This is a very short book. You’re either going to read it because you like Lee Child’s writing or are curious what the author of the most successful contemporary series of books about an archetypal hero has to say on this subject. If you know someone who likes Lee Child, this may be the perfect gift.
I like Lee Child’s writing a lot. He delivers great Jack Reacher books on schedule once a year and more often than not they are brilliant, and always they are exactly what you want and expect from these stories. I am not damning with faint praise here – he is a superb writer. I heard – or read – him say once that he took a great deal of care over his sentences, and was always delighted by ones he liked, but that success was writing that didn’t draw attention to itself.
I mention this because this book is a lovely example of his writing outside of the Reacher series. It’s an essay on the origins of fiction and of the idea of the hero. Both the prose and the structure are a joy to read – just like Child’s fiction they pull you in, carefully, steadily and keep you transfixed. Friends have told me they read Reacher books faster than any other and the reason is the writing – it’s hard to take your attention away. It’s almost as if you are afraid you will miss something. That’s good writing.
I read it in one sitting.
The essay takes you on a waltz through history and anthropology and evolutionary psychology without ever showing off or slowing down.
I loved it. You should buy it and read it too.
TL;DR: “dynamic, self-adjusting system cannot be governed by a static, unbending policy” is academic for “everybody has a plan until they get punched in the face”.
Mike Tyson said, “Everybody has plans until they get hit.” In the odd process that popular quotations go through, it is often misquoted as “Everybody has a plan until they get punched in the face.”
Tyson also said: “When you see me smash somebody’s skull, you enjoy it.” And: “This country wasn’t built on moral fiber. This country was built on rape, slavery, murder, degradation and affiliation with crime.” Unsurprisingly, neither of those one-liners has made it to as many inspirational slides in keynote presentations and self-help seminars as the one about plans going awry.
Donella Meadows was an environmental scientist, who contributed a lot to the developing field of systems thinking, especially in her books Systems Thinking: A Primer and The Limits to Growth, the latter being an ur-text in the environmental movement. The quote below is of the principles Meadows proposes in her article “Dancing with Systems”, in Whole Earth (published in 2001, the year she died).
I couldn’t find any accounts of Mike Tyson, world champion boxer and quotable killer, meeting Donella Meadows, but they were thinking along similar lines.
“You can imagine why a dynamic, self-adjusting system cannot be governed by a static, unbending policy. It’s easier, more effective, and usually much cheaper to design policies that change depending on the state of the system. Especially where there are great uncertainties, the best policies not only contain feedback loops, but meta-feedback loops–loops that alter, correct, and expand loops. These are policies that design learning into the management process.”
– DH Meadows
There’s a lot going on there. I’m going to need to break it down and make some connections.
“…a dynamc, self-adjusting system…”
There are all kinds of systems. Once you understand them – throw in a working knowledge of network theory and ecology to speed you along – you see the whole world as systems, from the weather, the sun, the wildlife around us, to human cities, supply chains and less visible infrastructure. But I’m most interested in human social systems, and that’s what I’m talking about here. Partly because I lead – and what lead means in this context is a slippery concept – a group of humans in a company, and help leaders in other organisations do work in this area too.
All groups of humans are dynamic, self-adjusting systems. We lived in layers and interlocking lattices of human social networks. Someone does something, others respond then even more people feel the second and third order effects of those actions and make decisions and take actions as they perceive a new reality. Even with just a few people the connections and contexts people are working with and that are affecting each other makes the group a complex-adaptive system. Our brains probably evolved to be so big and capable because of the advantage that being able to live in and get things done with these social networks. There’s a perspective that says that high-order intelligence, language, art, culture and the whole shimmering wonder of humanity is a side-effect of our getting better at living in dynamic, self-adjusting systems.
…cannot be governed by a static, unbending policy.”
Planning is not a bad idea, unless you then pretend that what you have planned is the only way that things can play out. That’s the “unbending policy” that Meadows is talking about. A policy is another word for a plan. This is how we’re going to run things people, please read the paper and then do exactly what it says Or as close as you can…
A static policy is one that once the exhausted planners have agreed upon it, they will not change course. It has emerged in the plan as the answer, and fuck you if you don’t like that answer. This kind of plan, or attitude to plans is utterly pointless.
