day. Maybe I was just lucky, or maybe my GP was as worried as me. But it all felt very calm. When I arrived there was only one other patient waiting, and I was in and out in less than ten minutes – and mightily reassured I can tell you! It felt like a high quality service that I could trust if-and-when I needed it, which fortunately is very infrequently.

<Dr Bill> I dream of being able to offer a service like that! I am prepared to bet you are registered with a group practice and you see whoever is available rather than your own GP. Single-handed GPs like me who offer the old fashioned personal service are a rarity, and I can see why. We must be suckers!

<Bob> OK, so I’m starting to get a sense of this now. Has it been like this for a long time?

<Dr Bill> Yes, it has. When I was younger I was more resilient and I did not mind going the extra mile.  But the pressure is relentless and maybe I’m just getting older and grumpier.  My real fear is I end up sounding like the burned-out cynics that I’ve heard at the local GP meetings; the ones who crow about how they are counting down the days to when they can retire and gloat.

<Bob> You’re the same age as me Bill so I don’t think either of us can use retirement as an exit route, and anyway, that’s not your style. You were never a quitter at university. Your motto was always “when the going gets tough the tough get going“.

<Dr Bill> Yeah I know. That’s why it feels so frustrating. I think I lost my mojo a long time back. Maybe I should just cave in and join up with the big group practice down the road, and accept the inevitable loss of the personal service. They said they would welcome me, and my list of 1500 patients, with open arms.

<Bob> OK. That would appear to be an option, or maybe a compromise, but I’m not sure we’ve exhausted all the other options yet.  Tell me, how do you decide how long a patient needs for you to solve their problem?

<Dr Bill> That’s easy. It is ten minutes. That is the time recommended in the Royal College Guidelines.

<Bob> Eh? All patients require exactly ten minutes?

<Dr Bill> No, of course not!  That is the average time that patients need.  The Royal College did a big survey and that was what most GPs said they needed.

<Bob> Please tell me if I have got this right.  You work 9-to-5, and you carve up your day into 10-minute time-slots called “appointments” and, assuming you are allowed time to have lunch and a pee, that would be six per hour for seven hours which is 42 appointments per day that can be booked?

<Dr Bill> No. That wouldn’t work because I have other stuff to do as well as see patients. There are only 25 bookable 10-minute appointments per day.

<Bob> OK, that makes more sense. So where does 25 come from?

<Dr Bill> Ah! That comes from a big national audit. For an average GP with and average  list of 1,500 patients, the average number of patients seeking an appointment per day was found to be 25, and our practice population is typical of the national average in terms of age and deprivation.  So I set the upper limit at 25. The workload is manageable but it seems to generate a lot of unhappy patients and I dare not increase the slots because I’d be overwhelmed with the extra workload and I’m barely coping now.  I feel stuck between a rock and a hard place!

<Bob> So you have set the maximum slot-capacity to the average demand?

<Dr Bill> Yes. That’s OK isn’t it? It will average out over time. That is what average means! But it doesn’t feel like that. The chaos and pressure never seems to go away.


There was a long pause while Bob mulls over what he had heard, sips his pint of Black Sheep and nibbles on the dwindling bowl of peanuts.  Eventually he speaks.


<Bob> Bill, I have some good news and some not-so-good news and then some more good news.

<Dr Bill> Oh dear, you sound just like me when I have to share the results of tests with one of my patients at their follow up appointment. You had better give me the “bad news sandwich”!

<Bob> OK. The first bit of good news is that this is a very common, and easily treatable flow problem.  The not-so-good news is that you will need to change some things.  The second bit of good news is that the changes will not cost anything and will work very quickly.

<Dr Bill> What! You cannot be serious!! Until ten minutes ago you said that you knew nothing about how my practice works and now you are telling me that there is a quick, easy, zero cost solution.  Forgive me for doubting your engineering know-how but I’ll need a bit more convincing than that!

<Bob> And I would too if I were in your position.  The clues to the diagnosis are in the story. You said the process problem was long-standing; you said that you set the maximum slot-capacity to the average demand; and you said that you have a fixed appointment time that was decided by a subjective consensus.  From an engineering perspective, this is a perfect recipe for generating chronic chaos, which is exactly the symptoms you are describing.

<Dr Bill> Is it? OMG. You said this is well understood and resolvable? So what do I do?

<Bob> Give me a minute.  You said the average demand is 25 per day. What sort of service would you like your patients to experience? Would “90% can expect a same day appointment on the first call” be good enough as a starter?

<Dr Bill> That would be game changing!  Mrs H would be over the moon to be able to say “Yes” that often. I would feel much less anxious too, because I know the current system is a potentially dangerous lottery. And my patients would be delighted and relieved to be able to see me that easily and quickly.

<Bob> OK. Let me work this out. Based on what you’ve said, some assumptions, and a bit of flow engineering know-how; you would need to offer up to 31 appointments per day.

<Dr Bill> What! That’s impossible!!! I told you it would be impossible! That would be another hour a day of face-to-face appointments. When would I do the other stuff? And how did you work that out anyway?

<Bob> I did not say they would have to all be 10-minute appointments, and I did not say you would expect to fill them all every day. I did however say you would have to change some things.  And I did say this is a well understood flow engineering problem.  It is called “resilience design“. That’s how I was able to work it out on the back of this Black Sheep beer mat.

<Dr Bill> H’mm. That is starting to sound a bit more reasonable. What things would I have to change? Specifically?

<Bob> I’m not sure what specifically yet.  I think in your language we would say “I have taken a history, and I have a differential diagnosis, so next I’ll need to examine the patient, and then maybe do some tests to establish the actual diagnosis and to design and decide the treatment plan“.

<Dr Bill> You are learning the medical lingo fast! What do I need to do first? Brace myself for the forensic rubber-gloved digital examination?

<Bob> Alas, not yet and certainly not here. Shall we start with the vital signs? Height, weight, pulse, blood pressure, and temperature? That’s what my GP did when I went with my scary lump.  The patient here is not you, it is your St. Elsewhere’s® Practice, and we will need to translate the medical-speak into engineering-speak.  So one thing you’ll need to learn is a bit of the lingua-franca of systems engineering.  By the way, that’s what I do now. I am a systems engineer, or maybe now a health care systems engineer?

<Dr Bill> Point me in the direction of the HCSE dictionary! The next round is on me. And the nuts!

<Bob> Excellent. I’ll have another Black Sheep and some of those chilli-coated ones. We have work to do.  Let me start by explaining what “capacity” actually means to an engineer. Buckle up. This ride might get a bit bumpy.


This story is fictional, but the subject matter is factual.

Bob’s diagnosis and recommendations are realistic and reasonable.

Chapter 1 of the HCSE dictionary can be found here.

And if you are a GP who recognises these “symptoms” then this may be of interest.

How Do We Know We Have Improved?

Phil and Pete are having a coffee and a chat.  They both work in the NHS and have been friends for years.

They have different jobs. Phil is a commissioner and an accountant by training, Pete is a consultant and a doctor by training.

They are discussing a challenge that affects them both on a daily basis: unscheduled care.

Both Phil and Pete want to see significant and sustained improvements and how to achieve them is often the focus of their coffee chats.


<Phil> We are agreed that we both want improvement, both from my perspective as a commissioner and from your perspective as a clinician. And we agree that what we want to see improvements in patient safety, waiting, outcomes, experience for both patients and staff, and use of our limited NHS resources.

<Pete> Yes. Our common purpose, the “what” and “why”, has never been an issue.  Where we seem to get stuck is the “how”.  We have both tried many things but, despite our good intentions, it feels like things are getting worse!

<Phil> I agree. It may be that what we have implemented has had a positive impact and we would have been even worse off if we had done nothing. But I do not know. We clearly have much to learn and, while I believe we are making progress, we do not appear to be learning fast enough.  And I think this knowledge gap exposes another “how” issue: After we have intervened, how do we know that we have (a) improved, (b) not changed or (c) worsened?

<Pete> That is a very good question.  And all that I have to offer as an answer is to share what we do in medicine when we ask a similar question: “How do I know that treatment A is better than treatment B?”  It is the essence of medical research; the quest to find better treatments that deliver better outcomes and at lower cost.  The similarities are strong.

<Phil> OK. How do you do that? How do you know that “Treatment A is better than Treatment B” in a way that anyone will trust the answer?

 <Pete> We use a science that is actually very recent on the scientific timeline; it was only firmly established in the first half of the 20th century. One reason for that is that it is rather a counter-intuitive science and for that reason it requires using tools that have been designed and demonstrated to work but which most of us do not really understand how they work. They are a bit like magic black boxes.

<Phil> H’mm. Please forgive me for sounding skeptical but that sounds like a big opportunity for making mistakes! If there are lots of these “magic black box” tools then how do you decide which one to use and how do you know you have used it correctly?

<Pete> Those are good questions! Very often we don’t know and in our collective confusion we generate a lot of unproductive discussion.  This is why we are often forced to accept the advice of experts but, I confess, very often we don’t understand what they are saying either! They seem like the medieval Magi.

<Phil> H’mm. So these experts are like ‘magicians’ – they claim to understand the inner workings of the black magic boxes but are unable, or unwilling, to explain in a language that a ‘muggle’ would understand?

<Pete> Very well put. That is just how it feels.

<Phil> So can you explain what you do understand about this magical process? That would be a start.


<Pete> OK, I will do my best.  The first thing we learn in medical research is that we need to be clear about what it is we are looking to improve, and we need to be able to measure it objectively and accurately.

<Phil> That  makes sense. Let us say we want to improve the patient’s subjective quality of the A&E experience and objectively we want to reduce the time they spend in A&E. We measure how long they wait. 

<Pete> The next thing is that we need to decide how much improvement we need. What would be worthwhile? So in the example you have offered we know that reducing the average time patients spend in A&E by just 30 minutes would have a significant effect on the quality of the patient and staff experience, and as a by-product it would also dramatically improve the 4-hour target performance.

<Phil> OK.  From the commissioning perspective there are lots of things we can do, such as commissioning alternative paths for specific groups of patients; in effect diverting some of the unscheduled demand away from A&E to a more appropriate service provider.  But these are the sorts of thing we have been experimenting with for years, and it brings us back to the question: How do we know that any change we implement has had the impact we intended? The system seems, well, complicated.

<Pete> In medical research we are very aware that the system we are changing is very complicated and that we do not have the power of omniscience.  We cannot know everything.  Realistically, all we can do is to focus on objective outcomes and collect small samples of the data ocean and use those in an attempt to draw conclusions can trust. We have to design our experiment with care!

<Phil> That makes sense. Surely we just need to measure the stuff that will tell us if our impact matches our intent. That sounds easy enough. What’s the problem?

<Pete> The problem we encounter is that when we measure “stuff” we observe patient-to-patient variation, and that is before we have made any changes.  Any impact that we may have is obscured by this “noise”.

<Phil> Ah, I see.  So if the our intervention generates a small impact then it will be more difficult to see amidst this background noise. Like trying to see fine detail in a fuzzy picture.

<Pete> Yes, exactly like that.  And it raises the issue of “errors”.  In medical research we talk about two different types of error; we make the first type of error when our actual impact is zero but we conclude from our data that we have made a difference; and we make the second type of error when we have made an impact but we conclude from our data that we have not.

<Phil> OK. So does that imply that the more “noise” we observe in our measure for-improvement before we make the change, the more likely we are to make one or other error?

<Pete> Precisely! So before we do the experiment we need to design it so that we reduce the probability of making both of these errors to an acceptably low level.  So that we can be assured that any conclusion we draw can be trusted.

<Phil> OK. So how exactly do you do that?

<Pete> We know that whenever there is “noise” and whenever we use samples then there will always be some risk of making one or other of the two types of error.  So we need to set a threshold for both. We have to state clearly how much confidence we need in our conclusion. For example, we often use the convention that we are willing to accept a 1 in 20 chance of making the Type I error.

<Phil> Let me check if I have heard you correctly. Suppose that, in reality, our change has no impact and we have set the risk threshold for a Type 1 error at 1 in 20, and suppose we repeat the same experiment 100 times – are you saying that we should expect about five of our experiments to show data that says our change has had the intended impact when in reality it has not?

<Pete> Yes. That is exactly it.

<Phil> OK.  But in practice we cannot repeat the experiment 100 times, so we just have to accept the 1 in 20 chance that we will make a Type 1 error, and we won’t know we have made it if we do. That feels a bit chancy. So why don’t we just set the threshold to 1 in 100 or 1 in 1000?

<Pete> We could, but doing that has a consequence.  If we reduce the risk of making a Type I error by setting our threshold lower, then we will increase the risk of making a Type II error.

<Phil> Ah! I see. The old swings-and-roundabouts problem. By the way, do these two errors have different names that would make it  easier to remember and to explain?

<Pete> Yes. The Type I error is called a False Positive. It is like concluding that a patient has a specific diagnosis when in reality they do not.

<Phil> And the Type II error is called a False Negative?

<Pete> Yes.  And we want to avoid both of them, and to do that we have to specify a separate risk threshold for each error.  The convention is to call the threshold for the false positive the alpha level, and the threshold for the false negative the beta level.

<Phil> OK. So now we have three things we need to be clear on before we can do our experiment: the size of the change that we need, the risk of the false positive that we are willing to accept, and the risk of a false negative that we are willing to accept.  Is that all we need?

<Pete> In medical research we learn that we need six pieces of the experimental design jigsaw before we can proceed. We only have three pieces so far.

<Phil> What are the other three pieces then?

<Pete> We need to know the average value of the metric we are intending to improve, because that is our baseline from which improvement is measured.  Improvements are often framed as a percentage improvement over the baseline.  And we need to know the spread of the data around that average, the “noise” that we referred to earlier.

<Phil> Ah, yes!  I forgot about the noise.  But that is only five pieces of the jigsaw. What is the last piece?

<Pete> The size of the sample.

<Phil> Eh?  Can’t we just go with whatever data we can realistically get?

<Pete> Sadly, no.  The size of the sample is how we control the risk of a false negative error.  The more data we have the lower the risk. This is referred to as the power of the experimental design.

<Phil> OK. That feels familiar. I know that the more experience I have of something the better my judgement gets. Is this the same thing?

<Pete> Yes. Exactly the same thing.

<Phil> OK. So let me see if I have got this. To know if the impact of the intervention matches our intention we need to design our experiment carefully. We need all six pieces of the experimental design jigsaw and they must all fall inside our circle of control. We can measure the baseline average and spread; we can specify the impact we will accept as useful; we can specify the risks we are prepared to accept of making the false positive and false negative errors; and we can collect the required amount of data after we have made the intervention so that we can trust our conclusion.

<Pete> Perfect! That is how we are taught to design research studies so that we can trust our results, and so that others can trust them too.

<Phil> So how do we decide how big the post-implementation data sample needs to be? I can see we need to collect enough data to avoid a false negative but we have to be pragmatic too. There would appear to be little value in collecting more data than we need. It would cost more and could delay knowing the answer to our question.

<Pete> That is precisely the trap than many inexperienced medical researchers fall into. They set their sample size according to what is achievable and affordable, and then they hope for the best!

<Phil> Well, we do the same. We analyse the data we have and we hope for the best.  In the magical metaphor we are asking our data analysts to pull a white rabbit out of the hat.  It sounds rather irrational and unpredictable when described like that! Have medical researchers learned a way to avoid this trap?

<Pete> Yes, it is a tool called a power calculator.

<Phil> Ooooo … a power tool … I like the sound of that … that would be a cool tool to have in our commissioning bag of tricks. It would be like a magic wand. Do you have such a thing?

<Pete> Yes.

<Phil> And do you understand how the power tool magic works well enough to explain to a “muggle”?

<Pete> Not really. To do that means learning some rather unfamiliar language and some rather counter-intuitive concepts.

