GUEST POST from Tim Kastelle

It’s much better to think of innovation as a process than to think of it as an event.  I think about it as the process of idea management inside an organisation.

This means that in order to innovate effectively, you not only have to generate great ideas, but you have to select the ones that you want to invest in, then execute them, figure out how to keep people inside the organisation committed as you go through the process, then get the new ideas to spread out in the world. And if one part of that process goes wrong, then your innovation efforts will likely fail.

That’s kind of scary.

One of the tools that I use to help organisations assess where they are is the Innovation Value Chain – which helps assess how effective an organisation is at each step.

When you start measuring, it turns out that organisations rarely suffer from not having enough good ideas. I’ve had my MBA and Executive Education students assess their own organisations for a few years now. They have analysed more than 200 organisations, which cover nearly every type that you can imagine: big multinationals, small 1 or 2 person firms, for profits, not-for-profits, government agencies, schools, churches, high tech firms, low tech firms. Out of those 200+ organisations, fewer than 10 have idea problems.

That’s less than 5%! The other 95% are split pretty evenly between having problems with selection and development, or with sustaining and diffusing.

Here’s a practical example. I did two different Exec Ed classes for one firm this year. The first one with a group of senior managers, and the second was with a group identified as future leaders of the firm. Here are the results of their innovation value chain analyses for the firm:

The scores are the average for each group, and low scores are better. If there is a score of 5 in a category, then the firm is as good as they could possibly be, but if the score is 15, then they have major problems.

I surveyed the senior leaders in March, and their scores on the right. The steps are ranked from 1-5 in red, with 1 being their strongest area, and 5 being their weakest. As you can see, idea generation is by far their strongest area. They have problems with Selection and Implementation.

I ran the survey with the young leaders a couple of months later. I was a bit worried – what if their results were completely different? Astonishingly, they listed the five steps in exactly the same order! Idea generation best, Selection and Implementation the worst. This makes me feel better about the validity of the tool.

There’s one noticeable difference though – the rankings for the young leaders were worse across the board than those of the senior managers. What do you make of that? After spending a week with each group, my conclusion is that the young leaders feel much less empowered. The senior managers score things relatively well because they feel in control of the situation. The younger group does not. This kind of gap between senior managers and line workers is a sign of a broken innovation process.

So what should they do? Obviously, there are cultural issues to address. But in terms of managing innovation as a process, there are a few options. A couple of years ago, the Australian Public Service Management Advisory Committee put together a great report called Empowering Change: Fostering Innovation in the Australian Public Service. This includes an appendix that has a quiz you can use to evaluate your innovation value chain, along with a set of actions you can use to improve each part of the process.

Their summary table looks like this:

So here is how to use this tool:

1. Evaluate where you are right now. Use the quiz to identify your current strengths and weaknesses in the innovation process.
2. Find the weakest link.
3. Choose some actions that are designed to improve your weakest area, and execute them. The MAC report includes brief descriptions of all of the tools.  The execution bit is obviously very important.
4. Give it some time to see an effect.
5. Remeasure. If you’re doing it right, then your first weakest link should improve. So after the remeasure, figure out where you’re weakest now, then:
6. Iterate!

For this to work you will need to have any extra cultural issues sorted. However, if you do this, it is a systematic approach to improving your innovation process.

Organisations that are score high on Innovation Competence in The Innovation Matrix usually do well at all five parts of the innovation process. A well-managed process is one of the key measures of competence.

I will put an online version of the quiz up sometime in the near future. When I do, you can use it to test your own organisation’s innovation management process. Or, if you’re anxious to get going sooner, you can download the public sector report and use the quiz in it. In either case, I hope you find this tool to be useful!

Just remember that innovation is still a people process – don’t depend on tools alone to save you.

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GUEST POST from Tim Kastelle

The Biggest Innovation Obstacle: Fear of failing is one of the biggest innovation obstacles around.

Within organisations, mistaking ideas for innovation is the most common innovation mistake that I come across. In part, this is due to fear of failing. If your idea is never executed, then it can’t fail, right?

The problem is that if the idea is never executed, then it will never succeed either. As Wayne Gretzky said, “you miss 100% of the shots you never take.”

I’m currently reading Brené Brown’s superb book Daring Greatly, and it’s giving me some great insight into this.

