I just had the major misfortune of acquiring a copy of the latest Antifragile bandwagon-jumper book, ‘The Anti-Fragility Edge’. So bad was it that it prompted me to compose my first ever Amazon review, in a no doubt vain attempt to warn people away from the dangerous, counter-productive monstrosity I believe it to be.
The first problem is that Nassim Nicholas Taleb ignited what looks set to become a pretty big fire when he gave the world the word antifragile back in (was it really that long ago?) 2012.
The bigger problem, looking at the four years that have passed since the book first appeared is perhaps that Taleb is, to quote a different favourite author, ‘too far ahead of the crowd for people to recognise he’s part of the crowd’. And that includes – on the evidence of The Anti-Fragility Edge or any of the other handful of books that have tried to cash-in on the antifragile meme – all the early-adopters required to turn the initial spark into a proper flame aren’t up to the task at hand.
This is somewhat ironic when I think about what antifragile is all about: making systems stronger by subjecting them to adversity. Having your good work misinterpreted and mangled by people who clearly don’t understand what they’re doing, could, in some weird parallel world be the exceptions that prove the rule. Maybe, Nassim Taleb, is sat in his lab thinking, these terrible books are the very stressors that my beautiful Antifragile baby needs in order to become the global phenomenon it deserves to be?
Sadly, I don’t think the world works that way. Nor does antifragility. At least not at this point in its evolutionary history.
One of the key ideas behind subjecting systems to adversity, is that you need to know just how much adversity. It’s a classic Goldilocks and the Three Bears scenario: too little adversity and the system doesn’t need to shift and so doesn’t evolve; too much adversity and you kill it.
In TRIZ terms this need to find ‘just the right amount’ of adversity represents a classic contradiction problem. Antifragile needs adversity and no adversity.
Solving the contradiction means knowing exactly when and how to separate the two contradictory requirements. And, when it comes to the rise – or otherwise – of an important new idea, one of the best ways to understand the separation dynamic is to bring the Hype Cycle in to play. What the Hype Cycle tells us is that there are clearly different stages in the evolution of the new idea. During some of the stages, the system is very vulnerable and needs relatively little adversity, and then during others, the system is much more accommodating and actually needs lots of adversity in order to reach a meaningful maturity.
The big problem with the current crop of bandwagon-jumpers is that they represent exactly the wrong kind of adversity at the wrong time. The Anti-Fragility Edge, for example, purports to be a ‘How To’ book. In theory, this is a good idea. Taleb’s book is a ‘what’ and a ‘why’ book. If antifragile ideas are going to take hold, someone will have to hold the hands of the fragile and guide them towards greater levels of antifragility. No ‘how to’ book, no widespread adoption. But if the ‘how to’ book that people locate is a really bad book, all it does is kills the idea before the idea has a chance to get off the ground.
In the long term the dire post-Taleb antifragile literature will no doubt fade into historical insignificance. In the meantime, the fact that they’ve appeared when they have means the only impact they will have is to delay meaningful action. And my guess, given the enormous operational-excellence-driven fragility of most of the enterprises on the planet right now plus the even bigger narcissist-driven instability heading in all our directions, is that this can only be a bad thing. Predictable, maybe, but bad nevertheless.
In the end we never got a chance to publish our Brexit analysis. Time moved on and other things seemed more important. Like the American election. Which turned out – per our prediction – pretty much the same as Brexit. And which also triggerred much hand-wringing and self-flagellation by the media, political commentators and losing-candidate voters of the world.
Now I find myself reading the media’s post-mortem analyses of 2016 and fighting off a gnawing sense of depression. Not because the world is heading towards crisis and catastrophe – we worked that out a few years ago already – but because of the media’s deepening misunderstanding of how the world works.
The search for the ‘root cause’ of the Brexit result bumbles along fruitlessly, with six months of incubation seemingly doing nothing to bring any clarity. A lot like the drunk man looking for his car keys under the streetlight. The media demands a root cause because they’ve been taught there must be a root cause. There must be something or – preferably – someone to take the blame. The problem is, like the drunk, we’re looking for something that isn’t there. But we look anyway because it’s easier than thinking.
At least the end-of-year media analyses allowed me to update our collection of previously mooted Brexit ‘root cause’ candidates. Of which there have now been a lot. Some more ridiculous than others, but all ultimately doomed to pointless either/or debates in pubs up and down the land and on Question Time. Do we blame Gove? Or Johnson? Or Churchill (!)? Or deGaulle (!!)? Wrong question, dummy.
In a complex system, there is no such thing as a root-cause, and so any attempt to try and find one is a Sisyphus-like exercise in pushing dumb-as-a-rock thinking up the mountain, thus ensuring no meaningful progress gets made. Maybe that’s the point?
Personally, I’d rather try and make sense of what’s happening. Not that there’s anything I am likely to be able to do about the result. But at least, I’ll have a better idea about how I and the Systematic Innovation team can best find a place in the world that makes sure we’re more likely to thrive than dive.
Here’s what happened when I took all the ‘root cause’ candidates and shifted the focus to mapping the relationships between them:
I know, I know, you can’t see all the details. That’s not the point. The point is that the picture hopefully makes clear that there is no such thing as a root-cause. The only good news, if ‘good’ is anywhere close to the right word, looking at the rats-nest is that there is only one vicious cycle. The conspiracy of causes, in other words, all seems to converge on one downward loop of hell. Here’s what it looks like in more detail:
The main conclusion this picture perhaps suggests is ‘hello loudmouth, bye-bye truth’. Or, ‘welcome to the shoot-the-expert, post-truth, best-fiction-wins society’.
The other might be that we all begin to nurture and value the truth-curators once more. Or maybe, better yet, the people that write the truth-detecting software. I think the mist is clearing. I think my 2017 is becoming clear…
“Oh, beauty before me, beauty behind me, beauty to the right of me, beauty to the left of me, beauty above me, beauty below me, I’m on the pollen path.”