<Phil> Is that the magical stuff I hear lurks between the covers of a medical statistics textbook?

<Pete> Yes. Scary looking mathematical symbols and unfathomable spells!

<Phil> Oh dear!  Is there another way for to gain a working understanding of this magic? Something a bit more pragmatic? A path that a ‘statistical muggle’ might be able to follow?

<Pete> Yes. It is called a simulator.

<Phil> You mean like a flight simulator that pilots use to learn how to control a jumbo jet before ever taking a real one out for a trip?

<Pete> Exactly like that.

<Phil> Do you have one?

<Pete> Yes. It was how I learned about this “stuff” … pragmatically.

<Phil> Can you show me?

<Pete> Of course.  But to do that we will need a bit more time, another coffee, and maybe a couple of those tasty looking Danish pastries.

<Phil> A wise investment I’d say.  I’ll get the the coffee and pastries, if you fire up the engines of the simulator.

Pride and Joy

stick_figure_superhero_anim_150_wht_1857Have you heard the phrase “Pride comes before a fall“?

What does this mean? That the feeling of pride is the reason for the subsequent fall?

So by following that causal logic, if we do not allow ourselves to feel proud then we can avoid the fall?

And none of us like the feeling of falling and failing. We are fearful of that negative feeling, so with this simple trick we can avoid feeling bad. Yes?

But we all know the positive feeling of achievement – we feel pride when we have done good work, when our impact matches our intent.  Pride in our work.

Is that bad too?

Should we accept under-achievement and unexceptional mediocrity as the inevitable cost of avoiding the pain of possible failure?  Is that what we are being told to do here?


The phrase comes from the Bible, from the Book of Proverbs 16:18 to be precise.

proverb

And the problem here is that the phrase “pride comes before a fall” is not the whole proverb.

It has been simplified. Some bits have been omitted. And those omissions lead to ambiguity and the opportunity for obfuscation and re-interpretation.

pride_goes_before_a_fall
In the fuller New International Version we see a missing bit … the “haughty spirit” bit.  That is another way of saying “over-confident” or “arrogant”.


But even this “authorised” version is still ambiguous and more questions spring to mind:

Q1. What sort of pride are we referring to? Just the confidence version? What about the pride that follows achievement?

Q2. How would we know if our feeling of confidence is actually justified?

Q3. Does a feeling of confidence always precede a fall? Is that how we diagnose over-confidence? Retrospectively? Are there instances when we feel confident but we do not fail? Are there instances when we do not feel confident and then fail?

Q4. Does confidence cause the fall or it is just a temporal association? Is there something more fundamental that causes both high-confidence and low-competence?


There is a well known model called the Conscious-Competence model of learning which generates a sequence of four stages to achieving a new skill. Such as one we need to achieve our intended outcomes.

We all start in the “blissful ignorance” zone of unconscious incompetence.  Our unknowns are unknown to us.  They are blind spots.  So we feel unjustifiably confident.

hierarchy_of_competence

In this model the first barrier to progress is “wrong intuition” which means that we actually have unconscious assumptions that are distorting our perception of reality.

What we perceive makes sense to us. It is clear and obvious. We feel confident. We believe our own rhetoric.

But our unconscious assumptions can trick us into interpreting information incorrectly.  And if we derive decisions from unverified assumptions and invalid analysis then we may do the wrong thing and not achieve our intended outcome.  We may unintentionally cause ourselves to fail and not be aware of it.  But we are proud and confident.

Then the gap between our intent and our impact becomes visible to all and painful to us. So we are tempted to avoid the social pain of public failure by retreating behind the “Yes, But” smokescreen of defensive reasoning. The “doom loop” as it is sometimes called. The Victim Vortex. “Don’t name, shame and blame me, I was doing my best. I did not intent that to happen. To err is human”.


The good news is that this learning model also signposts a possible way out; a door in the black curtain of ignorance.  It suggests that we can learn how to correct our analysis by using feedback from reality to verify our rhetorical assumptions.  Those assumptions which pass the “reality check” we keep, those which fail the “reality check” we redesign and retest until they pass.  Bit by bit our inner rhetoric comes to more closely match reality and the wisdom of our decisions will improve.

And what we then see is improvement.  Our impact moves closer towards our intent. And we can justifiably feel proud of that achievement. We do not need to be best-compared-with-the-rest; just being better-than-we-were-before is OK. That is learning.

the_learning_curve

And this is how it feels … this is the Learning Curve … or the Nerve Curve as we call it.

What it says is that to be able to assess confidence we must also measure competence. Outcomes. Impact.

And to achieve excellence we have to be prepared to actively look for any gap between intent and impact.  And we have to be prepared to see it as an opportunity rather than as a threat. And we will need to be able to seek feedback and other people’s perspectives. And we need to be to open to asking for examples and explanations from those who have demonstrated competence.

It says that confidence is not a trustworthy surrogate for competence.

It says that we want the confidence that flows from competence because that is the foundation of trust.

Improvement flows at the speed of trust and seeing competence, confidence and trust growing is a joyous thing.

Pride and Joy are OK.

Arrogance and incompetence comes before a fall would be a better proverb.

Value, Verify and Validate

thinker_figure_unsolve_puzzle_150_wht_18309Many of the challenges that we face in delivering effective and affordable health care do not have well understood and generally accepted solutions.

If they did there would be no discussion or debate about what to do and the results would speak for themselves.

This lack of understanding is leading us to try to solve a complicated system design challenge in our heads.  Intuitively.

And trying to do it this way is fraught with frustration and risk because our intuition tricks us. It was this sort of challenge that led Professor Rubik to invent his famous 3D Magic Cube puzzle.

It is difficult enough to learn how to solve the Magic Cube puzzle by trial and error; it is even more difficult to attempt to do it inside our heads! Intuitively.


And we know the Rubik Cube puzzle is solvable, so all we need are some techniques, tools and training to improve our Rubik Cube solving capability.  We can all learn how to do it.


Returning to the challenge of safe and affordable health care, and to the specific problem of unscheduled care, A&E targets, delayed transfers of care (DTOC), finance, fragmentation and chronic frustration.

This is a systems engineering challenge so we need some systems engineering techniques, tools and training before attempting it.  Not after failing repeatedly.

se_vee_diagram

One technique that a systems engineer will use is called a Vee Diagram such as the one shown above.  It shows the sequence of steps in the generic problem solving process and it has the same sequence that we use in medicine for solving problems that patients present to us …

Diagnose, Design and Deliver

which is also known as …

Study, Plan, Do.


Notice that there are three words in the diagram that start with the letter V … value, verify and validate.  These are probably the three most important words in the vocabulary of a systems engineer.


One tool that a systems engineer always uses is a model of the system under consideration.

Models come in many forms from conceptual to physical and are used in two main ways:

  1. To assist the understanding of the past (diagnosis)
  2. To predict the behaviour in the future (prognosis)

And the process of creating a system model, the sequence of steps, is shown in the Vee Diagram.  The systems engineer’s objective is a validated model that can be trusted to make good-enough predictions; ones that support making wiser decisions of which design options to implement, and which not to.


So if a systems engineer presented us with a conceptual model that is intended to assist our understanding, then we will require some evidence that all stages of the Vee Diagram process have been completed.  Evidence that provides assurance that the model predictions can be trusted.  And the scope over which they can be trusted.


Last month a report was published by the Nuffield Trust that is entitled “Understanding patient flow in hospitals”  and it asserts that traffic flow on a motorway is a valid conceptual model of patient flow through a hospital.  Here is a direct quote from the second paragraph in the Executive Summary:

nuffield_report_01
Unfortunately, no evidence is provided in the report to support the validity of the statement and that omission should ring an alarm bell.

The observation that “the hospitals with the least free space struggle the most” is not a validation of the conceptual model.  Validation requires a concrete experiment.


To illustrate why observation is not validation let us consider a scenario where I have a headache and I take a paracetamol and my headache goes away.  I now have some evidence that shows a temporal association between what I did (take paracetamol) and what I got (a reduction in head pain).

But this is not a valid experiment because I have not considered the other seven possible combinations of headache before (Y/N), paracetamol (Y/N) and headache after (Y/N).

An association cannot be used to prove causation; not even a temporal association.

When I do not understand the cause, and I am without evidence from a well-designed experiment, then I might be tempted to intuitively jump to the (invalid) conclusion that “headaches are caused by lack of paracetamol!” and if untested this invalid judgement may persist and even become a belief.


Understanding causality requires an approach called counterfactual analysis; otherwise known as “What if?” And we can start that process with a thought experiment using our rhetorical model.  But we must remember that we must always validate the outcome with a real experiment. That is how good science works.

A famous thought experiment was conducted by Albert Einstein when he asked the question “If I were sitting on a light beam and moving at the speed of light what would I see?” This question led him to the Theory of Relativity which completely changed the way we now think about space and time.  Einstein’s model has been repeatedly validated by careful experiment, and has allowed engineers to design and deliver valuable tools such as the Global Positioning System which uses relativity theory to achieve high positional precision and accuracy.


So let us conduct a thought experiment to explore the ‘faster movement requires more space‘ statement in the case of patient flow in a hospital.

First, we need to define what we mean by the words we are using.

The phrase ‘faster movement’ is ambiguous.  Does it mean higher flow (more patients per day being admitted and discharged) or does it mean shorter length of stage (the interval between the admission and discharge events for individual patients)?

The phrase ‘more space’ is also ambiguous. In a hospital that implies physical space i.e. floor-space that may be occupied by corridors, chairs, cubicles, trolleys, and beds.  So are we actually referring to flow-space or storage-space?

What we have in this over-simplified statement is the conflation of two concepts: flow-capacity and space-capacity. They are different things. They have different units. And the result of conflating them is meaningless and confusing.


However, our stated goal is to improve understanding so let us consider one combination, and let us be careful to be more precise with our terminology, “higher flow always requires more beds“. Does it? Can we disprove this assertion with an example where higher flow required less beds (i.e. space-capacity)?

The relationship between flow and space-capacity is well understood.

The starting point is Little’s Law which was proven mathematically in 1961 by J.D.C. Little and it states:

Average work in progress = Average lead time  X  Average flow.

In the hospital context, work in progress is the number of occupied beds, lead time is the length of stay and flow is admissions or discharges per time interval (which must be the same on average over a long period of time).

(NB. Engineers are rather pedantic about units so let us check that this makes sense: the unit of WIP is ‘patients’, the unit of lead time is ‘days’, and the unit of flow is ‘patients per day’ so ‘patients’ = ‘days’ * ‘patients / day’. Correct. Verified. Tick.)

So, is there a situation where flow can increase and WIP can decrease? Yes. When lead time decreases. Little’s Law says that is possible. We have disproved the assertion.


Let us take the other interpretation of higher flow as shorter length of stay: i.e. shorter length of stay always requires more beds.  Is this correct? No. If flow remains the same then Little’s Law states that we will require fewer beds. This assertion is disproved as well.

And we need to remember that Little’s Law is proven to be valid for averages, does that shed any light on the source of our confusion? Could the assertion about flow and beds actually be about the variation in flow over time and not about the average flow?


And this is also well understood. The original work on it was done almost exactly 100 years ago by Agner Krarup Erlang and the problem he looked at was the quality of customer service of the early telephone exchanges. Specifically, how likely was the caller to get the “all lines are busy, please try later” response.

What Erlang showed was there there is a mathematical relationship between the number of calls being made (the demand), the probability of a call being connected first time (the service quality) and the number of telephone circuits and switchboard operators available (the service cost).


So it appears that we already have a validated mathematical model that links flow, quality and cost that we might use if we substitute ‘patients’ for ‘calls’, ‘beds’ for ‘telephone circuits’, and ‘being connected’ for ‘being admitted’.

And this topic of patient flow, A&E performance and Erlang queues has been explored already … here.

So a telephone exchange is a more valid model of a hospital than a motorway.

We are now making progress in deepening our understanding.


The use of an invalid, untested, conceptual model is sloppy systems engineering.

So if the engineering is sloppy we would be unwise to fully trust the conclusions.

And I share this feedback in the spirit of black box thinking because I believe that there are some valuable lessons to be learned here – by us all.


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Patient Traffic Engineering

motorway[Beep] Bob’s computer alerted him to Leslie signing on to the Webex session.

<Bob> Good afternoon Leslie, how are you? It seems a long time since we last chatted.

<Leslie> Hi Bob. I am well and it has been a long time. If you remember, I had to loop out of the Health Care Systems Engineering training because I changed job, and it has taken me a while to bring a lot of fresh skeptics around to the idea of improvement-by-design.

<Bob> Good to hear, and I assume you did that by demonstrating what was possible by doing it, delivering results, and describing the approach.

<Leslie> Yup. And as you know, even with objective evidence of improvement it can take a while because that exposes another gap, the one between intent and impact.  Many people get rather defensive at that point, so I have had to take it slowly. Some people get really fired up though.

 <Bob> Yes. Respect, challenge, patience and persistence are all needed. So, where shall we pick up?

<Leslie> The old chestnut of winter pressures and A&E targets.  Except that it is an all-year problem now and according to what I read in the news, everyone is predicting a ‘melt-down’.

<Bob> Did you see last week’s IS blog on that very topic?

<Leslie> Yes, I did!  And that is what prompted me to contact you and to re-start my CHIPs coaching.  It was a real eye opener.  I liked the black swan code-named “RC9” story, it makes it sound like a James Bond film!

<Bob> I wonder how many people dug deeper into how “RC9” achieved that rock-steady A&E performance despite a rising tide of arrivals and admissions?

<Leslie> I did, and I saw several examples of anti-carve-out design.  I have read though my notes and we have talked about carve out many times.

<Bob> Excellent. Being able to see the signs of competent design is just as important as the symptoms of inept design. So, what shall we talk about?

<Leslie> Well, by co-incidence I was sent a copy of of a report entitled “Understanding patient flow in hospitals” published by one of the leading Think Tanks and I confess it made no sense to me.  Can we talk about that?

<Bob> OK. Can you describe the essence of the report for me?

<Leslie> Well, in a nutshell it said that flow needs space so if we want hospitals to flow better we need more space, in other words more beds.

<Bob> And what evidence was presented to support that hypothesis?

<Leslie> The authors equated the flow of patients through a hospital to the flow of traffic on a motorway. They presented a table of numbers that made no sense to me, I think partly because there are no units stated for some of the numbers … I’ll email you a picture.

traffic_flow_dynamics

<Bob> I agree this is not a very informative table.  I am not sure what the definition of “capacity” is here and it may be that the authors may be equating “hospital bed” to “area of tarmac”.  Anyway, the assertion that hospital flow is equivalent to motorway flow is inaccurate.  There are some similarities and traffic engineering is an interesting subject, but they are not equivalent.  A hospital is more like a busy city with junctions, cross-roads, traffic lights, roundabouts, zebra crossings, pelican crossings and all manner of unpredictable factors such as cyclists and pedestrians. Motorways are intentionally designed without these “impediments”, for obvious reasons! A complex adaptive flow system like a hospital cannot be equated to a motorway. It is a dangerous over-simplification.

<Leslie> So, if the hospital-motorway analogy is invalid then the conclusions are also invalid?

<Bob> Sometimes, by accident, we get a valid conclusion from an invalid method. What were the conclusions?

<Leslie> That the solution to improving A&E performance is more space (i.e. hospital beds) but there is no more money to build them or people to staff them.  So the recommendations are to reduce volume, redesign rehabilitation and discharge processes, and improve IT systems.

<Bob> So just re-iterating the habitual exhortations and nothing about using well-understood systems engineering methods to accurately diagnose the actual root cause of the ‘symptoms’, which is likely to be the endemic carveoutosis multiforme, and then treat accordingly?

<Leslie> No. I could not find the term “carve out” anywhere in the document.

