It’s a plum pudding of a book. Stick your thumb in and you’ll find something to hold your attention.

There’s Roman Polanksi’s fateful encounter with Sharon Tate. Or Robert Towne dreaming out the script… ‘Dreaming you’re in paradise and waking up in the dark—that’s Chinatown’. And the help-yourself bowl of cash (and another of cocaine) on Jack Nicholson’s coffee table for friends to dip into.

And much more.

What held my attention was the story of Robert Evans, the youthful boss of Paramount, plucked from anonymity by Norma Shearer, who saw him poolside working a telephone and though she couldn’t hear what he was saying, saw ‘the passion and enjoyment, his fullness of attention’ – and thought of her long-dead husband Irving Thalberg.

When Evans became head of production at Paramount, he was the laughing-stock of Hollywood: ‘too young, too green, too good looking (a former actor!)’.

Not for long.

After he cast Ali MacGraw and Ryan O’Neal in Love Story, the film’s phenomenal run blew the doubters off and gave Evans and his offsider Peter Bart carte blanche at the studio they called ‘The Mountain’.

They used it to nurture a string of fabulous hits. Barefoot in the Park, The Odd Couple, Rosemary’s Baby, Harold and Maude, The Godfather, The Godfather Part II, Serpico, The Conversation…. and Chinatown.

Wasson describes Evans’ way of working:

‘He woke late, in time for lunch, and went to bed, with the help of sleeping pills, long after Hollywood had punched out. In between he was a man attached to a phone. His home, at one time, had exactly thirty-two, an average of two per room, but his favorite—a relationship that would last longer than any of his marriages—was the one he kept in bed, propped up on a pillow between his Rolodex and his view of the pool. Writers had the blank page; Robert Evans had the dialtone. All his imagining—his multilayered consideration of scripts and how to get them into movies—began here, on the phone, with slightly more than nothing, just seven digits and a hunch…’

Evans was one of a new generation of studio bosses, among them John Calley at Warners, Richard Zanuck at Fox and David Picker at United Artists. All in the their 30s. When they started, Evans told Bart it was ‘back to basics’. The script and the talent. Nothing else.

As Wasson notes: ‘Evans’s assertion ran against the grain in midsixties Hollywood, where a gerontocracy in crisis was fighting the small screen with grand expenditure, the more-is-more strategy of the road-show economy.’

It will be interesting to watch the next generation of thirty-somethings when they arrive and ‘passion and enjoyment (and) fullness of attention’ are once again let loose.

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Not so.

Long run data series show scientific impact is highly unequal. The top 1 percent of scientists author or co-author 42 percent of all scientific papers – and 87 percent of all papers with more than 1,000 citations.

I’ll say that again: The top 1 percent generate 87 percent of all papers with more than 1,000 citations.

This is wildly unequal. These are not clerks in an office churning through paperwork at a more or less equal rate. These are rock stars whose papers ricochet through the idea-sphere – as Dashun Wang and Albert-Lászlów Barabási show in their fascinating book The Science of Science.

Wang and Barabási have data for artists and film directors too, though they lack a comparable measure of impact. But the similarities are plain enough.

Knowledge work is not like physical work, where there is not much variation in performance. It’s like the movies, a business in restless search of hits. And its best performers are stars.

There’s a wealth of data in Wang and Barabási’s book. On ‘hot streaks’, the role of teams, the ‘random impact rule’ – which shows hits can happen at any point in a career, early or late – and more.

But the data that made me really sit up concerned the influence of star performers on the people around them.

To measure this they tracked what happened when a star scientist moved to a new university. They found that the collective output of papers (weighted by citation count) increased by 54 percent.

‘This increase could not be attributed to the publications of the stars themselves: After removing the direct contributions of the star, the output of the department still increased by 48 percent.’

Which suggests that stardom is infectious. People learn by watching what stars do and the lessons have immediate impact.

This has enormous implications for the way we train up new talent. It means we need to bring them into close contact with proven talent. Let them watch, talk, and eat together.

That’s the thinking behind Compton’s Rainmakers project. Talent may be god-given but out-performance can be learned.

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In Lorraine Daston’s account, there are many kinds of rules but all come in one of two basic shapes. Thick or thin.

Thick rules are loose, full of exceptions, caveats, examples, and discretionary allowances. They work locally, through careful application.

Thin rules by contrast are sharp, ‘unencumbered by examples and exceptions; they do not traffic in specifics; they float above context’.

And the thinnest, sharpest rules of all are algorithms.

Of course the beauty of algorithms is that they scale. Stripped of nuance they can cut through dense thickets of choice and difference. They do a lot of work, quickly and efficiently.

So here’s my question: which would you rather live by?

My instinctive answer is: thick. I want there to be nuance and allowable exceptions to the rule – not least in case I fall foul of it!