I finally got a chance to read Joseph Campbell’s last book, ‘The Inner Reaches Of Outer Space’ while on a trans-Atlantic flight this month. If there are two kinds of people in life – lumpers and splitters – Campbell, like TRIZ-founder, Genrich Altshuller was one of my favourite someone-somewhere-already-solved-your-problem, ‘lumpers’.
Campbell’s major pattern-finding contribution was the Hero’s Journey – the result of a lifetime spent studying and revealing the underlying patterns of successful literature. As far as I can tell, he never understood the concept of s-curves and discontinuous change as we now know them in the innovation world, but the Hero’s Journey described the precise steps that discontinuous change requires.
The Inner Reaches Of Outer Space explores the underlying patterns between a different kind of discontinuous change, life transitions. And especially things like rites-of-passage transition into adulthood. These too, Campbell shows, are also Hero’s Journeys.
My favourite part of the book was the Pollen Path. And particularly Campbell’s description of how the Navajo elders mapped out the initiation journey of their young adults. Again, neither Campbell nor the Navajo elders knew about S-curves. Except, as we can see in the depiction of the Pollen Path, they absolutely did.
To the point that, just maybe, they add a few clues to the nature of discontinuous change process:
Firstly, the Pollen Path itself, which is all about the period in the Journey before you jump off your current s-curve and start the search for the next. Before you jump, make sure you prepare yourself with some growth-sparking, high-density nutrition.
Then, when you’re in the ‘Special World’ no-mans land between your old s-curve and the next – the place where, along the Pollen Path, you’ll find rainbows and lightning you’ll also need:
* Food along the way (the corn ears hidden along the path in the painting)
* Both male and female traits (the black and yellow characters on either side of the path)
* To stick to the middle ground and recognise that the cul-de-sac detours are precisely that (the go-nowhere offshoots from the path)
I often find myself showing a copy of Dave Snowden’s Cynefin model when I need to explain some of the challenges of innovation. People seem to instinctively ‘get it’. Especially when I use this three-dimensional version of the model:
It’s great beauty – the thing that seems to resonate most with prospective innovators struggling to cope with their ‘Operational Excellence’ colleagues – is the cliff-edge between ‘Obvious’ and ‘Chaos’. The effect becomes amplified when we think about Operational Excellence as a way of thinking that seeks to ‘manage’ situations that are inherently complex through a strategy of simplification. Ever since F.W. Taylor, the prevailing logic has been that its only possible to scale businesses by segmenting work into small chunks that are easily trainable into new employees. Looked at through the Cynefin lens, Taylor’s efforts can be seen as a series of scientific studies to understand each given operation in a process, such that everything could be cropped down to a very simple set of instructions. Taylor worked out the optimum size of shovel so that a novice shoveller could become productive almost immediately after they picked it up. Taylor’s view when talking to the shovellers was, ‘I’m here to make your job easier for you’. When he was selling his process to the managers, on the other hand, he was effectively saying, ‘we don’t need workers with brains, I’ve done all the necessary thinking for them’. In Cynefin terms, Taylorism specifically, and ‘Operational Excellence in general can be seen as a management strategy that looks like this:
What Taylor didn’t understand, and what most Operational Excellence people still don’t usually understand (at least until its too late) is that their efforts are optimizing systems to the edge of chaos. Nearly all of 430 Fortune500 companies from 1950 that no longer exist, disappeared because they fell off this cliff. They ‘always did what they’d always done’ because it was efficient to do so. Within their bubble at least. The only problem was that the world outside that bubble had moved on. They hadn’t understood that in a complex environment like ‘the market’, if you always do what you’ve always done, you can only legitimately expect that you will probably get what you’ve always got.
As more and more enterprises become aware of complexity, they slowly begin to realise that Operational Excellence is a temporary, stop-gap answer. One of the strongest signals of this awareness is the current vogue for ‘Design Thinking’. Especially with the management community… designers, good ones at least, inherently understand complexity and ‘do’ design thinking naturally. Managers for the most part don’t. Until they’ve spent a week at a D.School and ‘see the light’. Divergence and experimentation are the order of the day. Most Design Thinking educators might not know that they’re doing it, but when we look at Design Thinking through the Cynefin lens, we see that it is attempting to reverse the killer effects of Operational Excellence. Design Thinking is about embracing complexity:
It’s not clear to me yet that Design Thinking will help save the day as far as many enterprises are concerned. Partly because it has typically been presented in a stand-alone faddish manner, and partly because when new users attempt to dig below the surface, there’s not an awful lot of usable content. Not to mention that an awful lot of it is a crude re-badging of Edward De Bono’s work (clue: look at all of the ‘Big’ Design Thinkers – they’re all British and were all raised at a time when, if you were interested in creativity, you inevitably found yourself reading The Mechanism Of Mind and its surrounding family of books).
I think Cynefin has a role to play in helping to solve this ‘save the day’ problem. Especially when we connect the Cynefin model to the evolutionary S-Curve.
Operational Excellence, in S-Curve terms, is all about climbing the current curve. Combine this idea with the different stages of Operational Excellence as emerge from th Cynefin model and the S-Curve climbing journey looks something like this:
At the start of a new-S-curve, Chaos reigns. Lots of prospective innovators are trying to find a new solution and most will fail.
Eventually one or two ‘lucky ones’ will prevail. They’ll find ‘a’ solution that is good enough to attract one or two brave early customers. There are no processes or protocols, so provider and customer need to be engaged in a mutually beneficial dance to evolve the solution to a point where it becomes worth the investment of everyone’s time and money. ‘Fail fast, fail forward’, and other complexity-consistent strategies are brought into play. Thought of in terms of the Hype Cycle, this period of evolution is all about peaks of over-inflated expectation and troughs of despondency.
