It might have been coincidence. Or it might not. Yesterday I received my copy of the Nassim Nicholas Taleb foreworded version of Carlo Cipolla’s mini-classic, ‘The Basic Laws Of Human Stupidity’. And yesterday, the UK Parliament decided that the country would have a general election on December 12.

The will-they-won’t-they election decision has been debated for several weeks now. The Conservatives have been nervous because Boris Johnson promised – on his die-in-a-ditch life – that the UK would leave the EU on 31 October and now we know he has failed, there is likely to be a backlash. Picture Nigel Farage rubbing his grubby-hands with glee at the upcoming advertising campaign. On the other side of the house, the Labour party have been trying to put off the election for as long as possible because they’re about 14 points behind in the polls thanks in no small part to the fact that, in Jeremy Corbyn, they have a leader that appears almost totally un-electable by anyone other than a devout Marxist. The Liberals, being the liberal wimps they are, seem relieved that the election decision gave them a get-out-of-jail-free card in terms of failing to stop Brexit from happening. Thanks to the first-past-the-post election system, they will win a few more seats and, better yet, when the dust settles, get to shrug their shoulders and say they did the best a small party could do in the circumstances. The Scottish Nationalist Party, meanwhile, are rubbing their hands with glee at the prospect they will wipe out the Conservative Party in Scotland, and lay the foundations of another independence referendum that, this time around, thanks to Brexit, they will likely win. The SNP will thus, in their minds, do a good thing for Scotland, but in reality will end up making themselves and the rest of the UK worse off. Which, finally, leaves the DUP, who have swiftly sunk back to their pre-2017 level of irrelevance outside the Unionist community of Northern Ireland. The election decision means they no longer have any of the very non-linear power they’ve held since the Conservatives were forced to buy them off after the 2017 election. One day they decide for the nation; the next, no-one gives a damn what they think any more. It’s a tough game, politics.

Plot this sorry mess onto Cipolla’s Map Of Stupidity and the UK political scene currently looks like this:

The Conservatives get to be the win-lose Stupid Bandits; the SNP and DUP get to be intelligent Bandits; Labour look like they’ve just sleep-walked into the Boris Johnson Bandits trap and, thanks to Jeremy Corbyn’s lack of leadership prowess, get to play the plain Stupid role in proceedings. Jo Swinson’s Liberal Party continue in their Helpless role – ‘winning’ a few seats while losing the prize they could’ve had. Which leaves Caroline Lucas and the Green Party as the only vaguely ‘intelligent’ players in the game. They too will likely win more votes and, who knows, even one or two extra parliamentary seats, and might even help build some more Save-the-Planet momentum. But, of course, will largely have no impact on the Brexit state of play at all.

All in all, the omens are not good for a meaningful outcome on December 13. Labour and Conservatives are already playing to their Stupid and Bandit types and are trying to make the election about more than just Brexit. But with Brexit in its current unfinished business state, the election can be about nothing else. And here, then, is the real problem. Anyone that voted Remain in the EU referendum is basically dis-enfranchised right now. The Conservatives want (hard) Brexit. The Brexit Party will push them to go even harder. Labour, in theory, are standing on the idea of a confirmatory referendum, but everyone knows that Corbyn doesn’t believe in the idea, and as a consequence he’s trusted almost as little as Johnson. The Liberals have chickened out. The Greens offer little more than a protest vote. Leaving only the SNP offering a meaningful home for Remain voters. Nice if you live in Scotland, not so good for everyone else. Unless they start fielding candidates in the rest of the UK.

As the last three years have shown, almost any kind of worst-case scenario imaginable proves to be inadequate within short order in Brexit Britain. The half-life of British political Truth is now measurable in hours and minutes. Meaning that predictions of what will happen are little better than a coin toss. Especially, too, in light of the fact that there’s the Facebook-broke-democracy element still to take into account. This election, in other words, takes place in an environment in which every party now understands that Facebook and other social media channels offer a non-legislatable, largely illegal Wild-West in which quite literally anything goes. Lying politicians has always been an oxymoron. Today, thanks to Facebook, they get to customize those lies to target the weak, the vulnerable, and the racist. Except, if I read Cipolla’s Stupidity Map right, I believe a prediction saying things will continue to get worse is very likely to be right. Which, to my mind, means December 13 (a Friday – surprise!) will bring the UK another hung parliament on December 13. This will then be followed by yet another extension begging letter to the EU by the middle of January. This will then prolong the agnoy for several more months until, finally, in utter despair, enough careerist politicians will stick their head above the political parapet and tentatively suggest what has always been the only sensible way through this mess, another referendum. This will then result in a revocation of Article 50, and the UK can safely return to its (comparatively) blissful 2015 state. Only several hundred billion pounds poorer thanks to the five years of combined political Banditry and Stupidity.

