Once in a while I find myself building a model to help explain an idea or principle to a client. The emphasis in these situations is usually to build something quickly. Which in turn usually means not worrying too much about consistency with other spur-of-the-moment models. Most of the time this works out okay. Sometimes a model takes on a life of its own and finds its way into the language with several different clients. For some reason its often the colour aspect of the models that helps with its spread. And that’s where things can easily start to turn out not okay.

The most recent series of colour clashes have come through the Red-World/Green-World discussion I started in the wake of the Innovation Capability Maturity Model book. An attempt to get people to recognise that Operational Excellence (‘Red World’) and Innovation (‘Green World’) are polar opposites. After I’d decided I needed a model to compare and contrast the two Worlds, I spent about 5 minutes thinking about the best colours to characterise them. The logic behind the use of green was, a) green is the colour of the ‘creativity’ Hat in Edward DeBono’s Six Thinking Hats model, and, b) green is the colour of the Systematic Innovation logo. Having chosen green, and recognising that I needed a second colour to describe green’s polar opposite, I went to the colour wheel and, hey presto, red was that colour. Decision made.

Spool the clock forward a couple of years and the colours of the different Value Systems in the Everythink book also started to connect with a number of clients. Which meant the arrival of questions like, ‘is the green of Green World the same as the Communitarian green found in Everythink?’ To which the answer, sadly, is no it isn’t.

Then someone else hears me talking about the Intel-initiated, only-the-paranoid-survive idea of companies comprising a Red Team and a Blue Team. The Blue Team being the majority of people in the existing business, and the Red Team being a small group of lateral thinkers whose job was to try and find ways to put the Blue Team out of business. Now the colour problem becomes much worse. Now I find myself describing how Blue Team lives in Red World and Red Team lives in Green World. And, worse again, that Red Team people in Green World will work best if they they’re thinking with the Yellow value system. It was only small consolation to then be able to say that they should be wearing Green Hats most of the time.

Act in haste, repent at leisure.

Innovator’s live in Green World, wear Green (and sometimes Black – like baddies) Hats, have Yellow value-systems and one of their roles is to act as a Red Team.

Operational Excellence workers live in a Red World, wear mainly White Hats (like goodies), ideally have Blue value-systems and are Blue Team.

Not that it helps an awful lot, but if I had my time again I’d re-label Red-World and Green World as, respectively, Blue World and Yellow World. That way at least there’d be a consistency between ICMM and Everythink. And that would then just leave the tiny inconvenience of having companies like Intel and people like Edward DeBono in the world. Messing things up as usual. With their Purple ways.

In this month’s SI ezine (http://systematic-innovation.com/assets/iss-229-apr-21.pdf) I introduce the seven habits of highly effective innovation project manager acronym, NEPTUNE. Navigator, Empath, Plate-spinner, Transcender, Umbrella, Ninja, Umbrella. It sounded like a weird distorted version of the NATO phonetic alphabet. Which then made me wonder whether it might be possible to make a whole alphabet of similar innovation-relevant words. Here’s the long list of candidate words I managed to compile:

A AntiFragile/Autonomy/Altshuller

B Belonging/PlanB

C Contradiction/Competence/Chutzpah/Cockroach/Cybernaut

D Diamonds (Diverge-Converge)/Duende/Disrupt/Diversity

E Empath/Elephant/Emergence

F Function

G Grit

H Hairball/Hero’sJourney

I Ideality/IFR

J Jugaad/Jazz

K Komorebi

L Leapfrog/Lagom

M Moonshot/Meaning

N Navigator/Ninja

O Outcome/Orbit-Shift

P Plate-Spinner/PlanB/Pirate

Q Quintessence

R Riptide

S System/SkinInTheGame/S-Curve

T Transcender/Tipping-Point/TRIZ/Turtles/10x

U Uniter/Umbrella

V Value(s)

W Whakapapa

X Xenomorph/X-Factor

Y Yarak

Z Zen

Hopefully, most of the words are self-explanatory. The NEPTUNE ones get explained in the aforementioned Seven Habits article. Here are the ones that perhaps need a little more explanation:

Hairball: from Orbiting The Giant Hairball, an off-beat innovation classic text. Subtitle: ‘a corporate fool’s guide to surviving with grace.’