Lessons From My Biggest Screwup:

Before that, though, let me tell you a story.

I was a pretty good student in high school, and I was pretty excited when I was accepted by Princeton. Up ’til then, I defined myself by how well I did in school.

So I felt a great deal of shame when I failed out halfway through.

There were plenty of reasons that I did (and everyone’s first guess, partying, was definitely not one of them!), but the main reason was that I was scared to try my hardest and fail. Instead, I didn’t try much at all – I sabotaged myself. It gave me the illusion of control, but it also made me deeply unhappy.

To my amazement, it wasn’t as disastrous as I thought it would be. I went back to live with my parents for a couple of years, and worked in a feedmill. I saved enough money to pay for finishing up college myself, and when I was readmitted to Princeton, I did pretty well, and graduated.

I learned a few important lessons from all of this. The first is that it is foolish to define ourselves by how we’re viewed by others. In the end, trying to be “the good student” wasn’t a very good strategy. Here is what Brown says about this in the book:

“What we all share in common—what I’ve spent the past several years talking to leaders, parents, and educators about—is the truth that forms the very core of this book: What we know matters, but who we are matters more. Being rather than knowing requires showing up and letting ourselves be seen. It requires us to dare greatly, to be vulnerable. The first step of that journey is understanding where we are, what we’re up against, and where we need to go.”

I wasn’t willing to be vulnerable – rather than try and maybe fail, I just didn’t try.

The second lesson is that you don’t learn the important things in the classroom – you learn them by doing. Instead of partying, the main thing that I did while avoiding my schoolwork was spend time at the campus radio station. I was a DJ, and ended up holding bunch of different management positions there.

DJing went most of the way towards getting me over the painful shyness that plagued me in high school. And I learned an unbelievable amount about managing (and about myself) while helping to run the station. Meanwhile, my time at the mill kicked most of the remaining arrogance out of me, and taught me a lot about resilience as well.

I’ve only learned the last lesson recently – and that is that everything that I have done and experienced has made me who I am – and I need to draw on all of it if I am going to achieve the things that I’m aiming for. Here is how Nilofer Merchant put it in her post Why I’m Glad I Got Fired – one of the inspirations for this post:

“But just as my success led to failure, my failure led to success. Thinking more and more about these questions, I started a consulting practice that ultimately blossomed into a multi-million dollar business, with the idea that having a great strategy wasn’t enough to win. If we didn’t also address the organization’s ability to change, to behave differently, to believe in the new direction itself, then any good idea would simply fail. Strategy without an adaptive context to absorb the idea into its fiber would fail. Winning once wasn’t enough — organizations had to build the ability to co-create solutions and thereby win repeatedly.

I had changed. I had changed from being an accomplished, smart, results-oriented person with the corner office to someone who was also a human being, wanting to belong and co-create something that endured. I accepted that part of me didn’t have all the answers, and that led me to ask more questions. Who I was after that firing was a fuller me.”

True in my case too.

Why You Need to be Vulnerable to Innovate:

Watch Brené Brown’s talk from TEDxHouston – it’s well worth your time:

Brown quotes Peter Sheahan in Daring Greatly, who says:

“If you want a culture of creativity and innovation, where sensible risks are embraced on both a market and individual level, start by developing the ability of managers to cultivate an openness to vulnerability in their teams. And this, paradoxically perhaps, requires first that they are vulnerable themselves. This notion that the leader needs to be “in charge” and to “know all the answers” is both dated and destructive. Its impact on others is the sense that they know less, and that they are less than. A recipe for risk aversion if ever I have heard it. Shame becomes fear. Fear leads to risk aversion. Risk aversion kills innovation.”

Vulnerability leads to innovation. How many great ideas have been pre-emptively killed because we’re afraid that they might fail? A lot. We can talk all we want about frameworks and tools, but if we don’t address this problem, none of these can help us.

Brown takes her title from this speech by Theodore Roosevelt:

“It is not the critic who counts; not the man who points out how the strong man stumbles, or where the doer of deeds could have done them better.