Wake me up in 2021.

I guess deep-down I’m still a fan of anthropologist cum marketer Clotaire Rapaille’s work on Culture Codes. The big idea is that popular products can become associated in the minds of consumers with powerful metaphors that, if the product design or advertising shifts to become inconsistent with those metaphors will create a mental mismatch, that in turn will create a decline in sales of that product.

Rapaille opens the book with one of the less credible of his client engagements. Iconic off-road vehicle producer, Jeep, found themselves struggling with sales at a certain point in time, and went to Rapaille and his team to see if they could unravel why. Rapaille interviewed lots of Jeep customers in order to try and establish whether there were any deep cultural metaphors. It turned out there were. In parts of Europe, for example, the Jeep was associated with ‘rescue’. This metaphor appeared towards the end of the Second World War when, if you were a person living in, say, rural Italy, the first time you ever saw a jeep very likely was when an enemy-vanquishing American drove in to town.

In the US, where, because there was no enemy-vanquishing to be done, the culture code word for the Jeep turned out to be ‘horse’. The Jeep, in other words, was being associated with the same off-road goals as would traditionally have been achieved by four-legged friend riding cowboys. And, hey presto, Rapaille was able to announce to the Jeep marketing folks, the reason for your drop in sales is because you’ve just switched from round headlights to square ones. Horses don’t have square eyes and so now the vehicle doesn’t fit the code.

And so, Jeep apparently ordered a switch back to round headlights and sales of the Jeep magically turned in the right direction again.

If nothing else, I have to say I still stand in awe of Clotaire Rapaille’s powers of persuasion if even half of this story is true. ‘Culture Codes’ – if they exist at all (and I tend to think some of them do), can sound about as un-scientific as it is possible to be.

I’ve been increasingly reminded of the whole Jeep-as-Horse story lately thanks to the increasing appearance on my radar of the Jeep Renegade. And in particular the oddly star-shaped tail-lights. Which, turn out to be not nearly as odd as you might think in the context of Rapaille’s culture code…

…either that, or someone in the Jeep design team has finally had their revenge on the Marketing team suckers. Which, if it’s true, might just bring Culture Codes to a whole new level of reality. I have my fingers-crossed. If you’ll excuse the potential pun.

Like 85% of all drivers, I am above average. My finely tuned driving skills (i.e. driving at 36mph in a 30mph zone) meant I had to spend an afternoon at what is notionally known in the UK as Naughty Drivers Club. You get caught speeding and are given a choice: accept three penalty points on your driving licence, or attend a Naughty Drivers Club workshop so you can learn why speeding is a bad thing.

Deep down, I kind of already knew that driving too fast is a bad thing. Even if it is 2am and everyone else is asleep. That said, my expectations for a knowledge-packed telling-off by the Police were not high. I was wrong.

My first learning, when I entered a classroom with twenty-three other Naughty Drivers, was that 16 of us had been caught at precisely the same speed-trap. This suggested to me that rather than being a road-safety device, the speed-trap was in actual fact a money-grabbing scheme by the local council.

My second learning came closer to the end of the session when we were shown a one-minute drivers-eye video of a car being driven through a semi-urban scene and asked to record how many potential dangers we could see.

The clip started.
There was a young mother walking along the side of the road with a toddler.
They were approaching a junction.
Along the side of the road there were rows of bins, put out ready for collection.
There was another junction.
There was a car parked on a double-yellow line on the other side of the road. The road was wide enough for two vehicles, but not three. Two cars were approaching behind the parked car. The driver looked like he was waiting to get out of the car.
A sign said, ‘School ahead, 20mph speed limit when lights are flashing’. The lights were flashing.
Another junction. This time with a car waiting to join the traffic.
A cat sat on a garden wall.
The school. Various parents milling around outside.
More flashing lights.
A lollipop-woman poised to step in to the road.
A man with a dog on a long lead walking towards her.

You get the picture.

When the video finished, the Naughty Drivers Club instructor asked us to total up the number of danger points we had identified.

I let a bit guilty because I lost my concentration towards the end and only found 34.

The woman sat next to me stuck her hand up, ‘twelve,’ she announced.
Everyone else joined in. Lots of sixes. Lots of sevens. A few tens. Another twelve.
Then someone shouted out ‘eighteen’.
Everyone looked at him. The instructor smiled, ‘what do you do for a living, sir?’
‘Coach driver’, the man answered. One of the sixteen of us that had kindly decided to give the local council some free money.