Jazz: if operational excellence looks like an orchestra playing a score, innovation is a jazz combo improvising.

Jugaad: a colloquial Indian word, referring to a non-conventional, frugal innovation, often termed a “hack”. It could also refer to an innovative fix or a simple work-around, a solution that bends the rules, or a resource that can be used in such a way. Indicative of the perennial innovator drive to obtain the maximum amount of learning from the minimum amount of resource.

Komorebi: a word I first learned in Peter Fisk’s recent book, Business Recoded. Picture a hot sunny day, lying in the shade, and seeing the few streaks of light hitting the grass through the branches of a leafy tree. That’s the perfect place to be during the Japanese summer: komorebi. Like Ideal Final Result only more poetic.

Lagom: one of Sweden’s three great contributions to the English language (the other two being smorgasbord and ombudsman :)), lagom translates to “not too little, not too much” or “just right”—and in Sweden it represents the art of living a balanced, slower, fuss-free life. The first time I heard the word defined, I was told a story of warriors sitting around the dinner table passing around a bowl of stew and lagom was the uncanny ability of each person to know how to take just the right amount to ensure that all the other warriors would get their fair share. Which still feels like a good metaphor for what needs to happen inside any innovation team.  

Quintessence: the most rich and best example of something. The perfect embodiment. Another IFR end-goal pointer.

Riptide: defined in the dictionary as either a dangerous area of strongly moving water in the sea, where two or more currents meet, or a strong negative feeling or force that is difficult to control, riptide felt like a useful metap

Whakapapa: a Maori word defined as the “genealogical descent of all living things from the gods to the present time. “Since all living things including rocks and mountains are believed to possess whakapapa, it is further defined as “a basis for the organisation of knowledge in the respect of the creation and development of all things”. Whakapapa also implies a deep connection to land and the roots of one’s ancestry, and the idea of leaving a great legacy: ‘plant trees you’ll never see by being a good ancestor.’ Another word from Peter Fisk’s book, Business Recoded.

Xenomorph – not necessarily a real word, but used post movie franchise, Alien, to describe the Alien, ‘a highly aggressive endoparasitoid extraterrestrial species’. The Xenomorphs are vicious predatory creatures with no higher goals than the propagation of their species and the destruction of any life that could pose a threat to them. Not quite a perfect metaphor. Except for the bit about protecting their own and the ability to morph into different forms at different life stages. This is the word I think I’d be most likely to vote into any NATO suggestion scheme to change the classic phonetic alphabet.

Yarak’ – a Persian falconry term meaning ‘super-alert’, hungry-but-not-weak, and ready to hunt. Without this kind of mindset and these characteristics, in a critical mass of its people, a business will not succeed. Discussed at some length in the Hero’s Start-Up Journey book.

Zen – the parallel need for calm, mindfulness and a beginner’s mind.

And so, finally, here’s the proposed short-list…

A friend told me a story the other day. I don’t know whether it is correct or not. If it turns out to be apocryphal, I suspect it won’t affect the truth the story contains.

The story involves a Liberal Arts professor at a prestigious university. The professor tells his students that every student in the class will receive the same mark for their assignments. The mark being calculated by taking the average of each of the individual assignment scores.

In the first assignment everyone received an A. In the second, the average mark went down to a B. In the third assignment, everyone received a C-. The fourth assignment, everyone failed.

At first blush the story offers up what looks like an iconic example of how socialism quickly devolves to the lowest common denominator. When it comes to rewards, humans tend to care most about what they get relative to others, rather than absolutes. So, I’m okay with less provided that my neighbour is getting even less than me. Or, taking into account the fact that we all tend to be pain-avoiding before pleasure-seeking, I tend to be not okay if my neighbour is visibly doing better than me. Combine this relative-envy factor with the fact humans also tend to be lazy, and it doesn’t take long before everything combines into an exponential race to the bottom.