And then, if everyone pulls together well enough, the solution finds itself transcending a tipping point. Now it is useful enough that an increasing number of customers want the solution. Sales and Marketing teams get involved, and in order to help them sell the beautiful new solution, brochures get written and a sales process crystallises. ‘Understanding’ of how to sell and how to produce economically means the prevailing management strategy devolves to ‘complicated’.
Some time later, usually when the growth hits an inflexion point and the sales team start missing their targets, the focus shifts towards efficiency. Cut the bottom line. Along comes Lean and SixSigma, Value Stream Maps to try and squeeze every last drop of ‘waste’ from the system. The management strategy devolves further into the ‘obvious’.
…And keeps going, all the time things feeling more and more like a game of corporate whack-a-mole. Every time we try and improve one part of the system, it seems to have an adverse effect on some other part…
…the enterprise teeters ever closer to the edge of Chaos… no-one is able to improve the system any more, and those that are smart enough to understand what’s happening start to leave the stalled ship and go looking for lifeboats. Their chaotic search for the new solution is now on. The descent of the beautifully optimized old enterprise into chaos, on the other hand, is now merely a matter of time. The long established management team asleep at the wheel, safe in the knowledge that the operational excellence goals have been met, and their bonuses paid in full. It won’t be long ’til they’ve optimized the whole shebang full circle back into chaos.
So, the big news at the Lean conference seems to have been Agile. Which is a bit depressing when you think about it. I guess these things have to take turns. A few years ago it was Six Sigma. I imagine, in a few more years’ time, the carousel will have gone full circle and we’ll be back at Lean again. If it wasn’t so depressing, you’d probably laugh.
Someone asked the question, ‘has Lean innovated?’ I thought this was quite a good question. The answer didn’t appear to be immediately apparent. Clearly some Lean initiatives have delivered tangible benefit to the organisations that have deployed them. But is the benefit coming from step-changes to the Lean methodology or merely optimization of what’s been there from the first time Taiichi Ohno devised a better way to organise Toyota’s production systems?
It began to sound like a contradiction. Innovation or optimization? Or innovation and optimization? The more I thought about it, the more the resolution looked like a story of hierarchical separation. At the tool level, Lean has made several step changes. At the governing-principle level, I don’t think it has. The pillars of Lean have not changed over the years. Lean practitioners have, at best, optimized their understanding of these pillars. No doubt derailed along the way by diversions to investigate Six Sigma. And more recently, it now seems, via Agile.
Maybe the integration of the three is the innovation?
Sadly, if we look at the Iron Triangle of business, all Lean, SixSigma and Agile are really doing is shifting the emphasis between Cost, Quality and Speed. It’s still the same old same old: cost, quality, speed – choose any two you like… “everything was taking too long… so we went Agile… then we realised we were just doing the wrong things faster… which made us a bit confused so we brought in the Six Sigma Black Belts… which took out some of the variation… but that didn’t make the customer any happier…” and, hey presto, the carousel has come full circle again.
Should companies use Lean? Should they go Agile? Should they use SixSigma? Should they use Lean and Agile? All three? They’re all meaningless questions, because they’re all just causing the same stupid carousel to spin faster and faster. All three are fundamentally based on an erroneous assumption that life is full of inherent trade-offs. We can see it most vividly in the Agile Manifesto:
‘Over‘? What are you talking about? What these lines effectively say is, ‘there is a trade-off between X and Y, and we’re biased in the direction of X. Granted, it’s a choice, and sometimes choices are good. But rarely is this so if the initial question was a dumb one. Why can’t I have individuals and processes? Why can’t I have responsiveness and a plan?
In fairness to the Agile world, they do at least acknowledge that the Quality-Cost-Speed carousel stops being fun after a few spins. Coming from the high revolutions per minute world of software development, Agile practitioners have realised faster than most that the iron triangle actually has a fourth side: Scope.
Adding Scope to the carousel ride ought to be a good idea. But, sadly, not if – as the Agile practitioners have done – you just use it as another trade-off parameter. Here’s how the Agile community describes their four-sided carousel ride:
Essentially this picture reads: let’s stop fixing Scope and oscillating between over-budget, late and inadequate quality, and instead let’s fix those attributes and let the Scope be the thing that varies. Huh?
Again the wrong question. It’s not a trade-off. You just have to put yourself in the position of the customer to know that. The customer doesn’t want a ‘perm any three from four’ compromise. They want you to solve the contradictions and ‘get better’. Something like this:
Including ‘Scope’ on the carousel ride allows us to recognise that successful evolution has a direction. Everything evolves towards an Ideal Final Result end state in which all of the desire customer benefits get delivered ‘free, perfect and now’.
The way the world works is that we only step closer to that evolutionary end goal when we reveal and resolve contradictions. The only reliable method for doing that is TRIZ.
Lean, Agile and SixSigma have a role in life solely as optimization tools. The right blend of those tools then depends on the relative importance of Cost, Speed and Quality at any given moment in time. When people on the optimization carousel start to feel queasy, it’s probably a sign that there’s a need to solve a contradiction and make a jump to a better carousel. Something like this maybe:
I wish this could be the end of the discussion. Sadly, I suspect it won’t be, and before too long we’ll start seeing Lean-Agile-SixSigma education programmes. As if this is some new kind of panacea. And then we’ll get Certification. And then Standards. And before we know it, the whole optimization carousel will fly off its axis and spin into futile oblivion. Still, I suppose it keeps everyone from having to deal with the real issues. Like giving customers what they might actually want.
Progress happens fastest when contradictions are revealed and resolved. My job means I spend pretty much all my time looking for contradictions. Sometimes they reveal themselves more easily than others. Sometimes it’s necessary to dig quite deep before you discover things you thought were the same are actually not the same.
