Category Archives: Innovation

Peer review processes risk stifling creativity & limiting opportunities for game-changing scientific discoveries

Source: LSE, Sep 2017

Today, academics must prepare written proposals describing the research they wish to conduct and submit them to funding agencies for evaluation – a process known as peer review.

According to Don Braben and Rod Dowler, the current peer review process actually serves as a blocker to more radical research, stifling creativity and limiting opportunities for game-changing discoveries. Obviously peer review should not be abandoned entirely, but it is time to recognise the need for a separate category of highly innovative research with appropriate funding.

Einstein’s theory of relativity was criticised in 1931 in a book titled “100 authors against Einstein”. He replied that if they were right, one author would have been enough. This is an extreme example of the perils of peer review when dealing with brilliant researchers at the cutting edge of science. It is of vital importance right now to avoid suppressing genius in favour of apparent practicality. To achieve this, we need to find a way to continue to allow for the exceptional and to produce the science seeds that blossom into economic prosperity.

Today, academics must prepare written proposals on what they want to do and submit them to funding agencies for their evaluation – a process known as peer review. There is no escape from this process, which can take months that would otherwise be spent on research. Funding success rates are rarely more than 25 per cent. The agencies support only excellent proposals but as a result, freedom of research has been severely curtailed.

Scientific research should be open-ended. Serious-minded researchers should be capable of noticing anomalous behaviour in a system, carefully exploring wherever it may lead and hopefully thereby making great discoveries. How can constraining them not affect their creativity?

Current policies make sense for incremental or near-market research that may well lead to the creation of new technologies based on existing fundamental theories. The casualty of such policies, however, will be hard-to-predict radical discoveries, which are the ones that offer opportunities for growth on a global scale.

Related Resource: RAND, 2014

This report is a summary of Donald Braben’s work with BP’s Venture Research Unit (VRU), a research funding initiative that ran from 1980 to 1990. It is based on Braben’s reports in his books Pioneering Research and Scientific Freedom.

The VRU provided £20 million in research funding to about 30 researchers and small teams from Europe and North America. It aimed to fund determined researchers who questioned current thinking and would do transformative work. An important driver of the VRU approach was the idea that researchers with radical ideas would struggle to obtain funding through traditional means. Trust and freedom were considered essential aspects of the approach, and the unit’s organisers sought to minimise administrative burdens. Though VRU-funded work led to several notable outcomes, similar initiatives have not been introduced on a large scale in the UK.

Picking Tech Sides: US vs China

Source: WSJ, Aug 2020

The rest of this century seems likely to be an experiment to determine whether China can develop (or otherwise acquire) all it needs to maintain a modern technocratic surveillance state—not to mention expand its Chinese customer base to replace lost sales from beyond its borders.

The U.S. and its allies, meanwhile, face the loss of potentially huge markets in China. Eventually, it’s also likely to mean that American firms will manufacture less of their tech in China, though that could take decades. For internet companies, there isn’t as much at risk, as China’s Great Firewall long ago blocked Facebook, Google, Twitter, YouTube, Netflix, Wikipedia and most other sites and services of the mainstream Western internet.

In the current standoff, the U.S. “has a lot of power here,” says Dan Wang, technology analyst at Gavekal Dragonomics, a Beijing-based research firm, because in addition to banning these apps from the U.S., it has the power to prevent U.S. firms, and foreign companies that use technology from the U.S., from selling to Chinese tech companies.

China, meanwhile, has less leverage, says Patrick Moorhead, president of the technology research firm Moor Insights & Strategy, because it already blocked so many U.S. tech companies. “I think China played their card years ago,” he adds. Beijing could retaliate by other means, for example by canceling airplane orders with Boeing.

China is on its way to achieving not just a separate internet from the U.S., but a completely separate technology stack, from apps and services all the way down to the silicon microchips on which they run.


US Productivity

Source: Tyler Cowen/Medium, Aug 2020

In the UK that has better data, there was very, very little productivity growth until the Industrial Revolution.

Literally, from the time the Romans left in whatever, roughly 100 AD, until 1750, technological progress was very slow.

Sure, the British were more advanced at that point, but not dramatically. The estimates were like 0.1 percent a year, so very low. Then the Industrial Revolution starts, and it starts to speed up and speed up and speed up. And technological progress, in terms of productivity growth, peaks in the 1950s at something like 3 to 4 percent a year, and then it’s been falling ever since.