The only alternative, the political right and capitalists tell us, is competition. Competition, they say, creates a race to the top.

Or at least that’s what the theory predicts. Except, humans are still lazy, and so the road to the top quickly becomes hierarchy-shaped. Which means society makes a different kind of exponential shift, this time with 1% at the top of the pile and the other 99% scraping a living on zero-hours contracts and feeling they would have been better off in the socialist system. A system where, if nothing else, they wouldn’t have to stand outside the gates, looking at the rich coiffing champagne in their Mcmansions.

All this, of course, is just another example of weak, two-dimensional left-versus-right thinking. Those on the right might rub their hands with glee hearing the Liberal Arts professor story. And they might be right, but not for the reasons they think.

The archetypal socialist race-to-the-bottom doesn’t happen just because humans are lazy and envious. It also happens because the majority of tasks that modern life expects from us are essentially meaningless Mcjobs. And somewhere near the all-time top of the list of meaningless McJobs is the liberal arts assignment. Had the assignments been relevant to anything other than the professor’s blinkered ego, students might have ignored the fact that their best efforts would not score them a good grade and worked hard. Combine socialist measures and meaningless work, however, and students quickly work out there really is no point in trying at all.

The missing third-way dimension in the left-right spectrum is meaning. Or almost. Add meaning to socialism and, while we might slow the race to the bottom, we don’t get utopia either. Instead, we get great art and bad plumbing.

Which leaves the competition-and-meaning combination. While that inevitably won’t be perfect either, it would at least help cure the corrosive, post-truth, every-man-for-himself version of capitalism we now see in too many parts of the world. And it would, too, likely serve as the step-change to society’s next, right direction, s-curve.

Time was, when something or someone pissed you off, you’d come home and vent about it to an amenable member of your family. Or the cat. Half the time they’d help you to realise you were being over-sensitive, you didn’t know what you were talking about, and that you needed to grow-up and move on. The other half, the moment you heard yourself spouting the ill-formed, angry, frustrated words left your lips, you realised you didn’t need them to tell you. You worked it out for yourself. Either way, problem over.

Now, however, five seconds after the pissed-off event, everyone is on social media spouting those self-same ill-formed, angry, frustrated words. Only now to a couple of hundred anger-by-proxy seeking followers. Rinse and repeat a few hundred times, and there’s democracy dead and gone.

‘Russian bots’ might help reduce the number of iterations from 450 to 440 but they’re really just noise in the exponential dysfunction caused by the Social Media industry’s share-of-mind addiction. Bad news travels seven times faster than good (Microsoft Word – dec03 newsletter.doc (systematic-innovation.com), it is seven times more likely to be re-tweeted, and is at least seven times more likely to be Tweeted in the first place.

The root of the problem is trying to do in public what would normally happen in private. In private, being face to face with a logical, kind-of-rational family member (or cat) helps you count to ten, allows the anger-chemicals drowning out your common sense to drain away, and enables you to start to think kind-of-rationally again: maybe I was being a dick? Maybe I could’ve handled it better?

This is the way society used to function. The pause between stimulus and response. The pause that gave democracy a chance.

So, the new Jordan Peterson book is out. Beyond Order, ’12 More Rules For Life’ a complement to his original 12 Rules For Life. The main difference this time around being that the focus is on Rules for becoming a human capable of surviving in complex and chaotic environments. As opposed to the first 12 Rules, which were all about becoming a human capable of living resiliently in a Simple world – i.e. it was largely for Feudal Millennials that had never been taught some of the difficult lessons of life. Like tidying up their room.

Anyway, the pair of books fit into two of the most important triangles in our Complexity Landscape Model (CLM). The first 12 Rules in effect being all about (steady-state) Operational Excellence, and the second 12 being about (liminal) Innovation World:

As I got further through the new book, I began to realise that there was a further innovation connection to be made. Specifically the Law Of System Completeness. Which tells us that any viable system must contain a minimum of six different elements. And since ‘being a human’ involves a system, that system must contain these six elements. Or rather two times six – one viable Tangible system and one viable Intangible system. Which, if my maths is anywhere up to scratch suggests twelve system elements in all. The question then was, was this something Peterson was aware of?