The credit belongs to the man who is actually in the arena, whose face is marred by dust and sweat and blood; who strives valiantly; who errs, who comes short again and again, because there is no effort without error and shortcoming; but who does actually strive to do the deeds; who knows great enthusiasms, the great devotions; who spends himself in a worthy cause;who at the best knows in the end the triumph of high achievement, and who at the worst, if he fails, at least fails while daring greatly . . .”

If you’re a manager, you need to do whatever you can to help put people into positions to dare greatly.

If you have a great idea yourself, you have to tackle that fear of failure and take a shot. That makes you vulnerable. But it also makes you alive. And who knows – it might work! It’s the only way to find out…

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GUEST POST from Tim Kastelle

People often think it’s weird when they hear that I study innovation – even people in very innovative jobs.  The biggest reason for this is mistaking invention for innovation.  If you do this, then studying innovation makes no sense at all – what can you learn about the flash of insight, the stroke of genius, etc.?

That’s why defining innovation is important – and why nearly everyone in working in the intellectual domain of innovation comes up with their own definition!  Here is the definition that I use:

Innovation is executing new ideas to create value.

Here is one way to picture it:

Thinking of it visually emphasises that all three parts of the definition.  Everyone gets the “new idea” part of it.  But it’s not enough to have a great idea, you also have to execute it.  And even after you’ve done that, you’re not finished.  It’s not innovation if you’re not creating value for people.

This is the foundation of the Innovation Value Chain idea.  John and I outline the research behind this concept in this paper – but  the main idea is this: if you don’t have all three elements in place, you don’t have innovation.

At an organisational level, this means that innovation is a process – the process of idea management.

To be an innovative organisation, you again need to be good at all three parts: generating great ideas, selecting & executing them, and getting them to spread.

There are three important points about defining innovation to consider:

1. Your definition needs to work for you. I’ve given two talks on innovation to scientific groups over the past few days, and one of the guys yesterday said “Oh, you could also think of that as science, engineering and commercialisation.”  In their context, yes you can.  This raises an important point that Jorge Barba made recently – whatever innovation definition you use, you need to own it and it needs to work in your context:

“The end result, is that if you are an employee and you pitch your idea as a “true innovation that challenges the established order”, it might get rejected because it means the company is taking on an untested and unproven idea.

In other words, if it doesn’t fit with the mental model of your leaders, it won’t get noticed.

Point: Whether you believe innovation is something new applied, an increment or whatever, the bottom line is your organization needs to come up with collective definition of what innovation means to you. Not your competitors or anyone else.”

2. Getting the idea to spread is often the missing component. The two science organisations that I was talking with both felt that this is where they are weakest. This is a problem because both of them are doing outstanding science – and their ideas needto be adopted more widely.There are a couple of ways to address this. Within an organisation, you need to get people committed to getting their ideas to spread. As Ian Frazer says, “there’s no point curing mice.” The second path is to make sure that your ideas are solving real needs. Braden Kelly pointed out last week that his innovation definition explicitly takes this into account:

Innovation transforms the useful seeds of invention into solutions valued above every existing alternative.

That valued about other choices bit is important – you can’t do this if you’re not meeting genuine needs.

3. Innovation by definition is uncertain. The last point to keep in mind is that for something to really be innovative, you can’t know in advance with certainty that it will work. Matt Edgar pointed me to a quote from Bruno Latour that captures this perfectly:

…a project is considered innovative if the number of actors is not known from the outset.

As always with Latour, the quote is both a bit loopy but also insightful. The key issue here for me is the emphasis here on uncertainty – without uncertainty right from the start, you’re not being innovative according to Latour.

4. The misunderstandings about innovation that I run into most frequently arise through thinking about innovation as being the same as having ideas. If you view it that way, then there’s nothing for me to study, and nothing for you to manage.

To be usable, a working definition of innovation must go beyond just having ideas. One way or another it also has to involve actually executing these ideas. And probably most importantly, it must involve creating value. If you don’t create value, then the idea will not spread.

So that’s why I say that innovation is executing new ideas to create value.

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GUEST POST from Tim Kastelle

You may remember Webvan, probably the most spectacular flame-out in during the tech boom in the late 90s. If you don’t, Nicole Perlroth describes their blowup for Forbes:

“Of Web 1.0’s most memorable implosions, Webvan still takes the cake. The online grocer raised $375 million in an IPO, descended upon eight major U.S. cities, peddled a 26-city expansion plan and somehow warranted a $1.2 billion market cap—all with the burn rate of a ticking time bomb. Eighteen surreal months later, the company closed down shop, laid off 2,000 and had nothing to show for itself except 30,000 Webvan-branded cup holders at San Francisco’s Giant’s ballpark.”