I stayed quiet. For a few seconds I thought I must be going mad.

Then the instructor replayed the video. Only this time he gave us the benefit of his commentary while a colleague kept count. By the end of the video the official count total was thirty-two.

I wasn’t going mad.

Everyone else was. That or they were all walking through life in a trance.

And that’s my point. If professional drivers are missing almost half of the hazards around them, and if the average driver is missing three-quarters, then it shouldn’t be a great surprise that we’re all held up behind an ever-increasing spiral of road accidents. Modern life is turning us into mindless idiots.

Now I’ve got thirty five things to worry about. Thirty six if you count the fact the instructor continued to deny the cat sat on the wall was a hazard.

Aerospace engineers tend to be glass-half-empty kind of people. The same pretty much applies to ex-aerospace engineers like me. Pessimism kind of goes with the job. It’s the way you get to build the world’s safest industry: don’t believe anything anyone tells you; look for evidence; don’t stop until you’ve got enough of it, and seen enough of it with your own eyes to ensure the aeroplane you’re designing won’t fall out of the sky.

Living with this kind of perspective can be a heavy burden. One, it puts you somewhere close to the bottom most people’s list of other people you’d love to have at your next party. Two, in these post-truth times, the ratio of truth-to-crap can very easily become overwhelming. Particularly if you spend any time on social media. Which I increasingly try not to.

Up until recently, however, I did have a certain fondness for a good documentary. Now, alas, even that pleasure has gone. It went sometime during a programme on vaccinations that I caught up on last week. The programme centred around the tragic story of the return of previously eradicated diseases like measles. Measles is back because fewer and fewer parents are getting their kids vaccinated. In theory, it was a slam-dunk kind of story: a few decades ago, a couple of clinicians with poor knowledge of how to design an experiment and a large egomniac-clinician-sized chip on their shoulder published ‘research’ showing that vaccines are dangerous. They’re listened to for a while. Then they are discredited. End of story.

Except, in their desire for ‘balance’ the documentary makers – who also, evidently had no understanding of experiment design either – brought together a collection of interviewees, who for the most part also didn’t understand experiment design, and collectively then stitched together a narrative that failed to make the nonsense clear. I’m guessing, largely because there is no simple way to tell the story. And, above all else, it seems, the public wants and expects to here simple stories.

While I don’t doubt the nonsense of the discredited clinicians, the disappearance of my faith in documentary makers during the programme arrived with the thought that the documentary makers had absolutely no desire whatsoever to uncover and reveal the truth. Rather they were intent on making hour-long clickbait.

And, what they’ve learned from social media is that the best way to do that is to create content that evokes strong emotions. Preferably negative ones. People are, to my reckoning, around seven times more likely to respond to anger-inducing nonsense than they are fluffy-kitten, isn’t-it-loverly kind of nonsense.

Beating a 7:1 tide of crap is hard work. In the words of the aphorism, A lie can travel halfway around the world before the truth can get its boots on. Except, thanks to social media and the amazing self-learning algorithms present on Facebook, Twitter and the like, the lie has now done seven laps of the equator before the truth has even thought about boots.

All that said, as well as being a natural pessimist, I’m also a great optimist when it comes to believing that any problem is solvable. That’s what TRIZ did for me.

The post-truth problem is eminently solvable.

In theory.

In practice, when I combine my glass-half-full and glass-half-empty perspectives, its very easy to turn a solvable problem into an unsolvable one by introducing one too many constraints.

In theory, the post-truth problem can be solved, in the short term at least, by:
1) Acknowledging that human evolution has not yet reached sufficient maturity to deal with social media, we switch the whole shebang off.
2) Locking Mark Zuckerberg up in solitary confinement with a collection of Dunbar Number research and not letting him out until he understands there is no such thing as ‘connecting everyone’. Meanwhile all of his ill-gotten gains are re-distributed to each of the countries who’s elections, referenda and government surveys have been corrupted by his democracy-breaking algorithms. To pay for the re-running of those elections, referenda and surveys in a legal fashion.
3) Getting the mainstream media to re-recognise the idea that ‘balance’ is not about giving an equal voice to the different sides of an argument when one side is plainly and provably lying (“If someone says it’s raining, and another person says it’s dry, it’s not your job to quote them both. Your job is to look out the fucking window and find out which is true.”). To help journalists determine truth, we use software to assist in the identification of liars, deluded people and troublemakers.
4) We revoke the media ability to do voxpop interviews. Interviewing idiots in Stoke, while admittedly sometimes funny, is in reality nothing more than clickbait. Dangerous clickbait.