Time to start fitting his 12 Beyond Order Rules into the Law of System Completeness. The end result of which looks something like this:

(As Peterson-fans will attest, some of his Rule titles are a little obtuse and their connection to the various elements of the complete system only become clear through a proper reading of the relevant chapter. If you’ve already read the book, and have a passing acquaintance with the Law Of System Completeness, I imagine you will be able to make the same connections that I have. If you haven’t read Beyond Order, you’re going to have to take my word for it. And if you’re not familiar with the TRIZ Law Of System Completeness, you may want to hum the bits you don’t understand.)

According to Peterson, the 12 new Rules found in Beyond Order were distilled down from an original list of 42 (life, the universe and everything?) There’s no real explanation for how this process was conducted, but my impression is that he ended up with the twelve that had most frequently helped patients in his clinical psychology practice. There was, in other words, no attempt on his part to create any kind of coherent system of Rules. The fact that he ends up with eleven of the twelve that the Law Of System Completeness would have told him to go look for, therefore, is rather impressive.

Impressive enough to go back and re-visit the initial 12 Rules to see how well he’d done to map the complete system of Simple-Simple humanity. Here’s the result of doing that analysis (where, again, it was necessary to go back and re-read the whole thing in order to translate the obtuse rule names into their intended meaning – ‘petting cats’ for example doesn’t have an awful lot to do with petting cats, but quite a lot to do with human fragility):

Another impressive eleven-out-of-twelve score.

Close enough on both counts for me to start thinking about what the two ‘missing’ Rules might be. While I think I can do obtuse titles, I quickly found myself out of my depth in terms to coming up with something either pithy or meaningful. Which then usually means adopting the classic TRIZ stance of ‘someone, somewhere already solved your problem’. Were there other books, in other words, that might be able to slot into Peterson’s holes?

The Law of System Completeness offers some clues of course. As far as Beyond Order is concerned, Peterson doesn’t have a Rule to cover the Intangible ‘Tool’ part of the system. In the first book he did, and as I was re-reading that Rule, ‘be precise in your speech’, the best connection I could make to other works was my second all-time favourite book, Zen & The Art of Motorcycle Maintenance. The thrust of that book was (a metaphysics of) Quality. Pirsig extends this discussion in his follow-on, and my all time favourite book, Lila: An Inquiry Into Morals. The extension primarily centring around ‘dynamic quality’… what I firmly believe forms the missing piece in the Beyond Order jigsaw:

The Law of System Completeness also offers up clues as to the missing piece in Peterson’s first 12 Rules – the Intangible ‘Sensor’ is what needs to be found. Which means we’re in the realms of measurements and feedback loops as they pertain to the emotional aspects of our steady-state human ‘system’. In this case I wasn’t able to find a single solution to fill in the gap. The ‘character’ aspects of Steven M.R. Covey’s book ‘The Speed Of Trust’ seemed to capture some of the Sensor story, but missed much of what I see as the most frequent (mis)understanding problems that occur in human communication, biases. These days, mention of that word usually sends me immediately digging out the Bias Codex (https://www.darrellmann.com/cognitive-biases-as-a-system/). And there it was, Peterson’s 12 Rules For Life missing piece was two pieces…

…unless, that is, you know different?

More and more people seem to be coming to the conclusion that The Sovereign Individual book has played a significant behind-the-scenes role in the way the Brexit story has played out (https://alastaircampbell.org/2020/12/the-brexit-revolutionaries-have-barely-begun-britain-needs-to-wake-up-fast/). At the very least, the book does much to explain some of the more counter-intuitive moves of those implementing the strategy. In that sense it has much in common with other late-period Capitalist thinking. The most recent of which to cross my radar came from the (notorious?) Babson College, its commercial offshoot, Babson Global, and its Babson Global Competitiveness and Enterprise Development Project. Which, Babson Global CEO, Shahid Ansari has said, ‘gives us another powerful tool to use entrepreneurial thought and action to address the economic and social problems facing the world and allow individuals and societies to thrive and prosper during these challenging economic times’.

