Archive for category experiments
Innovation is Impossible
Posted by Tim in book riffs, experiments, variety on 5 January 2012
James Altucher recently suggested that “Eat All You Want of the Foods You Love and Still Lose Weight” would be a great book title – that no matter what was inside, it would sell. It’s easy to see why. Many of us like to eat all we want of the foods we love, and we also want to lose weight, so if we could do both at the same time, wouldn’t that be great?
Well, maybe.
In his new book Relentless Innovation: What Works, What Doesn’t–And What That Means For Your Business
Everyone understands from the beginning how difficult it is to create compelling new ideas in any sutation, uch less to convert those ideas into viable products and services. To compound the difficulty, executives are asking for disruptive ideas while expecting the business to continue to operate at full effectiveness and efficiency. Middle managers receive these messages and understand the unspoken dichotomy in the request: create radical, valuable new products and services but don’t upset the status quo.
Phillips nails the problem – many firms want an innovation program create radical, valuable new products and services but don’t upset the status quo.
If that’s what you want, innovation is impossible.
Relentless Innovation is a very good book. One of the key points that Phillips makes is that one of the major obstacles to innovation is the emphasis that many firms have on efficiency. You can innovate to become more efficient, and many firms do this well. However, to be successful over time, you also need to develop new products and services, and you can’t do this just through efficiency.
Here is a big part of the reason for that. Efficiency is all about reducing variation. When you’re a manufacturer, and you’re using statistical process control to improve the quality of your products, then this is great.
However, innovation that creates new products and services, requires increased variation. You have to try things that you’ve never done before, experiment, fail, learn, and get feedback from customers. This is the diametric opposite of increasing efficiency. Here is how Phillips puts it:
You must shift your thinking to recognize that experimentation and prototyping is as much about discovery and new insights as it is about validation of internal perspectives and theories. Your firm must make it far easier to test ideas, gain new insights, and “fail forward.”
In addition to increasing your experiment rate, Relentless Innovation includes a number of other practical steps you can take if you find yourself in a situation where innovation is impossible (you can check out Jeffrey’s blog too for more – Innovate on Purpose).
To innovate well, you have to become comfortable with disturbing the status quo. Deborah Mills-Scofield addresses this very well in a recent post – listing status quo objections to innovation and good response to each.
You also have to be able to maintain a focus on efficiency while also generating great new ideas. Efficiency reduces variation, but great new ideas increase variation. This is another of the ten tensions in innovation that must be balanced. In each of these situations, you need to think “both-and”, rather than taking an “Either-or” approach.
If you want to innovate without changing anything, then innovation is impossible. To get around this problem, you need to align innovation with your strategy, and build a capability for innovating consistently within your organisation. It’s not easy, but it is possible. Relentless Innovation gives us some good ideas about how to do this, and that makes it worth a read.
Note: If you want a more conventional review of the book (I’m lousy at reviewing), check out this one by Jorge Barba.
Disclaimer: I know and like Jeffrey, and I received a free pdf of the book. I also bought my own copy. I’m writing about the book because of its quality, not because of who wrote it or how I got it.
Innovation Obstacle: Gumption Traps
Posted by Tim in book riffs, experiments on 29 December 2011
Imagine that you have a great idea for how to make things work better at your job – it shouldn’t take too much effort, I’m sure you have plenty. Now think about an idea like that you had, but never acted upon – what happened? You probably thought of all the obstacles to executing the idea. People won’t go for it, they hate change, my boss won’t let me try it out, the organisation is too risk-averse, I didn’t get any recognition or support for the last idea I had, and so on. So you decided that the situation wasn’t really that bad, you could live without improving it if you really had to.
You just fell into a gumption trap.
Gumption Traps
Joe McCarthy talks about Gumption Traps in a series of typically excellent posts. The idea comes from Robert Pirsig’s Zen and the Art of Motorcycle Maintenance: An Inquiry into Values. Here is what Pirsig says about gumption and Gumption Traps:
I like the word “gumption” because it’s so homely and so forlorn and so out of style it looks as if it needs a friend and isn’t likely to reject anyone who comes along. I like it also because it describes exactly what happens to someone who connects with Quality. He gets filled with gumption.
A person filled with gumption doesn’t sit around dissipating and stewing about things. He’s at the front of the train of his own awareness, watching to see what’s up the track and meeting it when it comes. That’s gumption.
…
Throughout the process of fixing the machine things always come up, low-quality things, from a dusted knuckle to an accidentally ruined “irreplaceable” assembly. These drain off gumption, destroy enthusiasm and leave you so discouraged you want to forget the whole business. I call these things “gumption traps.”
