Archive for category evolving economic entities
Innovation Problem: New Ideas Spread Slowly
Posted by Tim in book riffs, complex systems, evolving economic entities on 30 January 2012
There’s a big problem with innovation: ideas spread much more slowly than we expect them to.
Ideas follow an S-Curve as they spread that looks like this:
They pick up steam very slowly, until they either die off or hit a tipping point and take off. The slow build-up is the time I’ve indicated as X in the drawing.
The idea for the S-Curve is based on the great work by Everett Rogers on innovation diffusion.
Based on his research, the population of users is divided into groups he called innovators, early adopters, the early and late majorities, and the laggards. In the populations that he looked at, the percentages of people in each group look like this:
You can see these numbers in the survey that Sophos Security released last week on the reactions of Facebook users to the new timeline feature:
This is being presented as a big problem for Facebook, but if you look at the numbers, they’re actually better than the stats from Rogers would lead us to expect. The survey doesn’t include the laggards, who probably still aren’t on Facebook, but the rest of the numbers map onto Rogers’ pretty well.
All of the people that hate the new timeline want to go back to the News Feed, another feature that had even worse approval numbers when it was introduced. And now people love it and don’t want it to change.
That’s the way that ideas spread. People resist, a small number adopt, and eventually over time, the idea wins. If you’re lucky.
There was another story over the weekend about the diffusion of Edison’t incandescent lightbulbs that tells the same story.
Here is what they say about adoption of electrical lighting:
By 1910, more than 30 years after Thomas Edison invented the incandescent bulb in 1879, only about 10 percent of American homes had been wired. Even in the glittering Roaring Twenties, only about 20 percent of homes had electricity — not because of a lack of electrical contractors, but because of a lack of consumer enthusiasm.
Advertisers proclaimed that homes with electricity would be brighter, cozier and happier, but the public wasn’t buying.
And this is for a product that was demonstrably better, cheaper and safer.
Again, the value for X was much longer than expected.
This is an issue that is addressed extremely well by James Gardner in his excellent new book Sidestep & Twist: How to create hit products and services that people will queue up to buy.
The book is worth reading and Gardner does a great job of explaining the S-Curve and its implications. One of the key outcomes of this is one that makes a lot of the people that have encountered Gardner’s ideas uncomfortable: breakthroughs don’t pay.
The long X shows us why. It takes so long for new ideas to spread that whoever introduces them is not always set up to capture the value from them.
This is kind of scary, because those of us that generate ideas want to think that a great idea will win. But they don’t automatically. One point that he makes is that you work around this by building on existing ideas:
A lack of genuine originality is a feature of almost every category-defining product in the last decade. Was Facebook the first social network? Certainly not: MySpace, Friendster and a host of others preceded it. In fact, the first real social network was a site called SixDegrees.com, and it was founded a decade before Facebook’s meteoric rise began. Was it Google that created web search? Of course not: the company’s contribution was to improve what Alta Vista and the other web search engines that had pioneered the field were doing already.
I could spend pages and pages going through examples like these, and will do so later on in this book. But one thing unites all these products and services: they’re built on something that was working well somewhere else.
Gardner has more good suggestions about what to do about this, and I discuss these more here. But for today, I just wanted to take the Facebook and Edison examples to illustrate the problem that we are trying to address. If you are trying to get ideas to spread, you must develop a good understanding of the idea diffusion S-Curves and what they mean.
The fact that ideas spread slowly is crucially important to understand. It is part of what makes it difficult to win through innovation. This is why we must manage innovation as a process.
It’s dangerous to think of innovation only as generating new ideas. That’s not enough. You also have to get the great ideas to spread. They spread through S-Curves, and we have to include these when we develop our innovation strategies.
Two Great Innovation Misquotes
Posted by Tim in book riffs, design, evolving economic entities on 27 January 2012
There are two popular quotes that often get used when discussing innovation that were never actually said or written by the people to whom they are attributed. Despite the fact that they are fake quotes, there are still things that we can learn from them.
The first common quote is attributed to Henry Ford:
If I had asked people what they wanted, they would have said faster horses.