Going a step further, “There is simply no greater challenge faced by mankind than helping to lift people out of poverty and frame a world of abundance, and not of scarcity,” said Shanker Singham, Managing Director of the CED Project. “By leveraging the forces of the competitive market system, as opposed to relying on aid, the Babson Global Competitiveness and Enterprise Development Project seeks to identify new ways of delivering economic growth to countries around the world.”

The Babson worldview represents classic Gravesian, ER, Orange thinking. Which looks at a DQ, Blue world of fairness and use of state-aid to ‘help’ those at the bottom of society and concludes that such things fundamentally don’t work. And that they don’t work for two reasons. Firstly, at an individual level, they create a state of ‘learned helplessness’ that serves only to perpetuate the need for more state-aid. Secondly, at a state level, comes comes a recognition that aid comes with an inherent level of inertia, which in turn provokes corruption.  At first, the competition that capitalism sparks will very likely achieve what Babson Global is trying to achieve. The key phrase being, ‘at first’. The problem being that sooner or later the fundamental law of the s-curve kicks in. In the first half of a capitalism s-curve, we see what might be thought of as the sort of ‘good capitalism’ the Babson Enterprise Project is trying to spark. In the second half, however, when the law of diminishing returns kicks in, good capitalism turns inherently bad. It’s one thing to introduce the developing world into this new world of capitalism, but, sadly, most parts of the developed world are already well into the bad second-half of the curve. A second half that means, fundamental human nature being what it is, capitalists start their own version of cheating and corrupting the system. This cheating, unlike the DQ version, usually comes in the form of ‘externalisation’. Businesses that produce toxic side-effects try and hide them. The gig economy – probably the definitive manifestation of bad-capitalism – tricks individuals into believing they’ve been offered ‘freedom’, when in fact they’ve been turned into little more than indentured slaves. Anything that can’t be measured or generates problems that only become apparent in the long term (oestrogen-based pesticides for example) becomes grist to the short-termist bad-capitalist mill. Failing to be able to sensibly measure things like ‘quality of life’, adverse effect on mental health, etc mean they become candidates for more externalisation.

So much for global fundamentals. The answer to such top-of-s-curve challenges, however, is not to regress to the previous s-curve. Solving ER’s bad-capitalism, in other words, doesn’t happen by reverting to DQ’s bad fairness. That’s basically what was attempted in the aftermath of the GFC. The capitalists demonstrated that de-regulation gave them the perfect opportunity to ‘externalise’ a whole bunch of things they shouldn’t have been allowed to externalise. But trying to fix the problem by creating a mountain of new (Sarbanes-Oxley, DQ) regulation merely created a worst-of-both-worlds solution. Far better would have been solving the ER and bad-capitalism contradictions and ‘breaking through’ to the next s-curve.

Perhaps the Babson work, much as it betrays their abject lack of understanding of s-curves as they might apply to societal progress, does make some kind of attempt to distill the world down to first principles. At least in a Newtonian sense.

Here is Shanker Singham’s capitalist version of Newton’s Laws:

1. Wealth can be created or destroyed.
2. Wealth is easier to destroy than create
3. Competition is the greatest force for liberating wealth-creating forces

If we now bring the idea of societal s-curves into this story, we might speculate that the next s-curve after DQ’s Order and ER’s Competition, has to be FS’s ‘communitarian’ paradigm. There’s no rule at this point that says the structure of any first principles of an FS-lead society have to follow the same structure as Singham’s reframing of Newton. But we do know that the FS world-view is still one that does not fully understand the innate complexities of the world. i.e. the FS world is also a Newtonian world. That knowledge, then, might cause us to at least start with a hypothesis that Singham’s structure makes for a valid set of FS-based first principles. Here’s what I think they translate to:

1. Meaning can be created or destroyed.
2. Meaning is easier to destroy than create.
3. xxx is the greatest force for liberating meaning-creating forces.