Of course, in practice, none of this will happen. Except in China. Which is a whole other story. One that currently rests on the general mis-understanding that politics is a two-dimensional left-right spectrum rather than a contradiction needing to be solved.

Meanwhile, on a personal level, while I’m often tempted to adopt the increasingly widespread strategy of blocking idiots from Stoke (other cities are available), I also know that this strategy also doesn’t work. Two-dimensional thinking again. Thinking that serves merely to increase the separation between the myriad us-bubbles and them-bubbles. What I need to do instead is to at least manage the contradiction. Which, as of now means remembering the importance of a two-second pause between reading clickbait and responding to it in order to realise there’s no point responding to it. Then all I need to do is keep in mind that 98% of what I’m exposed to these days is clickbait.

Which means lots more pauses than I’m used to. Who knows, if I’m somehow able to pool together some of those pauses I might re-gain a more sedate, relaxed, time-to-think lifestyle. And an end to blood-pressure medication.

It might be argued that the whole of the Brexit debacle started and ended with the subject of immigration. There are too many people in the country, we heard, too many still arriving, we heard, and we therefore need to ‘take back control of our borders’. So went the cries from Brexiteers.

Politics aside, what concerns me here is what does the data say? If anyone is going to make a decision on the subject, it is a fairly safe to say that having meaningful data would be a fairly important first step. We established PanSensic as way to help enterprises to measure what matters rather than what was merely convenient. As much as anything it has now become a way of innovating in the measurement domain: working out what we really need to know, and then working out how to measure it.

This is pretty much the opposite of the philosophy adopted by others in the measurement business. Some of them seem to have veered so far towards the ‘what’s easiest’ end of the spectrum it’s a wonder they can still see any kind of useful purpose in what they end up delivering. One such organisation here in the UK is the Office Of National Statistics. These are the people tasked by the Government with providing the information upon which policies like Immigration are determined. Being in effect a government agency (they were made ‘independent’ a decade ago), they have their own special version of ‘what’s easiest’ and that is, ‘whatever way we’ve always used’. Change, in other words, does not make up a significant part of the DNA of the people that work there. I know this from having had the occasional opportunity to work with their Senior Leadership Team.

‘Whatever way we’ve always used’ usually turns out to either employing an army of people to conduct telephone surveys (this is how a lot of VAT collection calculations are made, for example) or people with clipboards meeting members of the public face to face. This is the strategy used, it was revealed last week, to gather the country’s immigration data. One of the main characteristics of either of these methods is they are very expensive. Another is that, because people are generally speaking sick to death of being cold called or accosted by people with clipboards in the street, they tend to, ahem, not tell the truth, the whole truth and nothing but the truth. (See an earlier blog on our ‘5G’ model.) So, what we end up with is a method that is simultaneously the most expensive and the most shit. Excellent.

Not only are the UK’s immigration figures based on measurements taken by clip-board carrying ONS personnel, it also now transpires that they make the measurements at precisely two airports and zero other entry points on our borders. The two airports are Heathrow and Gatwick. And then somehow – by mathematical chi-squared unicorn-dust – they are able to extrapolate from these two clipboards-worth of data to produce national figures. To six significant figures. More excellent.

If you were setting out to make the least accurate, least meaningful way of calculating immigration, I suspect you would be hard pushed to do it. Unless you were taking Class-A hallucinogenic drugs. Which to my mind I’m not totally sure can be precluded from the discussion in this instance.

Having had this survey method ‘revealed’ last week, the UK Government has been forced to respond by downgrading the quality of the results produced to ‘experimental’. Class-A drugs might also have been involved here too in so far as the committee that opted for that word don’t appear to have had much more of a clue what they were doing than the clipboard bearers.

Experimental implies that, at the very least, you sat down and thought about the problem and then designed something. Key words: ‘thought’ and ‘designed’. For a start, thinking about the 28 airports and 11 ports that receive international passengers, and the destinations that people are able to travel from, and then thinking about the questions you might ask people to elicit a true and meaningful answer rather than the one they think you would like to hear.

But then, I think, pretty soon you’d conclude that, hmm, this all sounds like a lot of hard work. So then you start to wonder whether there might be other ways to work out how many people are living in or leaving the country. Something far easier. Things you’re already measuring, maybe. On Social Media, for example, or mobile phone signals. All the time knowing that you don’t need to calculate absolute numbers (the census will do that for you), merely relative ones. When I sat down and spent half an hour thinking about it, I concluded I could – with only the public domain data available to a shlub like me – design, build and commission a more accurate system than the current ONS effort in about three weeks. Step One: sack all Oxbridge-educated ONS statisticians (about 90% of the total my BS-detector suspects); Step Two: teach the rest Complex Systems 101 and Human First Principles 101; Step Three: sack them too. Step Four: Phone Google.