This is the experience I had when I attended the Lean educators conference last month. One of the governing principles of Lean is the drive for ‘Perfection’. For a long while I assumed this was the same principle as the ‘Ideality’ pillar in TRIZ. I thought, too, that both were present in order to provide those tasked with improving and evolving systems with a compass heading. Everyone knows that ‘perfect’ is a hypothetical end destination that will never occur in practice. Everyone in the TRIZ and Lean communities also knows that unless you know where you’re heading, you’ll never know if you’re moving in the right direction or not.
The fact that Lean ‘Perfect’ and TRIZ ‘Ideal Final Result’ are not the same kind of crept up on me during the conference. Lean people constantly tell me that Taiichi Ohno, the father of the Toyota Production System, made no distinction between innovation and optimization, and that in striving for perfection one would sometimes be making incremental improvements, and other times discontinuous jumps. I can kind of see this in theory. What happens in practice, however, especially if you examine the Lean toolkit, is that the incremental is precipitated much more readily than the step-change. Ohno’s start point was the elimination of waste, and specifically, what he saw as the overriding waste of ‘over-production’. All of the other 7, 11, 15 or – pick a number – ‘wastes’ were introduced merely because Ohno’s start point was deemed too abstract by those he tasked with improving Toyota’s manufacturing operations. The ‘Waste of Over-production’ in Ohno’s terms, by definition incorporated the potential waste of a lost customer, but if you look at the catalogue of Wastes being managed in most organisations, you will see how this difficult one tends to get side-lined in favour of the ‘easier’ internal wastes. This is particularly evident when we look at Lean Manufacturing initiatives. Anyone responsible for squeezing Perfection out of a production facility – like Ohno – has no ability to do anything about lost customers. ‘Perfection’ in this manufacture-oriented context effectively means building the Perfect Car. And that in turn means a car that leaves the production line having generated Zero Waste.
While this might be a good direction-providing (unattainable) target, it is very definitely not the same as the Ideal Final Result found in TRIZ. Like Lean, TRIZ focuses on the customer. The Ideal Final Result is first and foremost the customers’ Ideal Final Result. But there the similarity ends. In the Lean world, the customer gets a Perfect Car. In the TRIZ world, the customer gets Perfect Transport. In TRIZ world, there is a clear recognition that what customer’s really want is the Function. They are trying to get from A to B, rather than have a shiny new, waste-free, Prius in the garage.
Ideal Final Result in TRIZ is defined as the (unattainable) end point of delivering all of the desired Benefits, without any of the Costs or Harms. TRIZ, in other words, takes the B/(C+H) value equation and extrapolates it to its logical end point: all of the positives with none of the negatives.
The fact that Toyota still makes cars and didn’t invent Uber tells me that the Toyota Production System is very clearly not working towards the TRIZ version of Perfect. I think we can see similar dangers of having the wrong ‘Perfect’ goal in any organisation that find itself gazumped by upstart providers offering customers the function rather than the product. Whenever I see Lean being introduced into an enterprise, my first thought these days is, “here is a business heading on a ‘make the wrong thing perfectly’ road to certain oblivion”.
The TRIZ definition of Perfect is a better target, but it too – now I’m thinking about it – carries its own set of dangers. TRIZ emerged into the world at around the same time as Ohno was pulling together the various borrowed threads of the Toyota Production System. The world in the 50s and 60s – at least from a management perspective – was built very much around tangible and measurable factors. Value meant tangible-Benefits, tangible-Costs and tangible-Harm.
What 21st Century ‘design-lead’ companies like Apple, Tesla, and Uber taught the business world was that customer Value was as much, if not more, defined by intangible factors such as trust, fairness, autonomy, belonging and competence. The definition of the (unattainable) end target needed to change. And that’s why, whenever you see the Systematic Innovation version of the TRIZ Ideality equation, you’ll see it has the word ‘Perceived’ added to it. Value in the SI world is defined as Perceived{Benefits/(Cost + Harm)}, and Perfect in this definition is when the customer perceives they have received all of the tangible and intangible benefits they desire without any of the tangible or intangible negatives.
Adding ‘intangibles’ into the definition of Perfect is, I think, a subtle but quite profound step-change in the evolution of the compass heading of any improvement initiative. It forces those tasked with improving the system to consciously build in to their efforts the need to improve customers’ sense of autonomy, belonging, competence and meaning, etc, as well as delivering all of the tangible elements written into the specifications. It thus also opens up the search for a whole new set of conflicts and contradictions – when the tangible conflicts with the intangible, those are some of the richest opportunities to step-change to a better solution.
In theory, the (unattainable) P{B/(C+H)} end-point is the point at which ‘all’ of the conflicts and contradictions have been eliminated. Every individual customer receives a solution that is Perfectly customised to their own personal needs and wishes.
But, of course, the moment we think we’re anywhere close to what we initially might think ‘Perfect’ might mean, we begin to realise that we’re merely approaching a horizon that, once we get within touching distance, we realise keeps moving further and further away from us.
What could possibly be better as a compass heading for any improvement activity than every customer getting their own personal perfect solution, complete with all of the implications that carries of how fickle we are as a species? What’s perfect for me to day, is anything but perfect tomorrow. Perfect in human terms is potentially a very ethereal and transient thing. In theory the Systematic Innovation definition of ‘Perfect’ doesn’t exclude such fickle-ness, but on the other hand, I now believe the ‘AntiFragile’ work of Nassim Nicholas Taleb provides us with a need to look further over the Perfect horizon and build the concept of anti-fragility in to our definition. The (next) true Perfect solution not only gives individual customers exactly what they want, whenever they might want it, it also self-learns to adapt and change as the tangible and intangible needs of the customer shift and evolve. The more the customer might change their definition of ‘Perfect’, the more the Perfect solution is able to compensate, adapt and anticipate future changes. It becomes, to put it another way, ‘meta-Perfect’ – perfectly working out what ‘perfect’ means to the customer.