The first idea being that in the FS Communitarian world, ‘meaning’ supplants Capitalist ER’s ‘wealth’.

Which then just leaves the question of xxx. Competition is to wealth as xxx is to meaning. Answer? Xxx is truth. Or, more accurately, the ‘true and correct’ second Quadrant of this 2×2…

…One we’ve been using quite  bit these past few months. Maybe now we’re beginning to understand why?

Now we live in a world of constant coronavirus testing, the question of how to make a step-change improvement in testing rates arises.

Back in November, a group of Israeli scientists announced their method for revolutionising testing protocols in a hospital lab, with a change they say can instantly quadruple the capacity of almost any coronavirus screening facility in the world.

Systems immunologist, Professor Tomer Hertz announced that the lab at Soroka Medical Center in Beersheba would be shifting immediately to the new strategy.

From a TRIZ perspective the test-rate problem represents a simple to describe contradiction. Namely that we want to improve speed, and the number of tests required to be analysed prevents us. Here’s what the Contradiction Matrix has to say about the problem:

And the Soroka Medical Center solution? The change isn’t powered by a medical or technological innovation, but rather by some cleverly applied mathematics. Labs will use only their regular computers and widely available machines to implement the solution. Which, in classic ‘blinding flash of the retrospective obvious’ involves testing in batches. The normal impediment to such ‘pooling’ solutions is that they are logistically clunky and require a two-stage process. The minority of labs that currently “pool” samples combine the RNA from several people and test it as if it were a single sample. Then, if a positive result is detected in the batch, each individual sample is retested to see who generated the positive result.

The new method eliminates this two-stage approach, telling lab workers exactly who is positive from the initial “pooled” test.  

It is the brainchild of Open University computational biologist Noam Shental. Or rather, in a sense, his mother. In March she reminded him during a family lunch that a decade ago he had developed a pooled method to test sorghum, a flowering plant from the grass family, for a genetic disorder, and urged him to repurpose the research for coronavirus in humans.

Shental started thinking through the maths on the drive home, and quickly got Hertz and another Ben-Gurion professor, Angel Porgador, on board to do exactly as his mother had said.

The basis of their method is that a range of “pools” is prepared in a lab at once, and RNA from each sample is added to several of them, often around nine. “What happens then is that we ‘read’ the pools,” said Hertz. “This means that we look at the pattern of which pools showed positive results, using a modified version of the sorghum calculation, which tells us exactly who is positive.”

“Unlike in regular pooled testing, there’s no need for us to reexamine samples from pools that tested positive in order to pinpoint exactly who is positive. We already know.”

From a contradiction-solving perspective, the solution offers up an elegant illustration of Inventive Principles 5 (Merging) and 10 (Preliminary Action).

From a more general perspective, the Covid-sorghum connection offers an iconic example of the more general TRIZ philosophy of ‘someone, somewhere already solved your problem’, albeit the ‘someone’ in this case was the same person. Just ten years earlier.

Thirdly, and perhaps most important of all, the case offers up a timely example of the emerging Covid-sparked Crisis Period innovation paradigm. First, Covid-19 triggered the arrival of a host of expedient testing solutions, and now we see the frustrations associated with those initial solutions provoking the true innovation.

Amid all the SI talk of wobbling societal dominoes, it feels like another one might just have wobbled too far this week. All thanks to millions of amateur traders working together to take on some of Wall Street’s most sophisticated investors — and, for the moment at least, winning. Propelled by a mix of greed and boredom, gleefully determined to teach Wall Street a lesson, and turbocharged by an endless flow of get-rich-quick hype and ideas delivered via social media, these investors have piled into trades around several companies, pushing their stock prices to stratospheric levels.