I’m not sure whether the blind-people feeling different parts of an elephant metaphor has reached Peak Cliché yet, but it still seems appropriate when I think about some of the smart people buzzing around the periphery of the innovation world.

In their desperation to not-use TRIZ or Systematic Innovation, these smart people periodically grasp at concepts they think will explain how innovation works. We saw it vividly with biomimetics. And then uber-fad, Design-Thinking. And now I find myself hearing the word ‘exaptation’ being used as the next innovation Holy Grail. Alas, like biomimetics, it turns out to be yet another tiny part of a much bigger picture. Albeit one that is easier to understand than TRIZ… which, of course, is a big part of its attraction. To gain a meaningful appreciation of TRIZ requires time and hard work. Far easier to gather half a dozen examples of engineers designing solutions inspired by biology. Or, from the exaptation perspective, to collect half a dozen examples (most of them biological anyway as it happens) of solutions that initially performed one function that were exapted to perform another. I’ve heard the bloody bird-feather exaptation story so many times now, I come out in a rash every time I hear the latest exaptation advocate prattling on about it.

People like easy, of course. On the other hand, systematically ploughing through ten million innovation case studies is definitely hard work. Had this research showed that biomimetics or exapatation were dominant innovation mechanisms, we might well have closed the research down a decade ago. The natural world ‘innovates’ at a glacial pace. And ‘exaptation’ doesn’t happen much faster. To calibrate us on how infrequent these mechanisms are, we might note that when Genrich Altshuller started the TRIZ research and spent a decade reverse-engineering important patents to generate the 40 Inventive Principles, exaptation was not one of them. It was our work in the early noughties in fact that we tentatively started talking about ‘Change Function’ as a recognisable strategy with any kind of statistical significance. If something takes over fifty years to spot, the researchers are either suffering from massive Confirmation Bias, or the something is pretty darn rare.

So, let’s try and set the record straight in terms of which is which. Just how big a part of the innovation story is exaptation? To help with the task, let’s bring in to play the work of
Pierpaolo Andriani and Giuseppe Carignani ( in particular, their paper, ‘Modular exaptation: A missing link in the synthesis of artificial form’), two of the current exaptation preachers. They built their thinking around a 2×2 Matrix that looked at whether an artefact did or didn’t undergo a change of function, and then whether the ‘module’ into which that artefact was contained went through its own did or didn’t change of function:

If neither artefact nor module function are changed, Andriani and Carignani use the rather disingenuous term ‘adaptive innovation’. In TRIZ terms, this type of innovation is what we call ‘contradiction solving’. Next up, what they describe as ‘internal exaptation’, is in actual fact what TRIZ calls ‘Function Transfer’. These are situations where an artefact that delivers a useful function (‘cyclone separates solid’) is installed in a domestic vacuum cleaner rather than an industrial sawmill. In so many words, this is the Dyson innovation strategy. Any connection to ‘exaptation’ here is tenuous to say the least.

More like the dictionary definition of exaptation is Andriani and Carignani’s term ‘external exaptation’. These are situation where the function of the ‘artefact’ does get changed. 3M’s Post-It Notes, Viagra, and Coal Tar offer up classic examples of this kind of Change Function innovation: Viagra was an ineffective cure for angina that turned out to be much more effective as a means of creating, ahem, male tumescence; Post-Its were the perfect solution for ‘rubbish glue’, etc.

Finally, comes ‘radical exaptation’. This is the situation where both the artefact and the ‘module’ change function. This is a much more difficult one to spot. Which means that nearly everyone ends up talking about microwave ovens, and not a lot else. Radical exaptations might indeed be important innovations when they happen, but, alas, they don’t happen very often at all.

To calibrate us on just how infrequently this type of innovation happens, bearing in mind our usual definition of innovation as ‘successful step-change’ (i.e. the 2% of innovation attempts that were successful versus the 98% that failed), here’s how the four different types of innovation add up:

Which means, based on our ten million case studies, ‘exaptation’ accounts for slightly less than 1% of the story. Which, I think, is a way to say to the exaptation-advocates, ‘please shut up’. At least until you’re prepared to do the hard-yards to appreciate what innovation actually is: solving contradictions.

I’m having a quiet week. In theory spending my time doing physical labour in the garden, but in practice looking for excuses not to. Enter an academic Twitter troll. Perfect.