Taken all together, I think the various worlds of Lean, TRIZ, Systematic Innovation and AntiFragile give us a story of the evolution of ‘Perfect’. The story seems to me to look something like this:
So what? you say, if the whole thing is unattainable, why should companies care that the end point has moved? If we’re nowhere near the ‘Perfect Car’, why should anyone be building Anti-Fragile Meta-Perfect definitions into their way of doing business?
For me, we just have to look at the amount of value Uber has stolen from the automotive companies to get the answer we need. Our understanding of ‘Perfect’ might be evolving, but the underlying customer understanding of what they want has always been there. Any organisation working in a high-pulse rate change environment – i.e. nearly all of us – needs to recognise that today’s customers already want useful functions our product delivers, not the stupid product itself, they already want all the intangible factors we don’t know how to manage, and, now Professor Taleb has given us the word, they already know they want the antifragility.
Any question containing the word ‘or’, I propose, is a bad question. ‘Is it nature or nurture?’ ‘Should I vote Labour or Conservative?’ Either/or questions everywhere. I blame the intelligentsia. Mostly, though, I blame Socrates. He was the one that made a science out of either/or thinking, encouraging us all – anyone that spent any time in a classroom at least – to bludgeon our way through an argument until one person emerges the victor. In reality, most people – the people stood at the front of the classroom aside, obviously – have learned enough to know that the right answer to these kinds of question is both or neither. Respectively.
Listen out for the word ‘or’ during conversation and it’s amazing to me how widespread it is. Trade-off thinking is everywhere. When you start to point it out to people, at first they don’t know what you’re talking about. Then later, if you badger them long enough, they start removing the ‘or’. So the question then becomes, ‘should we go to Blackpool for our holiday?’ Unfortunately, the shorthand hasn’t taken away the either/or thrust of the question. The word ‘or’ didn’t feature in the actual words, but the way it was meant to be interpreted was still very much, ‘should we go to Blackpool for our holiday or somewhere else?’
This is a much more insidious form of trade-off thinking. Especially if it results in me having to go to Blackpool again. Thinking about it, Blackpool is a very either/or kind of place too. I’ve been there five times in my life, and four times I found myself in a fist-fight. Usually in a pub, and usually coming shortly after the question, ‘are you looking at me?’
Granted, I probably shouldn’t have responded on the most recent occasion, that did he know he’d just used an implied or. ‘Are you looking at me or were you merely scanning your eyes around the room?’. It just goes to show how dangerous either/or thinking can turn out to be.
If you think people use the word ‘or’ too much, just wait til you start listening out for the implied or. Either/or thinking is so endemic we’ve made it invisible.
Every time you hear a closed question, you’re hearing an implied or. Most times you hear a future-tense statement, you’re also hearing an implied or. Every time you hear the word Blackpool… you get the idea.
We built a PanSensic narrative lens to pick up on ‘or’s and implied ors. Just to see how endemic endemic is. The answer turns out to be ‘very’. Especially if you also go listen out for the trade-off solving ‘and’ words and calculate the ratio of ‘or’s to ‘and’s.
I was at a conference last week. A reviewer put in their feedback form at the end of the two days that they thought it had been a very ‘and’ event. I ran all of the papers and narrative content I could find through PanSensic. The ‘or/and’ ratio was a shade over 40. If that makes it an ‘and’ event, I think the best we can say about society as a whole is that we still have a long way to go. Or…
No-one goes to work intent on doing a bad job. W. Edwards Deming taught me that. I also believe that merely arriving at work with an intention to do good things does not mean that good things will inevitably happen. Deming taught me that too. Sometimes, very well intentioned people do an incredible amount of harm.
Like, for example, the people tasked with writing Standards.
I was once on a Committee tasked with writing an International Standard. Every time I went to one of the meetings I used to get a knot in my stomach. At the time I didn’t know why. In the end, I made my apologies and left. I never really understood the reason either for the knots or the departure.
More recently, I’ve been in the position of watching other people participate in the Standard writing process. The forthcoming ISO18404 to be precise. A Standard that is designed to regulate the Lean, SixSigma and ‘Lean & SixSigma’ markets. Under normal circumstances I’d watch the emerging shambles with a wry smile on my face. There are only so many ills one person can get themselves worked up over. And, in theory at least, a Lean and/or SixSigma Standard ought to have nothing at all to do with innovation. One might go so far as to say they are the very antithesis. In practice, however, I have a sneaking suspicion ISO18404 will do even more damage to the world of innovation that it inevitably will to the Lean and SixSigma communities.
What I know about Standards in general and ISO18404 in particular is that they have been established because ‘someone’ has realised that as industries grow they invariably attract rogue elements. Encourage enough Lean practitioners into the consulting market, in other words, and sooner or later it will begin to fill up with consultants that don’t really know what they’re doing.
These rogue elements, therefore, the well-intentioned Standards Committee members conclude, need to be weeded out. Good ones will be ISO18404 ‘Certified’ and, bad ones will not meet the regulated competencies (of which there are 23 in the case of Lean) and hence won’t be certified. So much for the theory. So much for helping wary prospective clients from hiring a ‘bad’ consultant.
The first question that needs to be asked, I think, is how much harm ‘bad’ consultants actually cause? We saw the ‘bad consultant’ problem in the TRIZ world in several countries for a while a decade ago. Idiots that go on a two-day TRIZ course and then think they’re qualified to solve nuclear fission problems for clients. It was a problem for the TRIZ world for about a year, and it was a problem for prospective clients – the real customer – for about a day.