We’ve always known this. The two best quotes about plans are, of course Tyson (see above) and Moltke, the 19th Century military theorist who said “No plan survives first contact with the enemy.”
The reason that we get “static, unbending” planning is that we are simple creatures who like to understand the world through stories, and once we have a good story we will do almost anything not to let go of it.
So there are plans that might as well be cosmic ordering mumbo-jumbo – universe, please grant me this order of things (and accept the burning of this budgeted amount of money as tribute to your might). There are plans that are fantasy – this is how things will be because I will them to be thus.
You can’t bend complexity to your will by pretending it is just complicated and imposing your will upon it via “levers”.
Complicated vs. Complex
A quick aside on this distinction, because it comes up a lot and I don’t think I’ve written one down before, although I’ve discussed the idea of tame and wicked problems (tame = complicated and wicked = complex). A process is complicated if you can, with sufficient analysis, accurately predict or control the outcome. If a process is complex you may be able to predict the outcome, but only after it has taken place. Connect 4 is complicated, chess is complex. Choosing which trains to get from London to Vienna is complicated, driving around the Arc de Triomphe is complex.
It’s a case of learning to see systems. Have a working model of your own organisation’s systems and then how it interacts with other systems. Start building and refining systems views. Don’t think of them as creating accurate maps, but as a way of exercising your ability to visualise systems. When I started reading about systems thinking I think I was hoping for a simple visual language and methodology for mapping systems. They don’t really exist. It’s useful to borrow from electrical systems, flow charts, and systems diagrams of all kinds, but ultimately you need to develop your own way of seeing them and explaining what you see to others.
No one of these systems views is going to show you the world as it is. They will give you other perspectives. Maybe you combine a few and try to triangulate the truth from their reference data. Whatever you do don’t pick a favourite, it means you are making yourself willfully blind to possibilities.
“…the best policies not only contain feedback loops, but meta-feedback loops–loops…”
That annoying acronym KISS (Keep It Simple Stupid) is useful in mass communications but useless when it comes to managing systems.
None of them are pointless exercises, as long as you don’t cling to them too tightly once the enemy has been sighted, once causes generate effects, once actions start to be taken.
The most useful kind of planning is going will do two things:
- Allows the planners to practice decision-making, responding, thinking about how they will measure and decide upon new courses of actions.
- Sees the things that are within their sphere of control and influence, usually the team or company they are working within, as a dynamic system and how that system might change if they need it to.
“…design learning into the management process.”
This is about cadence of feedback loops. Building in reflection to rhythms of decision-making and review. Simple things that need to be repeated to the point where you don’t think about them, where you know that they are going to happen. But it also means that when you are drawing a system, or being so precocious as to design a system, you need to acknowledge the bits in the flows and the loops where the system can improve itself. It’s not just results, data, metrics that flow back in those feedback loops, it’s learning. “Learning is a deliverable”, is a useful catchphrase we sometimes bandy around. When you’re innovating, experimenting or – more importantly, having the humility to realise that the best laid plans are questions, and the best executions may be ones that bring back answers you weren’t expecting. Think of every outward flow in a systems loops diagram as a question and everything that comes back as a provocation, facts and findings that demand nothing less than another, slightly better question.
Systems thinking, more generally
Over the past few years, I’ve been learning about systems thinking and applying some of what I have learned to both what we do at Brilliant Noise and how the company itself works as a system.
So I know that I know a little, but also that I may be standing at “the peak of Mount Stupid” on this field. Must. Tread. Carefully. Treat this post then, dear reader, as notes from a novice rather than an authoritative account on the topic. (An attempt to dress it up as such would make the sermon from Mount Stupid, I suppose.)
On the recommendation of our excellent team coach, David Webster, I read Peter Senge’s The Fifth Discipline Handbook, a brilliant and applicable collection of practices and ideas about systems thinking in the workplace.
I’m now working my way steadily through Systems Thinkers, a collection of articles and essays by people who have contributed to the field since the 50s, when it was known as cybernetics. It is edited and given a useful commentary by Karen Shipp and Magnus Ramage.
I imagine, if you come back here, you’ll hear more on the subject soon.