<Bob> Oh dear.  Based on that observation, I do not believe this latest Think Tank report is going to be any more effective than the previous ones.  Perhaps asking “RC9” to write an account of what they did and how they learned to do it would be more informative?  They did not reduce volume, and I doubt they opened more beds, and their annual report suggests they identified some space and flow carveoutosis and treated it. That is what a competent systems engineer would do.

<Leslie> Thanks Bob. Very helpful as always. What is my next step?

<Bob> Some ISP-2 brain-teasers, a juicy ISP-2 project, and some one day training workshops for your all-fired-up CHIPs.

<Leslie> Bring it on!


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The Pressure Cooker

About a year ago we looked back at the previous 10 years of NHS unscheduled care performance …

click here to read

… and warned that a catastrophe was on the way because we had unintentionally created a urgent care “pressure cooker”.

 

Did waving the red warning flag make any difference? It seems not.

The catastrophe unfolded as predicted … A&E performance slumped to an all-time low, and has not recovered.


A pressure cooker is an elegantly simple self-regulating system.  A strong metal box with a sealed lid and a pressure-sensitive valve.  Food cooks more quickly at a higher temperature, and we can increase the boiling point of water by increasing the ambient pressure.  So all we need to do is put some water in the cooker, close the lid, set the pressure limit we need (i.e. the temperature we want) and apply some heat.  Simple.  As the water boils the steam increases the pressure inside, until the regulator valve opens and lets a bit of steam out.  The more heat we apply – the faster the steam comes out – but the internal pressure and temperature remain constant.  An elegantly simple self-regulating system.


Our unscheduled care acute hospital “pressure cooker” design is very similar – but it has an additional feature – we can squeeze raw patients in through a one-way valve labelled “admissions”.  The internal pressure will eventually squeeze them out through another one-way pressure-sensitive valve called “discharges”.

But there is not much head-space inside our hospital (i.e. empty beds) so pushing patients in will increase the pressure inside, and it will trigger an internal reaction called “fire-fighting” that generates heat (but no insight).  When the internal pressure reaches the critical level, patients are squeezed out; ready-or-not.

What emerges from the chaotic internal cauldron is a mixture of under-cooked, just-right, and over-cooked patients.  And we then conduct quality control audits and we label what we find as “quality variation”, but it looks random so it gives us no clues as to the causes or what to do next.

Equilibrium is eventually achieved – what goes in comes out – the pressure and temperature auto-regulate – the chaos becomes chronic – and the quality of the output is predictably unacceptable and unpredictable, with some of it randomly spoiled (i.e. harmed).

And our acute care pressure cooker is very resistant to external influences. It is one of its key design features, it is an auto-regulating system.


Option 1: Admissions Avoidance
Squeezing a bit less in does not make any difference to the internal pressure and temperature.  It auto-regulates.  The reduced inflow means a reduced outflow and a longer cooking time and we just get less under-cooked and more over-cooked output.  Oh, and we go bust because our revenue has reduced but our costs have not.

Option 2: Build a Bigger Hospital
Building a bigger pressure cooker (i.e. adding more beds) does not make any sustained difference either.  Again the system auto-regulates.  The extra space-capacity allows a longer cooking time – and again we get less under-cooked and more over-cooked output.  Oh, and we still go bust (same revenue but increased cost).

Option 3: Reduce the Expectation
Turning down the heat (i.e. reducing the 4 hr A&E lead time target yield from 98% to 95%) does not make any difference. Our elegant auto-regulating design adjusts itself to sustain the internal pressure and temperature.  Output is still variable, but least we do not go bust.


This metaphor may go some way to explain why the intuitively obvious “initiatives” to improve unscheduled care performance appear to have had no significant or sustained impact.

And what is more worrying is that they may even have made the situation worse.

Also, working inside an urgent care pressure cooker is dangerous.  People get emotionally damaged and permanently scarred.


The good news is that a different approach is available … a health and social care systems engineering (HSCSE) approach … one that we could use to change the fundamental design from fire-fighter to flow-facilitator.

Using HSCSE theory, techniques and tools we could specify, design, build, verify, implement and validate a low-pressure, low-resistance, low-wait, low-latency, high-efficiency unscheduled care flow design that is safe, timely, effective and affordable.

But we are not training NHS staff to do that.

Why is that?  Is is because we are not aware that this is possible, or that we do not believe that it can work, or that we lack the capability to do it? Or all three?

The first step is raising awareness … so here is an example that proves it is possible.

Bloodsucking Bugs

BloodSuckerThis is a magnified picture of a blood sucking bug called a Red Poultry Mite.

They go red after having gorged themselves on chicken blood.

Their life-cycle is only 7 days so, when conditions are just right, they can quickly cause an infestation – and one that is remarkably difficult to eradicate!  But if it is not dealt with then chicken coop productivity will plummet.


We use the term “bug” for something else … a design error … in a computer program for example.  If the conditions are just right, then software bugs can spread too and can infest a computer system.  They feed on the hardware resources – slurping up processor time and memory space until the whole system slows to a crawl.


And one especially pernicious type of system design error is called an Error of Omission.  These are the things we do not do that would prevent the bloodsucking bugs from breeding and spreading.

Prevention is better than cure.


In the world of health care improvement there are some blood suckers out there, ones who home in on a susceptible host looking for a safe place to establish a colony.  They are masters of the art of mimicry.  They look like and sound like something they are not … they claim to be symbiotic whereas in reality they are parasitic.

The clue to their true nature is that their impact does not match their intent … but by the time that gap is apparent they are entrenched and their spores have already spread.

Unlike the Red Poultry Mites, we do not want to eradicate them … we need to educate them. They only behave like parasites because they are missing a few essential bits of software.  And once those upgrades are installed they can achieve their potential and become symbiotic.

So, let me introduce them, they are called Len, Siggy and Tock and here is their story:

Six Ways Not To Improve Flow

Crash Test Dummy

CrashTestDummyThere are two complementary approaches to safety and quality improvement: desire and design.

In the improvement-by-desire world we use a suck-it-and-see approach to fix a problem.  It is called PDSA.

Sometimes this works and we pat ourselves on the back, and remember the learning for future use.

Sometimes it works for us but has a side effect: it creates a problem for someone else.  And we may not be aware of the unintended consequence unless someone shouts “Oi!” It may be too late by then of course.


The more parts in a system, and the more interconnected they are, the more likely it is that a well-intended suck-it-and-see change will create an unintended negative impact.

And in that situation our temptation is to … do nothing … and put up with the problems. It seems the safest option.


In the improvement-by-design world we choose to study first, and to find the causal roots of the system behaviour we are seeing.  Our first objective is a diagnosis.

With that we can propose rational design changes that we anticipate will deliver the improvement we seek without creating adverse effects.

But we have learned the hard way that our intuition can trick us … so we need a way to test our designs … a safe and controlled way.  We need a crash test dummy!


What they do is to deliberately experience our design in a controlled experiment, and what they generate for us is constructive feedback. What did work, and what did not.

A crash test dummy is tough and sensitive at the same time.  They do not break easily and yet they feel the pain and gain too.  They are resilient.


And with their feedback we can re-visit our design and improve it further, or we can use it to offer evidence-based assurance that our design is fit-for-purpose.

Safety and Quality Assurance is improvement-by-design. Diagnosis-and-treatment.

Safety and Quality Control is improvement-by-desire. Suck-and-see.

If you were a passenger or a patient … which option would you prefer?

Fragmentation Cost

figure_falling_with_arrow_17621The late Russell Ackoff used to tell a great story. It goes like this:

“A team set themselves the stretch goal of building the World’s Best Car.  So the put their heads together and came up with a plan.

First they talked to drivers and drew up a list of all the things that the World’s Best Car would need to have. Safety, speed, low fuel consumption, comfort, good looks, low emissions and so on.

Then they drew up a list of all the components that go into building a car. The engine, the wheels, the bodywork, the seats, and so on.

Then they set out on a quest … to search the world for the best components … and to bring the best one of each back.

Then they could build the World’s Best Car.

Or could they?

No.  All they built was a pile of incompatible parts. The WBC did not work. It was a futile exercise.


Then the penny dropped. The features in their wish-list were not associated with any of the separate parts. Their desired performance emerged from the way the parts worked together. The working relationships between the parts were as necessary as the parts themselves.

And a pile of average parts that work together will deliver a better performance than a pile of best parts that do not.

So the relationships were more important than the parts!


From this they learned that the quickest, easiest and cheapest way to degrade performance is to make working-well-together a bit more difficult.  Irrespective of the quality of the parts.


Q: So how do we reverse this degradation of performance?

A: Add more failure-avoidance targets of course!

But we just discovered that the performance is the effect of how the parts work well together?  Will another failure-metric-fueled performance target help? How will each part know what it needs to do differently – if anything?  How will each part know if the changes they have made are having the intended impact?

Fragmentation has a cost.  Fear, frustration, futility and ultimately financial failure.

So if performance is fading … the quality of the working relationships is a good place to look for opportunities for improvement.

The Capstan

CapstanA capstan is a simple machine for combining the effort of many people and enabling them to achieve more than any of them could do alone.

The word appears to have come into English from the Portuguese and Spanish sailors at around the time of the Crusades.

Each sailor works independently of the others. There is no requirement them to be equally strong because the capstan will combine their efforts.  And the capstan also serves as a feedback loop because everyone can sense when someone else pushes harder or slackens off.  It is an example of simple, efficient, effective, elegant design.


In the world of improvement we also need simple, efficient, effective and elegant ways to combine the efforts of many in achieving a common purpose.  Such as raising the standards of excellence and weighing the anchors of resistance.

In health care improvement we have many simultaneous constraints and we have many stakeholders with specific perspectives and special expertise.

And if we are not careful they will tend to pull only in their preferred direction … like a multi-way tug-o-war.  The result?  No progress and exhausted protagonists.

There are those focused on improving productivity – Team Finance.

There are those focused on improving delivery – Team Operations.

There are those focused on improving safety – Team Governance.

And we are all tasked with improving quality – Team Everyone.

So we need a synergy machine that works like a capstan-of-old, and here is one design.

Engine_Of_ExcellenceIt has four poles and it always turns in a clockwise direction, so the direction of push is clear.

And when all the protagonists push in the same direction, they will get their own ‘win’ and also assist the others to make progress.

This is how the sails of success are hoisted to catch the wind of change; and how the anchors of anxiety are heaved free of the rocks of fear; and how the bureaucratic bilge is pumped overboard to lighten our load and improve our speed and agility.

And the more hands on the capstan the quicker we will achieve our common goal.

Collective excellence.

Undiscussables

Chimp_NoHear_NoSee_NoSpeakLast week I shared a link to Dr Don Berwick’s thought provoking presentation at the Healthcare Safety Congress in Sweden.

Near the end of the talk Don recommended six books, and I was reassured that I already had read three of them. Naturally, I was curious to read the other three.

One of the unfamiliar books was “Overcoming Organizational Defenses” by the late Chris Argyris, a professor at Harvard.  I confess that I have tried to read some of his books before, but found them rather difficult to understand.  So I was intrigued that Don was recommending it as an ‘easy read’.  Maybe I am more of a dimwit that I previously believed!  So fear of failure took over my inner-chimp and I prevaricated. I flipped into denial. Who would willingly want to discover the true depth of their dimwittedness!


Later in the week, I was forwarded a copy of a recently published paper that was on a topic closely related to a key thread in Dr Don’s presentation:

understanding variation.

The paper was by researchers who had looked at the Board reports of 30 randomly selected NHS Trusts to examine how information on safety and quality was being shared and used.  They were looking for evidence that the Trust Boards understood the importance of variation and the need to separate ‘signal’ from ‘noise’ before making decisions on actions to improve safety and quality performance.  This was a point Don had stressed too, so there was a link.

The randomly selected Trust Board reports contained 1488 charts, of which only 88 demonstrated the contribution of chance effects (i.e. noise). Of these, 72 showed the Shewhart-style control charts that Don demonstrated. And of these, only 8 stated how the control limits were constructed (which is an essential requirement for the chart to be meaningful and useful).

That is a validity yield of 8 out of 1488, or 0.54%, which is for all practical purposes zero. Oh dear!


This chance combination of apparently independent events got me thinking.

Q1: What is the reason that NHS Trust Boards do not use these signal-and-noise separation techniques when it has been demonstrated, for at least 12 years to my knowledge, that they are very effective for facilitating improvement in healthcare? (e.g. Improving Healthcare with Control Charts by Raymond G. Carey was published in 2003).

Q2: Is there some form of “organizational defense” system in place that prevents NHS Trust Boards from learning useful ‘new’ knowledge?


So I surfed the Web to learn more about Chris Argyris and to explore in greater depth his concept of Single Loop and Double Loop learning.  I was feeling like a dimwit again because to me it is not a very descriptive title!  I suspect it is not to many others too.

I sensed that I needed to translate the concept into the language of healthcare and this is what emerged.

Single Loop learning is like treating the symptoms and ignoring the disease.

Double Loop learning is diagnosing the underlying disease and treating that.


So what are the symptoms?
The pain of NHS Trust  failure on all dimensions – safety, delivery, quality and productivity (i.e. affordability for a not-for-profit enterprise).

And what are the signs?
The tell-tale sign is more subtle. It’s what is not present that is important. A serious omission. The missing bits are valid time-series charts in the Trust Board reports that show clearly what is signal and what is noise. This diagnosis is critical because the strategies for addressing them are quite different – as Julian Simcox eloquently describes in his latest essay.  If we get this wrong and we act on our unwise decision, then we stand a very high chance of making the problem worse, and demoralizing ourselves and our whole workforce in the process! Does that sound familiar?

And what is the disease?
Undiscussables.  Emotive subjects that are too taboo to table in the Board Room.  And the issue of what is discussable is one of the undiscussables so we have a self-sustaining system.  Anyone who attempts to discuss an undiscussable is breaking an unspoken social code.  Another undiscussable is behaviour, and our social code is that we must not upset anyone so we cannot discuss ‘difficult’ issues.  But by avoiding the issue (the undiscussable disease) we fail to address the root cause and end up upsetting everyone.  We achieve exactly what we are striving to avoid, which is the technical definition of incompetence.  And Chris Argyris labelled this as ‘skilled incompetence’.


Does an apparent lack of awareness of what is already possible fully explain why NHS Trust Boards do not use the tried-and-tested tool called a system behaviour chart to help them diagnose, design and deliver effective improvements in safety, flow, quality and productivity?

Or are there other forces at play as well?

Some deeper undiscussables perhaps?

Type II Error

figure_pointing_out_chart_data_150_clr_8005It was the time for Bob and Leslie’s regular Improvement Science coaching session.

<Leslie> Hi Bob, how are you today?

<Bob> I am getting over a winter cold but otherwise I am good.  And you?

<Leslie> I am OK and I need to talk something through with you because I suspect you will be able to help.

<Bob> OK. What is the context?

<Leslie> Well, one of the projects that I am involved with is looking at the elderly unplanned admission stream which accounts for less than half of our unplanned admissions but more than half of our bed days.

<Bob> OK. So what were you looking to improve?

<Leslie> We want to reduce the average length of stay so that we free up beds to provide resilient space-capacity to ease the 4-hour A&E admission delay niggle.

<Bob> That sounds like a very reasonable strategy.  So have you made any changes and measured any improvements?

<Leslie> We worked through the 6M Design® sequence. We studied the current system, diagnosed some time traps and bottlenecks, redesigned the ones we could influence, modified the system, and continued to measure to monitor the effect.

<Bob> And?

<Leslie> It feels better but the system behaviour charts do not show an improvement.

<Bob> Which charts, specifically?

<Leslie> The BaseLine XmR charts of average length of stay for each week of activity.