In one particularly memorable (as in ‘I still bear the emotional scars’ way) experience, we had a client that insisted they wanted to go through a ‘real’ ARIZ session. So we found them a real TRIZ Master (Certified by Altshuller himself), and helped set the workshop up. The Russian TRIZ Master told us the session would need three days. At the end of the first day, the client pulled me over on one side and said, ‘don’t worry, we’ll of course pay you for all three days, but, please, we need to end this here’. It had taken them a day to realise that TRIZ ‘Master’ or not, they were in the presence of someone that had absolutely no ability to empathise in any way with a room full of restless engineers.
In reality ‘bad’ consultants aren’t a real problem at all for clients. If the client is looking to, say, embark on a Lean journey, the most likely thing they’re going to do is put out a Request For Proposals. Lots of Lean practitioners will see these proposals, and the least busy will very likely submit proposals.
At the moment none of these proposals will show any kind of Standard accreditation. This is a little bit inconvenient for the client, because it means they are actually going to have to read the proposal. That’s probably going to cost about half an hour. If it’s a really bad consultant, though, they will very likely be found out at this stage. If it’s a more cunning bad consultant, they might get past this first down-select. They might get to a point where they are invited to turn up and talk face-to-face with the client. Another couple of hours gone, but it’s pretty difficult for incompetent people to hide their incompetence for more than an hour when someone is looking them in the eye. When someone lies about their past track record, a simple phone call to references will pick up the problem. And even if the bad consultant prevails through this evaluation and gets the job, their incompetence will be found out within a couple of days of starting it.
Put frankly, if a prospective client isn’t able to weed out bad consultants very quickly and very easily, they deserve all they get. Call it a self-organising system. Idiots deserve idiots. Its exactly the same situation as when clients choose their consultants on the basis of price and it goes wrong: the failure is annoying, but at least they learned something important: choosing on today’s ticket price is a dumb way to go about any kind of business.
Here’s what a Standard will do in the above scenario: a) clients will look for the ISO badge and as soon as they see it will tend to stop reading the proposals and – worse – stop thinking (this is called ‘plausible deniability’ – when things go wrong, they can now shrug their shoulders, point their boss to the ISO logo, and say, what else could I have done?’), b) the self-organising nature of the industry becomes progressively destroyed and everyone – clients and consultants – become more interested in the badge than thinking about the actual need, c) before too long, the whole charade descends into a ‘badge collecting’ industry. Good consultants waste time administering their ongoing Certification evidence; bad consultants spend theirs working out how to subvert the system. See ISO 9000 for a good example of what this looks like when the system is properly ‘mature’.
It’s a bad thing that this happens. Even worse that it appears to be universal.
But it’s not the worst thing. The worst thing is that the well-intentioned Standard-writing do-gooders have only ever looked at half the story. They (naively) see a ‘bad practice’ problem and decide they had to fix it. But they never look at the other side of the coin. Standards do good things, but they also do bad things. Standards are, by their very nature Contradictions: ‘We want a Standard and we don’t want a Standard’. We want Standards (in theory) to weed out the ‘bad’; we don’t want them because they impede the ‘good’.
And in the case of ISO 18404, the specific ‘good’ I think they’re inadvertently about to kill is innovation:
Standards lock in today’s practices and impede advances. They stop people thinking, and as a consequence they become a ready-made excuse to not innovate. That’s what I see. I’ve had this argument several times with Standards people. ‘Ah, yes,’ they will say to me, ‘but we review the Standards every three years’. To which my answer is why three years? What happens when the world pulses at a rate faster than three years… as is the case in most industries today.
But even this is the wrong argument to get into – we should always know that if a question contains the word ‘or’ in it, it’s the wrong question. It’s not about should we review a Standard every three years or every six weeks. The right question is ‘how can we have a Standard AND not a Standard?’
Now, I admit that I’ve never met a Standards person yet that understands what the hell I’m talking about when I use this kind of TRIZ language. Sometimes I even try to tone my language down a bit. ISO18404 – like every other Standard before it – kills innovation because no-one has done anything to cater for the down-side. Maybe I don’t need to mention ‘contradictions’, maybe instead, all we need to do is get Standards people to think about the likely negative consequences of their actions and to build a solution to these consequences into the Standard.
Its not even that its hard to do this, it simply means that people have to give themselves permission to think about the down-sides and incorporate something into the Standard to prevent them from happening.
In the case of ISO18404, for example, it would have been very, very easy to include a twenty-fourth competence that ‘Good’ Lean or SixSigma or ‘Lean & SixSigma’ practitioners would have to demonstrate their abilities against:
‘Practitioners need to be able to demonstrate that they understand the limits of the Standard, and that they do not encourage or endorse client solutions that will impede the innovation ability of the client’.
That’s called ‘solving the contradiction’.
It’s time for another Standard, I believe. A Standard for Standards writers. A Meta-Standard. A Standard that prevents Standards from turning into value-destroying industries that serve only the officials they employ. It probably only needs two clauses:
Clause 1: the system should be designed in such a way that it emerges in a progressively self-organising manner, that will eventually eliminate the need for the Standard.
Clause 2: whenever an either/or Contradiction emerges that hinders the achievement of Clause 1, Standards Committees should devise solutions that eliminate such Contradictions.
The only downside, I suppose, is that it will kill the Standards-writing industry. And then where would the ‘bad’ consultants go and work?
The more I do work in the healthcare sector, the more sceptical I get about ‘clinical evidence’.
I started my career in the aerospace so I understand the idea of evidence. When aerospace engineers get things wrong, aeroplanes fall out of the sky, and that’s never a good thing. Evidence is what keeps planes flying.