Then you ask that rate of fall — it’s 5 percent, roughly. It would have fallen if we held inputs constant. The one thing that’s been offsetting that fall in the rate of progress is we’ve put more and more resources into it. Again, if you think of the US, the number of research universities has exploded, the number of firms having research labs.

Thomas Edison, for example, was the first lab about 100 years ago, but post–World War II, most large American companies have been pushing huge amounts of cash into R&D. But despite all of that increase in inputs, actually, productivity growth has been slowing over the last 50 years. That’s the sense in which it’s harder and harder to find new ideas. We’re putting more inputs into labs, but actually productivity growth is falling.

What Drives Innovation?

Source: FS, Aug 2020

What does it take for a society to be technologically creative?

Mokyr explores some of the possible factors that contribute to a society’s technological creativity. In particular, he seeks to explain why Europe experienced such a burst of technological creativity from around 1500 to the Industrial Revolution, when prior to that it had lagged far behind the rest of the world.

Mokyr explains that “invention occurs at the level of the individual, and we should address the factors that determine individual creativity. Individuals, however, do not live in a vacuum. What makes them implement, improve and adapt new technologies, or just devise small improvements in the way they carry out their daily work depends on the institutions and the attitudes around them.”

While environment isn’t everything, certain conditions are necessary for technological creativity.

The social infrastructure

First of all, the society needs a supply of “ingenious and resourceful innovators who are willing and able to challenge their physical environment for their own improvement.”

Fostering these attributes requires factors like good nutrition, religious beliefs that are not overly conservative, and access to education. It is in part about the absence of negative factors—necessitous people have less capacity for creativity.

Mokyr writes: “The supply of talent is surely not completely exogenous; it responds to incentives and attitudes. The question that must be confronted is why in some societies talent is unleashed upon technical problems that eventually change the entire productive economy, whereas in others this kind of talent is either repressed or directed elsewhere.”

In Britain during and prior to the Industrial Revolution, Mokyr considers invention to have been the main possible path for creative individuals, as other areas like politics leaned towards conformism.

The social incentives

… there need to be incentives in place to encourage innovation. This is of extra importance for macroinventions – completely new inventions, not improvements on existing technology – which can require a great leap of faith.

The person who comes up with a faster horse knows it has a market; the one who comes up with a car does not. Such incentives are most often financial, but not always.

Awards, positions of power, and recognition also count.

Mokyr explains that diverse incentives encourage the patience needed for creativity: “Sustained innovation requires a set of individuals willing to absorb large risks, sometimes to wait many years for the payoff (if any.)”

The social attitude

a technologically creative society must be diverse and tolerant.

People must be open to new ideas and outré individuals. They must not only be willing to consider fresh ideas from within their own society but also happy to take inspiration from (or to outright steal) those coming from elsewhere. If a society views knowledge coming from other countries as suspect or even dangerous, unable to see its possible value, it is at a disadvantage.

If it eagerly absorbs external influences and adapts them for its own purposes, it is at an advantage. Europeans were willing to pick up on ideas from each other. and elsewhere in the world.

As Mokyr puts it, “Inventions such as the spinning wheel, the windmill, and the weight-driven clock recognized no boundaries”

Within societies, certain people and groups seek to maintain the status quo because it is in their interests to do so.

Mokyr writes that “Some of these forces protect vested interests that might incur losses if innovations were introduced, others are simply don’t-rock-the-boat kind of forces.”

In order for creative technology to triumph, it must be able to overcome those forces. While there is always going to be conflict, the most creative societies are those where it is still possible for the new thing to take over. If those who seek to maintain the status quo have too much power, a society will end up stagnating in terms of technology.

Ways of doing things can prevail not because they are the best, but because there is enough interest in keeping them that way.

Unlike modern times, Mokyr explains, for most of history technology did not emerge from “specialized research laboratories paid for by research and development budgets and following strategies mapped out by corporate planners well-informed by marketing analysts.

Technological change occurred mostly through new ideas and suggestions occurring if not randomly, then in a highly unpredictable fashion.”

Seeing as technological creativity requires a particular set of circumstances, it is not the norm.

Throughout history, Mokyr writes, “Technological progress was neither continuous nor persistent. Genuinely creative societies were rare, and their bursts of creativity usually short-lived.”

Not only did people need to be open to new ideas, they also needed to be willing to actually start using new technologies. This often required a big leap of faith. …  Innovations can take a long time to defuse, with riskier ones taking the longest.