<Bob> And you locked the limits when you made the changes?

<Leslie> Yes. And there still were no red flags. So that means our changes have not had a significant effect. But it definitely feels better. Am I deluding myself?

<Bob> I do not believe so. Your subjective assessment is very likely to be accurate. Our Chimp OS 1.0 is very good at some things! I think the issue is with the tool you are using to measure the change.

<Leslie> The XmR chart?  But I thought that was THE tool to use?

<Bob> Like all tools it is designed for a specific purpose.  Are you familiar with the term Type II Error.

<Leslie> Doesn’t that come from research? I seem to remember that is the error we make when we have an under-powered study.  When our sample size is too small to confidently detect the change in the mean that we are looking for.

<Bob> A perfect definition!  The same error can happen when we are doing before and after studies too.  And when it does, we see the pattern you have just described: the process feels better but we do not see any red flags on our BaseLine© chart.

<Leslie> But if our changes only have a small effect how can it feel better?

<Bob> Because some changes have cumulative effects and we omit to measure them.

<Leslie> OMG!  That makes complete sense!  For example, if my bank balance is stable my average income and average expenses are balanced over time. So if I make a small-but-sustained improvement to my expenses, like using lower cost generic label products, then I will see a cumulative benefit over time to the balance, but not the monthly expenses; because the noise swamps the signal on that chart!

<Bob> An excellent analogy!

<Leslie> So the XmR chart is not the tool for this job. And if this is the only tool we have then we risk making a Type II error. Is that correct?

<Bob> Yes. We do still use an XmR chart first though, because if there is a big enough and fast enough shift then the XmR chart will reveal it.  If there is not then we do not give up just yet; we reach for our more sensitive shift detector tool.

<Leslie> Which is?

<Bob> I will leave you to ponder on that question.  You are a trained designer now so it is time to put your designer hat on and first consider the purpose of this new tool, and then create the outline a fit-for-purpose design.

<Leslie> OK, I am on the case!

Grit in the Oyster

Pearl_and_OysterThe word pearl is a metaphor for something rare, beautiful, and valuable.

Pearls are formed inside the shell of certain mollusks as a defense mechanism against a potentially threatening irritant.

The mollusk creates a pearl sac to seal off the irritation.


And so it is with change and improvement.  The growth of precious pearls of improvement wisdom – the ones that develop slowly over time – are triggered by an irritant.

Someone asking an uncomfortable question perhaps, or presenting some information that implies that an uncomfortable question needs to be asked.


About seven years ago a question was asked “Would improving healthcare flow and quality result in lower costs?”

It is a good question because some believe that it would and some believe that it would not.  So an experiment to test the hypothesis was needed.

The Health Foundation stepped up to the challenge and funded a three year project to find the answer. The design of the experiment was simple. Take two oysters and introduce an irritant into them and see if pearls of wisdom appeared.

The two ‘oysters’ were Sheffield Hospital and Warwick Hospital and the irritant was Dr Kate Silvester who is a doctor and manufacturing system engineer and who has a bit-of-a-reputation for asking uncomfortable questions and backing them up with irrefutable information.


Two rare and precious pearls did indeed grow.

In Sheffield, it was proved that by improving the design of their elderly care process they improved the outcome for their frail, elderly patients.  More went back to their own homes and fewer left via the mortuary.  That was the quality and safety improvement. They also showed a shorter length of stay and a reduction in the number of beds needed to store the work in progress.  That was the flow and productivity improvement.

What was interesting to observe was how difficult it was to get these profoundly important findings published.  It appeared that a further irritant had been created for the academic peer review oyster!

The case study was eventually published in Age and Aging 2014; 43: 472-77.

The pearl that grew around this seed is the Sheffield Microsystems Academy.


In Warwick, it was proved that the A&E 4 hour performance could be improved by focussing on improving the design of the processes within the hospital, downstream of A&E.  For example, a redesign of the phlebotomy and laboratory process to ensure that clinical decisions on a ward round are based on todays blood results.

This specific case study was eventually published as well, but by a different path – one specifically designed for sharing improvement case studies – JOIS 2015; 22:1-30

And the pearls of wisdom that developed as a result of irritating many oysters in the Warwick bed are clearly described by Glen Burley, CEO of Warwick Hospital NHS Trust in this recent video.


Getting the results of all these oyster bed experiments published required irritating the Health Foundation oyster … but a pearl grew there too and emerged as the full Health Foundation report which can be downloaded here.


So if you want to grow a fistful of improvement and a bagful of pearls of wisdom … then you will need to introduce a bit of irritation … and Dr Kate Silvester is a proven source of grit for your oyster!

New Meat for Old Bones

FreshMeatOldBonesEvolution is an amazing process.

Using the same building blocks that have been around for a lot time, it cooks up innovative permutations and combinations that reveal new and ever more useful properties.

Very often a breakthrough in understanding comes from a simplification, not from making it more complicated.

Knowledge evolves in just the same way.

Sometimes a well understood simplification in one branch of science is used to solve an ‘impossible’ problem in another.

Cross-fertilisation of learning is a healthy part of the evolution process.


Improvement implies evolution of knowledge and understanding, and then application of that insight in the process of designing innovative ways of doing things better.


And so it is in healthcare.  For many years the emphasis on healthcare improvement has been the Safety-and-Quality dimension, and for very good reasons.  We need to avoid harm and we want to achieve happiness; for everyone.

But many of the issues that plague healthcare systems are not primarily SQ issues … they are flow and productivity issues. FP. The safety and quality problems are secondary – so only focussing on them is treating the symptoms and not the cause.  We need to balance the wheel … we need flow science.


Fortunately the science of flow is well understood … outside healthcare … but apparently not so well understood inside healthcare … given the queues, delays and chaos that seem to have become the expected norm.  So there is a big opportunity for cross fertilisation here.  If we choose to make it happen.


For example, from computer science we can borrow the knowledge of how to schedule tasks to make best use of our finite resources and at the same time avoid excessive waiting.

It is a very well understood science. There is comprehensive theory, a host of techniques, and fit-for-purpose tools that we can pick of the shelf and use. Today if we choose to.

So what are the reasons we do not?

Is it because healthcare is quite introspective?

Is it because we believe that there is something ‘special’ about healthcare?

Is it because there is no evidence … no hard proof … no controlled trials?

Is it because we assume that queues are always caused by lack of resources?

Is it because we do not like change?

Is it because we do not like to admit that we do not know stuff?

Is it because we fear loss of face?


Whatever the reasons the evidence and experience shows that most (if not all) the queues, delays and chaos in healthcare systems are iatrogenic.

This means that they are self-generated. And that implies we can un-self-generate them … at little or no cost … if only we knew how.

The only cost is to our egos of having to accept that there is knowledge out there that we could use to move us in the direction of excellence.

New meat for our old bones?

Survival of the Fittest

business_race__PA_150_wht_3222There is a widely held belief that competition is the only way to achieve improvement.

This is a limiting belief.

But our experience tells us that competition is an essential part of improvement!

So which is correct?


When two athletes compete they both have to train hard to improve their individual performance. The winner of the race is the one who improves the most.  So by competing with each other they are forced to improve.

The goal of improvement is excellence and the test-of-excellence is performed in the present and is done by competing with others. The most excellent is labelled the “best” or “winner”. Everyone else is branded “second best” or “loser”.

This is where we start to see the limiting belief of competition.

It has a crippling effect.  Many competitive people will not even attempt the race if they do not feel they can win.  Their limiting belief makes them too fearful. They fear loss of self-esteem. Their ego is too fragile. They value hubris more than humility. And by not taking part they abdicate any opportunity to improve. They remain arrogantly mediocre and blissfully ignorant of it. They are the real losers.


So how can we keep the positive effect of competition and at the same time escape the limiting belief?

There are two ways:

First we drop the assumption that the only valid test of excellence is a comparison of us with others in the present.  And instead we adopt the assumption that it is equally valid to compare us with ourselves in the past.

We can all improve compared with what we used to be. We can all be winners of that race.

And as improvement happens our perspective shifts.  What becomes normal in the present would have been assumed to be impossible in the past.


This week I sat at my desk in a state of wonder.

I held in my hand a small plastic widget about the size of the end of my thumb.  It was a new USB data stick that had just arrived, courtesy of Amazon, and on one side in small white letters it proudly announced that it could hold 64 Gigabytes of data (that is 64 x 1024 x 1024 x 1024). And it cost less than a take-away curry.

About 30 years ago, when I first started to learn how to design, build and program computer system, a memory chip that was about the same size and same cost could hold 4 kilobytes (4 x 1024).  

So in just 30 years we have seen a 16-million-fold increase in data storage capacity. That is astounding! Our collective knowledge of how to design and build memory chips has improved so much. And yet we take it for granted.


The second way to side-step the limiting belief is even more powerful.

It is to drop the belief that individual improvement is enough.

Collective improvement is much, much, much more effective.


Cell_StructureEvidence:

The human body is made up of about 50 trillion (50 x 1000 x 1000 x 1000 x 1000) cells – about the same as the number of bytes could store on 1000 of my wonderful new 64 Gigabyte data sticks!

And each cell is a microscopic living individual. A nano-engineered adaptive system of wondrous complexity and elegance.

Each cell breathes, eats, grows, moves, reproduces, senses, learns and remembers. These cells are really smart too! And they talk to each other, and they learn from each other.

And what makes the human possible is that its community of 50 trillion smart cells are a collaborative community … not a competitive community.

If all our cells started to compete with each other we would be very quickly reduced to soup (which is what the Earth was bathed in for about 2.7 billions years).

The first multi-celled organisms gained a massive survival advantage when they learned how to collaborate.

The rest is the Story of Evolution.  Even Charles Darwin missed the point – evolution is more about collaboration than competition – and we are only now beginning to learn that lesson. The hard way.  


come_join_the_team_150_wht_10876So survival is about learning and improving.

And survival of the fittest does not mean the fittest individual … it means the fittest group.

Collaborative improvement is the process through which we can all achieve win-win-win excellence.

And the understanding of how to do this collaborative improvement has a name … it is called Improvement Science.

Early Adoption

Rogers_CurveThe early phases of a transformation are where most fall by the wayside.

And the failure rate is horrifying – an estimated 80% of improvement initiatives fail to achieve their goals.

The recent history of the NHS is littered with the rusting wreckage of a series of improvement bandwagons.  Many who survived the crashes are too scarred and too scared to try again.


Transformation and improvement imply change which implies innovation … new ways of thinking, new ways of behaving, new techniques, new tools, and new ways of working.

And it has been known for over 50 years that innovation spreads in a very characteristic way. This process was described by Everett Rogers in a book called ‘Diffusion of Innovations‘ and is described visually in the diagram above.

The horizontal axis is a measure of individual receptiveness to the specific innovation … and the labels are behaviours: ‘I exhibit early adopter behaviour‘ (i.e. not ‘I am an early adopter’).

What Roger’s discovered through empirical observation was that in all cases the innovation diffuses from left-to-right; from innovation through early adoption to the ‘silent’ majority.


Complete diffusion is not guaranteed though … there are barriers between the phases.

One barrier is between innovation and early adoption.

There are many innovations that we never hear about and very often the same innovation appears in many places and often around the same time.

This innovation-adoption barrier is caused by two things:
1) most are not even aware of the problem … they are blissfully ignorant;
2) news of the innovation is not shared widely enough.

Innovators are sensitive people.  They sense there is a problem long before others do. They feel the fear and the excitement of need for innovation. They challenge their own assumptions and they actively seek solutions. They swim against the tide of ignorance, disinterest, skepticism and often toxic cynicism.  So when they do discover a way forward they often feel nervous about sharing it. They have learned (the hard way) that the usual reaction is to be dismissed and discounted.  Most people do not like to learn about unknown problems and hazards; and they like it even less to learn that there are solutions that they neither recognise nor understand.


But not everyone.

There is a group called the early adopters who, like the innovators, are aware of the problem. They just do not share the innovator’s passion to find a solution … irrespective of the risks … so they wait … their antennae tuned for news that a solution has been found.

Then they act.

And they act in one of two ways:

1) Talkers … re-transmit the news of the problem and the discovery of a generic solution … which is essential in building awareness.

2) Walkers … try the innovative approach themselves and in so doing learn a lot about their specific problem and the new ways to solving it.

And it is the early adopters that do both of these actions that are the most effective and the most valuable to everyone else.  Those that talk-the-new-walk and walk-the-new-talk.

And we can identify who they are because they will be able to tell stories of how they have applied the innovation in their world; and the results that they have achieved; and how they achieved them; and what worked well; and what did not; and what they learned; and how they evolved and applied the innovation to meet their specific needs.

They are the leaders, the coaches and the teachers of improvement and transformation.

They See One, Do Some, and Teach Many.

The early adopters are the bridge across the Innovation and Transformation Chasm.

Not as Easy as it Looks

smack_head_in_disappointment_150_wht_16653One of the traps for the inexperienced Improvement Science Practitioner is to believe that applying the science in the real world is as easy as it is in the safety of the training environment.

It isn’t.

The real world is messier and more complicated and it is easy to get lost in the fog of confusion and chaos.


So how do we avoid losing our footing, slipping into the toxic emotional swamp of organisational culture and giving ourselves an unpleasant dunking!

We use safety equipment … to protect ourselves and others from unintended harm.

The Improvement-by-Design framework is like a scaffold.  It is there to provide structure and safety.  The techniques and tools are like the harnesses, shackles, ropes, crampons, and pitons.  They give us flexibility and security.

But we need to know how to use them. We need to be competent as well as confident.

We do not want to tie ourselves up in knots … and we do not want to discover that we have not tied ourselves to something strong enough to support us if we slip. Which we will.


So we need to learn an practice the basics skills to the point that they are second nature.

We need to learn how to tie secure knots, quickly and reliably.

We need to learn how to plan an ascent … identifying the potential hazards and designing around them.

We need to learn how to assemble and check what we will need before we start … not too much and not too little.

We need to learn how to monitor out progress against our planned milestones and be ready to change the plan as we go …and even to abandon the attempt if necessary.


We would not try to climb a real mountain without the necessary training, planning, equipment and support … even though it might look easy.

And we do not try to climb an improvement mountain without the necessary training, planning, tools and support … even though it might look easy.

It is not as easy as it looks.

The “I am Great (and You are Not)” Trap

business_race__PA_150_wht_3222When we start the process of learning to apply the Science of Improvement in practice we need to start within our circle of influence.

It is just easier, quicker and safer to begin there – and to build our capability, experience and confidence in steps.

And when we get the inevitable ‘amazing’ result it is natural and reasonable for us to want to share the good news with others.  We crossed the finish line first and we want to celebrate.   And that is exactly what we need to do.


We just need to be careful how we do it.

We need to be careful not to unintentionally broadcast an “I am Great (and You are Not)” message – because if we do that we will make further change even more difficult.


Competition can be healthy or unhealthy  … just as scepticism can be.

We want to foster healthy competition … and to do that we have to do something that can feel counter-intuitive … we have to listen to our competitors; and we have to learn from them; and we have to share our discoveries with them.

Eh?


Just picture these two scenarios in your mind’s eye:

Scenario One: The competition is a war. There can only be one winner … the strongest, most daring, most cunning, most ruthless, most feared competitor. So secrecy and ingenuity are needed. Information must be hoarded. Untruths and confusion must be spread.

Scenario Two: The competition is a race. There can only be one winner … the strongest, most resilient, hardest working, fastest learning, most innovative, most admired competitor.  So openness and humility are needed. Information must be shared. Truths and clarity must be spread.

Compare the likely outcomes of the two scenarios.

Which one sounds the more productive, more rewarding and more enjoyable?


So the challenge for the champions of improvement is to appreciate and to practice a different version of the “I’m Great … ” mantra …

I’m Great (And So Are You).