This quote usually comes up when people are discussing focus groups, or design-driven innovation. However, there’s no evidence that Ford ever said or wrote it.
Even though it’s not a real quote, it raises some interesting points. You can interpret it as meaning “you should ignore customers,” or some people even seem to think it means “customers are stupid.”
But that’s not really what it’s saying at all. People do have limited vision if you ask them open-ended questions. And as innovators, our job is to invent the future. Nevertheless, there is useful information in the faster horses idea.
If people really had told Ford that they wanted faster horses, what would that mean? If you frame it in a jobs-to-be-done way, it means that the main job that they’re trying to do is to get somewhere fast. That actually is a pretty good argument in favour of automobiles.
In his HBR post on this topic, Patrick Vlaskovits sums up the issue well:
An innovator should have understanding of one’s customers and their problems via empirical, observational, anecdotal methods or even intuition. They should also feel free to ignore customers’ inputs. Because by now it should be clear that Ford’s adherence to his vision of the mass-market car and how to materialize that vision was instrumental in both his early success in growing Ford Motor Company as well as his later failure to respond in a timely and effective manner to rapid innovation in the marketplace.
The real lesson learned was not that that Ford’s failure was one of not listening to his customers, but of his refusal to continuously test his vision against reality, which led to the Ford Motor Company’s failure of continuous innovation, resulting in a catastrophic loss of market share from which it never recovered.
So the quote is useful, even if Ford never said it.
The second quote is a bit more problematic – this one is frequently attributed to Charles Darwin:
It is not the strongest of the species that survives, nor the most intelligent that survives. It is the one that is most adaptable to change.
As with the Ford quote, Darwin never actually said or wrote this (he never wrote “survival of the fittest” either – that was Herbert Spencer building on Darwin). This one is a bit more problematic too, because it is actually a major misinterpretation of Darwin.
Consider the Large Ground Finch, one of the species from the Galapagos Islands described by Darwin:
In a remarkable research project that has spanned nearly 40 years now, Peter and Rosemary Grant have studied the evolution of Darwin’s Finches in the Galapagos (the work was beautifully described in The Beak of the Finch: A Story of Evolution in Our Time
Here is their key finding. When times are good, there is wide variation in the beaks of the finches. However, the Galapagos are subject to the El Niño/La Niña weather cycles, which means that they have frequent droughts. In times of drought, the finch populations dive. In the case of the Large Ground Finch, the individuals that survive these events have the biggest beaks. Why? Because the bigger beaks enable them to crack larger seeds, which would be ignored as too hard to crack when there are plenty of seeds around.
In other words, it is precisely the strongest of the species that survives.
The fake Darwin quote is completely wrong with regard to which individuals survive. But it might tell us something about which species survive. The reason that Large Ground Finches have been around for as long as they have is that there is enough variation in the species that whenever conditions are extreme, some individuals in the population will be able to adapt to the change.
If we apply this to innovation, you might think of it this way: products are like individuals and organisations are like species. To do well, products need to be the best at getting some job done for some group of customers.
However, for an organization to do well over time, it needs to be adaptable. This means that unless its environment is unusually stable, it needs to generate variety. Even though economic evolution is directed by the choices that people make, we still don’t have much control over which ideas work and which don’t. Or over which take off, and which never really click.
To maintain variety, to improve responsiveness to change, we must experiment.
Why have these two quotes become so widespread? It’s not the internet – both incorrect attributions were made in books. Both quotes are catchy and short, and they capture ideas that seem like they reflect what Ford and Darwin thought. Even though the Darwin quote is not very Darwinian, it reflects a very common misinterpretation.
The catchiness is one thing, but also, we like to argue from authority. If we don’t want to run focus groups, it’s easier to get Henry Ford to make the argument than it is for us to do it ourselves.
I wanted to think through these quotes for a couple of reasons. One is that they do offer some useful lessons. The second is that we need to figure out how to make compelling arguments ourselves. This is the key to getting our own ideas to spread – not by arguing from authority.
(The superb Large Ground Finch photo is from flickr/Steven Bedard under a Creative Commons License)
Three Signs of Business Model Innovation Opportunities
Posted by Tim in business models, evolving economic entities on 25 January 2012
How can you tell when there is an opportunity for business model innovation?