A couple of year’s ago, after a particularly frustrating experience with a part of the UK NHS that will remain nameless for the moment, we did a few calculations to translate the current level of safety performance of the NHS into aerospace terms. The numbers came out a bit scary. So we did them again. And then again from a different direction. Expressed in mortality rates, the NHS, we concluded, is currently equivalent to a shade under 2000 plane crashes per day. Over UK air-space.
When we shared the data with this part of the NHS, asking them to check over our numbers to see where we were going wrong, surprise, surprise, we never heard from them again.
Clinical Evidence matters came to a head again a couple of months ago. This time with a different part of the NHS. This time in a workshop setting. We were talking about Complex Systems Theory. And someone – inevitably I now see – asked the clinical evidence question. Where’s your evidence that treating healthcare as a complex system is a better way of doing things?
For a few moments, I didn’t know what to say. Fortunately, the question came just before a break, so I muttered a no-doubt inane answer and tried to move on.
Over the break a made a new slide. Here’s a copy of it:
After the break, when everyone was back in the room, I put it up on the screen and asked for a hands-up vote. Everyone sat there, paralysed. ‘Any thoughts?’ I probed. Nothing.
I’d kind of anticipated the reaction, so, after I’d let the tension build a bit more, I advanced the presentation to a new version of the slide. This is it:
Now answering the question had become easy. Within a minute we had a collective answer: 10% A, 90% C.
It’s a fine line sometimes. And it’s difficult to know which side we’re on.
Is it better to treat a system as a system or not as a system? There’s a clue in the question, right?
Is it better to treat – say – a headache as a system or with a pill?
Is it better to deal with crime as a system or by longer prison sentences?
Is it better to deal with education as a system or by re-introduction of grammar schools?
Is it better, post the Brexit vote, to have experts or not to have experts?
At which point on the line do we make the transition from tautology to ‘we really don’t know, so we need to go gather some actual evidence’?
I have some sympathy with those that, per Michael Gove’s epoch-making statement, ‘have had enough of experts’. But the alternative is not to say, ‘oh, in that case, let’s listen to dumb, stupid people instead’, it’s to ask the question, ‘experts in what?’
Wherever we all might individually draw the tautology line, given the choice of treating a system as a system or not a system, there’s really only one sensible answer. And a good part of the answer to the ‘experts in what?’ question, therefore, ought to be, ‘experts in systems’.
So why then did 90% of the people in my workshop ignore the obvious? People say and do things for two reasons; the good one and the real one. Apparent absence of clinical evidence is a good reason for denying the need to treat systems as systems. The real reason, of course, is that the 90% of people that voted ‘C’ in my workshop simply didn’t understand what a system was, and so used clinical evidence as their get-out-of-jail-free’ card.
To me, anyone that doesn’t understand systems, probably shouldn’t be working within one, but that, unfortunately, would mean no-one could go to work anymore. Everything in life is a system. Life is systems. So, assuming we have to have people working within systems that don’t understand systems, that doesn’t also mean we can or should allow managers the same privilege. And there’s the problem in a nutshell. Not just in the NHS, but in all walks of life, 90% of managers or leaders have no idea what a system is. So what we end up with are a million and one ‘fixes’ that backfire: headache medications that lead to addiction and long-term digestive tract injury; harsher prison sentences that increase crime-rates; education standards initiatives that increasingly make students into dysfunctional members of society; homeless shelters that perpetuate homelessness; food-aid programmes that increase starvation.
When it comes to politics my main rule is anyone that wants to be a politician, shouldn’t be allowed to become one. My second rule is, whoever’s left over, is only allowed to become a politician once they’ve graduated Systems Theory class. My new rule, as of two months ago, is that what applies to politicians also applies to managers and leaders.
Every complex problem has a million simple wrong answers. If you’re lucky – if you can get to the core principles of the system – you might just find a simple right answer. Most people don’t get lucky because they don’t know how to get to the core principles. Most people don’t get lucky because they listen to supposedly smart people who also don’t know how to get to the core principles.
Take Frederick F. Reichheld, the man that wrote, ‘One Number You Need To Grow’ in 2003. What manager wouldn’t want to know what that ‘one number’ was? It was a sure-fire Harvard Business Review hit, and it spawned the monster we now know as Net Promoter Score.
The one number starts from one question. Even simpler. “On a scale of 0-10, how likely is it that you would recommend our company/product/service to a friend or colleague?”
It’s a simplicity that turns out to be flawed on so many levels it’s stops being funny after about five minutes. The laughter turns to tears when Frederick F Reichheld spotted that a good Net Promoter score was correlated to company share price.
Despite the fact that Reichheld himself eventually worked out that he’d fallen into the correlation-isn’t-causation bearpit, it was too late. Every Fortune500 company in every Fortune500 listing had taken for the bait, and so a whole industry of NPS surveyors found themselves riding a gravy train that still feels like one of the greatest gravy trains in the history of gravy trains.
The rules of the Hype Cycle – fortunately – tell us no ride goes on forever. Some will die outright. Those that have some underlying merit will prevail, once everyone works out what the underlying merit is. And, more important, how to meaningfully get to it.
Given the choice of knowing or not knowing whether I’m making our customers happy or not, the responsible side of me thinks I’d rather know. That’s the ‘underlying merit’ of NPS: knowing whether my customers are actually happy. Whether or not I can meaningfully know that my customers are happy or not, and – more importantly – knowing what actions I should take to make sure everything is moving in the right direction, becomes the critical question.
Answering it requires at least three things:
1) I need to know that my customers are telling me the truth
2) I need to know the local context within which they gave me their answer
3) I’d like a measure of a customer’s ‘threshold for action’
Current NPS assessment methods fail on all three counts.