Over-Egged Expectation

FISH_ISP_eggs_jumpingResistance-to-change is an oft quoted excuse for improvement torpor. The implied sub-message is more like “We would love to change but They are resisting“.

Notice the Us-and-Them language.  This is the observable evidence of an “We‘re OK and They’re Not OK” belief.  And in reality it is this unstated belief and the resulting self-justifying behaviour that is an effective barrier to systemic improvement.

This Us-and-Them language generates cultural friction, erodes trust and erects silos that are effective barriers to the flow of information, of innovation and of learning.  And the inevitable reactive solutions to this Us-versus-Them friction create self-amplifying positive feedback loops that ensure the counter-productive behaviour is sustained.

One tangible manifestation are DRATs: Delusional Ratios and Arbitrary Targets.


So when a plausible, rational and well-evidenced candidate for an alternative approach is discovered then it is a reasonable reaction to grab it and to desperately spray the ‘magic pixie dust’ at everything.

This a recipe for disappointment: because there is no such thing as ‘improvement magic pixie dust’.

The more uncomfortable reality is that the ‘magic’ is the result of a long period of investment in learning and the associated hard work in practising and polishing the techniques and tools.

It may look like magic but is isn’t. That is an illusion.

And some self-styled ‘magicians’ choose to keep their hard-won skills secret … because by sharing them know that they will lose their ‘magic powers’ in a flash of ‘blindingly obvious in hindsight’.

And so the chronic cycle of despair-hope-anger-and-disappointment continues.


System-wide improvement in safety, flow, quality and productivity requires that the benefits of synergism overcome the benefits of antagonism.  This requires two changes to the current hope-and-despair paradigm.  Both are necessary and neither are sufficient alone.

1) The ‘wizards’ (i.e. magic folk) share their secrets.
2) The ‘muggles’ (i.e. non-magic folk) invest the time and effort in learning ‘how-to-do-it’.


The transition to this awareness is uncomfortable so it needs to be managed pro-actively … by being open about the risk … and how to mitigate it.

That is what experienced Practitioners of Improvement Science (and ISP) will do. Be open about the challenged ahead.

And those who desperately want the significant and sustained SFQP improvements; and an end to the chronic chaos; and an end to the gaming; and an end to the hope-and-despair cycle …. just need to choose. Choose to invest and learn the ‘how to’ and be part of the future … or choose to be part of the past.


Improvement science is simple … but it is not intuitively obvious … and so it is not easy to learn.

If it were we would be all doing it.

And it is the behaviour of a wise leader of change to set realistic and mature expectations of the challenges that come with a transition to system-wide improvement.

That is demonstrating the OK-OK behaviour needed for synergy to grow.

Co-Labor-Ation

Dr_Bob_ThumbnailBob and Leslie were already into the dialogue of their regular ISP coaching session when Bob saw an incoming text from one of his other ISPees. It was simply marked: “Very Urgent”.

<Bob> Leslie, I have just received an urgent SMS that I think I need to investigate immediately. Could we put this conversation on ice for 10 minutes and I will call you back?

<Leslie> Of course. I have lots to do. Please do not rush back if it requires more time.

<Bob> Thank you.

Ten minutes later Leslie saw that Bob was phoning and picked up.

<Leslie> Hi Bob.  I hope you were able to sort out the urgent problem. The fact that you are back suggests you did.

<Bob> Hi Leslie.  Thank you for your understanding and patience. The issue was urgent and the root cause is not yet solved, but lessons are being learned.  And this is one you are going to come up against too so it may be an opportune time to explore it.

<Leslie> H’mm. Now you have pricked my curiosity. But you can’t discuss someone else’s problem with me surely!

<Bob> No indeed.  Strict confidentiality is essential.  We can talk about the generic issue though, without disclosing any details.  Do you remember that project you were doing last year where you achieved an initial success and then it all seemed to go wobbly?

<Leslie> Yes. At the time you said that I needed to put that one on the shelf and to press on with other projects. I think the phrase you used was “it needs to stew for a while“.

<Bob> And what happened?

<Leslie> The hard won improvement in performance slipped back and I felt like a failure and started to lose confidence. You said not to blame myself but to learn and  move on.  The lesson was I did not appreciate the difference between circles of control and circles of influence. I was trying to influence others before I had mastered self-control.

<Bob> Yes. There was another factor too but I did not feel it was the time to explore it. Now feels like a better time.

<Leslie> OK … now my curiosity is really fired up.

<Bob> Do you remember last week’s blog about the Improvement Gearbox?

<Leslie> Yes. I really liked the mechanical metaphor.  It resonated with so many things. I have used it several times this week in conversations.

<Bob> Well, there is a close relationship between the level of challenge and the gearbox.  As complexity increases we need to be able to use more of the gears, and to change up and down with ease and according to need.

<Leslie> Change down? I sort of assumed that once you got to fourth gear you stay there.

<Bob> That is true if the terrain is level and everyone is on board the bus with the same destination in mind.  In reality the terrain goes up and down and as we learn we need to stop and let some people get off and take others on board.

<Leslie> So we need to change down gears on the uphill bits, change up gears on the downhill, and go through the whole gear sequence when we deliberately slow to a halt, and then get on our way again.

<Bob> Yes. Well put. The world is changing all the time and the team on board is in dynamic flux. Some arrive, some leave and others stay on the bus but change seats as we move along.  Not all seats suit all people. What is comfortable for one may be painful for another.

<Leslie> So how come the urgent call?

<Bob> A fight had broken out on their bus, the tribes were arguing because the improvements they have made have blown away some of the fog and exposed some deeper cultural cracks. Cracks that had been there all the time but were concealed by the fog of the daily chaos and the smoke of the burning martyrs. They had taken their eye off the road and were heading for a blind bend unaware of what was around the corner.

<Leslie> So your intervention was to shout “Pay attention to the road and make a decision … steer or stop!

<Bob> Yes, that about sums it up.  A co-labor-ation call.

<Leslie> Eh? Dis you just say collaboration in a weird way?

<Bob> Yes. I chopped it up into concepts … “co” means together, “labor” means work and “ation” means action or process.  If they do not learn to co-labor-ate then they will come off the road, crash, and burn. And join the graveyard of improvement train wrecks that litter the verges of the rocky road of change.

<Leslie> Fourth gear stuff?

<Bob> Whole gearbox stuff. All gears between first and fourth because they are all necessary at different times.  Each gear builds on those which go before. There are no good or bad gears just fit-for-current-purpose or not.  Bad driving is ineptitude. Not using the vehicle’s gearbox effectively and efficiently and risking the safety and comfort of the passengers and other road users. Poor leadership is analogous to poor driving. Dangerous.

<Leslie> So an effective leader of change needs to be able to use all the gears competently and to know when to use which and when to change. And in doing so demonstrate what a safe pair of leadership hands looks like and what it can achieve … through collaborative effort.

<Bob> Perfect!  It is time for you to tear up your L plates.

The Improvement Gearbox

GearboxOne of the most rewarding experiences for an improvement science coach is to sense when an individual or team shift up a gear and start to accelerate up their learning curve.

It is like there is a mental gearbox hidden inside them somewhere.  Before they were thrashing themselves by trying to go too fast in a low gear. Noisy, ineffective, inefficient and at high risk of blowing a gasket!

Then, they discover that there is a higher gear … and that to get to it they have to take a risk … depress the emotional clutch, ease back on the gas, slip into neutral, and trust themselves to find the new groove and … click … into the higher gear, and then ease up the power while letting out the clutch.  And then accelerate up the learning  curve.  More effective, more efficient. More productive. More fun.


Organisations appear to behave in much the same way.

Some scream along in the slow-lane … thrashing their employee engine. The majority chug complacently in the middle-lane of mediocrity. A few accelerate past in the fast-lane to excellence.

And they are all driving exactly the same model of car.

So it is not the car that is making the difference … it is the driving.


Those who have studied organisations have observed five cultural “gears”; and which gear an organisation is in most of the time can be diagnosed by listening to the sound of the engine – the conversations of the employees.

If they are muttering “work sucks” then they are in first gear.  The sense of hopelessness, futility, despair and anger consumes all their emotional fuel. Fortunately this is uncommon.

If we mainly hear “my work sucks” then they are in second gear.  The feeling is of helplessness and apathy and the behaviour is Victim-like.  They believe that they cannot solve their own problems … someone else must do it for them or tell them what to do. They grumble a lot.

If the dominant voice is “I’m great but you lot suck” then we are hearing third gear attitudes. The selfishly competitive behaviour of the individualist achiever. The “keep your cards close to your chest” style of dyadic leadership.  The advocate of “it is OK to screw others to get ahead”. They grumble a lot too – about the apathetic bunch.

And those who have studied organisations suggest that about 80% of healthcare organisations are stuck in first, second or third cultural gear.  And we can tell who they are … the lower 80% of the league tables. The ones clamouring for more … of everything.


So how come so many organisations are so stuck? Unable to find fourth gear?

One cause is the design of their feedback loops. Their learning loops.

If an organisation only uses failure as a feedback loop then it is destined to get no more than mediocrity.  Third gear at best, and usually only second.

Example.
We all feel disappointment when our experience does not live up to our expectation.  But only the most angry of us will actually do something and complain.  Especially when we have no other choice of provider!

Suppose we are commissioners of healthcare services and we are seeing a rising tide of patient and staff complaints. We want to improve the safety and quality of the services that we are paying for; so we draw up a league table using complaints as feedback fodder and we focus on the worst performing providers … threatening them with dire consequences for being in the bottom 20%.  What happens? Fear of failure motivates them to ‘pull up their socks’ and the number of complaints falls.

Job done?

Unfortunately not.

All we have done is to bully those stuck in first or second gear into thrashing their over-burdened employee engine even harder.  We have not helped anyone find their higher gear. We have hit the target, missed the point, and increased the risk of system failure!

So what about those organisations stuck in third gear?

Well they are ticking their performance boxes, meeting our targets, keeping their noses clean.  Some are just below, and some just above the collective mean of barely acceptable mediocrity.

But expectation is changing.

The 20% who have discovered fourth gear are accelerating ahead and are demonstrating what is possible. And they are raising expectation, increasing the variation of service quality … for the better.

And the other 80% are falling further and further behind; thrashing their tired and demoralised staff harder and harder to keep up.  Complaining increasingly that life is unfair and that they need more, time, money and staff engagement. Eventually their executive head gaskets go “pop” and they fall by the wayside.


Finding cultural fourth gear is possible but it is not easy. There are no short cuts.  We have to work our way up the gears and we have to learn when and how to make smooth transitions from first to second, second to third and then third to fourth.

And when we do that the loudest voice we hear is “We are OK“.

We need to learn how to do a smooth cultural hill start on the steep slope from apathy to excellence.

And we need to constantly listen to the sound of our improvement engine; to learn to understand what it is saying; and learn how and when to change to the next cultural gear.

Circles

SFQP_enter_circle_middle_15576For a system to be both effective and efficient the parts need to work in synergy. This requires both alignment and collaboration.

Systems that involve people and processes can exhibit complex behaviour. The rules of engagement also change as individuals learn and evolve their beliefs and their behaviours.

The values and the vision should be more fixed. If the goalposts are obscure or oscillate then confusion and chaos is inevitable.


So why is collaborative alignment so difficult to achieve?

One factor has been mentioned. Lack of a common vision and a constant purpose.

Another factor is distrust of others. Our fear of exploitation, bullying, blame, and ridicule.

Distrust is a learned behaviour. Our natural inclination is trust. We have to learn distrust. We do this by copying trust-eroding behaviours that are displayed by our role models. So when leaders display these behaviours then we assume it is OK to behave that way too.  And we dutifully emulate.

The most common trust eroding behaviour is called discounting.  It is a passive-aggressive habit characterised by repeated acts of omission:  Such as not replying to emails, not sharing information, not offering constructive feedback, not asking for other perspectives, and not challenging disrespectful behaviour.


There are many causal factors that lead to distrust … so there is no one-size-fits-all solution to dissolving it.

One factor is ineptitude.

This is the unwillingness to learn and to use available knowledge for improvement.

It is one of the many manifestations of incompetence.  And it is an error of omission.


Whenever we are unable to solve a problem then we must always consider the possibility that we are inept.  We do not tend to do that.  Instead we prefer to jump to the conclusion that there is no solution or that the solution requires someone else doing something different. Not us.

The impossibility hypothesis is easy to disprove.  If anyone has solved the problem, or a very similar one, and if they can provide evidence of what and how then the problem cannot be impossible to solve.

The someone-else’s-fault hypothesis is trickier because proving it requires us to influence others effectively.  And that is not easy.  So we tend to resort to easier but less effective methods … manipulation, blame, bullying and so on.


A useful way to view this dynamic is as a set of four concentric circles – with us at the centre.

The outermost circle is called the ‘Circle of Ignorance‘. The collection of all the things that we do not know we do not know.

Just inside that is the ‘Circle of Concern‘.  These are things we know about but feel completely powerless to change. Such as the fact that the world turns and the sun rises and falls with predictable regularity.

Inside that is the ‘Circle of Influence‘ and it is a broad and continuous band – the further away the less influence we have; the nearer in the more we can do. This is the zone where most of the conflict and chaos arises.

The innermost is the ‘Circle of Control‘.  This is where we can make changes if we so choose to. And this is where change starts and from where it spreads.


SFQP_enter_circle_middle_15576So if we want system-level improvements in safety, flow, quality and productivity (or cost) then we need to align these four circles. Or rather the gaps in them.

We start with the gaps in our circle of control. The things that we believe we cannot do … but when we try … we discover that we can (and always could).

With this new foundation of conscious competence we can start to build new relationships, develop trust and to better influence others in a win-win-win conversation.

And then we can collaborate to address our common concerns – the ones that require coherent effort. We can agree and achieve our common purpose, vision and goals.

And from there we will be able to explore the unknown opportunities that lie beyond. The ones we cannot see yet.

A School for Rebels

Troublemaker_vs_RebelSystem-wide, significant, and sustained improvement implies system-wide change.

And system-wide change implies more than 20% of the people commit to action. This is the cultural tipping point.

These critical 20% have a badge … they call themselves rebels … and they are perceived as troublemakers by those who profit most from the status quo.

But troublemakers and rebels are radically different … as shown in the summary by Lois Kelly.


Rebels share a common, future-focussed purpose.  A mission.  They are passionate, optimistic and creative.  They understand synergy and how to release and align the stored emotional energy of both themselves and others.  And most importantly they are value-led and that makes them attractive.  Values such as honesty, integrity and industry are what make leaders together-effective.

SHCR_logoAnd as we speak there is school for rebels in healthcare gaining momentum …  and their programme is current, open to all and free to access. And the change agent development materials are excellent!

Click here to download their study guide.


Converting possibilities into realities is the essence of design … so our merry band of rebels will also need to learn how to convert their positive rhetoric into practical reality. And that is more physics than psychology.

Streams flow because of physics not because of passion.SFQP_Compass

And this is why the science of improvement is important because it is the synthesis of the people dimension and the process dimension – into a system that delivers significant and sustained improvement.

On all dimensions. Safety, Flow, Quality and Productivity.

The lighthouse is our purpose; the whale represents the magnitude of our challenge; the blue sky is the creative thinking we need … to avoid trying to boil the ocean.

And the noisy, greedy, s****y seagulls are the troublemakers who always will plague us.

[Image by Malaika Art].


People first or Process first?

stick_figure_balance_mind_heart_150_wht_9344A recurring theme this week has been the interplay between the cultural and the technical dimensions of system improvement.

The hearts and the minds.  The people and the process.  The psychology and the physics.

Reflecting on the many conversations what became clear was that both are required but not always in the same amount and in the same sequence.

The context is critical.