“The key takeaway—for venture capitalists, grocery chains and well, everyone else—was that carting small-ticket, low-margin items to people’s front doors from billion dollar warehouses did not a sound business model make.”

Bad idea, right?

Well, maybe not. When I was visiting my friends Jim and Sarah in Seattle recently the were talking about how they were ordering groceries through Amazon Fresh. And that seems to be working ok. Perlroth’s article describes the success of another online grocer, Relay. In fact, there are quite a few online grocers that are actually doing pretty well these days.

Many think that Webvan scaled too fast. This was particularly a problem because there were a bunch of issues with online groceries at the time. How do you deliver them if no one is home? How do you make money on small orders? Are people really willing to buy groceries online?

In the years since, these and other questions have been answered, by firms that built their business models slowly, experimenting to figure out what works and what doesn’t in this market.

Webvan was the right idea, but at the wrong time.

Here is Jack Dorsey describing his first attempt at building something like Twitter, back in 2000:

The technology worked. The problem was that at the time, no one had mobile phones that allowed them to use the tool – it really only worked with the latest Blackberry phones.

Right idea, wrong time.

This is the digital camera that Kodak invented in 1975:

If they invented the digital camera, why didn’t they end up dominating the market? The big problem in 1975 is that memory was very expensive, and very big. So you couldn’t actually record many pictures at all on a digital camera, and even then it cost a bunch. There was no way that digital cameras could work in 1975.

Once more, right idea, wrong time.

This is a big innovation problem – the right idea at the wrong time is still wrong.

Innovations diffuse along an s-curve. They start slowly, build for a long time (much longer than we expect), then finally tip. Or they fail – you can’t tell in advance.

The value for X is a lot longer than we think it will be. This is what creates the problem of the right idea at the wrong time. You can see where things are heading, the technology might even all be there, but for one reason or another, the business model doesn’t work yet.

Business models have to be developed over time. At the start, it’s hard to know exactly how your great new idea is going to work. You have to test the hypotheses in your business model in the market. This hypothesis validation is really where Webvan fell over.

There are other steps that you can take to accelerate this process, but there’s a serious timing issue in innovation.

It’s not enough to come up with a great idea, you also have build a great validated business model for it, and the supporting and market both have to be ready for it.

Of course, some ideas are just terrible no matter when you have them:

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GUEST POST from Tim Kastelle

Here’s my candidate for the worst innovation quote ever:

Now, to be fair, it’s actually a paraphrasing of Emerson. Or, to be more accurate, a misquote.

Nevertheless, it reflects a very common innovation misconception – that it’s all about the idea.

Andrew Hargadon has written a terrific post on this topic, which I encourage you to read. In it, he points out that since the U.S. Patent Office was founded in 1828, there have been more than 4,400 patents granted for mousetraps, with about 40 per year still being granted. Yet out of all of these, only a handful have made money.

Why? Because for the most part, the mousetrap problem was solved in 1894.

The mousetrap story has several important implications:

There’s much more to innovation than ideas. Hargadon explains why continually trying to fix a solved problem is a problem itself:

“Recall Emerson’s famous line: ‘ Build a better mousetrap, and the world will beat a path to your door.’ People are obsessed with building better mousetraps. For scientists, this creates a mindset in which the hard work lies in coming up with the idea—usually culminating in publishing a paper. For the engineer, this usually means developing a design, or a model. For the would-be entrepreneur, or corporate innovator, this usually means an extensive excel spreadsheet or polished powerpoint description of the next great idea. And for managers managing for ‘innovation,’ to revive or maintain their business’s growth, this usually means searching for better ideas from inside the company, from among its customers, or from the larger ‘idea’ marketplace.”

“If I have learned anything while traveling the country, talking to people in companies about their innovation process, and working with scientists from around the globe, it is this: There is no shortage of good ideas. We are waist-deep in ideas, good and bad. We’ve just lost the ability to recognize them, separate the good from the bad, and throw ourselves into building the best ones into real businesses.”