The different approaches at WPP and Publicis are examined in an FT article today. While both companies have endured falling share prices for the past few years, there are signs that WPP may be beginning to recover. Meanwhile, Publicis is talking a good game, but the markets are impatient for them to deliver better results.
Mr Sadoun [CEO of Publicis] is attempting to survive a revolution with Publicis’ margins — the highest in the sector — intact. It is investing in its own data and technology to help brands “take back control” of their customer relationship, a service it believes clients will prize more highly. Mr Read, meanwhile, is trying to steady a listing ship, paying down debt, selling data assets and trying to bring closer the traditional and digital wings of the WPP empire.
The FT says that digital disruption has hit European advertising groups especially hard because they invested heavily in media agencies. Automation, declining media viewing, and better targeting have made digital ads more attractive and CPG / FMCG clients have “slashed their marketing spend” accordingly.
Publicis is taking a “bold and strong” approach to transforming the company, while WPP is:
managing expectations, tidying up the corporate structure and repairing its balance sheet, in large part by raising $3.1bn from the sale of a majority stake in Kantar, its data and research business. WPP returned to quarterly growth for the first time in a year, albeit with slimmer margins; the 0.7 per cent rate was even a touch ahead of the Big Four’s average.
The future for neither company is certain, however.
“What worries me,” said one gloomy veteran of the industry, “is that both of them may be wrong”.
The are complexities in this sector that may be hidden from the view of market analysts. Agency groups are good tackling tame problems, where the solution is known and just needs expertise and competence to manage the system, but marketing in the age of digital disruption does not have a set of challenges in a steady state. What’s required is rapid experimentation and learning, something that favours in-house marketing organsiations working with partners to speed up planning and execution. Media agencies are being hollowed out with talent migrating to jobs with platforms like Google and Facebook while many media agency jobs are being replaced by algorithms. Meanwhile, clients are deepening their digital capability and their relationships with the big ad platforms.
Marc Pritchard, CMO at P&G, is right when he says that the challenge is to reinvent the whole marketing ecosystem. That doesn’t mean a more technologically adept media agency, it means a re-framing of what the challenge is for marketers and a new system of technology, processes and partners to get brands the results they need.
Scott Galloway kills it with his combination of lo-fi diagrams and deadpan insights. For example, how much it costs each of the three streaming giants to win an Emmy:
Not that he leaves it to the pictures to do all the trash talk:
I believe Amazon’s $6 billion spend on original content is the most expensive hair plugs in history. Put another way, it costs a tech guy who looks like Jeff Bezos $6 billion to take his new girlfriend to the Emmys.
Friday is lie day, it appears.
In an article in The Economist, “Lie Detector“, we learn about Demaskuok, a Lithuanian tool developed to spot fake news, a much larger problem there because of the intensity of its information war with Russia.
The tool spots fake news story candidates for analysis by humans by looking for things that make content more likely to be disinformation, including that it’s posted on a Friday.
Another clue is that disinformation is crafted to be shared. Demaskuok therefore measures “virality”—the number of times readers share or write about an item. The reputations of websites that host an item or provide a link to it provide additional information. The software even considers the timing of a story’s appearance. Fake news is disproportionately posted on Friday evenings when many people, debunkers included, are out for drinks.
Other reasons for posting fake news on a Friday spring to mind. People are tired and their defences are lower at the end a working week. Take a look at gyms on Friday morning vs Monday, or see how many people have a pastry or other treat instead of healthy porridge. In matters of information vigilance perhaps we are, as with diet and exercise, Spartans on Mondays and fatigued guards half asleep at our posts by Friday.
Velocity is another possible reason. As The Economist notes, fighting fake news is a race against time. If fake stories survive unchallenged in the news and social media for long enough they stick in people’s minds and become accepted. Weekends mean fewer people at work who may be able to spot and debunk information that is wrong. They get two days of lower scrutiny in which their story can take hold and start spreading under its own momentum.
Disinformation may be getting easier to identify with techniques and tools like this, but the goals of information war are harder to see. It’s commonly thought that the professional dissemblers are trying to stir up
Moreover, some worry that even Demaskuok’s success may play into Russia’s hands. Rob Procter, professor of social informatics at the University of Warwick, in Britain, offers a sobering thought. The Kremlin’s goal, he suggests, is not so much to convince Westerners that certain falsehoods are the truth. Rather, it wants its adversaries to doubt that anything can be trusted as true. If this is the aim, software that increases the number of news reports which get debunked may, paradoxically, have the opposite effect to that intended
Or maybe that’s just what they want you to think.