In some cases we can start with some technical stuff. Some flow physics and a Gantt and Run chart or two.

In other cases we have to start with some cultural stuff. Some conversations about values, beliefs and behaviours.

And they are both tricky but in different ways.


The technical stuff is counter-intuitive.  We have to engage our logical, rational thinking brains and work it through step-by-step, making every assumption explicit and every definition clear.

If we go with our gut we get it wrong (although we feel it is right) and then we fail, and then we blame others or ourselves. Either way we lose confidence.  The logical thinking is hard work. It makes our heads ache. So we cut corners.

But once we have understood then it gets much easier because we can then translate our hard won understanding into a trusted heuristic.  We do not need to work it out every time. We can just look up the correct recipe.

And there lurks a trap … the problem that was at first unrecognised, then impossible, then difficult, and then doable … becomes easy and even obvious … but only after we have worked out a solution. And that obvious-in-hindsight effect is a source of many dangers …

… we can become complacent, over-confident, and even dismissive of others who have not been through the ‘pain’ of learning. We may be tempted to elevate our status and to inflate our importance by hoarding our hard-won understanding. We risk losing our humility … and when we do that we stop being curious and we stop learning. And then we are part of the problem again.

So to avoid those traps we need to hold ourselves in the role of the teacher and coach. We need to actively share what we have learned and explain how we came to know it.  One step at a time … the blood, the sweat and the tears … the confusion and eureka moments. Not one giant leap from where we started to where we got to.  And when we have the generosity to share our knowledge … it is surprising how much we learn!  We learn more from teaching than by being taught.


The cultural stuff is counter-intuitive too.  We have to engage our emotional, irrational, feeling brains and step back from the objective fine-print to look at the subjective full-picture. We have to become curious. We have to look at the problem from as many perspectives as we can. We have to practice humble inquiry by asking others what they see.

If we go with our gut  and rely only on our learned and habitual beliefs, our untested assumptions and our prejudices … we get it wrong. When we filter reality to match our rhetoric, we leap to invalid conclusions, and we make unwise decisions, and they lead to counter-productive actions.

Our language and behaviour gives the game away … we cannot help it … because all this is happening unconsciously and out of our awareness.

So we need to solicit unfiltered feedback from trusted others who will describe what they see.  And that is tough to do.


So how do we know where to act first? Cultural or technical?

The conclusion I have come to is to use a check-list … the Safe System Improvement check-list so to speak.

Check cultural first – Is there a need to do some people stuff? If so then do it.

Check technical second – Is there a need to do some process stuff? If so then do it.

If neither are needed then we need to get out of the way and let the people redesign the processes. Only they can.

Metamorphosis

butterfly_flying_around_465Some animals undergo a remarkable transformation on their journey to becoming an adult.

This metamorphosis is most obvious with a butterfly: the caterpillar enters the stage and a butterfly emerges.

The capabilities and behaviours of these development stages are very different.  A baby caterpillar crawls and feeds on leaves;  an adult butterfly flies and feeds on nectar.


There are many similarities to the transformation of an organisation from chaotic to calm; from depressed to enthused; and from struggling to flying.

It is the metamorphosis of individuals within organisations that drives the system change – the transformation from inept sceptics to capable advocates.


metamorphosis_1The journey starts with the tiny, hungry, baby caterpillar emerging from the egg.

This like a curious new sceptic emerging from denial and tentatively engaging the the process of learning. Usually triggered by seeing or hearing of a significant and sustained success that disproves their ‘impossibility hypothesis’.


metamorphosis_2A caterpillar is an eating machine. As it grows it sheds its skin and becomes larger. It also changes its appearance and eventually its behaviour.

Our curious improvement sceptic is devouring new information and is visibly growing in knowledge, understanding and confidence. 


metamorphosis_3When the caterpillar sheds the last skin a new form emerges. A pupa. It has a different appearance and behaviour. It is now stationary and it does not move or eat.

This is the contemplative sceptic who appears to have become dormant but is not … they are planning to change. This stage is very variable: it may be minutes or years.


metamorphosis_5Inside the pupa the solid body of the caterpillar is converted to ‘cellular soup’ and the cells are reassembled into a completely new structure called an adult butterfly.

Our healthy sceptic is dissolving their self-limiting beliefs and restructuring their mental model. It is stage of apparent confusion and success is not guaranteed.


metamorphosis_7And suddenly the adult butterfly emerges: fully formed but not yet able to fly. Its wings are not yet ready – they need to be inflated, to dry and be flexed.

So it is with our newly hatched improvement practitioner. They need to pause, prepare, and practice before they feel safe to fly solo.  They start small but are thinking big.


metamorphosis_8After a short rest the new wings are fully expanded and able to lift the butterfly aloft to explore the new opportunities that await. A whole new and exciting world full of flowers and nectar.

Our improvement practitioner can also feel when they are ready to explore. And then they fly – right first time.


An active improvement practitioner will inspire others to emerge, and many of those will hatch into improvement caterpillars who will busily munch on the new knowledge and grow in understanding and confidence. Then it goes quiet and, as if by magic, a new generation of improvement butterflies appear. And they continue to spread the word and the knowledge.

That is how Improvement Science grows and spreads – by metamorphosis.

World Class Improvement

figure_weight_lift_success_150_wht_12334Improvement Science is exactly like a sport: it requires training and practice to do well.

Elite athletes do not just turn up and try hard … they have invested thousands of hours of blood, sweat and tears to even be eligible to turn up.

And their preparation is not random or haphazard … it is structured and scientific.  Sport is a science.

So it is well worth using this sporting metaphor to outline some critical-to-success factors … because the statistics on improvement projects is not good.

It is said that over 70% of improvement projects fail to achieve their goals.

figure_weight_lift_fail_anim_150_wht_12338That is a shocking statistic. It is like saying 70% of runners who start a race do not finish!

And in sport if you try something that you are not ready for then you can seriously damage your health. So just turning up and trying hard is not enough. In can actually be counter-productive!

Common sense tells us that those fail to complete the course were not well enough prepared to undertake the challenge.  We know that only one person can win a race … but everyone else could finish it.  And to start and finish a tough race is a major achievement for each participant.

It is actually their primary goal.

Being good enough to when we need to is the actual objective;  being the best-on-the-day is a bonus. Not winning is not a failure. Not finishing is.


So how does an Improvement Scientist prepare for the improvement challenge?

First, we need enough intrinsic motivation to get out of bed and to invest the required time and effort.  We must have enough passion to get started and to keep going.  We must be disappointed enough with past failures to commit to preventing future ones.  We must be angry enough with the present problems to take action … not on the people … but on the problem. We must be fearful enough of the future consequences of inaction to force us to act. And we need to be excited enough by the prospect of success to reach out for it.

Second, we need some technical training.  How to improve the behaviour and performance of  a complex adaptive system is not obvious. If it were we would all know how to do it. Many of the most effective designs appear counter-intuitive at first sight.  Many of our present assumptions and beliefs are actually a barrier to change.  So we need help and guidance in identifying what assumptions we need to unlearn.

stick_woman_toe_touch_150_wht_12023Third, We need to practice what we have learned until it becomes second-nature, and almost effortless. Deceptively easy to the untrained eye.  And we develop our capability incrementally by taking on challenges of graded difficulty. Each new challenge is a bit of a stretch, and we build on what we have achieved already.  There are no short cuts or quick fixes if we want to be capable and confident at taking on BIG improvement challenges.


And we need a coach as well as a trainer.

The role of a trainer is to teach us technical skills and to develop our physical strength, stamina and resilience.

The role of the coach is to help us develop our emotional stamina and resilience.  We need to learn to manage our minds as much as our muscles. We all harbour self-defeating attitudes, beliefs and behaviours. Bad habits that trip us up and cause us to slip, fall and bruise our egos and confidence.

The psychological development is actually more important than the physical … because if is our self-defeating “can’t do” and “yes but” inner voices that sap our intrinsic motivation and prevent us crawling out of bed and getting started.

bicycle_racer_150_wht_5606The UK Cycling Team that won multiple goal medals in the 2012 Olympics did not just train hard and have the latest and best equipment. They also had the support of a very special type of coach. Dr Steve Peters … who showed them how to manage their inner Chimp … and how to develop their mental strength in synergy with their technical ability. The result was a multi-gold medal winning engine.

And we can all benefit from this wisdom just by reading The Chimp Paradox by Dr Steve Peters.


So when we take on a difficult improvement challenge, one that many have tried and failed to overcome, and if we want world class performance as the outcome … then we need to learn the hard-won lessons of the extreme athletes … and we need to model their behaviour.

Because that is what it takes to become an Improvement Science Practitioner.

Our goal is to finish each improvement race that we start … to deliver a significant and sustained improvement.  We do not need to be perfect or the best … we just need to start and finish the race.

A Little Law and Order

teamwork_puzzle_build_PA_150_wht_2341[Bing bong]. The sound heralded Lesley logging on to the weekly Webex coaching session with Bob, an experienced Improvement Science Practitioner.

<Bob> Good afternoon Lesley.  How has your week been and what topic shall we explore today?

<Lesley> Hi Bob. Well in a nutshell, the bit of the system that I have control over feels like a fragile oasis of calm in a perpetual desert of chaos.  It is hard work keeping the oasis clear of the toxic sand that blows in!

<Bob> A compelling metaphor. I can just picture it.  Maintaining order amidst chaos requires energy. So what would you like to talk about?

<Lesley> Well, I have a small shoal of FISHees who I am guiding  through the foundation shallows and they are getting stuck on Little’s Law.  I confess I am not very good at explaining it and that suggests to me that I do not really understand it well enough either.

<Bob> OK. So shall we link those two theme – chaos and Little’s Law?

<Lesley> That sounds like an excellent plan!

<Bob> OK. So let us refresh the foundation knowledge. What is Little’s Law?

<Lesley>It is a fundamental Law of process physics that relates flow, with lead time and work in progress.

<Bob> Good. And specifically?

<Lesley> Average lead time is equal to the average flow multiplied by the average work in progress.

<Bob>Yes. And what are the units of flow in your equation?

<Lesley> Ah yes! That is  a trap for the unwary. We need to be clear how we express flow. The usual way is to state it as number of tasks in a defined period of time, such as patients admitted per day.  In Little’s Law the convention is to use the inverse of that which is the average interval between consecutive flow events. This is an unfamiliar way to present flow to most people.

<Bob> Good. And what is the reason that we use the ‘interval between events’ form?

<Leslie> Because it is easier to compare it with two critically important  flow metrics … the takt time and the cycle time.

<Bob> And what is the takt time?

<Leslie> It is the average interval between new tasks arriving … the average demand interval.

<Bob> And the cycle time?

<Leslie> It is the shortest average interval between tasks departing …. and is determined by the design of the flow constraint step.

<Bob> Excellent. And what is the essence of a stable flow design?

<Lesley> That the cycle time is less than the takt time.

<Bob>Why less than? Why not equal to?

<Leslie> Because all realistic systems need some flow resilience to exhibit stable and predictable-within-limits behaviour.

<Bob> Excellent. Now describe the design requirements for creating chronically chaotic system behaviour?

<Leslie> This is a bit trickier to explain. The essence is that for chronically chaotic behaviour to happen then there must be two feedback loops – a destabilising loop and a stabilising loop.  The destabilising loop creates the chaos, the stabilising loop ensures it is chronic.

<Bob> Good … so can you give me an example of a destabilising feedback loop?

<Leslie> A common one that I see is when there is a long delay between detecting a safety risk and the diagnosis, decision and corrective action.  The risks are often transitory so if the corrective action arrives long after the root cause has gone away then it can actually destabilise the process and paradoxically increase the risk of harm.

<Bob> Can you give me an example?

<Leslie>Yes. Suppose a safety risk is exposed by a near miss.  A delay in communicating the niggle and a root cause analysis means that the specific combination of factors that led to the near miss has gone. The holes in the Swiss cheese are not static … they move about in the chaos.  So the action that follows the accumulation of many undiagnosed near misses is usually the non-specific mantra of adding yet another safety-check to the already burgeoning check-list. The longer check-list takes more time to do, and is often repeated many times, so the whole flow slows down, queues grow bigger, waiting times get longer and as pressure comes from the delivery targets corners start being cut, and new near misses start to occur; on top of the other ones. So more checks are added and so on.

<Bob> An excellent example! And what is the outcome?

<Leslie> Chronic chaos which is more dangerous, more disordered and more expensive. Lose lose lose.

<Bob> And how do the people feel who work in the system?

<Leslie> Chronically naffed off! Angry. Demotivated. Cynical.

<Bob>And those feelings are the key symptoms.  Niggles are not only symptoms of poor process design, they are also symptoms of a much deeper problem: a violation of values.

<Leslie> I get the first bit about poor design; but what is that second bit about values?

<Bob>  We all have a set of values that we learned when we were very young and that have bee shaped by life experience.  They are our source of emotional energy, and our guiding lights in an uncertain world. Our internal unconscious check-list.  So when one of our values is violated we know because we feel angry. How that anger is directed varies from person to person … some internalise it and some externalise it.

<Leslie> OK. That explains the commonest emotion that people report when they feel a niggle … frustration which is the same as anger.

<Bob>Yes.  And we reveal our values by uncovering the specific root causes of our niggles.  For example if I value ‘Hard Work’ then I will be niggled by laziness. If you value ‘Experimentation’ then you may be niggled by ‘Rigid Rules’.  If someone else values ‘Safety’ then they may value ‘Rigid Rules’ and be niggled by ‘Innovation’ which they interpret as risky.

<Leslie> Ahhhh! Yes, I see.  This explains why there is so much impassioned discussion when we do a 4N Chart! But if this behaviour is so innate then it must be impossible to resolve!

<Bob> Understanding  how our values motivate us actually helps a lot because we are naturally attracted to others who share the same values – because we have learned that it reduces conflict and stress and improves our chance of survival. We are tribal and tribes share the same values.

<Leslie> Is that why different  departments appear to have different cultures and behaviours and why they fight each other?

<Bob> It is one factor in the Silo Wars that are a characteristic of some large organisations.  But Silo Wars are not inevitable.

<Leslie> So how are they avoided?

<Bob> By everyone knowing what common purpose of the organisation is and by being clear about what values are aligned with that purpose.

<Leslie> So in the healthcare context one purpose is avoidance of harm … primum non nocere … so ‘safety’ is a core value.  Which implies anything that is felt to be unsafe generates niggles and well-intended but potentially self-destructive negative behaviour.

<Bob> Indeed so, as you described very well.

<Leslie> So how does all this link to Little’s Law?

<Bob>Let us go back to the foundation knowledge. What are the four interdependent dimensions of system improvement?

<Leslie> Safety, Flow, Quality and Productivity.

<Bob> And one measure of  productivity is profit.  So organisations that have only short term profit as their primary goal are at risk of making poor long term safety, flow and quality decisions.

<Leslie> And flow is the key dimension – because profit is just  the difference between two cash flows: income and expenses.

<Bob> Exactly. One way or another it all comes down to flow … and Little’s Law is a fundamental Law of flow physics. So if you want all the other outcomes … without the emotionally painful disorder and chaos … then you cannot avoid learning to use Little’s Law.

<Leslie> Wow!  That is a profound insight.  I will need to lie down in a darkened room and meditate on that!

<Bob> An oasis of calm is the perfect place to pause, rest and reflect.

Feel the Fear

monster_in_closet_150_wht_14500We spend a lot of time in a state of anxiety and fear. It is part and parcel of life because there are many real threats that we need to detect and avoid.

For our own safety and survival.

Unfortunately there are also many imagined threats that feel just as real and just as terrifying.

In these cases it is our fear that does the damage because it paralyses our decision making and triggers our ‘fright’ then ‘fight’ or ‘flight’ reaction.