Some of the names are from an earlier business era. BlackBerry’s shares are up nearly 280 percent this year. Stock in AMC, the movie theater chain, has surged nearly 840 percent. But the trade that captures the David-versus-Goliath nature of the moment involves GameStop, the troubled video game retailer that was once a fixture in suburban malls.

On Wall Street, individual investors are often derided as ‘dumb money’, destined to lose against the highly compensated analysts and traders who buy and sell stocks for a living. But in recent days, individual investors — many of them followers of a popular, juvenile, foul-mouthed Reddit page called Wall Street Bets — have upended that narrative by banding together to put the squeeze on at least two hedge funds that had bet GameStop’s shares would fall. At the time of writing, GameStop’s share price is already up 1700% and, thanks to the fact that the game has created a ‘virtuous cycle’, looks set to continue rising high enough to send the two hedge-funds to the wall.

I’ve never been a great fan of the stock market, but very definitely at the evil end of the morality spectrum, it seemed to me, were those organisations that sought to earn their way in life by betting on the poor fortunes of others. Worse yet, organisations whose actions wittingly served to accelerate the poor fortune of others.

And so it feels more than fair that when a domino falls it falls squarely on those responsible for the shorting-evil.

Looked at from a contradiction solving perspective, a desire to destroy these short-focused funds has traditionally been prevented by the fact that Wall Street looks after its own. From a Business Matrix perspective, this situation can be generalised as a Support Risk versus Support Capability conflict. The four most frequent ways to resolve such conflicts are currently:

  Principle 13, The Other Way Around

  Principle 10, Preliminary Action

  Principle 4, Asymmetry

  Principle 35, Parameter Change

All of which point quite astutely to the still unfolding GameStop situation. A handful of Financial Elites outdone by (Principle 4) millions of ‘dumb’ (Principle 13) investors, who got together online (Principle 35) and worked out a (Principle 10) work-together plan.

Extrapolating just a little, the 99% seem to have unlocked a peaceful and potent way to disrupt the invulnerable ‘1%’. Social Media might already be responsible for destroying democracy. Now, if the momentum is allowed to continue building it might just be on its way to doing the same for capitalism. Or, at the very least, establishing a ‘virtuous cycle’ that will see the end of the shorters.

How will it all end? Probably badly. The bigger the balloon, the louder the pop. And, thanks to being bailed out in the GFC, and being artificially pumped up by Quantitative Easing fake money ever since, the Wall Street balloon has become the biggest in mankind’s history.

#EatTheRich.

Just when you thought it wasn’t possible for the UK Government’s Covid-19 strategy to get any worse, you wake up to find they’re considering giving £500 to anyone that tests positive. And it’s not even April Fool’s Day.

Then you think, well, maybe this time there is a cunning plan. Just because something is counter-intuitive, doesn’t necessarily mean it is dumb.

Then you think, okay, let’s draw a Perception Map to see what it has to say on the matter.

Here’s what it looks like:

Then you look at it. And see, yup, the idea is really dumb. Some counter-intuitive ideas turn out to be brilliant. Just not this one.

Still, out of stupidity comes opportunity. Anyone thinking of setting up an app to facilitate trading of positive-tests, I’m ready and willing to invest.

For those poor unfortunate people that have never heard fo TRIZ, one of the few problem solving lessons come via the German psychologist Karl Duncker, who posed his now famous ‘radiation problem’. In the problem, a doctor has a patient with a malignant tumour. The patient cannot be operated upon, but the doctor can use a particular type of ray to destroy the tumour. However, the ray will also destroy healthy tissue. At a lower intensity the rays would not damage the healthy tissue but would also not destroy the tumour.

When asked what they would do to destroy the tumour, only about 10% of people manage to generate a meaningful solution to this problem.