• Innovation is the process of idea management. It follows from this that to innovate, we actually have to manage ideas all the way through the process. It’s not enough to have a great idea, and it’s not even enough to execute a great idea. You also have to get the idea to spread. All of these skills are necessary to innovate successfully.

• To get your ideas to spread, solve real problems. Here’s the real issue with the Emerson quote – it doesn’t focus on needs. Like I said, the mousetrap problem was basically solved in 1894. Ruth Kessinger calls the mousetrap the “most frequently invented device in U.S. history,” and some of the more recently invented ones are undoubtedly better than the snap trap design. Just not better enough to make switching worthwhile. In an established market, you usually need a 10X performance improvement to displace an established competitor. It’s pretty hard to get that in mousetraps.

In some respects, mousetrap manufacturers had it easy, because they were replacing competitors that couldn’t really fight for market share:

Of course, cats made a pretty good pivot…

The bottom line here is that if you place too much value on ideas, you won’t be an effective innovator. It’s better to focus on solving a well-defined need. Alex Osterwalder lays out a good process for doing this in an excellent post today, which provides a method for effectively matching your value proposition to customer needs.

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GUEST POST from Tim Kastelle

We see many systems these days where all of the intelligence in the system is embedded in the technology.

Some examples:

• Driverless vehicles, in mines and on the streets.
• Highly sophisticated prosumer cameras.
• Most tablets – they can’t be programmed at all, really.
• High speed stock trading.

When I talked about this recently, I made this table to outline the issue:

All of these highly tech-enabled examples are in Stage 3 – where all of the intelligence sits in the technology, and none is assumed to reside in the users – the tech is smart so that the people don’t have to be.

This often seems like a logical endpoint, but smart tech/dumb people is an extremely unstable system. For the latest proof, look at the latest news from high-speed trading – the blowup of Knight Capital.

Dominic Basulto has a terrific write-up on this. He says:

“Have we given too much power to the machines?”

“To give you an idea of the scale of the problem: in the trading of a single stock, the algorithm was literally losing 15 cents on every trade, 2,400 times a minute, for 30 minutes straight. Knight, which saw millions of dollars hacked off its stock price in the course of days, was begging for a $440 million rescue package from creditors over the weekend. Rather than admit the scope of the problem – which affected trading in 148 different stocks – Knight refers to this as ‘a technology issue’ – as if it were something that the office IT guy could fix.”

“Quite simply, a rogue algorithm could take down Wall Street because we no longer know exactly what’s inside all of these marvelous black boxes owned by companies like Goldman Sachs. Trades are executed in the blink of an eye, with computers zipping out of stocks multiple times per minute.
…
The major financial participants are literally more worried about the speed of their algorithmic computers than they are the intelligence of the humans programming those machines. But isn’t there a hubris in assuming that we are able to reduce the financial markets to a series of blinking 1’s and 0’s, and that whoever has the fastest supercomputer wins?”

That’s a pretty much perfect description of smart tech/dumb people system. And they always blow up. Well, they always have. Maybe some day we’ll be good enough at programming that these systems will be stable.

Stage 3 leads to a false economy – systems here are operated in the belief that we can save costs on people by embedding the intelligence into the technology. This might work over the short term, but the costs of the blow-ups more than make up for these savings.

The innovation opportunity here is huge – figure out how to move to Stage 4 – smart tech operated by smart people.

That’s where a lot of modern medicine is these days. And weapon systems. A handful of people with their Nikon D90s have gotten there too, through learning.

Learning is the key. Stage 3 technology is psychopathic. To be genuinely smart, technology needs to interact with and be directed by smart people. Getting to that point is where the real opportunity lies for trading companies.

And probably for yours too.

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GUEST POST from Tim Kastelle

I was teaching an exec ed the other day, which is always a lot of fun. During one of the breaks, one of the people in the class said to me “This has been really valuable to me because it reinforces that I’m not the only one with these problems.”

A very important point, which made me think of three big obstacles to innovation that I often encounter:

1. You are not a special snowflake. Many people resist innovation by talking about all of the special problems they face. Too many constraints, Too much regulation, a risk-averse corporate culture, a complacent, traditional industry, or a unique set of obstacles that you can’t possibly understand if you don’t face them yourself – all of these are terrible excuses for not innovating.