Fear is not bad … the emotional energy it releases can be channelled into change and improvement. Just as anger can.


So we need to be able to distinguish the real fears from the imaginary ones. And we need effective strategies to defuse the imaginary ones.  Because until we do that we will find it very difficult to listen, learn, experiment, change and improve.

So let us grasp the nettle and talk about a dozen universal fears …

Fear of dying before one’s time.
Fear of having one’s basic identity questioned.
Fear of poverty or loss of one’s livelihood.
Fear of being denied one’s fundamental rights and liberties.

Fear of being unjustly accused of wrongdoing.
Fear of public humiliation.
Fear of being unjustly seen as lacking character.
Fear of being discovered as inauthentic – a fraud.

Fear of radical change.
Fear of feedback.
Fear of failure.
Fear of the unknown.

Notice that some of these fears are much ‘deeper’ than others … this list is approximately in depth order. Some relate to ‘self’; some relate to ‘others’ and all are inter-related to some degree. Fear of failure links to fear of humiliation and to fear of loss-of-livelihood.


Of these the four that are closest to the surface are the easiest to tackle … fear of radical change, fear of feedback, fear of failure, and fear of the unknown.  These are the Four Fears that block personal improvement.


Fear of the unknown is the easiest to defuse. We just open the door and look … from an emotionally safe distance so that we can run away if our worst fears are realised … which does not happen when the fear is imagined.

This is an effective strategy for defusing the emotionally and socially damaging effects of self-generated phobias.

And we find overcoming fear-of-the-unknown exhilarating … that is how theme parks and roller-coaster rides work.

First we open our eyes, we look, we see, we observe, we reflect, we learn and we convert the unknown to the unfamiliar and then to the familiar. We may not conquer our fear completely … there may be some reasonable residual anxiety … but we have learned to contain it and to control it. We have made friends with our inner Chimp. We climb aboard the roller coaster that is called ‘life’.


Fear of failure is next.  We defuse this by learning how to fail safely so that we can learn-by-doing and by that means we reduce the risk of future failures. We make frequent small safe failures in order to learn how to avoid the rare big unsafe ones!

Many people approach improvement from an academic angle. They sit on the fence. They are the reflector-theorists. And this may because they are too fearful-of-failing to learn the how-by-doing. So they are unable to demonstrate the how and their fear becomes the fear-of-fraud and the fear-of-humiliation. They are blocked from developing their pragmatist/activist capability by their self-generated fear-of-failure.

So we start small, we stay focussed, we stay inside our circle of control, and we create a safe zone where we can learn how to fail safely – first in private and later in public.

One of the most inspiring behaviours of an effective leader is the courage to learn in public and to make small failures that demonstrate their humility and humanity.

Those who insist on ‘perfect’ leaders are guaranteed to be disappointed.


And one thing that we all fail repeatedly is to ask for, to give and to receive effective feedback. This links to the deeper fear-of-humiliation.

And it is relatively easy to defuse this fear-of-feedback too … we just need a framework to support us until we find our feet and our confidence.

The key to effective feedback is to make it non-judgemental.

And that can only be done by developing our ability to step back and out of the Drama Triangle and to cultivate an I’m OK- You’re OK  mindset.

The mindset of mutual respect. Self-respect and Other-respect.

And remember that Other-respect does not imply trust, alignment, agreement, or even liking.

Sworn enemies can respect each other while at the same time not trusting, liking or agreeing with each other.

Judgement-free feedback (JFF) is a very effective technique … both for defusing fear and for developing mutual respect.

And from that foundation radical change becomes possible, even inevitable.

Strength and Resilience

figure_breaking_through_wall_anim_150_wht_15036The dictionary definition of resilience is “something that is capable of  returning to its original shape after being stretched, bent or otherwise deformed“.

The term is applied to inanimate objects, to people and to systems.

A rubber ball is resilient … it is that physical property that gives it bounce.

A person is described as resilient if they are able to cope with stress without being psychologically deformed in the process.  Emotional resilience is regarded as an asset.

Systems are described as resilient when they are able to cope with variation without failing. And this use of the term is associated with another concept: strength.

Strong things can withstand a lot of force before they break. Strength is not the same as resilience.

Engineers use another term – strain – which means the amount of deformation that happens when a force is applied.

Stress is the force applied, strain is the deformation that results.

So someone who is strong and resilient will not buckle under high pressure and will absorb variation – like the suspension of you car.

But is strength-and-resilience always an asset?


Suppose some strong and resilient people finds themselves in a relentlessly changing context … one in which they actually need to adapt and evolve to survive in the long term.

How well does their highly valued strength-and-resilience asset serve them?

Not very well.

They will resist the change – they are resilient – and they will resist it for a long time – they are strong.

But the change is relentless and eventually the limit of their strength will be reached … and they snap!

And when that happens all the stored energy is suddenly released. So they do not just snap – they explode!

Just like the wall in the animation above.

The final straw that triggers the sudden failure may appear insignificant … and at any other time  it would be.

But when the pressure is really on and the system is at the limit then it can be just enough to trigger the catastrophic failure from which there is no return.


Social systems behave in exactly the same way.

Those that have demonstrated durability are both strong and resilient – but in a relentlessly changing context even they will fail eventually, and when they do the collapse is sudden and catastrophic.

Structural engineers know that catastrophic failure usually starts as a localised failure and spreads rapidly through the hyper-stressed structure; each part failing in sequence as it becomes exposed and exceeds the limit of its strength.  That is how the strong and resilient Twin Towers failed and fell on Sept 11th 2001. They were not knocked over. They were weakened to the point of catastrophic failure.

When systems are exposed to varying strains then these localised micro-fractures only occur at the peaks of stress and may not have time to spread very far. The damage is done though. The system is a bit weaker than it was before. And catastrophic failure is more likely in the future.

That is what caused the sudden loss of some of the first jet airliners which inexplicably just fell out of the sky on otherwise uneventful flights.  It took a long time for the root cause to be uncovered … the square windows.

Jet airliners fly at high altitude because it allows higher speeds and requires less fuel and so allows long distance flight over wide oceans, steppes, deserts and icecaps. But the air pressure is low at high altitude and passengers could not tolerate that; so the air pressure inside an airliner at high altitude is much higher than outside. It is a huge pressurised metal flying cannister.  And as it goes up and down the thin metal skin is exposed to high variations in stress which a metal tube can actually handle rather well … until we punch holes in it to fit windows to allow our passengers a nice view of the clouds outside.  We are used to square windows in our houses (because they are easier to make) so the original aircraft engineers naturally put square windows in the early airliners.  And that is where the problem arose … the corners of the windows concentrate the stress and over time, with enough take-offs and landings,  the metal skin at the corners of the windows will accumulate invisible micro-fractures. The metal actually fatigues. Then one day – pop – a single rivet at the corner of a square window fails and triggers the catastrophic failure of the whole structure. But the aircraft designers did not understand that process and it took quite a long time to diagnose the root cause.

The solution?

A more resilient design – use round-cornered windows that dissipate the strain rather than concentrate it.  It was that simple!


So what is the equivalent resilient design for social system? Adaptability.

But how it is possible for a system to be strong, resilient and adaptable?

The design trick is to install “emotional strain gauges” that indicate when and where the internal cultural stress is being concentrated and where the emotional strain shows first.

These emotometers will alert us to where the stresses and strains are being felt strongest and most often – rather like pain detectors. We use the patterns of information from our network of emotometers to help us focus our re-design attention to continuously adapt parts of our system to relieve the strain and to reduce the system wide risk of catastrophic failure.

And by installing emotometers across our system we will move towards a design that is strong, resilient and that continuously adapts to a changing environment.

It really is that simple.

Welcome to complex adaptive systems engineering (CASE).

A Sisyphean Nightmare

cardiogram_heart_signal_150_wht_5748[Beep] It was time for the weekly e-mentoring session so Bob switched on his laptop, logged in to the virtual meeting site and found that Lesley was already there.

<Bob> Hi Lesley. What shall we talk about today?

<Lesley> Hello Bob. Another old chestnut I am afraid. Queues.  I keep hitting the same barrier where people who are fed up with the perpetual queue chaos have only one mantra “If you want to avoid long waiting times then we need more capacity.

<Bob> So what is the problem? You know that is not the cause of chronic queues.

<Lesley> Yes, I know that mantra is incorrect – but I do not yet understand how to respectfully challenge it and how to demonstrate why it is incorrect and what the alternative is.

<Bob> OK. I understand. So could you outline a real example that we can work with.

<Lesley> Yes. Another old chestnut: the Emergency Department 4-hour breaches.

<Bob> Do you remember the Myth of Sisyphus?

<Leslie> No, I do not remember that being mentioned in the FISH course.

<Bob> Ho ho! No indeed,  it is much older. In Greek mythology Sisyphus was a king of Ephyra who was punished by the Gods for chronic deceitfulness by being compelled to roll an immense boulder up a hill, only to watch it roll back down, and then to repeat this action forever.

Sisyphus_Cartoon

<Lesley> Ah! I see the link. Yes, that is exactly how people in the ED feel.  Everyday it feels like they are pushing a heavy boulder uphill – only to have to repeat the same labour the next day. And they do not believe it can ever be any better with the resources they have.

<Bob> A rather depressing conclusion! Perhaps a better metaphor is the story in the film  “Ground Hog Day” where Bill Murray plays the part of a rather arrogant newsreader who enters a recurring nightmare where the same day is repeated, over and over. He seems powerless to prevent it.  He does eventually escape when he learns the power of humility and learns how to behave differently.

<Lesley> So the message is that there is a way out of this daily torture – if we are humble enough to learn the ‘how’.

<Bob> Well put. So shall we start?

<Lesley> Yes please!

<Bob> OK. As you know very well it is important not to use the unqualified term ‘capacity’.  We must always state if we are referring to flow-capacity or space-capacity.

<Lesley> Because they have different units and because they are intimately related to lead time by Little’s Law.

<Bob> Yes.  Little’s Law is mathematically proven Law of flow physics – it is not negotiable.

<Lesley> OK. I know that but how does it solve problem we started with?

<Bob> Little’s Law is necessary but it is not sufficient. Little’s Law relates to averages – and is therefore just the foundation. We now need to build the next level of understanding.

<Lesley> So you mean we need to introduce variation?

<Bob> Yes. And the tool we need for this is a particular form of time-series chart called a Vitals Chart.

<Lesley> And I am assuming that will show the relationship between flow, lead time and work in progress … over time ?

<Bob> Exactly. It is the temporal patterns on the Vitals Chart that point to the root causes of the Sisyphean Chaos. The flow design flaws.

<Lesley> Which are not lack of flow-capacity or space-capacity.

<Bob> Correct. If the chaos is chronic then there must already be enough space-capacity and flow-capacity. Little’s Law shows that, because if there were not the system would have failed completely a long time ago. The usual design flaw in a chronically chaotic system is one or more misaligned policies.  It is as if the system hardware is OK but the operating software is not.

<Lesley> So to escape from the Sisyphean Recurring ED 4-Hour Breach Nightmare we just need enough humility and enough time to learn how to diagnose and redesign some of our ED system operating software? Some of our own policies? Some of our own mantras?

<Bob> Yup.  And not very much actually. Most of the software is OK. We need to focus on the flaws.

<Lesley> So where do I start?

<Bob> You need to do the ISP-1 challenge that is called Brainteaser 104.  That is where you learn how to create a Vitals Chart.

<Lesley> OK. Now I see what I need to do and the reason:  understanding how to do that will help me explain it to others. And you are not going to just give me the answer.

<Bob> Correct. I am not going to just give you the answer. You will not fully understand unless you are able to build your own Vitals Chart generator. You will not be able to explain the how to others unless you demonstrate it to yourself first.

<Lesley> And what else do I need to do that?

<Bob> A spreadsheet and your raw start and finish event data.

<Lesley> But we have tried that before and neither I nor the database experts in our Performance Department could work out how to get the real time work in progress from the events – so we assumed we would have to do a head count or a bed count every hour which is impractical.

<Bob> It is indeed possible as you are about to discover for yourself. The fact that we do not know how to do something does not prove that it is impossible … humility means accepting our inevitable ignorance and being open to learning. Those who lack humility will continue to live the Sisyphean Nightmare of ED Ground Hog Day. The choice to escape is ours.

<Lesley> I choose to learn. Please send me BT104.

<Bob> It is on its way …

Actions Speak

media_video_icon_anim_150_wht_14142In a recent blog we explored the subject of learning styles and how a balance of complementary learning styles is needed to get the wheel-of-change turning.

Experience shows that many of us show a relative weakness in the ‘Activist’ quadrant of the cycle.

That implies we are less comfortable with learning-by-doing. Experimenting.

This behaviour is driven by a learned fear.  The fear-of-failure.

So when did we learn this fear?

Typically it is learned during childhood and is reinforced throughout adulthood.

The fear comes not from the failure though  … it comes from the emotional reaction of others to our supposed failure. The emotional backlash of significant others. Parents and parent-like figures such as school teachers.

Children are naturally curious and experimental and fearless.  That is how they learn. They make lots of mistakes – but they learn from them. Walking, talking, tying a shoelace, and so on.  Small mistakes do not created fear. We learn fear from others.

Full-of-fear others.

To an adult who has learned how to do many things it becomes easy to be impatient with the trial-and-error approach of a child … and typically we react in three ways:

1) We say “Don’t do that” when we see our child attempt something in a way we believe will not work or we believe could cause an accident. We teach them our fears.

2) We say “No” when we disagree with an idea or an answer that a child has offered. We discount them by discounting their ideas.

3) We say “I’ll do it” when we see a child try and fail. We discount their ability to learn how to solve problems and we discount our ability to let them.

Our emotional reaction is negative in all three cases and that is what teaches our child the fear of failure.

So they stop trying as hard.

And bit-by-bit they lose their curiosity and their courage.

We have now put them on the path to scepticism and cynicism.  Which is how we were taught.


This fear-of-failure brainwashing continues at school.

But now it is more than just fear of disappointing our parents; now it is fear of failing tests and exams … fear of the negative emotional backlash from peers, teachers and parents.

Some give up: they flee.  Others become competitive: they fight.

Neither strategies dissolve the source of the fear though … they just exacerbate it.


So it is rather too common to see very accomplished people paralysed with fear when circumstances dictate that they need to change in some way … to learn a new skill for example … to self-improve maybe.

Their deeply ingrained fear-of-failure surfaces and takes over control – and the fright/flight/fight behaviour is manifest.


So to get to the elusive win-win-win outcomes we want we have to weaken the fear-of-failure reflex … we need to develop a new habit … learning-by-doing.

The trick to this is to focus on things that fall 100% inside our circle of control … the Niggles that rank highest on our Niggle-o-Gram®.

And when we Study the top niggle; and then Plan the change; and then Do what we planned, and then Study effect of our action … then we learn-by-doing.

But not just by doing …. by Studying, Planning, Doing and Studying again.

Actions Speak not just to us but to everyone else too.

Learning in Style

PARTImprovement implies learning – new experiences, new insights, new models and new ways of doing things.

So understanding the process of learning is core to the science of improvement.

What many people do not fully appreciate is that we differ in the way we prefer to learn.  These are habitual behaviours that we have acquired.

The diagram shows one model – the Honey and Mumford model that evolved from an earlier model described by Kolb.

One interesting feature of this diagram is the two dimensions – Perception and Processing which are essentially the same as the two core dimensions in the Myers-Briggs Type Index.

What the diagram above does not show so well is that the process of learning is a cycle – the clockwise direction in this diagram – Pragmatist then Activist then Reflector then Theorist and back to Pragmatist.

This is the PART sequence.  And it can start at any point … ARTP, RTPA, TPAR.

We all use all of these learning styles – but we have a preference for some more than others – our preferred learning styles are our learning comfort zones.