There are hundreds of different kinds of gumption traps, maybe thousands, maybe millions. I have no way of knowing how many I don’t know. I know it seems as though I’ve stumbled into every kind of gumption trap imaginable. What keeps me from thinking I’ve hit them all is that with every job I discover more. Motorcycle maintenance gets frustrating. Angering. Infuriating. That’s what makes it interesting.
I highly recommend reading all of McCarthy’s post on this, but here is part of what he says about Gumption Traps:
Pirsig uses motorcycle maintenance as a metaphor for life, and explores a variety of gumption traps – externally induced out-of-sequence reassembly, intermittent failure and parts problems as well as internally induced traps arising from value rigidity, ego, anxiety, boredom and impatience – and ways of addressing and overcoming them.
In innovation, we have both internal and external Gumption Traps.
How to Avoid Gumption Traps
There are a few things that we can do to avoid Gumption Traps. The first is that we have to be doing something that we believe in. This provides powerful motivation to act on our ideas. As is often the case, Hugh MacLeod captures this idea perfectly:
There are also some very useful steps to follow in Nine Things Successful People Do Differently
The nine things are not really surprising, but they are powerful. The one that most directly addresses the Gumption Trap is number 6: Have Grit:
Grit is a willingness to commit to long-term goals, and to persist in the face of difficulty. Studies show that gritty people obtain more education in their lifetime, and earn higher college GPAs. Grit predicts which cadets will stick out their first grueling year at West Point. In fact, grit even predicts which round contestants will make it to at the Scripps National Spelling Bee.
The good news is, if you aren’t particularly gritty now, there is something you can do about it. People who lack grit more often than not believe that they just don’t have the innate abilities successful people have. If that describes your own thinking …. well, there’s no way to put this nicely: you are wrong. As I mentioned earlier, effort, planning, persistence, and good strategies are what it really takes to succeed. Embracing this knowledge will not only help you see yourself and your goals more accurately, but also do wonders for your grit.
Grit and Gumption are pretty much the same thing. Grit is an important part of innovation. Grit helps us learn from experiments that fail, instead of despairing. Grit helps us push our ideas even if the boss doesn’t directly support them.
Grit helps us change the world, if that’s what we’re trying to do. And we should be.
The next time you face a Gumption Trap, if you’re not finding a way around it, think of Halvorson’s nine ideas. They can help you change the world.
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?
The Exigency of Extrapolation
Posted by Tim in complex systems, experiments, selection on 12 December 2011
Noun 1. exigency – an unstable situation of extreme danger or difficulty;
I’ve had some jobs in which I’ve performed pretty well, and some where I haven’t been quite so good. Probably the worst job I’ve ever done was part of my portfolio when I was managing sales & marketing for a polytechnic in New Zealand. The specific job was new course evaluation.
We put in a modified stage-gate type process to evaluate potential new courses. It was my job to fill in the numbers. The one number that drove everything else was the expected number of students. If the expected number of students was high, we’d try to run the course. If not, we’d kill the proposal.
I developed a very elaborate model, based on historical data. I knew how many enquiries we could generate from advertising, how many of those we could convert into applications, and how many enrolments we got per application. In fact, figuring out these numbers was one of the biggest innovations that I executed there, and this model was of tremendous use in trying to figure out around November how many total students we could expect at the start of the new school year the next February.
However, the model was terrible at predicting new course enrolments. Why? In large part, because we’re really lousy at figuring out how something new will perform. We rejigged our new course approval process after I pointed out that we hadn’t approved a single new offering in over 6 months – our process was killing everything.
I was originally going to call this post The Perils of Prediction, but Greg Satell beat me to that title. Also, the specific problem that I’m talking about is really extrapolation. You should read all of Greg’s post, but here’s part of what he says:
The problem starts when smart people in nice suits and lab jackets proclaim that “the data says…” In truth, the data never says anything. We interpret it in one way or another and there are lots of ways to interpret it incorrectly.
Data is, after all, messy. It doesn’t spring forth whole, but must be collected in some way. We count, measure, survey, aggregate, slice and dice, picking up errors all the time. We need to make choices about which data we want to focus on and which fades into the background.
How do we deal with this? Usually by finding some numbers from the past and extrapolating them. However, there are a few problems with this approach, including:
- We tend to think in straight lines, but there aren’t any straight lines in business: that’s really the point being made by the xkcd cartoon. Taking a straight line and extrapolating it into the future almost never gives us the right answer.