Technological stagnation is the norm. In most places, at most times, people have not come up with new technology. It takes a lot for individuals to be willing to wrestle something new from nothing or to question if something in existence can be made better. But when those acts do occur, they can have an immeasurable impact on our world.

Generating Ideas

Source: Sam Altman, May 2020

Having ideas is among the most important qualities for a startup founder to have—you will need to generate lots of new ideas in the course of running a startup.

if you want to be a founder and can’t get an idea for a company, you should probably work on getting good at idea generation first.

How do you do that?

It’s important to be in the right kind of environment, and around the right kind of people.

You want to be around people who have a good feel for the future, will entertain improbable plans, are optimistic, are smart in a creative way, and have a very high idea flux.

These sorts of people tend to think without the constraints most people have, not have a lot of filters, and not care too much what other people think. 

The best ideas are fragile; most people don’t even start talking about them at all because they sound silly. Perhaps most of all, you want to be around people who don’t make you feel stupid for mentioning a bad idea, and who certainly never feel stupid for doing so themselves.

Stay away from people who are world-weary and belittle your ambitions. Unfortunately, this is most of the world. But they hold on to the past, and you want to live in the future.

You want to be able to project yourself 20 years into the future, and then think backwards from there. Trust yourself—20 years is a long time; it’s ok if your ideas about it seem pretty radical.










Another way to do this is to think about the most important tectonic shifts happening right now. How is the world changing in fundamental ways? Can you identify a leading edge of change and an opportunity that it unlocks? The mobile phone explosion from 2008-2012 is the most recent significant example of this—we are overdue for another!

In such a tectonic shift, the world changes so fast that the big incumbents usually get beaten by fast-moving and focused startups. (By the way, it’s useful to get good at differentiating between real trends and fake trends. A key differentiator is if the new platform is used a lot by a small number of people, or used a little by a lot of people.)

A good question to ask yourself early in the process of thinking about an idea is “could this be huge if it worked?” There are many good ideas in the world, but few of them have the inherent advantages that can make a startup massively successful. Most businesses don’t generate a valuable accumulating advantage as they scale.

a good test for an idea is if you can articulate why most people think it’s a bad idea, but you understand what makes it good.

Imagination Matters

Source: HBR, Apr 2020

In recessions and downturns, 14% of companies outperform both historically and competitively, because they invest in new growth areas. For example, Apple released its first iPod in 2001 — the same year the U.S. economy experienced a recession that contributed to a 33% drop in the company’s total revenue. Still, Apple saw the iPod’s ability to transform its product portfolio: It increased R&D spending by double digits. The launch of the iTunes Store (2003) and new iPod models (2004) sparked an era of high growth.

How to Develop Your Organization’s Capacity for Imagination

Based on our research for a new book on the imaginative corporation we share seven imperatives:

1. Carve out time for reflection.

2. Ask active, open questions.

the possibility of shaping events to our advantage only arises if we ask active questions, such as “How can we create new options?”

Creativity involves reaching beyond precedents and known alternatives to ask questions that prompt the exploration of fresh ideas and approaches.

3. Allow yourself to be playful.

“Creativity is the rearrangement of existing knowledge into new, useful combinations,” Jorgen Vig Knudstorp, chairman of the LEGO Brand Group

4. Set up a system for sharing ideas.

Someone, somewhere in your organization is likely being forced by circumstances to experiment with new ways of doing things. The imaginative corporation picks up, codifies, and scales these innovations.

Imagination doesn’t just happen on an individual level. Ideas evolve and spread by being able to skip between minds. Companies need to facilitate collective imagination. The key to this is allowing new ideas to be shared while they are still in development: creating forums for people to communicate in a casual way, without hierarchy, reports, permissions, or financial justifications

5. Seek out the anomalous and unexpected.

Imagination is triggered by surprising inputs. Our pattern-seeking minds adapt our mental models when we see something that does not fit. And when we adapt our mental models, we entertain different strategies and courses of action.

To solve tough new problems, look externally. Examine accidents, anomalies, and particulars, and ask: “What doesn’t fit here?” Digging into what we find will prompt reframing, rethinking, and the discovery of new possibilities.

6. Encourage experimentation.

Although a crisis stretches our resources, it is important to encourage experiments — even if only on a shoestring budget. Natural systems are most resilient when they are diverse, and that diversity comes from trying new ways of doing new things. Our ideas only become useful if they are tested in the real world, often generating unexpected outcomes and stimulating further thinking and new ideas.