The resulting correspondence is too boring to repeat here, but, needless to say, it was prompted by me prodding at academics doing pointless research.

The UK is still somewhat reeling from the pre-Brexit Referendum that people have had enough of experts. Which means this is a particularly testing time to be an expert. The answer to the contradiction – ‘we want experts and we don’t want experts’ – include, a) a recognition that not listening to experts anymore is not to be equated to a demand for blind ignorance (as we are seeing three years into the still-not-over Brexit debacle), and b) that our definition of experts needs to be updated.

The large majority of so-called experts, and nearly all experts of the academic persuasion, are specialists. They have lots of vertical knowledge, and, too often, not enough horizontal, inter-disciplinary knowledge. In a world as complex as the one we now all inhabit, this lack of horizontal knowledge becomes a bigger and bigger problem. In complex systems, its not so much the ‘things’ that are important as the relationships ‘between’ the things.

What we know from the last twenty years of our innovation research is that 98% of innovation attempts fail. Ten million case-studies into the subject, we now know some of the core characteristics of the 2% that were successful that were not present in the 98% of prospective innovators that failed.

The 2%:
– Had a clear (Ideal Final Result oriented) direction
– Understood the importance of revealing causal (as opposed to merely correlated) relationships
– Understood the importance of revealing and resolving conflicts and contradictions to eliminate trade-offs
– Understood the characteristics of complex adaptive systems
– Understood the often considerable gap between what customers say they want and what they subsequently spent their money on

‘Research’ may be seen to have a variety of different purposes, but in almost all cases, the work being undertaken is a precursor to some form of innovation. We research to enable innovation.
If we accept that to be the case, then the above five Innovation ‘DNA’ strands also extend to the world of research.

A big part of our ongoing Systematic Innovation research involves trawling the various worlds of human endeavour. Our biggest source of data still comes from the global patent databases. The second biggest is the academic literature.

Taking on the job of sifting through all of this apparent ‘knowledge’ with the limited resources available to us very swiftly forced us to develop heuristics that allowed us to find what we now know to be the relatively rare needles in the global knowledge haystack. It was the imperative to solve that contradiction that enabled us to reveal the innovation DNA. Now we know it, it enables us to eliminate about 85% of the patents that are granted (97% will never make any money, but a somewhat bigger percentage have some contriadiction-solving merit worthy of sharing with others). As far as academia is concerned, it allows us to eliminate around about 98% of all of the academic literature.

On one hand the lack of relevance of the vast majority of academic output makes our job rather easy. On the other, from a value-for-money perspective it is, I think, a fairly damning indictment of the current academic system. Academia used to be the place to go if a person wanted to work at the frontiers of mankind’s understanding of the world. But once the world started evolving faster than academics and their desire to do everything in PhD-size three-year chunks, then a problem began to arise. The problem was especially great if you were a person tasked with innovating. And so, as is always the case, necessity is the mother of invention. When those tasked with innovating got no joy from academia, they went off and did things themselves. And it turns out that enough of the armies of trial-and-error amateurs, flaneurs, sceptics, and frustrated, pig-headed ornery souls succeed to now make a literal and practical mockery of the academic world.

What I failed to get through to my temporary academic-troll was that this doesn’t mean that doing research is a waste of time or money. There have been enough of the flaneurs now to reveal the innovation DNA. Now we know it, it ought to be incumbent on any ‘expert’ working in the research and innovation domains to make use of it. Which means designing research using the DNA. Or designing research that challenges that DNA and seeks to deepen our collective first-principle understanding of the world.

It does not mean wasting precous resources doing research that doesn’t have a meaningful direction, doesn’t actively seek causal relationships, doesn’t look for or resolve contradictions, fails to embrace the complexities of the world, or fails to recognise that customers (and that includes academics) do things for two reasons – a good one and a real one. Academics, for the most part, it seems, understand the ‘good’ part, but are still for the most part it seems utterly clueless on the ‘real’ bit.

For the last twelve months I’ve picked up a new hobby: thinking about some of the ‘big’ problems that none of our clients ever ask us to work on. High on my list has been to try and understand why most bee populations are in decline.

It didn’t take long for the investigation to reach ‘The Feminization of Nature’ a book published in 1997 and focusing primarily on the feminization of humankind. Over the course of the last 60 years, the book reports on massive drops in male fertility and corresponding massive increases in breast, testicular and prostate cancers. Its one of those doomsday books that, for some reason, the public at large has chosen to bury.