This percentage rises to about 30% after subjects are exposed to a second, analogous problem. Here’s the usual one:

“A small country was ruled from a strong fortress by a dictator. The fortress was situated in the middle of the country, surrounded by farms and villages. Many roads led to the fortress through the countryside. A rebel General vowed to capture the fortress. The General knew that an attack by his entire army would capture the fortress. He gathered his army at the head of one of the roads, ready to launch a full-scale direct attack. However, the general then learned that the dictator had planted a ring of mines on each of the roads. The mines were set so that any large group of enemy troops would set them off. It therefore seemed impossible to capture the fortress. However, the general devised a simple plan. He divided his army into small groups and dispatched each group to the head of a different road. When all was ready he gave the signal and each group marched down a different road. Each group continued down its road to the fortress so that the entire army arrived together at the fortress at the same time. In this way, the General captured the fortress and overthrew the dictator.”

The 30% of people that successfully recognised this dictator problem was analogous to the tumour problem, were then able to translate the General’s strategy and apply it to solve the tumour doctor’s problem:

From a TRIZ perspective, the General’s strategy was basically to use Inventive Principle 1, Segmentation.

That’s the easy bit of the problem-solving story.

In Duncker’s context, he had to do the hard work of finding the tumour/fortress analogy (and even here, some might argue it is quite contrived). Perhaps the real power of TRIZ is it makes it much easier to find analogies so that the problem solver themselves can work through a problem without clues from a friendly analogy-supplying psychologist.

The tumour problem is a classic physical contradiction: a high dose of the rays is required to destroy the tumour and a low dose is required to avoid damage to the surrounding tissue. And, likewise, for the fortress problem, a high number of troops are needed to destroy the dictator and a low number are required to weave past the mines.

Both problems require high and low. Moreover, when we start thinking about how the contradiction might be separated, it quickly becomes clear that Separation in Space is the most viable solution strategy in both cases. Which then means we can jump to a prioritised list of the Inventive Principles that others have previously used to solve the problem:

The advantage we get here, apart for the structured analogy approach, is that, in addition to receiving the Segmentation solution strategy, we also get Principle 17, Another Dimension. Which takes us even closer to the actual solutions. Destroying the tumour by segmenting the ray is part of the solution, but we only get to something that might work when we also realise that the segmented rays need to arrive from different directions.

Talking of contrived, I first encountered Duncker’s radiation problem while reading David Epstein’s otherwise rather excellent book, Range (more about that in the February Issues of the SI ezine). The main thesis of Range is that generalists make better wicked problem solvers. Largely because they’ve seen a broader range of problems and thus have access to a broader range of potential analogies. I suspect he was also picking up on the post-Duncker finding that the 30% of people solving the radiation problem increased to something over 90% when they were given multiple analogies, and therefore wanted to provide an analogy of his own. Which ends up going something like this:

“A small-town Fire-Chief arrives at the scene of a woodshed fire. The woodshed was about 50 yards from a very conveniently placed lake, and true to the cliché, a chain of bucket-passing locals had been formed to transfer water from the lake to the fire. Alas, as each bucket load of water was thrown on the fire, it wasn’t really having any impact.”

So, what did the Fire-Chief do?

Now I don’t know whether Epstein was being very clever here, or whether he merely demonstrated the difficulty of finding analogous situations when you don’t know TRIZ. In his mind, the Fire Chief problem is similar to the tumour and dictator problems. And, true enough it is also a high-and-low contradiction. In that we need a high amount of water to put out the fire, and each bucket-load only contains a small amount. But it is also 180 degrees opposite to the tumour and dictator problems. In that, solution-wise, the bucket-chain has in effect already used Segmentation, but it is not helping.

Rather what’s required – and what the Dire Chief knew to recommend – was to break up the chain, give every person a bucket, send them to the lake to fill it, then all come back and throw their bucket-load onto the fire simultaneously.

i.e. while the fire problem is indeed a high-and-low problem, it’s solvable not just by a Separation in Space strategy, but also by Separation in Time and by Interface. In which case, we learn that Principle 5, Merging is more likely to help:

It’s too late for Karl Duncker, who passed away in 1940, but if anyone knows how to contact David Epstein, I’ll be happy to send him a copy of Business Matrix 3.0. Help him to work out how to build analogies at will. And turn him into a proper specialist generalist.