For a little while, first thing this morning, the most-read article on the FT this morning wasn’t Brexit*, war or impending catastrophe of any of the current flavours, but a heartwarming story of how a few kind words from a member of cabin crew made someone feel a bit better.
It wasn’t dramatically over the top service. They didn’t perform a miracle. They were just an empathetic and tried to make things a little better. But it won over Pilita Clark:
“In an age of relentless customer service surveys and blather about “customer delight”, that flight attendant was a reminder of how little it takes to turn customer relations disaster into triumph — and how rarely it is done well. I have lost count of the times a bank or phone company person has responded to a plea for help with a computer-assisted wall of chill. Sympathetic, warm and humorous people may not be the easiest to find. But any company that manages to put them at the heart of customer relations will always be one step ahead, especially when that help is most needed 30,000 feet up in the air.”
There’s going to be a flurry high fives and glowing emails of pride over at Qantas HQ this morning.
You might take the wrong moral from this story: treat every customer as if they are an FT columnist because… they might be! The better lesson is to hire, train and support humans to be able to act like nice humans when faced by another sub-set of humans called customers. This can be achieved by letting the first kind of human have enough humanity left intact after undergoing processing and by the corporate machine that they can show it to the customer kind of human.
* This was about 6 a.m. An hour later when I checked, the top story was – once again as it seems it shall ever be – Brexit.
“Madame, all our words from loose using have lost their edge…”— Death in The Afternoon, by Ernest Hemingway
Hemingway, as usual, hit the thing on the head. When words get used too often, their usefulness erodes. Sometimes we call that jargon. Or cliché.
It isn’t just inelegant, then, to talk of “leveraging solutions” and “stakeholder buy-in” and “customer satisfaction” – it’s not good communication full stop.
In The Science of
Researchers recently tested [the] idea that cliched metaphors become ‘worn-out’ by overuse. They scanned people reading sentences that included action-based metaphors (‘they grasped the idea’), some of which were well-worn and others fresh. ‘The more familiar the expression, the less it activated the motor system,’ writes the neuroscientist Professor Benjamin Bergen. ‘In other words, over their careers, metaphorical expressions come to be less and less vivid, less vibrant, at least as measured by how much they drive metaphorical simulations.’– The Science of Storytelling, by Will Storr
So jargon can be excluding, annoying and sometimes dangerous. Loose meanings, loosely used, cause misdirection and misunderstanding. We hide the meaning of things even from ourselves when we start talking like an insider (or what we imagine an insider should sound like).
If you’re going to use images in your language, make sure they vivid and clear and new. If you’re just doing an impression of the last corporate shmuck’s soliloquy you heard, then you’re aiming low and no one is really listening to what you’re saying. (And if you’re reading that nonsense off a PowerPoint slide, you’re virtually guaranteeing that no one knows what you were trying to say – if indeed you were actually trying to say anything of substance in the first place.)
Sure, a lot of this is cultural, habitual, hard to stop doing; but the least you can do is to start to notice when you do it – and make a note to have a word with yourself later.
The idea of “personal brand” seems to be resurgent. Ten years ago, when I wrote Me and My Web Shadow it was a thing – but then seemed to fade from conversation. I avoided using the term; reputation is a much more useful idea to focus on for individuals – it is something you can affect but it is something earned, an outcome, defined by the perceptions of others.
There’s something more controlled and designed about the idea of personal brand; an idea attached to it that you can set out how you will be seen and experienced by others. You can’t.
Reputation = what you do + what others think and say about you.
Perhaps the term personal brand is increasing used because of anxiety about how the internet can spawn mobs that will rip apart the reputation of an individual. An ugly phenomenon – once shocking, now commonplace.
Angela Nagle is an academic who studies the online culture wars. Even studying them can be hazardous, she’s found. Cross the alt-right and they will dox the offender. Question a liberal taboo, especially when it comes to identity politics and you will feel their wrath.