Recent events in higher education might give us a good indication.
There are a few issues in university education these days. The main one is that education is information based, and over the past 20 years we have seen nearly every single business model based on control of scarce information get disrupted. This has played out dramatically in the U.S.A. recently with the battle over SOPA/PIPA.
There are three signs that the business model for higher education provides real innovation opportunities right now. These probably apply to any industry approaching an inflection point:
- Everyone starts asking if your business model is broken: people like David Tapscott and Seth Godin have started talking about problems with the higher education business model. Questions have started to come from the inside too – David Parry and Joshua Gans have both discussed this issue recently. Clayton Christensen has even written a book on it.
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Where’s there is smoke, there’s usually fire.
- Business as usual stops working: there are plenty of things that are currently broken in higher education. I’m lucky in that things in Australia are better (for now) than most everywhere else. But the trends are unmistakable. See the infographic at the bottom of the post from OnlinePhD for details.
Budgets are getting cut everywhere, it’s hard to find new staff, the journal publishing industry is under pressure, everything on the delivery side is looking a bit shaky. These are all signs that the higher education business model is under pressure.
- Everyone starts experimenting (except for the incumbents): there are experiments happening all over the place:
- The post by Josh Gans talks about the alliance between Khan Academy and Vi Hart. Both have been testing out new ways to deliver material on video. Here is what Gans says about the alliance:
The fact that these two are getting together demonstrates something important regarding online education. Experiments are happening and the successful ones are complementary to one another. In particular, both Kahn and Hart have evolved a particular style of video instruction. It is a style that removes the lecturer from the picture. Previous videos for educative purposes did not do that.
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There are people out there, for the most part far removed from traditional education, who are experimenting and working out how to make modular, compelling content that can free teacher time. They are finding each other and that is great news for the future.That is great news for the future – but it might not be for universities.
- Apple is trying to reinvent textbooks – a part of the business model that rarely even gets mentioned when people discuss problems in higher education.
- There are lots of experiments with massive open online courses. George Siemens, one of the pioneers in this area, talks about the big news this week, which is the foundation of new group that will do precisely this. The group is called Udacity, and it was put together by Sebastian Thrun, who ran a big open course at Stanford last year. It was wildly successful.
His response to that success: “I can’t teach at Stanford again.”
Even the experiments that take place inside of universities aren’t staying there.
Experiments are a key part of innovation, and that is how we find out what works. New business models in higher education will come about through experiments. And the people that do the experiments will have a lot of impact on what the new business models look like.
If you were a university right now, wouldn’t you want that to be you?
- The post by Josh Gans talks about the alliance between Khan Academy and Vi Hart. Both have been testing out new ways to deliver material on video. Here is what Gans says about the alliance:
Our job is to invent the future. When you start to see questions about what that future should be, major problems with business as usual, and a sharp increase in experimentation, that is a sure sign that there is a big opportunity for business model innovation.
If you’re in higher education, now might be a good time to start trying to shape that future, instead of letting the future happen to you.
Created by: Online PhD
When is it OK to Ignore Innovation?
Posted by Tim in book riffs, evolving economic entities, selection, time on 8 January 2012
The earth has been around for 4.5 billion years or so. If you think of the last 10% of that time, a fair bit has happened. There have periods of major global warming, and a few ice ages. There have been asteroid strikes, and other natural disasters too numerous to count. Continents that were one continuous land mass 450 million years ago are now separated by oceans. And there have been five major extinction events.
Through all of that change, disruption and chaos, what has been the most stable environment on earth? The deep ocean. There’s no light down there, so it doesn’t matter if an asteroid strike kicks so much stuff into the air that all of the coral reefs and dinosaurs die out. It’s always cold, so climate change up on the surface doesn’t have much of an impact either. The deep ocean has stayed pretty much the same all the way through.
And that’s where the Coelacanth lives.
I’ve been fascinated with Coelacanths since I first read about them in On Methuselah’s Trail: Living Fossils and the Great Extinctions
The first fish in this family show up in the fossil record about 400 million years ago. Their fossils are pretty consistently around for a long time, until they disappeared about 65 million years ago around the Cretaceous extinction, the one that killed off the dinosaurs.