A big clue to the potential reason why this might be the case comes in the last chapter, which focuses on how ‘industry’ was doing its best to challenge and invalidate the evidence. Specifically, the chemical industry. And even more specifically that part of the industry making chemicals with ‘endocrine disrupting’ or oestrogenic properties (mainly pesticides, but also several plastics).

Taken at face value this chapter represents an iconic example of ‘It Is Difficult to Get a Man to Understand Something When His Salary Depends Upon His Not Understanding It’ operating at a whole-industry level.

What this has meant in the case of the feminization of nature is that every piece of experimental evidence obtained by those outside the industry gets countered by those operating within the industry. The easiest way to counter such experiments is to say that they don’t ‘prove’ anything. Closely followed by setting up a different experiment to demonstrate the opposite result.

And herein lies the real problem. If the problem being tackled is a complex one – as is the case with the feminization of nature – there will never be such a thing as ‘proof’.

The more complex the problem, the further from provability things get. One of the biggest drivers of complexity in this regard are the time-lags between cause and effect. Some of the causal loops in The Feminization Of Nature are measurable in decades: a woman ingests traces of a particular oestrogenic chemical during pregnancy, and her offspring develop testicular cancer when they hit puberty. Or how about the causal link between another mild oestrogenic chemical and breast cancer that affects Caucasian and black women, but only affects Japanese women after their families have lived in the West for two generations. If the consequence doesn’t get manifest for forty years, then we really ought to be teaching scientists a different set of tools and methods to the ones they’re taught today.

Unfortunately (‘for the world’ in this case), the vast majority of scientists and, as far as I can see, every regulator on the planet doesn’t understand complex systems and can’t, therefore, begin to fathom how to design solutions that are safe in complex environments. This allows whole industries to – quite literally in the case of oestrogenic chemicals – get away with murder.

Without wishing to sound melodramatic, not doing anything about the fall of bee populations (or the decline in human fertility, or climate change) until we have ‘proof’ is the same as signing their (and our) collective death warrant.

In the twenty-two years since the publication of The Feminization of Nature, my investigation went on to find, it seems like almost nothing has happened. Lots more experiments, and lots more counter-argument, but essentially all a way to look busy while all the time the problem continues to get worse. Quite literally fiddling while Rome burns. Scientists trying to tackle a complex problem looking for something that doesn’t exist using tools and methods that are wholly inappropriate.

We can never ‘prove’ that oestrogenic chemicals are causing the decline in bee populations in the same way that we can never prove that smoking causes lung cancer.

What is required instead is a way of thinking that acknowledges the complexity, stops looking for ‘root causes’ (there aren’t any in a complex system), stops looking for ‘proof’ (ditto) and instead starts mapping the ‘conspiracy of causes’ and ‘systems’ from which the unfortunate symptoms emerge.

That’s what ultimately happened to the tobacco industry, despite their decades of kicking and screaming protest. There are myriad factors that causally-connect to produce lung cancer, and we know one of them is the smoking of tobacco. Having established that, it is incumbent upon legislators and producers to work to reduce the smoking of tobacco. And to keep doing so for as long as the causal link continues to exist.

Likewise, there are a myriad causally-connected factors that collectively conspire to affect bee populations and human fertility and hedgehogs too, as it happens. In all three cases, one of those causally-connected factors is the release of oestrogenic chemicals into the environment. And because that is so, it ought to be incumbent upon those operating in the domain to a) start building better and progressively more refined conspiracy-of-causes systems maps in order to begin to understand the impact of whatever changes they are thinking of trying, and, b) most importantly of all, work diligently to reduce the release of oestrogenic chemicals into the environment, and to keep doing so for as long as the causal links continue to exist.

I spent most of Saturday afternoon at the Design Museum in London. Three-quarters of the visit was awe-inspiring and quite brilliant. The other quarter was depressing. The three-quarters part was the Stanley Kubrick exhibition, which I would heartily recommend anyone takes a few hours to go visit should it visit a town near you. Or even not near you.

The other quarter was everything else in the Design Museum. Before Saturday, I thought the best way to make myself angry was to spend time at academic conferences. Now I know it is visiting the Design Museum. In fairness to other design museums, specifically, the London version. The one in Copenhagen, by contrast, I thought was full of ideas. Well, I suppose the London version was full of ideas too. But whereas I left the Copenhagen museum with a notebook full of good ideas, my notes from London were pretty much all about how idiotic most ‘designers’ are.

I’m guessing a big part of the problem is curation. The curators at Copenhagen seemed to have a very clear grasp about what design is. After my visit there, I drew this:

Everything I saw in London was built on the assumption that the feel/function relationship is some kind of an ongoing either/or debate. Here’s a room full of random stuff that was very functional. And over here is another room, this time full of random stuff that looks pretty. The end result being that it all looked like a collection of random stuff that only by accident ever achieved ‘both’.