But another part of me answers: thin. I want the rules to be clear, simple and transparent. And the same for everyone. No exceptions, no favourites.

40 years ago, working for the Australian Film Commission, I was involved in a long argument with Treasury about how to deliver assistance to film producers. They wanted thin rules: a simple yes-or-no, without nuance. We wanted thick rules: the discretion to move the goalposts.

We won the argument – it was hard fought – and the result was the Film Finance Corporation, a ‘film bank’ that broadly followed the market but was authorised to use its judgement case by case.

Looking back, I think Treasury probably had the better argument.

But then consider algorithms. Netflix for example. Delivering personalised recommendations to hundreds of millions of viewers. Since you watched that, that and that, we guess you’ll like this.

How often are they right, in your experience?

If you’re like me, you’ll spend about 20 minutes trawling Netflix’s recommendations and give up. Or Amazon, which has 25 years of my book-buying data, but keeps showing me books I have no interest in and – worse – keeps missing the books I really might be interested in.

The point is, their models are too thin. They take a set of data points and extrapolate a caricature. Then try to sell me the caricature’s probable choices.

It’s the reason I follow so many critics and walk into every bookstore I see. I need the thickness of human curation. I want to be surprised.

So there is no formula. Thin is good for fairness and for efficiency. Thick is good for humanity.

Read Daston’s book if you want to learn more. It’s brilliant.

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Most finance professors when they talk about leverage mean debt. But Desai means something more. He wants to know when it makes sense – in life or in business – to go big, and when it makes sense to go small. To explore this question, he tells the stories of writer George Orwell and artist Jeff Koons.

Two more extreme cases would be hard to find.

Koons is the in-your-face ‘Warhol of his time’ responsible amongst many other works for Rabbit, a series of three stainless steel sculptures of, yes, a rabbit – one of which sold at auction in 2019 for $96 million.

Jeff Koons, Rabbit

Vanity Fair reported in 2014 that Koons had a staff of 128: ‘64 in the painting department, 44 in the sculpture department, 10 in the digital department and 10 in administration’. Per Koons, their output averaged ‘6.75 paintings and 15 to 20 sculptures a year’.

In Desai’s terms, Koons was fully leveraged.

By contrast, George Orwell in 1946 was unwell, down on his luck, and ‘smothered under journalism’. In desperation, he retreated to an ‘extremely ungetatable’ cottage on a remote island in the Hebrides, where he spent his final years writing what became his last and classic work: 1984.

In other words, Orwell hunkered down. Or as Desai would say, de-leveraged.

So which is better? Desai and I both lean in our teaching towards levering up. In Desai’s words:

When you have a big project, or an ambitious plan – one that demands more than you can personally deliver – then you need leverage. People, money, backing: in a word, levers.

But not always. When people don’t understand what you’re trying to do, when the risks are too great, or when you’re out of time, then Orwell’s strategy makes sense.

Get into the smallest shape you can and hunker down.

This post is the second in a series I plan to publish based on my reading – the insights I’ve gathered and think worth sharing.

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Hands get shook and backs get slapped. As though they were bound together in their mutual enterprise: the movie business. Perhaps there’s some argy-bargy about profit shares but basically they are on the same page.

Yet the truth is: there is a fundamental disjunct between filmmaker and executive.

It’s not just that one is on salary while the other is eating their savings. Nor is it the power imbalance between them, or the different pathways they have followed to arrive where they are. It’s that one is operating at 30,000 feet and the other is dug in at ground level.

If you’re making a film, it occupies your entire field of view. You can’t see past it. You don’t have time or bandwidth to think about anyone else’s film. You are all in on one thing — the film you are making.

This is true financially too. You have put all your chips down on one square and you can’t take them back. Whereas the studio executive is managing a slate of films. They’ve got chips on 20 squares.

Harvard professor Mihir Desai calls this the core of finance. He starts his book The Wisdom of Finance with a story about chance and pattern. Chance is what the world looks like close up: an arena of luck, accidents, flukes, coincidences, or what the ancients called fortuna.

Whereas pattern is chance viewed over time – statistically. It’s what we notice when we study the world and keep records. It’s the view from 30,000 feet.

The study of patterns is what gave us the insurance business (the averaging of bad luck), portfolio theory in finance (strategic diversification) and the studio slate (the search for a hit). These are all methods of managing risk, of taming fortuna.

But our filmmaker has wandered into a casino and bet everything on single spin of the wheel. Their risk is irreducible. They don’t have the luxury of statistics.

So for all the backslapping, the studio executive and the filmmaker are really two different species. Different stakes, different aims, different view of the world.

For our filmmaker, chance is the whole point. The risk is not to be managed but to be taken.

This post is the first in a series I plan to publish based on my reading – the insights I’ve gathered and think worth sharing.

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