Because there was no record of them for 65 million years, scientists thought that they were extinct. And then a museum curator found one in the catch of a fishing boat off the coast of South Africa in 1938. In a curious aside, it turns out that the fishermen had known about the Coelacanths for a long time, but whenever they caught one they threw it back because they’re apparently very poor eating. It was only once they realised that museums were willing to pay them for specimens that they started to keep them.
There are two species of Coelacanth around now, and structurally they haven’t changed much at all since the first specimens from 400 million years ago.
In other words, they haven’t innovated one bit in 400 million years.
Why? Because they live in the deep ocean, the most stable environment in the world over that period of time.
So the answer to the question When is it OK to Ignore Innovation? is: when you’re in a stable environment.
Just as the Coelacanth shows that you don’t necessarily have to evolve to survive, in the economy you don’t necessarily have to innovate to survive. If, and it’s a big if, your environment is stable. It doesn’t need to be as stable as the deep ocean, but if you have good market share in an established industry, with little macroeconomic fluctuation, and you’re happy with your overall performance, then go ahead and ignore innovation.
The rest of us probably need to be thinking about how to execute some great new ideas, and also how to get those ideas to spread.
In his book The Evolutionary World: How Adaptation Explains Everything from Seashells to Civilization,
The evolutionary dividends of a warmer world are attainable only if three conditions are met. First, populations must have ready access to a plentiful supply of necessary resources, so that when an imperfect innovation arises, it can linger in the population long enough to be improved by selection. If the population is allowed to grow under a permissive regime of of predictable plenty, not every deviant individual is purged from the population, and selection has enough to work with. Second, competition for locally scarce resources – the main agency of enemy-related selection – must be intense enough and consistent enough to allow improvements to spread in the population. Third, there must be sufficient evolutionary time – thousands to millions of years – to allow selection to do its work.
You can translate these rules of evolutionary innovation over to economic innovation:
- You need slack resources to innovate. This is why efficiency and innovation often come into conflict. As Greg Satell says, most innovation is crappy. Vermeij points out that imperfect evolutionary innovations need sufficient resources to keep them around long enough to be improved by selection. It’s exactly the same for economic innovations. They rarely work as planned at the start – they need feedback from customers, suppliers and others to really become good. That takes time and resources.
- Innovation works best when there’s competition. Even though there are extra resources around, there still needs to be competition to drive improvement. If the environment is too stable, like the Coelacanth’s, the lack of competition leads to no innovation.
- You need time to turn your crappy innovation into something excellent. Innovative ideas diffuse along an S-Curve, and it usually takes a lot longer for this to happen than we expect it to. Fortunately, economic innovations don’t need hundreds of thousands of years for this to happen, but the gap between having the great idea and seeing it adopted is still usually very long.
Innovation is an evolutionary process, and you can learn interesting things about this process by studying natural history. And the story of the Coelacanth shows us that there even times when you don’t have to innovate at all.
Innovation Through Subtraction
Posted by Tim in book riffs, design, evolving economic entities, selection on 1 January 2012
I don’t like focus groups. I’ve found the information that you get from them to be too shallow to be useful. However, this doesn’t mean that when we’re innovating we should just pursue whatever ideas drift across our minds.
Steve Jobs was quoted last year about how Apple doesn’t use focus groups. A number of people used this quote to justify being completely out of touch with their customers, which is a perversion of the main point. The reason that Apple can skip focus groups is that they are incredibly good at understanding what people are really trying to accomplish with technology.
To do this, you have to develop a deep understanding of what the core issues in your field are. Here’s an analogy:
There is a chapter by the scientist/artist Jonathan Kingdon in the excellent new book Field Notes on Science & Nature
In the age of instant digital photography it may seem perversely old-fashioned to put a value on the slow, primitive, and inaccurate techniques of manual drawing. Photography teaches us that the very act of putting a line around the edge of an observed object is an artifice. Such outlines rarely appear in photographs, or, for that matter, in nature, and yet… and yet? Contemporary research on the human brain shows that it does NOT process images as a neutral camera does. The brain finds edges and builds constructions that are at least partly based on previous experience 0 possibly including past contacts with artifacts such as “drawings” as well as previous knowledge of natural objects. Visual neurobiology is a discipline in its infancy, but it confirms that visual constructions are both complex and integral to cognitive development. This implies that even an outline sketch that bears little relationship to the so-called objectivity of a photograph might actually transmit information to another human being more selectively, sometimes even more usefully, than a photograph.