- It’s really hard to tell what kind of curved line we’re on: this complicates things too. Even when we have historical data, it is nearly impossible to figure out what kind of engine is generating the output. Take a look at this data from an interesting post on climate change:
Is it likely that the data will progress in a straight line? Or will it level out at some point? Or will it increase exponentially? We don’t know. But when we’re predicting, it pays to consider what circumstances might lead to each of these outcomes.
- Even when things are accelerating quickly, they tend to level out: innovations spread through an s-curve, and this is a very common pattern in business.
This is one of the issues with everyone talking about the singularity – it assumes that exponential growth will continue forever. It might, but usually exponential growth levels out, and then it looks like an s-curve.
- However, by the far the biggest problem with extrapolation is that if we depend on extrapolation for predicting, we will never anticipate something new happening: extrapolation can only predict that things in the future will be mostly like things in the past. Here’s how Greg puts it:
And that’s what most analysts miss. The future is hard to predict not just because of our cognitive biases or inexplicable natural events, but because we have the power to make our own future.
The first new course that we approved at my Polytechnic after we scrapped the stage-gate process was a program that offered free computer and internet lessons to people in the community, particularly targeted at older adults. And the number of enrolments that we got went so far beyond anything that we had ever seen before that it was almost impossible to believe.
None of my models could have predicted that. When we innovate, our job is to invent the future. The exigency of extrapolation is that if that is the tool we use to predict, we won’t be able to invent anything that doesn’t already exist. And what kind of innovation is that?
What is Influence, Really?
Posted by Tim in connect, experiments, networks on 11 December 2011
One of my colleagues is doing research on social network use, and she asked me to help get people to take her survey. It takes about 8 minutes to fill it in. I was glad to help, and to do it, I set up a test.
First I posted the link on my Facebook page and asked my friends to take the test. About 20 out of 188 did so.
A few days later, I posted a link on Twitter, and asked everyone following me to take the test. Another 20 did, out of around 3000.
And now, here’s an interesting question: how do you blog readers stack up against my Facebook Friends and Twitter Followers? My bet is that you’ll win – to prove me right:
Click here to take the survey yourself!
The contrast in results between Facebook and Twitter illustrates some important lessons about influence. A lot of people have been talking recently about how to best measure online influence. Like innovation, influence is another thing that is awfully hard to measure.
One big problem is that influence is pretty hard to define in the first place. What does it mean? To me, influence is about getting people to take action. If that’s the case, you might think that I am lot more influential on Facebook (where about 11% of the people on my list of friends took the survey) than I am on Twitter (where about 0.7% of the people on my list of followers took the survey).
But I’m the same person – so am I influential or not?
One of the best thinkers around right now on the topic of influence is Valeria Maltoni – here is what she says about Klout’s attempt to measure influence:
I can tell you that Klout knows squat about me and my behavior. Zero, nothing, niente, nada. Got it? The fine folks behind the algorithm have no idea of who gets my emails and calls, which are the tools I use most to conduct my real business.
They know nothing about what I read and why I read it, because they are not reading these articles or talking with me. They are just tabulating the keywords and volume of my Twitter activity. Twitter. Shrink me into 140 characters. Or maybe they are 134 more than those in Pirandello’s play (more context was the lesson there, it is here, too).
Are the people in my life even on Twitter? You don’t know that.
Am I the person you read here every day? (And I thank you humbly and sincerely for reading and thinking about this content.) You are not just the person who is reading. You are much more than one thing you do, so why would I be just the person who is sharing here?
Martijn Linssen has done a lot of good work assessing the success of Klout in measuring influence.
This experiment illustrates some important points about influence:
- You can’t reduce a complex phenomenon to a single number: influence happens in person, online, with people we know well, and with people we’ve never met. This makes it very tricky to measure. This leads to:
- Don’t mistake the metric for what you’re trying to measure: the real problem with things like Klout is that once we have a metric, people will start trying to game the metric. You can do this, but it doesn’t increase your actual influence. The only way to do that is to do things that have a strong, positive impact on people, and to do it consistently. That’s a system that you can’t game – and if you focus too much on managing the metric, you’ll actually get worse at the thing that really matters.
- Influence really happens in networks: Duncan Watts has done a lot of excellent research that shows that the main thing that causes ideas to spread within networks is the extent to which the people in the network are likely to spread the idea. Here is how he put it in a recent post:
When we hear that a raging forest fire has consumed millions of acres of California forest, we don’t assume that there was anything special about the initial spark. Quite to the contrary, we understand that in context of the large-scale environmental conditions — prolonged drought, a buildup of flammable undergrowth, strong winds, rugged terrain, and on so — that truly drive fires, the nature of the spark itself is close to irrelevant.