Look, everyone faces these problems to some degree or another. And yes, context matters – different contexts are what make adapting “best practices” incredibly difficult. You need to be aware of your context. But this is another tension in innovation – you have to both be aware of your unique context and recognise the similarities your situation shares with others.

Finding similarities is particularly important because it enables learning by analogy, which is one of the best methods for finding innovative new ideas.

So, yes, your context is unique. But your innovation problems are not. They’re probably pretty common. Which means that we know a few things about how to attack them.

2. My boss won’t let me. Of course your boss won’t let you innovate. Here’s something that Seth Godin says about this excuse:

“But wait!” I hear you say. “My boss won’t let me. I want to do something great, but she won’t let me.”

“This is, of course, nonsense. Your boss won’t let you because what you’re really asking is: ‘May I do something silly and fun and, if it doesn’t work, will you take the blame – but if it does work, I get the credit?’ What would you say to an offer like that?”

“The alternative sounds scary, but I don’t think it is. The alternative is to just be remarkable. Go all the way to the edge. Not in a big thing, perhaps, but in a little one. Find some area where you have a tiny bit of authority and run with it. After you succeed, you’ll discover you’ve got more leeway for next time. And if you fail? Don’t worry. Your organisation secretly wants employees willing to push hard even if it means failing every so often.”

“And when? When should you start being remarkable? How’s this: if you don’t start tomorrow, you’re not really serious. Tomorrow night by midnight or don’t bother. You’re too talented to sit around waiting for the perfect moment. Go start.”

Yep. Go start.

3. People resist change. Yes, they will – someone will always resist change.

Here’s a French version of what you face with any change initiative:

Joe Hice writes about this from an education perspective:

“Jeffrey Papa and Tom Hayes, from the marketing firm SimpsonScarborough, point to the 20-60-20 rule about organizations as a major stumbling block to change in higher ed marketing: While 20 percent of employees will be enthusiastic about organizational change and 60 percent could be persuaded to go along, the remaining 20 percent will resist no matter what—and those could be longtime, tenured faculty members. ‘The people who don’t make the transition moving forward are the presidents who spend too much time and energy trying to persuade those 20 percent who are never going to change,’ Mr. Hayes says. ‘At some point you have to give the get-on-the-train speech: We love you people, but we’re going.’”

All of these excuses are gumption traps – an idea that Robert Pirsig outlines in Zen & The Art of Motorcycle Maintenance:

“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.”

It’s the same with innovation. We always face obstacles. As Paul Hobcraft once said to me in an email – “If innovation were easy, everyone would do it.”

Innovation makes you distinctive precisely because it’s challenging.

Joe McCarthy has some good suggestions for working through gumption traps – after all, his blog is called “Gumption” so he should know…

Another way to work through these excuses is to work on something worth doing. Hugh MacLeod captures this idea perfectly:

And if you do manage to change the world, maybe you are a special snowflake after all.

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GUEST POST from Tim Kastelle

One of the reasons that people try to avoid failing is that it seems like they’ve screwed up if they fail. This can certainly be the case, if your failure is major. But if you set up experiments to test ideas out, and you learn from them, then failing can be very productive.

Here is how Hugh MacLeod put it in his daily newsletter:

The cartoon pretty much says it all. Here’s what he wrote to go with it:

“I also love Esther Dyson’s great line, ‘Always make new mis­ta­kes’ …
It’s all about the same stuff: That our abi­lity to suc­ceed and to thrive is in direct pro­por­tion to our abi­lity to make mis­ta­kes and learn from them.
It ain’t roc­ket science, but it’s easily for­got­ten by some. Myself inc­lu­ded. Ouch…”

But there’s actually an interesting distinction between mistakes and experiments. Mistakes are things you do even though you know better. Experiments are tests designed to expand your knowledge. The big difference is that you learn from experiments (or at least you should).

I ran across a great post by Maddie Grant today that addresses this – Embracing Failure Does Not Mean Embracing Mistakes. She and her colleague Jamie Notter talk about a case study of NTEN that they wrote. Jamie said:

“If we fail at something, it will fuel learning, which will enable us to do it better next time. Failure is good.”