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If the brain is unlike a camera in actively seeking outlines, there is a strong implication that “outline drawings” (just to take a single type of visual expression) can represent, in themselves, artifacts that may correspond more closely with what the brain seeks than the charts of light-fall that photographs represent.
What does this mean in practice? It means that these drawings of a caracal by Kindgon may well transmit information to us that is more useful, more real, than what we could get from a series of photographs:
Those drawings do a great job of capturing something fundamental about the animal, as simple things often do. But to be able to draw them, you have to invest an enormous amount of time in observing the caracals, looking at what they do, in which contexts, to build up a deep knowledge of how their physical form expresses what they are trying to do.
You can’t ask a caracal (or even a house cat) what they are trying to express when they pin their ears back. But if you watch them long enough, the meaning becomes clear.
Now, customers can answer questions more clearly than a caracal. Usually, at least… But sometimes, this greater ease of communication actually makes it harder to understand what they’re really trying to achieve.
It’s not an accident that the Apple products look like art. The essence of great design is to be able to communicate simply by stripping down an object or a process to it’s fundamentals – which is the same problem with which artists grapple. This is filtering, and it’s how we deal with the avalanche of information which sometimes overwhelms us.
To innovate well, we need the same kind of deep understanding of our customers that artists have of their subjects. This allows us to strip our offerings down to their essence – innovation through subtraction.
(For more examples of some of the beautiful art in Field Notes on Science & Nature, check out this page from Wired.)
Two Reasons Why You Must Change Your Mind
Posted by Tim in evolving economic entities, experiments, time on 22 December 2011
One of the frustrating things about following politics is the idea, apparently deeply engrained, that you must never change your mind. If you do, you’re a flip-flopper, or wishy-washy, and you’re clearly not to be trusted.
The main problem with this line of thinking is that it is utterly and dangerously wrong. We live in a dynamic world, and our brains are dynamic – if you’re not changing your mind all the time, it’s a danger sign.
There are two very good reasons to change your mind: the facts have changed, or you have learned something.
Changing Facts
To those of us that take innovation seriously, Joseph Schumpeter is the patron saint of economists. He was the first person to really articulate the importance of innovation and how central it is to economic growth. Just to give you an idea of how important he is, here is a picture of picking out a new kitten last year, who is now named Schumpeter!
One question that Schumpeter considered in his first groundbreaking book, The Theory of Economic Development, is this: which type of firm is more innovative – small or large?
It’s a question he kept coming back to. Here is how Adrian Wooldridge put it in The Economist (and in another signal of the regard in which Schumpeter is held, his weekly column there is called “Schumpeter”):
Joseph Schumpeter, after whom this column is named, argued both sides of the case. In 1909 he said that small companies were more inventive. In 1942 he reversed himself. Big firms have more incentive to invest in new products, he decided, because they can sell them to more people and reap greater rewards more quickly. In a competitive market, inventions are quickly imitated, so a small inventor’s investment often fails to pay off.
Now, the big or small question is still interesting, but that’s not what I’m concerned with today. Instead, look at how he phrases this – “Schumpeter… argued both sides of the case.” This idea often comes up, and people usually try to say that Schumpeter was being slippery by trying to have things both ways.
But here’s the thing – Schumpeter changed his mind because the facts changed. In 1909, big firms didn’t innovate at all. The largest firms were mostly extractive. Nearly all new ideas came from smaller firms. Corporate R&D was just starting at the time, in Edison’s workshop and in the labs of the chemical companies that were trying to make new dyes for clothes.
A lot changed between then and the 1940s, including the innovation process. By the middle of the century, invention and innovation both were dominated by large corporate R&D. That was the birth of the mass market, an economic environment built by and favouring large firms.
Schumpeter changed his mind because the facts changed.