7. Stay hopeful.

Imagination feeds off the aspirations and aggravations that propel us to seek a better reality. When we lose hope and adopt a passive mindset, we cease to believe that we can meet our ideals or fix our problems.

Dealing with real risks involves taking imaginative risks, which requires hope.

“Never in our lifetimes has the power of imagination been more important in defining our immediate future,” Jim Loree, CEO of Stanley Black & Decker, told us. “Leaders need to seize the opportunity to inspire and harness the imagination of their organizations during this challenging time.”

How Tech Can Build

Sourch: Stratechery, Apr 2020

What it means to ask more of one another, at least in tech, is right there in the overlap between preferences and vision.

First, tech should embrace and accelerate distributed work. It makes tech more accessible to more people. It seeds more parts of the country with potential entrepreneurs. It dramatically decreases the cost of living for employees. It creates the conditions for more stable companies that can take on less risky yet still necessary opportunities that may throw off a nice dividend instead of an IPO. And, critically, it gives tech companies a weapon to wield against overbearing regulation, because companies can always pick-up-and-leave.

Second, invest in real-world companies that differentiate investment in hardware with software. This hardware could be machines for factories, or factories themselves; it could be new types of transportation, or defense systems. The possibilities, at least once you let go of the requirement for 90% gross margins, are endless.

Third — and related to both of the above — figure out an investing model that is suited to outcomes that have a higher likelihood of success along with a lower upside. This is truly the most important piece — and where Andreessen, given his position, can make the most impact. Andreessen Horowitz has thought more about how to change venture capital than anyone else, but the fundamental constraint has remained the assumption of high costs, high risk, and grand slam outcomes. We should keep that model, but surely there is room for another?

I do believe that It’s Time to Build stands alone: the point is not the details, or the author, but the sentiment. The changes that are necessary in America must go beyond one venture capitalist, or even the entire tech industry. The idea that too much regulation has made tech the only place where innovation is possible is one that must be grappled with, and fixed.

And yet, Andreessen himself said that we need to demand more from one another. We need to figure out how to fix Wisconsin, not flee from it. We need to figure out how to build real businesses that build real things, not virtualize everything. And we need to start fighting for not just infinite upside, but the sort of minute changes in cities, states, and nations that will make it possible to build the future.

Turing’s Vision

Source: New Scientist, Jun 2016

In his book Turing’s Vision, Chris Bernhardt deftly shows how Turing dashed one of Hilbert’s great ambitions with a masterful proof – in the course of which he inadvertently invented the modern computer.

The Entscheidungsproblem was part of Hilbert’s work to show that the basic axioms of mathematics are logically consistent. To that end, Hilbert sought an algorithm – a computational procedure – that would indicate whether a given mathematical statement could be proved from those axioms alone. Turing decisively showed that there was no such algorithm.

Turing had to first establish a working definition for the term algorithm – to define what it means to compute. Turing looked at human “computers” – people who made computations. The task involves writing symbols on paper, he noted. “The behaviour of the computer at any moment is determined by the symbols… he is observing and his ‘state of mind’.”

Breaking down apparently complex cogitation into simple arithmetical procedures, Turing made computation explicit and eliminated the human element. “Turing’s fresh insight was to define algorithms in terms of theoretical computing machines,” writes Bernhardt. “Anything that can be computed can be computed by a Turing machine.”

That’s why the machines were central to Turing’s paper. To show there were algorithms that Turing machines would run indefinitely and inconclusively was a way of showing Hilbert was mistaken. Turing proved “that there were questions that were beyond the power of algorithms to answer”.

as crucial as the theoretical machines were to Turing’s proof, they turned out to have even more impact in their own right, providing a conceptual model for modern computers. The influence was direct, informing John von Neumann’s pioneering 1945 design for electronic computers, and the room-sized machines that applied his architecture. Like Turing’s machines, the computers used ones and zeroes to encode programs and data. 

Related Resources:, Apr 2017

Turing had to define what an algorithm was; he explained this by breaking complex calculations down into simpler parts. He also defined the very concept of computation, using the concept of ‘Universal Machines’, machines that, he proved, can compute anything that is computable. In 1936, this was all still as theoretical as it gets.

RSArchive, Jun 2019

From Chapter 1: “Gödel had completely destroyed Hilbert’s program as it stood in 1920. Nevertheless, there was still the Entscheidungsproblem.”