In a recent an interview on the FT Alphaville podcast, Nagle said:
The appeal of the internet and of social media was that it offered us this narcissistic pleasure whereby we could almost brand manage ourselves …while the internet can give you this persona… it can also take it away and present a horrifying version of who you are.
When we look at the horror-show of the public sphere on Twitter and other social media today it can seem like the internet has created a horrifying version of us.
Some of the phenomena we are living through will be understood and analysed by future historians. We don’t know where this is all going, but we are definitely going somewhere new and we’ve moving quickly. Nagle seems to be writing a first draft of the sociology of our accelerated connected times.
Have a listen to the podcast. I’ve also put Angela Nagle’s book on my reading list: Kill All Normies: Online Culture Wars From 4Chan and Tumblr to Trump and the Alt-Right.
Image: The late, very great, Rutger Hauer presenting a horrifying version of us in Blade Runner.
Kraft Heinz became the deal where Warrent Buffet’s old rules for investment came unstuck.
The FT reported on Monday this week:
Kraft Heinz shares dived nearly 30 per cent on Friday after it took a $15bn writedown, cut its dividend payout and disclosed it was the subject of a probe by the Securities and Exchange Commission into its accounting policies.
Buffet is the Western world’s most admired investor. He is admired because of the largely unbroken success of his company Berkshire Hathaway; success founded on the disciplined application of his rules, the most important being to only bet on incumbent brands that have a “moat”, meaning that they were able to defend and grow their market position and to hold shares for a long time. He steered clear of innovators and tech firms – eventually buying Apple once it has clearly shed its disruptor status and established itself as an apparently immovable giant in the music and smartphone markets.
The success of his approach undermined the claims of gospel of The Innovator’s Dilemma. Some things did never change, the predictable Buffet wins said, you can’t go wrong with big brands that people love. And that was true, as they say, until it wasn’t.
Where CPG incumbents go, advertising holding groups follow
In the CB Insights newsletter the collapse of the Kraft Heinz share price was cited as an example of digital disruption’s effect of “gradually, then suddenly” downfalls of incumbents.
The FT’s John Gapper commented, “advertising flavoured with history is no longer enough”, an analysis that can be applied to the big advertising holding groups as well.
The old rules no longer apply. Our mission is to write the new ones.
Synthetic media is a term I’d not come across before hearing about Google’s paper on fighting disinformation that was published this week. It describes those eerily realistic images and video generated through artificial intelligence (AI) or machine learning (ML) techniques.
You might have seen the video of the Jennifer Lawrence press conference where she has been gifted Steve Buscemi’s face as an example of this.
Deep fakes are what we more commonly call these.
Google says it is sharing datasets of synthetic media so that others can use it to spot deep fakes and develop systems that can do this. However it admits that there are limits to what tech can do – always slightly galling for a tech giant – and says it will need to also work with “researchers, policymakers, civil society, and journalists around the world”. Although none of these watchdogs have enjoyed complete success dealing with disinformation generated by non-silicon based actors, to coin a phrase. This last ditch defence against the tidal waver of fakes has been breached many times before.
Check your anti-tech moral panic
While we are trembling at the prospect of future synthetic media horrors, we might also recall that manipulating and misleading through media is something humans have been doing without support from AI for as long as we care to recall. See The Daily Mail and other tabloids in the UK’s decades-long campaign of disinformation about the European Union, for an example of this.
The Economist recently provided a helpful infographic of disinformation spread by the British media since the early 90s, sadly including stories published by non-tabloids such as the BBC and The Times.
Source: The Economist
The eyes! The eyes!
Another deep fake demo that crossed my awareness this week was a website called This Person Does Not Exist, which claims to showcase images of human faces that have been generated by an algorithm, something that previously had been hard to achieve.
Hit refresh and another fake face pops up. Obviously helped by foreknowledge, I thought that many of these would bear up to a glance, but still teetered on the edge of the uncanny valley.
The giveaway – when there is one – always seems to be the eyes. Sometimes more obviously than others…
Although other things can go wrong too…
I’m not sure about the provenance of this website. I’m aware that I may be enjoying it because it plays on whatever cognitive biases I have that make me want to believe that machines will never be able to completely fool me. In fact, they probably already have.