Learning Something
Here’s a quote attributed to John Maynard Keynes:
When the facts change, I change my mind. What do you do, sir?
One of the implications implicit in that quote is that Keynes was always right. Unfortunately, most of us aren’t as infallible as he was. So we have to learn by being wrong.
This is a crucial innovation skill. We have a hypothesis about how we can make the world a better place – we have a great idea. The only way to turn it into an innovation is to experiment.
Often, our initial assumptions are wrong. By experimenting, we figure out which ideas work, and which don’t – we learn. And by learning, we change our minds.
Dynamics Minds for Dynamic Times
We live in a dynamic world. More importantly, we are learning machines. Both of these facts mean that we should be changing our minds all of the time. Rather than being a sign of weakness, a changed mind is a sign of someone that knows something more than they used to.
We should be learning all the time. Changing your mind is a sign of learning. We shouldn’t avoid it, we should seek it out. As Edward de Bono says:
If you never change your mind, why have one?
Three Ways to Kill a Business Model
Posted by Tim in business models, evolving economic entities on 21 December 2011
How do business models get killed?
It’s an interesting question. I was talking about business models with Jason Potts last week and he said “maybe the definition of a mature industry is one where the business model has stopped evolving.” This suggests that it’s not technological innovation that changes industries, but rather business model innovation. So maybe old business models are murdered by new ones.
Adrian Wooldridge makes an interesting point about this in an article on innovation in universities in The Economist:
Lawrence Lowell, the president of Harvard, argued that “institutions are rarely murdered; they meet their end by suicide…They die because they have outlived their usefulness, or fail to do the work that the world wants done.” America’s universities quickly began “the work that the world wants done” and started a century of American dominance of higher education. They need to repeat the trick if that century is not to end in failure.
So a business model can die by suicide by failing to do the work that the world wants done. Or it can be killed if someone comes up with a better business model (something that universities should be thinking about right now). Often, these two forces work together to kill a business model.
But sometimes, maybe a business model can only be temporary. In response to my post The Property Ladder Theory of Bubbles, my student Mathieu Halley made a great point in the comments. He said:
The question that this raises for me is something of a counterpoint: I wonder what the worth of establishing a fixed term business is?
Is it potentially worthwhile to establish a firm and specifically plan from the beginning for it exist only for the duration of a particular bubble/growth period, instead of implicitly expecting it to exist forever?
I ran across a perfect example of this the other day: websites selling off overstock from luxury brands. There’s a terrific post on by Matthew Carroll on The Business of Fashion called The Rise, Stumble and Future of Gilt Groupe’s Business Model. The whole post is worth reading. Gilt Groupe was formed in 2007, and it was one of the first websites designed to hold flash sales of luxury remainders. According to Carroll, the timing was pretty close to perfect:
The timing of Gilt’s launch couldn’t have been better. In the months that followed, fashion and apparel brands began to feel the impact of a global recession that would ultimately give rise to one of the most challenging macroeconomic environments in the history of modern retailing. Seemingly overnight, wholesale inventories became unmovable as retailers drastically reduced product assortments and orders.
As a consequence, many fashion brands were forced to liquidate excess inventory positions, causing a sudden and significant supply glut for “cut out” goods. Prior to the Great Recession, brands would have sold this excess inventory through off-price channels like Loehmann’s, T.J. Maxx and Century 21. But as the economy sank, these retailers were asking for discounts as high as 90 percent, while merchandising clothes in a haphazard fashion which did nothing to protect the high-end image brands had spent years cultivating.
Gilt has done pretty well for itself. Revenue in 2010 was $425 million, they’ve built a strong customer list, and all of their metrics are going up. Sounds great, right?
However, there are problems. To support that level of revenue, Gilt needs increasing amounts of name-brand goods to sell at a discount. However, in light of their success, there are now many flash sale clothing sites around, and all of them need designer clothes to sell cheap. And there aren’t that many cheap designer goods around.