“But during the session, someone asked Amy a question about NTEN being comfortable with making mistakes, and Amy was quick to jump in and clarify. “We don’t define failures and mistakes the same way,” she said. A mistake is when you do something wrong, even though you knew the right way to do it. Failure is when you are trying something new, and you don’t know ahead of time how to make it successful. A typo in a conference brochure is a mistake. It’s not like you didn’t know how to spell the word correctly. NTEN is not “comfortable” with mistakes as it is with failures. They work very hard to eliminate mistakes. (Though I doubt they are the kind of place to ruthlessly punish people for making mistakes either.)”

“But they are okay with failure. They love to learn from what they are doing. They recognize that if you don’t fail some of the time, then you aren’t pushing hard enough. You aren’t growing. Eliminating failure would mean doing ONLY what you already know how to do. You don’t grow that way.”

So this is an example of a mistake (well, at least three mistakes by my count).

Now, there’s a bit of a conflict between these quotes. Do we want mistakes or not? Are mistakes failures?

You Must Learn From Failure

To me, there are two key issues to consider with failing. One is that failure is valuable if and only if you learn from it. The best way to do this is to experiment – this way, the learning is built into the process. Experimenting keeps you conscious of the fact that you don’t know exactly how things work, and you’re trying to figure that out.

But you can also learn from mistakes. I remember the first time I was at fault in a car accident. I was looking for a cassette tape that I dropped and bumped the car in front of me. Fortunately, no major damage or injuries. It wasn’t experiment to test whether or not I could get away with driving while distracted – I wasn’t intentionally gathering data. That was a mistake. I knew better than to not pay attention, I just let myself get distracted.

But I learned from it. It was my first at fault accident, and so far, my only one. The fact that it was caused by a cassette tape tells you how long ago it was! One of the reasons that I haven’t had any more is that I learned from the first one – the mistake.

So failure can be productive, as long as learn from it. Experiments are the best way to do this.

Fail Quickly and Cheaply

Which leads to the second key point about failing – you need to do it as early in the process as possible. I’m doing some work with a collaborator right now trying to put together some tools aimed at helping small businesses. This scheme has several assumptions built into it. One big one is that the problem that we’re trying to solve is big enough that these firms will be willing to pay for help.

But will they?

We flat out don’t know. So we’re trying to build an experiment to help us figure out if they will. We’re doing this because it is much better for our assumption to fail now, than for our entire scheme to fail when we launch because the assumption was wrong.

If we try an experiment and the small firms won’t or can’t pay, then we an re-design our program targeting larger firms. Or a particular sector. Or whatever else our data tells us might work.

The key point is to force faulty assumptions into the open as soon as possible. If they’re wrong, we don’t want them to torpedo the whole operation later on.

Failure is always a contentious issue. If you fail, you lose resources that could been used elsewhere. The problem is, if every idea that you try works, then you’re not trying enough new ideas. So some ideas will need to fail. This can come through experiments, or mistakes. Experiments are better, but both can help as long as you make sure that you learn from them.

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GUEST POST from Tim Kastelle

There is a huge difference between entering an existing market and building a completely new one. To see an example, check this out – it is the very first Apple product, which Andrew Chen writes about in a terrific post:

You can see why IBM didn’t view personal computers as any kind of threat to their mainframe market. Chen talks about what the Apple I reveals about design, but there are a few other interesting points that this raises:

• Disruptive innovations start in niches. Or, as Greg Satell says, disruptive innovations are crappy. Personal computers started out with hobbyists. Pretty much everyone that bought one was also a programmer, because there weren’t programs to speak of at the time. In other words, they were all hackers. In the big picture, they were a microscopic niche. That’s why the first PCs could look like this.

• Building a market is different from entering one. When the Apple I launched, there was no PC market. When the iPhone launched, there was a mobile phone market, and there was also a smartphone market, and both were plenty crowded. If you enter an existing market, you need a new business model or a 10X performance improvement to succeed. If you’re building a market, you’re also building a business model that work for it. Steve Blank makes this point strongly in his books, and here is how he puts it:

“Here’s the point. Market Type changes how you evaluate customer needs, customer adoption rate, how the customer understands his needs and how you should position the product to the customer. Market Type also affects the market size as well as how you launch the product into the market. As a result different market types require dramatically different sales and marketing strategies.”