The first of the three is probably the easiest one to put right. Or, it is if you are using PanSensic and are able to map where a customer’s responses are on the 5Gs model:
Where you are on the map depends on a whole bunch of (measurable) things. One of them is your level of (over-)familiarity with NPS questions. Picture, if you can, the very first time you read that ‘how likely are you to recommend…’ question. You were probably in a restaurant. And it was probably part of a chain. Your surprise and lack of familiarity with the question probably meant you were intrigued. And very probably intrigued enough to do some actual, proper thinking about your answer. You were likely somewhere in the Golden middle of the 5G graph. Which was good for the restaurant. Now, bring yourself back to the present day, where it’s quite likely you’ve been asked ‘the question’ a couple of times during the last week. Not just in restaurants now, but on trains, at the airport, in the supermarket, at the mall, in the hospital. I even got asked it at a football game last month. Now you don’t think about your response any more. You probably have no inclination to respond at all. If you do feel inclined, it’s most likely because something extreme happened. Something extremely above-and-beyond-the-call-of-duty, or something horrendously bad. In neither case, though, are we going to answer the question objectively. That’s because the NPS question has progressively numbed our senses to the point where it has become meaningless the moment we see or hear it.
Local context is more difficult to capture, but still within the realm of possibility given the current range of different PanSensic lenses. Context, in terms of my likelihood or otherwise to recommend your products or services to my friends, has everything to do with the difference between correlation and causation. When I was asked whether I would recommend my friends to come and attend a game at the football club that asked me the question last month, the most sensible answer I could’ve given is ‘I’m an away supporter, I only came because my team is playing here.’ My actual likelihood of attending that club again – the causal link – is solely about whether they are in the same Division as my crappy team next season. I’m slightly ashamed to say that my actual answer to the questioner was, ‘yes, I am very likely to recommend your football club to my friends’. I watched as the questioner ticked the relevant box on her nifty Likert Scale. We were both happy. She was happy because she had something to correlate. The main reason I was happy, however, was because my crappy team had just beaten their even crappier team. If I’d been pushed any further, I’d very likely have made the request – as many of my fellow travelling fans chanted during the game – ‘can we play you every week?’ My reason for giving the answer I did, in other words, had precisely nothing to do with the way my answer was going to be interpreted.
So much for the situational aspect of ‘local context’. If you’re analysing the narrative around the answer rather than the score on the 0-10 scale it’s relatively easy to pick up this sort of situational effect. Ditto regarding whether someone is qualified to answer the question in terms of domain knowledge. I’ve been down this rant path before. Usually with things like Trip Advisor where the ‘reviews’ I read are usually written by people who stay in a hotel once in a blue moon and consequently have no way of saying this particular hotel is any better or worse than any other one on the planet. Their ‘review’ is usually – for the sorts of hotel I tend to stay at – based on a comparison between their experience and an advert they saw on TV for a seven star hotel in Dubai. i.e. fiction piled on fiction. “The taps weren’t even gold, two stars.”
The third aspect of ‘local context’ is the context of the person I might consider recommending your products and services to. I like music. I own a building full of records, tapes and CDs that aren’t going to be digitised and disposed of any time soon. When visitors see my music collection, they usually ask me to recommend something to them. A question that I can only usefully answer provided I know something about the sort of music they currently like. And how far in or out of their comfort zone they might want to go. And how much I want them to come back and ask for more recommendations in the future. It’s rarely as straightforward as saying, ‘Blue Nile, Hats’, although, I know that particular recommendation will work more often than it won’t, and if it doesn’t work, the visitor won’t be invited back very often in the future anyway.
Last up is ‘threshold for action’. This is the most difficult of the meaningful-NPS desire foundations. To an extent we know it boils down to the strength of the adjectives that people use to describe their experiences. Or rather the relative strengths.
Back to my football match. At half-time I – unusually – decided to go and get a cup of tea. There was a queue. I was stood behind a father and son duo. The son looked like he was about eight, and sounded like he hadn’t been to an away game before. Everything, therefore, was ‘awesome’. The journey to the ground had been awesome. The sandwiches were awesome. The floodlights were awesome. The two goals we’d scored were awesome. The late-night return home was also going to be awesome.
He was basically me forty-five years ago. Now I know that most things aren’t awesome. Our second goal, as it happens, was pretty awesome, but the first one was an umissable tap-in following a bad mis-kick by one of their defenders. It was never going to win any goal-of-the-season competition any time soon. Likewise, my cup of tea, when I eventually reached the front of the queue, tasted like it had been brewed a fortnight earlier, and had long past its moment of awesomeness. It doesn’t take much for an eight-year old to see that everything is awesome. For a cynical old man, awesome doesn’t happen very often any more. When it does happen, though, it probably means more in terms of useful feedback to a company than when they hear the same adjective come out of the mouth of the eight-year-old.
You need a lot of an individual’s narrative in order to calibrate their adjective use in order to work out where they need to be on an adjective-strength spectrum before they will act – i.e. recommend to their friends or family. Getting access to sufficient of this narrative is ‘possible’ if you have access to, say, the Facebook narrative of a smiley Millennial, but very often the people that talk the most are the ones with the least to say. In which case, the current ‘best’ way to calibrate the how well a customer thinks about you is to calibrate across many customers. Even better, thinking about the PanSensic ‘Mental Gear’ lens, is to calibrate across Blue, Orange, Green and (especially) Yellow customers, and then – most crucially of all – close the loop by finding some actual customers that actually did recommend you to their friends and family and examining their actual collective PanSensic profiles.
NPS is not as far along the maturity scale as other Weapons of Mass Distraction (Balanced Scorecard, SixSigma, QFD, PRINCE2, Scrum, Agile, etc). Unlike most of them, it at least has a valid start-point in that measuring customer emotions is a fundamentally good thing to do. Whether it gets to survive in the long term is largely dependent on how quickly it can evolve to a point where the measurements it’s is used to make are meaningful – as in truthful, context-relevant and actionable. Which is hopefully where PanSensic comes in to play.