Here is how Carroll frames the problem:
An anecdotal comparison of the brands and products available on Gilt today versus those available in the company’s first couple of years shows that, over time, quality level has gone down. Back in 2009, it was possible to find prestige brands like Ralph Lauren Purple Label and Porsche Design on Gilt, in stark contrast to the many unknown brands that populate the site today. This meant that each time a subscriber opened an email and the product did not communicate the excitement-to-value ratio that had originally made Gilt so successful, their inclination to open subsequent emails from Gilt, and the brand’s position as a curator of style, suffered.
He has some excellent suggestions about how to improve things for Gilt (and for the flash sale sites in general), and they could well work.
But what if this business model only really had a lifespan of 5 years? The early success was built on unusual market circumstances – you could call it a cheap luxury goods bubble. Sometimes we get exciting new business models out of bubbles that have long-term success. But sometimes the best thing you can do in a bubble is sell off at the right time.
I don’t know what the answer is in this particular case. But I do think it’s worth starting to think about the lifecycle of business models, regardless of your industry.
That’s three ways then that a business model might be killed: murder, suicide, or natural causes. Which is yours most susceptible to?
(The picture of the Gilt Groupe warehouse if from Fantabulously Frugal)
How to Make Things Look Simple
Posted by Tim in evolving economic entities, time on 7 December 2011
Here’s a story I’ve told a couple of times now:
One of the best live shows that I saw during my university days was Beat Happening and Girl Trouble. All of us were a long way from home in Washington when I saw them in New Jersey. While Beat Happening was playing what I thought was a pretty mesmerising show, my friend Tom leaned over to me and said ‘we could do that.’ I looked at him for a long time, then said ‘but we don’t, do we?’
Part of what was going on there was that Beat Happening made things look incredibly simple. As the success of Apple shows, simple is good. People like simple. But the Apple example also shows that you have to work awfully hard to make something complex seem simple. You need to work your way through simplistic and complex before you get to simple.
How can you do this?
The secret to making things look simple is to build a deep understanding of the system.
There was another example of this in the fantastic exhibition of drawings by Matisse that just opened at the Gallery of Modern Art here in Brisbane (and if you’ll be in Brisbane between now and March, I strongly recommend seeing it).
Here is a picture that I took at the exhibition (just before the guard yelled at me for taking pictures):
To paint one of his masterpieces, he did 3000 sketches first, over a nine year period. 3000!
So one way to make things look simple is to do them a lot, for a long time.
At the end of his career, Matisse started a series of work that he called themes and variations. These consisted of series of line drawings of the same subject. He did these by first making the theme drawing. He did both models and still lifes, and in each case he spent many hours on this theme drawing over a number of days. The point of this was to gain a deep understanding of the subject, and to figure out what elements were the most important. Here is one he made for a series of variations of his granddaughter – at this point it doesn’t look much like art:
The thing that he was trying to do was to capture the fleeting expressions that people have, which he believed revealed their personalities. This is very hard to do with a painting. So after sinking all of that time into building the theme drawing, he would very quickly do line drawings like this:
Simple, right?
But he could only do things that looked this simple after investing many hours into learning the subjects. And he only developed this method after 50 years as an artist. The key to this simplicity is the deep understanding that he built over all those years and all those iterations.
One of the keys to innovating is to make something novel that seems obvious once you show it to people. It is a creative enterprise. Making it seem obvious often means making it simple.
The challenge here is that simple is pretty hard. It takes time, it takes learning, and it takes skill. But if you get it right, the rewards can be great.
Here is a great quote from Ira Glass of NPR that I ran across yesterday which sums it up:
Learning From Failure
Posted by Tim in book riffs, evolving economic entities, experiments on 2 November 2011
What’s the biggest new product launch failure ever? The biggest I’ve seen was New Coke, but the example that often springs to mind is the Ford Edsel.
Ford put a lot of effort into the Edsel. They had lagged behind GM for a few years, and the Edsel was supposed to put them back in front. Ford sunk a lot of time and effort into product innovation for the Edsel, and into market research as well. They launched one of the biggest marketing campaigns ever.
And the Edsel sold miserably.
Steven Johnson has followed up Where Good Ideas Come From (discussed here) with another book on innovation, this time, an edited volume called The Innovator’s Cookbook. The first chapter is by Peter Drucker, who remains one of the best management thinkers we’ve seen.