“As a result, the standard product development model is not only useless, it is dangerous. It tells the finance, marketing and sales teams nothing about how to uniquely market and sell in each type of startup, nor how to predict the resources needed for success.”

• If you’re building a market, learning is the most important thing. If you are Procter & Gamble launching a new product, you pretty much know how to do it. Very structured product development systems work in this setting. However, if you are building a market, structure will kill your new product. Structure is deadly because it assumes that you know what business model will work, but that is actually what you’re searching to find.In their book A History of Silicon Valley, Arun Rao and Piero Scaruffi say:

“Silicon Valley works because it encourages smart failure. One oft-repeated piece of advice is ‘fail often but fail quickly.’ As the co-founders of MIT Entrepreneurship Review discovered after visiting the Valley, there still exists a trial-and-error or evolutionary process where failures could create opportunities and better innovations. Also failure is ‘encouraged and rarely punished,’ reflecting a still existing pioneer spirit of the American West.”

“One example Coleman offers is SUN Microsystems, which did everything wrong that was possible in creating products, but corrected course quickly. In Coleman’s view, ‘a startup is not a technology company – it is a learning machine.’ There are few business cultures in the world that are as tolerant of failure as the Valley. People who fail and learn from it become better entrepreneurs and managers.”

When you’re launching a new innovation, you must think carefully about the type of market that you are in. If you are building a market, the main objective needs to be learning. In that case, you can launch something that looks like the Apple I. In fact, you’re probably better off launching something like that fast, because that will accelerate the learning.

When you’re building markets, you need to be building dynamic business models that evolve. That’s why the Apple I looks so different from what we see now from Apple. More than anything else, it’s because they were operating in a very different type of market then.

image credit: whatifspecial

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GUEST POST from Tim Kastelle

I solved a mystery recently that had been bothering me for months.

There’s about a seven minute walk from the main faculty parking lot on campus to my office. About halfway through this walk, there are two paths that you can take – one covers significantly less distance. I’ve always taken this shorter route.

One day last year, I came out of the parking lot, and saw a guy that is a few doors down from me walking about 100 meters ahead of me. He is not a fast walker. By the time we had gotten to the split in the routes, I had caught up with him. He took the longer route, and I took the shorter one.

The shorter route involves going in through a building that is connected with ours, then crossing through onto our floor. When I came around the corner into the hallway, Peter was back in front of me.

How could this be??

I was clearly a faster walker, and I had taken the shorter route. I’m pretty sure that he didn’t start running the minute he left my site, only to fall back into a saunter once I could see him again.

I just couldn’t figure it out.

But, given the evidence, the longer route was clearly faster somehow. So that’s the one that I started taking.

Then last week I saw a chance to try another experiment. Victor was leaving our building at the same time as me, and I knew that we walked at about the same pace, and that he regularly took the longer route. So I took the short route to see what would happen.

We split up at the elevators in our building, and I headed across into the connected one. I took the elevator down, walked out onto the road, and went over to where the two routes connected up. Victor, who had taken the longer route, was 100 meters in front of me.

And that’s when I finally figured out what was going on.

The thing that makes the difference is not the route, or your walking pace. It’s how long you wait for the elevator. The elevators in our building are very fast, and few people use them. So you get one almost instantly, and it usually goes to the floor you want without stopping for other people. In the connected building, they are slow, and they are always stopping at nearly every floor. They are what make the shorter route slower.

I noticed a similar thing last week while I was driving around Silicon Valley. It’s the first time I’ve used a GPS in the car, and watching the estimated arrival time was interesting. Driving fast had no impact on the estimated arrival time. The only thing that changed it was getting stopped in traffic.

I’m going to extrapolate these experiences out to a general rule:

When you’re trying to get somewhere, how fast you’re moving isn’t nearly as important as how often you stop. Now, stopping is important when we’re trying to figure out where to go. If you don’t know, then thinking about it is pretty useful.

But if you have a target, it is stopping that slows down your progress. You don’t have to run to get there, and plotting out the shortest route doesn’t really help much. The main thing is to keep moving.

If you think about the goals that you are trying to reach right now, here is a question that can help you get there:

What’s stopping you?

image credit: saasmarketing & freelanceswitch

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