The confusion extended, too, to the design of the Museum itself. I’m guessing that whoever got the commission for the building and its fixtures and fittings was setting themselves up for a fall no matter how good a job they did. Designers can be spitefully cruel critics. I can empathise with that. I’d have to say that the aesthetic end of the either/or spectrum would probably be happiest as they walked around the London Design Museum. How that bias was allowed to continue into the rest-rooms, however is beyond me. Yes, they look pretty, but if there’s one place functionality is important, it’s a rest-room. Having to put up signs informing users how to wash their hands is a good indication the sink design is functionally rubbish.

The crowning example of how the London museum curators don’t understand ‘design’, however, hits you the moment you enter the building. You see this monstrosity:

It’s tangible aim, I guess, is to get people to donate money to the museum in a way that is – in theory – informative, and – bit more of a stretch – encourages some kind of thought process to take place. Is design ‘ideas made real’? Or ‘putting the future first’? Or ‘fearless progress’? Or… well, you get the idea. The key one being the implied word ‘or’. The moment we force people into either/or decisions we’ve just asked them to answer the wrong question. All we’re going to learn when we ask these questions is how to optimize the annoying compromises we’re about to ask our customers to make. And that, as Stanley Kubrick will tell you, has nothing to do with design at all…

Parts of the UK had their hottest July temperature ever this week. One or two spots had their hottest day ever. By about 0.2 degC. You could spot the hottest places by the train system chaos the extra 0.2degC created.

In recent years, the ill-starred British commuter has had to put up with a number of things. First we had the wrong kind of snow. Then we had leaves on the line. Now we’ve got sagging overhead power lines and buckling track.

Metal things expand when they gets hot. I get that. I learned about it in my first-year engineering degree. No, scratch that, I first learned about it in Physics class when I was about 11. What I learned in the first-year of my degree was how to design structures that were able to handle changing temperatures.

What I was taught was this. One, establish how big the range of temperatures might be. Two, add some safety margin. Three, work out the mean and median temperatures and use these as your ‘design point’. Four, once you’ve created the basic ‘average’ condition state, build in appropriate tolerances and make sure that the system still operates safely at the edge of these tolerances. And, if it can’t, put in place measures that prevent people operating the system outside the safe limits.

So, on one level, you’ve got to have some sympathy with the railway engineers in the UK. Some. Not much, but some. Climate change is meaning that highs are getting higher and lows are getting lower. The only thing we might fault them on here is their over-eagerness in Step Two above to minimise safety margins. No doubt because, the engineering college notes will tell you that more safety margin means adding more material, and that in turn means the system gets more expensive. I get that too.

The real problem here are the academics that taught those engineering design courses. People who, for the most part, don’t understand Ashby’s Law. Only variety can absorb variety. Which, in terms of designing rail track and overhead power cables means that if there is variation in the environment in which the design has to operate, there needs to be an equivalent amount of variability in the design to be able to cope with it. Taking a stance that says the designer should design for a so-called ‘optimum’ middle-ground design point, and then prevent the system from working outside the range of environmental variation, does not obey Ashby’s Law. What it does is mean that millions of commuters have a miserable journey home on very hot days.

The deeper problem here, however, is that not only do the academics not understand Ashby’s Law, they also have a virulent allergic reaction to TRIZ. Probably because they never learned about it in the first-year college notes they took when they were being taught engineering design. I can’t blame them for that. But I can – and do – blame them for not being willing to listen now that the world does know about it.

What TRIZ tells us is that variety in operating conditions very likely creates a contradiction: we want the overhead power lines to be the right length when the weather is hot, and we also want it to be the right length when the weather is cold. Or, better yet, if we think in terms of something else TRIZ tells us – ‘the customer wants the function‘ – we want power to be successfully transferred from the grid to the train when the weather is hot and cold.

Once we’ve found the contradiction, guaranteed someone, somewhere has already solved it. There are dozens of smart ways to solve the contradiction. Ditto when we then hit the next inevitable contradiction (probably cost-related). The real problem here is no-one has been looking for contradictions. And no-one has been looking for them, because no-one taught them they were a valid thing to go look for.

Which in turn means society has a complex problem to solve. Which then means that there is no ‘root-cause’ (another academic failing!). Which means we need to go look for ‘conspiracies of causes. Which, finally, with tongue slightly in cheek, tells us the vicious cycle that needs to be broken in order to create a railway system that works whatever the weather pretty much comes down to this…