Drucker outlines seven sources of innovation opportunity: unexpected occurrences, incongruities, process needs, industry & market changes, demographic change, changes in perception and new knowledge. The essay was originally published in Harvard Business Review, and one way or another, it’s worth tracking down to read.
In discussing unexpected occurrences, Drucker has an interesting take on the Edsel story:
Everyone knows about the Ford Edsel as the biggest new-car failure in automotive history. What very few people seem to know, however, is that the Edsel’s failure was the foundation for much of the company’s later success. Ford planned the Edsel, the most carefully designed car to that point in American automotive history, to give the company a full product line with which to compete with General Motors. When it bombed, despite all the planning, market research, and design that had gone into it, Ford realized that something was happening in the automobile market that ran counter to the basic assumptions on which GM and everyone else had been designing and marketing cars. No longer was the market segmented primarily on income groups; the new principle of segmentation was what we now call “lifestyles.” Ford’s response was the Mustang, a car that gave the company a distinct personality and reestablished it as an industry leader.
In other words, Ford learned from the failure of the Edsel. Here is how Matt Haig describes it in Brand Failures:
As Sheila Mello points out, between 1960 (when the Edsel was phased out) and 1964 (when the Mustang was launched) Ford, along with most of the car industry, had shifted its focus towards what the consumer actually wanted. ‘The success of the Mustang demonstrates that Ford Motor Company did learn from the Edsel experience,’ she writes. ‘The key difference between the ill-fated development of the Edsel and the roaring success of the 24 Brand failures Mustang was the shift from a product-centric focus to a customer-centric one.’
Here are some key points from this story:
- Failure is only useful if we learn from it: we often talk about the need to fail in innovation, however, there is only value in failure if it helps us learn.
- Try to fail as cheaply as possible: the main problem with the Edsel isn’t that it failed – it’s that it failed so expensively. There is a hierarchy of failure, and we need to figure out how to fail as early in the process as possible. One way of doing this is through prototyping.
The lesson from the Edsel is to learn from ideas that don’t work. And also, if you’re knocked over, get back up…
Innovation Obstacle: Bureaucracy?
Posted by Tim in book riffs, evolving economic entities, innovation on 21 September 2011
What is the innovation that led to civilization?
There are some interesting answers to this question in Why the West Rules, For Now by Ian Morris. As part of his research, Morris has developed a Social Development Index, which he uses to track the progress of civilizations from 14000 BC to present. The index tracks improvements in areas such as energy capture (both as food and as fuel), organizational capability, technology development, and information sharing capacity.
Here is what the graph shows (taken from this .pdf that summarizes the research):
The first big jump happened between 2000 and 1000 BC, indicated by the very crude arrow that I’ve added. What was the innovation that caused that jump?
The invention of Bureaucracy.
Morris (and many other historians) argue that it was the invention of bureaucracy that actually triggered the development of agriculture, written communication, and other tools that are necessary for people to undertake complex tasks.
Bureaucracy is one of the most important innovations in human history – without it, we’d still be in caves. So why does it get such a bad rap whenever we talk about innovation? It’s nearly impossible to discuss innovation within organisations without hearing complaints about bureaucracy and bureaucrats.
The problem isn’t actually with bureaucracy. Bureaucracy makes systems, supports the development of routines, and gives us some constraints – which are actually essential to innovation (see here and here for examples). We need all of these things to innovate.
The problem with bureaucracy is when we follow rules simply for the sake of following rules. This is another form of path dependence, which leads to lock-in on sub-optimal systems. The problem is with bureaucratic systems that don’t support strategy – these stifle innovation.
Bureaucracy is actually a neutral term, like aerodynamics. To call a car “aerodynamically designed” is a nonsense – all cars have aerodynamics. It’s just that Teslas and Porsches have excellent aerodynamics, while minivans and SUVs have terrible aerodynamics.
In the same way we can have excellent bureaucracy, which supports innovation, and terrible bureaucracy, which obstructs innovation.
Bureaucracy isn’t actually an innovation obstacle, but bad bureaucracy is.
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Tim was named #5 in the Top 40 Innovation Bloggers in 2011 at Innovation Excellence.
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