The Entscheidungsproblem is the halting problem – whether the computer program will finish running, i.e., halt, or continue running forever. “Turing would show that there were questions that were beyond the power of algorithms to answer. He would construct a proof … showing that there was no mechanical set of rules for the solutions of all mathematical problems and consequently that our activities as mathematicians would never come to an end.”

“Turing machines are theoretical models of our modern computers. Everything that can be computed on a computer can be computed by a Turing machine, so Turing’s paper is not just of historical interest; it tells us about what can and cannot be computed by any computer. It tells us that there are limitations to computation, and that there are simple questions that at first glance look straightforward, but are beyond the power of any computer to answer correctly … As Marvin Minsky writes: The sheer simplicity of the theory’s foundation and extraordinarily short path from this foundation to its logical and surprising conclusions give the theory a mathematical beauty that alone guarantees it a permanent place in computer theory.”

Reducing budget and trade deficits

Source: LawLiberty, Mar 2020

The market sent a shot over our bow to tell us that we cannot accumulate budget and trade deficits forever. We entered the crisis with full employment and a federal deficit of about 4 percent of GDP—an extraordinary situation. As noted, we may boost the deficit to 20 percent of GDP before the crisis is over.

There are a number of ways in which the necessary adjustment can occur, most of them unpleasant.

One is a general reduction in entitlements for future generations as well as spending cuts for the present.

Another is a higher level of savings, either on the part of households (who can save and buy government bonds) or on the part of government (which “saves” by increasing taxes on households and corporations in order to reduce “dis-saving” in the form of government deficits).

Both of the above would require a significant, one-time drop in consumption, and probably a severe recession. The political consequences of any of these scenarios would be ugly.

The other way in which the adjustment could occur is through a revival of productivity growth.

Labor productivity growth during the past decade has languished at the low end of an historic range. Productivity growth driven by technological innovation, for example, can substitute for savings, as it gives us more output for less effort.

If the United States were to reduce its current account deficit by reviving high-tech industries, which have inherently high productivity, average productivity growth would increase, especially if new technologies were brought to bear.

On the other hand, an industrial policy that centered on creating jobs in low-productivity industries would have the reverse effect. Conventional industrial policy tends to subsidize inefficient industries at the expense of the public, but government support for basic R&D on the model of the Kennedy Moonshot or the Reagan Strategic Defense Initiative has in the past put a tailwind behind productivity growth.

Clayton Christensen’s Contributions

Source: HBR, Jan 2020

Clayton M. Christensen is best known for his theory of disruptive innovation, in which he warns large, established companies of the danger of becoming too good at what they do best. To grow profit margins and revenue, he observes, such companies tend to develop products to satisfy the demands of their most sophisticated customers.

As successful as this strategy may be, it means that those companies also tend to ignore opportunities to meet the needs of less sophisticated customers — who may eventually form much larger markets.

An upstart can therefore introduce a simpler product that is cheaper and thus becomes more widely adopted (a “disruptive innovation”). Through incremental innovation, that product is refined and moves upmarket, completing the disruption of the original company.

Disruptive innovation:

the core theory of why bad things happen to good companies. “Disruptive Technologies: Catching the Wave” is the big-picture “why is this a problem” article warning established companies that a seemingly rational concern with profit margins can have disastrous results.

Product innovation: 

why good managers struggle to innovate successfully, this time focusing on the discipline of product innovation itself, rather than on organizational and management structures.

By understanding the tasks that customers look to a product for (the “job to be done”), a company can develop offerings — products, services, and whole brands — that customers truly value. Christensen uses the “milk shake” example to show how product developers should be considering their task.

The financial tools in the way

Established financial incentives often make it unattractive for companies to innovate. In “Innovation Killers: How Financial Tools Destroy Your Capacity to Do New Things,” Christensen and his coauthors target metrics such as discounted cash flow, net present value, and earnings per share, along with attitudes towards fixed and sunk costs. They suggest that leaders take up other methods for evaluating investments — ones that consider future value.

Business model innovation

Product innovations might be necessary, but to be truly disruptive, they often need to be delivered to the market through new business models.

In “Reinventing Your Business Model,” Christensen and his coauthors describe how to determine if your company needs a new business model and what makes one successful, using examples ranging from Apple’s iTunes to CVS’s MinuteClinics.

To Christensen, the role of every general manager is to lay a foundation for future growth. To that end, managers need to understand disruptive innovation, the threat it poses, and how to lead their teams and organizations to create growth that can keep pace with ever-evolving technologies, industries, and customers.