Yet when it comes to the social equivalent of the forest fire, we do in effect insist that there must have been something special about the spark that started it. Because our experience tells us that leadership matters in small groups such as Army platoons or start-up companies, we assume that it matters in the same way for the very largest groups as well. Thus when we witness some successful movement or organization, it seems obvious to us that whoever the leader is, his or her particular combination of personality, vision, and leadership style must have supplied the critical X factor, where the larger and more successful the movement, the more important the leader will appear.
- Consequently, understanding how ideas spread through networks is essential to understanding influence: this is an idea that Greg Satell has incisively written about. Here’s what he says:
In effect, starting an epidemic is similar to a broadcast search. You are better off casting your net as widely as possible and reaching influential people as well as less influential ones. (See this article for more about broadcast and directed network searches)
Some paths will fail, but the more paths you initiate, the more likely that your idea will infect those who are susceptible to it. Just like delays at any airport can affect large hubs, influence can originate anywhere in social networks.
So the real answer to the question of whether or not I’m influential is: yes. Or no. Or maybe. The one thing that we can say is that my Facebook friends seem to be a lot more willing to act on a request for help than my twitter followers are. But this again is a network effect, and doesn’t actually have that much to do with me personally. The connections on Facebook are different, and people use that network to meet objectives that differ from those that Twitter users are trying to achieve.
Influence is very important, but measuring it is hard. The best way to increase your influence is to keep producing ideas that help people.
Also, if you could retweet this, that would be cool – it would really help my Klout score…
(just kidding – I’d much rather have you fill in Sabine’s survey – and the number of people that have gone to the survey from here is now higher than we got from either Facebook or Twitter!)
(that’s The Minutemen playing their great song Take Our Test)
When Was the Last Time You Were Wrong?
Posted by Tim in experiments, time on 9 December 2011
Here’s just one of several examples from me today – I was completely wrong about the talk I gave this morning. I sent the slides through to the organisation I was giving it for on Wednesday. Then I spent the entire 90 minute drive down to the venue re-thinking what should go in the talk.
I thought of about 10 slides that I had to add, and I was sure that if I didn’t add them, the talk would be a disaster.
When it was time to set up, I looked on my usb stick to find the other talk that had the additional slides on it, but it wasn’t there. I had to go with my original ones.
So I did. And it ended up being the best public talk I’ve ever given.
I was completely wrong on the drive down about what had to change.
There all kinds of mistakes that we can make. We can overthink something like I did, or we can underthink it. We can try something that doesn’t work, or we can let fear keep us from trying something that would work. It was fear at work with me this morning. I had a talk that was quite different from others that I’ve given, and I wanted to add in some familiar slides so that I’d feel more comfortable. If I had, it would have ruined the talk. It’s good that I tried out the new talk – even if it hadn’t worked, I’d've learned something that would make the next one better, which wouldn’t have happened if I had gone with one of my standard talks.
Scott Berkun posted a great quote from Woody Allen from the American Masters documentary on him:
There are a lot of surprises that happen between writing it, doing it, and seeing it on the screen, most surprises are negative. Most surprises are that you thought something was good, or funny, and it’s not. I’ve made just about 40 films in my life and so few of them have really been worth anything. Because it’s not easy – if it’s easy it wouldn’t be fun, it wouldn’t be valuable.
The key point that I take from this is that we have to execute our ideas to see if they’ll work. The whole point of innovating is to experiment. Try something, find out what works, and learn from what doesn’t.
There always will be surprises, and not everything will work out as you plan. In fact, almost nothing will work out as you plan. That’s why we have to actually try things, because that’s the only way to find out what will actually work.
When was the last time you were wrong? I hope it was recently.
(The awesome photo is from flickr/elycefeliz under a Creative Commons License).
The Jenga Theory of Creativity
Posted by Tim in complex systems, experiments on 8 December 2011
I think I actually made yesterday’s post on simplicity too complex. Here’s another try.
Earlier this week I edited two different papers for journals. My main contribution was that I cut 2,000 words out of each. I also wrote about 400 words in each, but it was the cutting that helped the papers.
This reminds me of the drawings by Matisse I talked about yesterday – he was more interested in what he could take out than what he should put in. The key question that he asked was: what is the minimum number of lines that I need to capture the essence of what I’m drawing?
Creativity is often about subtraction as much as it’s about addition – it’s really like playing Jenga. You need to pull out as many pieces as possible while still retaining the shape of the idea that you’re working on.