The large observational studies conducted in the 1980’s using the PART model revealed that most people have moderate to strong preferences for only one or two of these styles. Less than 20% have a preference for three and very few feel equally comfortable with all four.

The commonest patterns are illustrated by the left and right sides of the diagram: the Pragmatist-Activist combination and the Reflector-Theorist combination.

It is not that one is better than the other … all four are synergistic and an effective and efficient learning process requires being comfortable with using all four in a continuous sequence.

Imagine this as a wheel – an imbalance between the four parts represents a distorted wheel. So when this learning wheel ‘turns’  it delivers an emotionally bumpy ‘ride’.  Past experience of being pushed through this pain-and-gain process will tend to inhibit or even block learning completely.

So to get a more comfortable learning journey we first need to balance our PART wheel – and that implies knowing what our preferred styles are and then developing the learning styles that we use least to build our competence and confidence with them.  And that is possible because these are learned habits. With guidance, focus and practice we can all strengthen our less favoured learning ‘muscles’.

Those with a preference for planning-and-doing would focus on developing their reflection and then their abstraction skills. For example by monitoring the effects of their actions in reality and using that evidence to challenge their underlying assumptions and to generate new ‘theories’ for pragmatic experimentation. Actively seeking balanced feedback and reflecting on it is one way to do that.

Those with a preference for studying-and-abstracting would focus on developing their design and then their delivery skills and become more comfortable with experimenting to test their rhetoric against reality. Actively seeking opportunities to learn-by-doing is one way.

And by creating the context for individuals to become more productive self-learners we can see how learning organisations will follow naturally. And that is what we need to deliver system-wide improvement at scale and pace.

Perfect Storm

lightning_strike_150_wht_5809[Drrrrring Drrrrring]

<Bob> Hi Lesley! How are you today?

<Leslie> Hi Bob.  Really good.  I have just got back from a well earned holiday so I am feeling refreshed and re-energised.

<Bob> That is good to hear.  It has been a bit stormy here over the past few weeks.  Apparently lots of  hot air hitting cold reality and forming a fog of disillusionment and storms of protest.

<Leslie> Is that a metaphor?

<Bob> Yes!  A good one do you think? And it leads us into our topic for this week. Perfect storms.

<Leslie> I am looking forward to it.  Can you be a bit more specific?

<Bob> Sure.  Remember the ISP exercise where I asked you to build a ‘chaos generator’?

<Leslie> I sure do. That was an eye-opener!  I had no idea how easy it is to create chaotic performance in a system – just by making the Flaw of Averages error and adding a pinch of variation. Booom!

<Bob> Good. We are going to use that model to demonstrate another facet of system design.  How to steer out of chaos.

<Leslie> OK – what do I need to do.

<Bob> Start up that model and set the cycle time to 10 minutes with a sigma of 1.5 minutes.

<Leslie> OK.

<Bob> Now set the demand interval to 10 minutes and the sigma of that to 2.0 minutes.

<Leslie> OK. That is what I had before.

<Bob> Set the lead time upper specification limit to 30 minutes. Run that 12 times and record the failure rate.

<Leslie> OK.  That gives a chaotic picture!  All over the place.

<Bob> OK now change just the average of the demand interval.  Start with a value of 8 minutes, run 12 times, and then increase to 8.5 minutes and repeat that up to 12 minutes.

<Leslie> OK. That will repeat the run for 10 minutes. Is that OK.

<Bob> Yes.

<Leslie> OK … it will take me a few minutes to run all these.  Do you want to get a cup of tea while I do that?

<Bob> Good idea.

[5 minutes later]

<Leslie> OK I have done all that – 108 data points. Do I plot that as a run chart?

<Bob> You could.  I suggest plotting as a scattergram.

<Leslie> With the average demand interval on the X axis and the Failure % on the  Y axis?

<Bob> Yes. Exactly so. And just the dots, no lines.

<Leslie> OK. Wow! That is amazing!  Now I see why you get so worked up about the Flaw of Averages!

<Bob> What you are looking at is called a performance curve.  Notice how steep and fuzzy it is. That is called a chaotic transition. The perfect storm.  And when fall into the Flaw of Averages trap we design our systems to be smack in the middle of it.

<Leslie> Yes I see what you are getting at.  And that implies that to calm the chaos we do not need very much resilient flow capacity … and we could probably release that just from a few minor design tweaks.

<Bob> Yup.

<Leslie> That is so cool. I cannot wait to share this with the team. Thanks again Bob.

A Stab At The Vitals

pirate_flag_anim_150_wht_12881[Drrring Drrring] The phone heralded the start of the weekly ISP mentoring session.

<Bob> Hi Leslie, how are you today?

<Leslie> Hi Bob. To be honest I am not good. I am drowning. Drowning in data!

<Bob> Oh dear! I am sorry to hear that. Can I help? What led up to this?

<Leslie> Well, it was sort of triggered by our last chat and after you opened my eyes to the fact that we habitually throw most of our valuable information away by thresholding, aggregating and normalising.  Then we wonder why we make poor decisions … and then we get frustrated because nothing seems to improve.

<Bob> OK. What happened next?

<Leslie> I phoned our Performance Team and asked for some raw data. Three months worth.

<Bob> And what was their reaction?

<Leslie> They said “OK, here you go!” and sent me a twenty megabyte Excel spreadsheet that clogged my email inbox!  I did manage to unclog it eventually by deleting loads of old junk.  But I could swear that I heard the whole office laughing as they hung up the phone! Maybe I am paranoid?

<Bob> OK. And what happened next?

<Leslie> I started drowning!  The mega-file had a row of data for every patient that has attended A&E for the last three months as I had requested, but there were dozens of columns!  Trying to slice-and-dice it was a nightmare! My computer was smoking and each step took ages for it to complete.  In the end I gave up in frustration.  I now have a lot more respect for the Performance Team I can tell you! They do this for a living?

<Bob> OK.  It sounds like you are ready for a Stab At the Vitals.

<Leslie> What?  That sounds rather piratical!  Are you making fun of my slicing-and-dicing metaphor?

<Bob> No indeed.  I am deadly serious!  Before we leap into the data ocean we need to be able to swim; and we also need a raft that will keep us afloat;  and we need a sail to power our raft; and we need a way to navigate our raft to our desired destination.

<Leslie> OK. I like the nautical metaphor but how does it help?

<Bob> Let me translate. Learning to use system behaviour charts is equivalent to learning the skill of swimming. We have to do that first and practice until we are competent and confident.  Let us call our raft “ISP” – you are already aboard.  The sail you also have already – your Excel software.  The navigation aid is what I refer to as Vitals. So we need to have a “stab at the vitals”.

<Leslie> Do you mean we use a combination of time-series charts, ISP and Excel to create a navigation aid that helps avoid the Depths of Data and the Rocks of DRAT?

<Bob> Exactly.

<Leslie> Can you demonstrate with an example?

<Bob> Sure. Send me some of your data … just the arrival and departure events for one day – a typical one.

<Leslie> OK … give me a minute!  …  It is on its way.  How long will it take for you to analyse it?

<Bob> About 2 seconds. OK, here is your email … um … copy … paste … copy … reply

Vitals_Charts<Leslie> What the ****? That was quick! Let me see what this is … the top left chart is the demand, activity and work-in-progress for each hour; the top right chart is the lead time by patient plotted in discharge order; the table bottom left includes the 4 hour breach rate.  Those I do recognise. What is the chart on the bottom right?

<Bob> It is a histogram of the lead times … and it shows a problem.  Can you see the spike at 225 to 240 minutes?

<Leslie> Is that the fabled Horned Gaussian?

<Bob> Yes.  That is the sign that the 4-hour performance target is distorting the behaviour of the system.  And this is yet another reason why the  Breach Rate is a dangerous management metric. The adaptive reaction it triggers amplifies the variation and fuels the chaos.

<Leslie> Wow! And you did all that in Excel using my data in two seconds?  That must need a whole host of clever macros and code!

<Bob> “Yes” it was done in Excel and “No” it does not need any macros or code.  It is all done using simple formulae.

<Leslie> That is fantastic! Can you send me a copy of your Excel file?

<Bob> Nope.

<Leslie>Whaaaat? Why not? Is this some sort of evil piratical game?

<Bob> Nope. You are going to learn how to do this yourself – you are going to build your own Vitals Chart Generator – because that is the only way to really understand how it works.

<Leslie> Phew! You had me going for a second there! Bring it on! What do I do next?

<Bob> I will send you the step-by-step instructions of how to build, test and use a Vitals Chart Generator.

<Leslie> Thanks Bob. I cannot wait to get started! Weigh anchor and set the sails! Ha’ harrrr me hearties.

The Learning Labyrinth

Minecraft There is an amazing phenomenon happening right now – a whole generation of people are learning to become system designers and they are doing it by having fun.

There is a game called Minecraft which millions of people of all ages are rapidly discovering.  It is creative, fun and surprisingly addictive.

This is what it says on the website.

“Minecraft is a game about breaking and placing blocks. At first, people built structures to protect against nocturnal monsters, but as the game grew players worked together to create wonderful, imaginative things.”

The principle is that before you can build you have to dig … you have to gather the raw materials you need … and then you have to use what you have gathered in novel and imaginative ways.  You need tools too, and you need to learn what they are used for, and what they are useless for. And the quickest way to learn the necessary survival and creative  skills is by exploring, experimenting, seeking help, and sharing your hard-won knowledge and experience with others.

The same principles hold in the real world of Improvement Science.

The treasure we are looking for is less tangible though … but no less difficult to find … unless you know where to look.

The treasure we seek is learning; how to achieve significant and sustained improvement on all dimensions.

And there is a mountain of opportunity that we can mine into. It is called Reality.

And when we do that we uncover nuggets of knowledge, jewels of understanding, and pearls of wisdom.

There are already many tunnels that have been carved out by others who have gone before us. They branch and join to form a vast cave network. A veritable labyrinth. Complicated and not always well illuminated or signposted.

And stored in the caverns is a vast treasure trove of experience we can dip into – and an even greater horde of new treasure waiting to be discovered.

But even now there there is no comprehensive map of the labyrinth. So it is easy to get confused and to get lost. Not all junctions have signposts and not all the signposts are correct. There are caves with many entrances and exits, there are blind-ending tunnels, and there are many hazards and traps for the unwary.

So to enter the Learning Labyrinth and to return safety with Improvement treasure we need guides. Those who know the safe paths and the unsafe ones. And as we explore we all need to improve the signage and add warning signs where hazards lurk.

And we need to work at the edge of knowledge  to extend the tunnels further. We need to seal off the dead-ends, and to draw and share up-to-date maps of the paths.

We need to grow a Community of Improvement Science Minecrafters.

And the first things we need are some basic improvement tools and techniques … and they can be found here.

Egomatosis

There is a common, and often fatal, organisational disease called “egomatosis”.

It starts as a swelling of the Egocentre in the Executive Organ that is triggered by a deficiency in the Humility Feedback Loop (HFL), which in turn is linked to underdevelopment or dysfunction of the phonic sensory input system – selective deafness.

Unfortunately, the Egocentre is located next to other perception centres – specifically insight – so as the egoma develops the visual perception also becomes progressively distorted until a secondary cultural blind-spot develops.

In effect, the Executive organ becomes progressively cut off from objective reality – and this lack of accurate information impairs the Humility Feedback Loop further – accelerating the further enlargement of the egoma.

A dangerous positive feedback loop is now created that leads to a self-amplifying spiral of distorted perception and a progressive decline of judgement and effective decision making.

The external manifestation of this state is a characteristic behaviour called “dystrustosis” – or difficulty in extending trust to others combined with a progressive loss of self-trust.

The unwitting sufferer becomes progressively deaf, blind, fearful, delusional, paranoid and insecure – often distancing themselves emotionally and physically and communicating only via intermediaries using One-Way-Directives.

Those who attempt to communicate with the sufferer of this insidious condition often resort to SHOUTING and using BIG LETTERS which, unfortunately, only mirrors the same behaviour.  As the sufferer’s perception of reality becomes more distorted their lack of insight and humility blocks them from considering themselves as a contributor to the problem.

The ensuing conflict only serves to accelerate their decline and the sufferer progresses to the stage of “fulminant egomatosis”.



“Fulminant egomatosis” is a condition that is easy to identify and to diagnose.  Just listen for the shouting, observe the dystrustosis and feel the fear.

Unfortunately, it is a difficult condition to manage because of the lack of awareness and insight that are the cardinal signs.

Many affected leaders and their organisations now enter a state of Denial – unconsciously hoping that the problem will resolve itself – which is indeed what happens eventually – though not in the way they desperately hope for.

In the interim, the health of the organisation deteriorates and many executives succumb, unaware of, or unwilling to acknowledge the illness that claimed them; meekly accepting the “inevitable fate” and submitting to the terminal option – usually delivered by the Chair of the Board – Retire or Resign!

The circling corporate vultures squabble over the fiscal remains – leaving no tangible sign to mark the passing of the sufferer and their hapless organisation.  There are no graveyards for the victims of fulminant egomatosis and the memory of their passing soon fades from the collective memory.  Failure is a taboo subject – an undiscussable.


Some organisations become aware of their affliction while they are still alive, but only after they have reached the terminal stage and are too sick to save.  The death throes are destructive and unpleasant to watch – and unfortunately fuel the self-justifying delusion of other infected organisations who erroneously conclude that “it could never happen to them” and then unwittingly follow the same path.


Unfortunately, egomatosis is an infectious cultural disease.  The spores, or “memes” as they are called, can spread to other organisations.  Just as Dr Ignaz Semmelweis discovered in 1847, the agents-of-destruction are often carried on the hands of those who perform organisational postmortems.  These meme vectors are often the very people brought into assist the ailing organisation, and so become chronically infected themselves and gravitate to others who share their delusions.  They are excluded by healthy organisations, but their siren-calls sound plausible and they gain entry to weaker organisations who are unaware that they carry the dangerous memes!  Actively employing the services of management consultants in preference to encouraging organisational innovation incurs a high risk of silent infection!  Appearance of the symptoms and signs is often delayed and by then it may be too late. 


The organisations that are naturally immune to egomatosis were “built to last” because they were born with a well-developed sense of purpose, vision, humility, confidence and humour.  They habitually and unconsciously look for, detect, and defuse the early signs of egomatosis.  They do not fear failure, and they have learned to leverage the gap between intent and impact.  These organisations have a strong cultural immune system and are able to both prevent infection and disarm the toxic-memes they inevitably encounter.  They are safe,  fun, challenging, exciting, innovative and motivating, places to work – characteristics that serve to strengthen their immunity, boost their resilience, and secure their future.


Some infected organisations are fortunate enough to become aware of their infection before it is too late, and they are able to escape the vicious cycle of decline.  These “good to great” organisations have enough natural humility to learn by observing the fate of others and are able to detect the early symptoms and to seek help from someone who understands their illness and can guide their diagnosis and treatment.  Such healers facilitate and demonstrate rather than direct and delegate.


All organisations are susceptible to egomatosis, so prevention is preferable to cure.

To prevent the disease, organisations must consciously and actively develop their internal and external feedback loops – using all their senses – including their olfactory organ.  Cultural and political bull**** has a characteristic odour!

They also regularly exercise their Humility Feedback Loop to keep it healthy – and they have discovered that the easiest way to do that is to challenge themselves – to actively look for their own gaps and gaffes – to look for their own positive deviants – to search out opportunities to improve – and to practice the very things that they know they are not good at.

They are prepared to be proved lacking and have learned to stop, look, laugh at themselves – then listen, learn, act, improve and share.

There is no known cure for egomatosis – it is a consequence of the 1.3 kg of ChimpWare between our ears that we have inherited from our ancestors – so vigilance must be maintained throughout the life of the organisation.