Hello all, and happy Monday.
There’s an age-old debate, especially in the creative industry, about where in organisations new innovations should come from. Should they be the product of dedicated innovation and R&D departments? Or should they be the responsibility of everyone in the organisation?
The answer is both – it just depends on which sort of innovations you’re talking about. This week’s article is about just that distinction, and how to tell whether you need an R&D department – or whether you just need to spend more time outside your comfort zone.
Have a great week!
This week’s article
Should innovation be a separate function and department within organisations? Or is it something everyone should do?
One of the greatest tensions in a mature business is the question of where innovation will come from. Producing what Clayton Christensen called sustaining innovations isn’t necessarily so hard – building upon what already exists, delivering more efficient or higher quality versions of existing products. But how do you produce something genuinely new?
One approach is to establish a research and development team. Freed from the responsibility to deliver immediate commercial value to customers or to shareholders, these R&D departments experiment in an attempt to push the boundaries of what’s possible. That makes total sense: starting a commercial project that relies on making advancements to bleeding-edge technology is a risky endeavour. As Bill Buxton put it:
“You can’t schedule scientific breakthroughs, so it is a bad idea to have your produce schedule depend on them. Save your gambling for the casino, and manage your research group separately from your development team.”1
Vaughn Tan, who has spent his career observing innovation in high-end, Michelin-starred restaurants, draws a similar conclusion. If you want to push the boundaries in food, it’s necessary to dedicate time, money, people and effort to pure research and development. Writing about Amaja, an Argentinian restaurant that consistently reimagined what was possible in cooking by researching new ingredients, recipes, and processes, Tan finds:
“These basic and applied research projects only sometimes bear fruit that the restaurant guest can detect in the form of new dishes. Maintaining so extensive a program of basic research while producing a steady stream of highly refined new dishes requires a dedicated R&D team.”2
How do you square this need for dedicated research and development resource with the attitude, particularly common in the creative industry, that innovation isn’t something that you can build a separate department for? “As soon as you have an ‘innovation department’, you’re buggered,” says Creative England CEO Caroline Norbury. “Absolutely everyone should be involved in innovation.” Don Sharp agrees: “When companies decide they need to innovate, they sometimes think the answer is to create an innovation department. It’s not.”
These two approaches aren’t necessarily contradictory. The point is that they apply to two different types of innovation. R&D departments are necessary when your objective is to push boundaries, when you’re trying to come up with ideas without knowing in advance what the commercial exploitation of those ideas might be, and when you’re willing to accept a high rate of failure. Separate from that, improvements can be made to everything that the organisation already does – improvements that aren’t necessarily transformational, but are important nevertheless.
Those kind of improvements are important partly because improvements to existing products and processes are straightforwardly valuable. But it’s also important because innovation improves the organisation itself. One phenomenon Tan observed among high-functioning teams was that they spent a lot of time outside their comfort zone: they practised “productive discomfort”. One example of this is their tendency to deliberately bite off more than they could chew, taking on projects that they knew were beyond them:
“These teams commit repeatedly to desperation projects which they know – explicitly – they can’t currently accomplish. Knowing this forces the teams to learn and change, to take on cognitive discomfort they would have avoided if they’d had the choice to. If the desperation project isn’t too far beyond the team’s capacity, this enforced learning lets them bridge the gap. They successfully complete projects that would previously have been impossible.”
These desperation projects aren’t reckless or foolhardy. They’re deliberately slightly outside the team’s comfort zone, not far outside it. But they remain risky, and by their nature will sometimes fail. Writing about the Copenhagen restaurant Noma’s MAD conference, a quintessential desperation project, Tan observed that Noma had staked their impressive reputation on the success of the project. As organiser Lars Williams said: “We’re totally committed. There’s no way we can wimp out now.” These high stakes and the threat of failure can, strangely, increase the chances of success – pushing the team to achieve things that they otherwise wouldn’t.
The distinction, then, becomes clearer. For speculative, cutting-edge research that pushes the boundaries of your field or your industry, and that has no immediate connection to commercial reality, it’s necessary to set up a dedicated R&D team. For day-to-day innovation that improves the dynamic of the organisation, what’s needed is to push yourself out of your comfort zone – applying perhaps more stick than carrot, using the fear of failure to spur you on. Recognising the difference will mean neatly avoiding trapping yourself at either extreme: believing that innovation is something that can only be achieved by a dedicated team, or believing that dedicated innovation teams will always fail.
Vaughn Tan. “The Uncertainty Mindset”. Columbia University Press, 2020
Vaughn Tan. “Productive Discomfort”. Substack, 2020
Bill Buxton. “Sketching User Experiences”. Morgan Kaufmann, 2007
This week’s five interesting links
An interesting paper by Samuel M. Hartzmark and Kelly Shue outlining a counter-intuitive aspect of ESG investing.
The ESG consensus is that you should invest in companies that do good, and not invest in companies that do bad. If you do that, you’ll make it harder to do business for companies doing bad things (by raising the cost of capital for them). That’s then a good incentive for those companies to behave better (and therefore access more, cheaper investment).
But Hartzmark and Shue argue that this is counterproductive. If you invest in an already-good business, there’s much less scope for them to improve in absolute terms. And if you don’t invest in bad businesses, you make it hard for them to make big investments (which means they won’t create new technologies to reduce emissions), and you put pressure on them to make money in the short term in order to survive (which means they’ll do bad things like mine more coal or produce more diesel engines).
ESG investing effectively makes bad companies worse, without making good companies better – because it lacks a mechanism for rewarding companies for absolute reductions in impact. #
A superb (and apposite) essay from Steve Randy Waldman, writing in 2011, on why finance is necessarily complex and opaque, and why removing that complexity and opacity is impossible and undesirable:
“This is the business of banking. Opacity is not something that can be reformed away, because it is essential to banks’ economic function of mobilizing the risk-bearing capacity of people who, if fully informed, wouldn’t bear the risk. Societies that lack opaque, faintly fraudulent, financial systems fail to develop and prosper. Insufficient economic risks are taken to sustain growth and development. You can have opacity and an industrial economy, or you can have transparency and herd goats.”
The “faintly fraudulent” aspect reminds me of Dan Davies’s brilliant book Lying for Money, which I wrote about last year. A certain amount of fraud in a society is desirable; completely eliminating fraud would also completely eliminate all other forms of commerce. #
A beautiful building, designed by Marc Thorpe, that appears to float over the surface of Crystal Lake in New York.
The great linguist Noam Chomsky outlines his frustrations with the buzz around generative AI: principally, that it might obscure the wonder of humanity and our incredible real intelligence.
“The human mind is not, like ChatGPT and its ilk, a lumbering statistical engine for pattern matching, gorging on hundreds of terabytes of data and extrapolating the most likely conversational response or most probable answer to a scientific question. On the contrary, the human mind is a surprisingly efficient and even elegant system that operates with small amounts of information; it seeks not to infer brute correlations among data points but to create explanations.
“Indeed, such programs are stuck in a prehuman or nonhuman phase of cognitive evolution. Their deepest flaw is the absence of the most critical capacity of any intelligence: to say not only what is the case, what was the case and what will be the case – that’s description and prediction – but also what is not the case and what could and could not be the case. Those are the ingredients of explanation, the mark of true intelligence.”
Sam Rye with a fascinating comparison between the informal, emergent relationships that become established in organisations and the mycorrhizal networks that link plants within forests.
“Much like when we began to understand the web of mycelial connections were fundamental to the health of the forest, illuminating relational infrastructure can help us see why leaving relationship building to happen in the coffee breaks is a terrible idea.”
(Thanks Flo!) #