Or, as Austin Kleon put it his great post How to Steal Like an Artist:
The key issue is how do you know what to take out? That is where experimentation, failure and learning come in. The only way that you identify the essential pieces to keep in is through testing (prototyping). Here is how Joe McCarthy (please go read his blog, it’s awesome) put it in a comment:
And just to bring it full circle, while I agree that getting it right requires learning and skill, I believe that learning and skill often arise primarily through making lots of mistakes (i.e., being wrong alot … but with an open mind).
And that’s what I’m trying here. I gave it a go yesterday, I’m not sure if it worked, so I’m trying a different way today.
If I keep working on it, eventually I’ll get it right.
The way to make something simple is to cut out all the extra bits. But you can only know what to cut when you have a deep understanding of the system in which you’re working. That’s the Jenga Theory of Creativity.
(Jenga picture from flickr/riNux under a Creative Commons License)
The Most Important Innovation of All Time
Posted by Tim in complex systems, experiments, innovation on 23 November 2011
What is the most important innovation ever?
There are plenty of candidates. Fire, the telegraph, electricity, and the internet would all have to be candidates.
There’s another one though, that has had an enormous impact on every single one of us. And surprisingly, it’s not a whiz-bang piece of technology. It’s a simple process innovation.
The most important innovation of all time is: medical practitioners washing their hands before they touch patients.
Hand washing has been an unbelievably important medical breakthrough. It is one of the main reasons that we actually live long enough to retire now.
As with many great innovations, hand washing started with a scientific discovery – the germ theory of disease. And as with some innovations, the theory was driven by beer. Louis Pasteur’s work was motivated by brewers who couldn’t figure out why some batches of beer fermented well, while others failed. So in trying to make better beer, Pasteur made us all healthier.
There are some critical innovation lessons here:
- Ideas need to be executed to create value: the germ theory of disease is an important scientific breakthrough, but a theory isn’t an innovation. Theories are often great ideas, but to become an innovation they have to be turned into something that can be executed to create value. Germ theory led to many important innovations: pasteurization, antibiotics, and hand washing. These innovations have had impact on a wide range of industries and activities, and that is where the value has been created.
- Innovation isn’t just about new technology: hand washing in hospitals isn’t a sexy new piece of technology (which is maybe part of why it’s still hard to get everyone to do it consistently). Hand washing is a process, and process innovation can be incredibly important. Just think about the assembly line, lean management, or agile software development. All are process innovations, all are important, like hand washing.
- Small innovations can have enormous impacts: one feature of complex systems is that small changes can results in gigantic change. That’s what happened with hand washing. This new process has made childbirth much safer, it improved the success rate of all surgeries, and it greatly reduced the chance of secondary infection in medical procedures. And it’s about the simplest thing imaginable!
So the next time you wash your hands before eating, think about what a great breakthrough you’re participating in. And when you’re thinking about innovation, remember that it’s often the smallest ideas that can make the biggest difference.
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…
There’s No Such Thing as a Good Idea…
Posted by Tim in experiments on 25 October 2011
Experimenting is a key part of innovating. In his new book REAMDE, Neal Stephenson has a great description of learning through experimenting:
Much like a teenager who starts playing a new video game without bothering to open the manual, he tried things and observed the results, abandoning whatever didn’t work and moving aggressively to exploit small successes. A profusion of ideas spewed forth from his mind. There was no such thing as a bad idea, apparently. But, perhaps, more important, there was no such thing as a good idea either, until it had been tried and coolly evaluated. It was clear how he had become the leader of a sort of gang back home: not by asserting his leadership but by being so relentless in his production, evaluation, and exploitation of ideas that his friends had been left with no choice but to form up in his wake.
It’s a great quote, and there are several crucial points about innovation in it:
- Prototype everything: the character being described was learning how to sail a boat after being left adrift. He did this by prototyping. We can prototype any type of innovation – a new product, a new service, or a new business model. Actually, it’s not just that we can prototype everything, it’s that we must prototype everything.
- We can win by experimenting faster: this is the principle drives John Boyd’s OODA loop. OODA is a method for winning in complex environments. It stands for Observation; Orientation; Decision; Action. Boyd’s idea is that if you go through this process faster, you will gain a competitive advantage. He developed the model to help fighter pilots, but it has been shown to work in business as well.
- There’s no such thing as a good idea, until it’s been tested: an unexecuted idea has no value at all. It’s not a good idea until we know if it will work or not. It’s a simple point, and an important one, and it’s often overlooked.
Stephenson has outlined an outstanding innovation strategy: prototype everything, experiment as quickly as you possibly can, and don’t think you have a good idea until you’ve tested it. Three steps for innovation success.
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