Tim Kastelle

Category: book riffs

  • Data Changes Everything

    I was talking with a friend tonight over dinner about the PhD that she is starting. One of the suggestions that I made was to get through the literature review and research design phase as quickly as possible. The reason for this is that data changes everything.

    PhD students share a common problem with inventors and innovators – they often get hung up on the value of their ideas.

    The problem with ideas is that they are just that – ideas. They are a hypothesis about the way that things work. In order to figure out if the idea is any good, you have to test it. This is scary for a bunch of reasons: it might not work, if it doesn’t work you’ll need to go and have another idea, if it doesn’t work people might think less of you, etc.

    In a Q&A session that he did to promote the new paperback version of his very good book The Myths of Innovation, Scott Berkun answered this question:

    Q: When a new idea looks strange, how do you tell a great one from stupid? Try them all and see what works, or select one and push it as far as you can?
    You [can’t] tell just by looking. You have to put in action. Make a prototype. See what happens when the idea meets the world. Sometimes keeping a strange idea around and poking at it now and then is simply good exercise. It keeps your creative muscles working, so when a weird idea that has the potential to be great comes along, you’ll be patient and persistent enough to discover its potential.

    Pivot Fakie.

    In startups, this idea is referred to as the pivot – the point where your business model makes a 90 degree turn. Here’s a terrific post by Steve Blank describing the process in more detail – you should read it. Here’s part of his description:

    Startups are inherently chaotic. The rapid shifts in the business model is what differentiates a startup from an established company. Pivots are the essence of entrepreneurship and the key to startup success. If you can’t pivot or pivot quickly, chances are you will fail.
    Pivot.
    Lessons Learned

    • A startup is an organization formed to search for a repeatable and scalable business model.
    • Most startup business models are initially wrong.
    • The process of iteration in search of the successful business model is called the Pivot.

    Data changes everything.

    See what happens when the idea meets the world.

    Pivots are the essence of entrepreneurship and the key to startup success.

    Having great ideas is exciting. It gives you a nice adrenalin rush, and it makes it feel you’re doing something. Testing ideas is often tedious, and it is a process that faces failure at every turn.

    But in the end, value is only created by ideas that are successfully executed. This is true whether you are writing a business or forming a startup.

    Get out there and start testing your great ideas.

    (Photo from flickr/Daniel Dale under a Creative Commons License)

  • 43 Rules for Better Leadership

    The first major management job that I had started with two crises on the day it was offered to me. I went straight into firefighting mode before I had even officially started the position. The last big management job that I started was almost the exact opposite – I walked into the office on the first day, sat down, looked at the empty desk and thought to myself “what am I supposed to do now?”

    In both cases, I could have used the advice contained in 42 Rules for Your New Leadership Role by Pam Fox-Rollin. It’s a very practical book that would be useful for anyone in a leadership role.

    There are a couple of things that I like about this book. One is that it breaks down management into a number of key themes – including setting up a strategy, figuring out what’s going in your new role, making a positive impact quickly, developing a management system, learning, and encouraging growth within your team.

    The last point is the other thing that I like about the book – Fox-Rollin talks about the importance of providing support when you’re in a leadership role. I believe that managing is more about removing obstacles for your team than it is about directing people, and the book seems to be reasonably well aligned with this belief (Fox-Rollin expands on the importance of getting everyone on your team to lead in this interview with Nilofer Merchant).

    Here is what she says about learning from mistakes – a critical skill in innovation:

    Remember your team will be looking to you, especially the first couple of times things go wrong. If you stay focused on serving your customer and improving the system, you’re teaching your team what to do. If you hide problems, shade truth, and lay blame, expect more of the same.
    …
    When a problem arises, reach out right away – to your team members, customers. Express your commitment to making things right, then fire up your curiosity and interview people as if for a case study. Save any non-urgent fixes until you and your team have developed a solid picture of the factors that contributed to the problem; consider faulty processes, limited frames of thinking, poor information, overly-simplistic metrics and incentives, even your lack of experience in picking up early signs of trouble.
    Repair the short-term damage, share the learnings across the team, and improve your processes. You leave the screw-up with processes and team stronger than before. Onward!

    In addition to Fox-Rollins 42 rules, I would add one more:

    Plan Your Change Agenda and Figure Out How Much Scope for Action You Have.

    In other words, figure out how much you can get away with.

    Every new manager has some mandate for change – it can be big or small. And every one has some ability to implement ideas in order to test out what does work and what doesn’t. Figure out how to take advantage of these two things.

    Your best chance to innovate in a new position is at the start of it. Don’t get too flustered by crises, or too intimidated by the big empty desk – these will both distract you from making that early impact.

    All managers need to innovate – it’s how we get things to change. So develop an innovation plan for your new leadership role as well.

  • The Innovation Filter Bubble

    Here is a must-watch video from Eli Pariser discussing some of the themes from his new book The Filter Bubble (reviewed well here by Cory Doctorow). It’s only 9 minutes, and it is well worth your time:

    Pariser’s main point is that the primary filters on the internet these days are algorithmic, and that these filters have a strong tendency to only expose you to viewpoints that reinforce whatever you currently think.

    This is very important for how we use the internet, but it also has huge implications for innovation as well. I think that many of us work inside of an innovation filter bubble, and that this makes it much harder for us to innovate.

    What is an innovation filter bubble? It is all of the habits and routines that prevent us from being exposed to novel ideas and new points of view. Some of these include:

    • The internet filters that Pariser discusses: much of our information comes from the web these days, and as he shows in the talk, this can lead to only running across viewpoints that reinforce our own.
    • Who we spend time with: do you always eat lunch with the same people? Or alone? Spending time with people that you know well is great (and we often don’t do enough of this), but at the same time, we usually spend time with these people because they think a lot like us.
    • Silos within our organisations: is where you work organised by specialty? Most organisations are. This has benefits in that it makes it easier to find the information that is most relevant to our jobs more easily. Still, this is another form of filtering that reinforces current views.

    The end result of the filtering that occurs through these routines is that the information that we are exposed to can become too restricted. As Pariser argues, these filters make it easy to find information that is relevant to the task at hand – and that is what makes them useful. But does access to information that is highly relevant to the task at hand help innovation? Probably not.

    Innovation is based on connecting ideas in novel and interesting ways. To do this, we need to run across information that is more than just relevant. We also need information that is important, uncomfortable, challenging, and that reflects other points of view.

    We have to make a conscious effort to break out of our innovation filter bubble.

    How can we do this? Here are some ideas:

    • Actively seek out new and different viewpoints: Ethan Zuckerman has some great ideas about how to do this on the internet. But also do it in your day to day activities. Once a week have lunch or a coffee with someone with a completely different background, area of expertise, or view of life. Go out and find those challenging ideas somewhere.
    • Use filters based on expertise instead of algorithms: as I’ve discussed before, there are at least five forms of filtering. The algorithmic filters are more efficient, but they fall prey to the problems outlined by Pariser. Make better use of expertise-based filters. You can do this by accessing people with expertise in different areas, and also by building broad networks and activating them to help you generate new ideas. Algorithms are great, but you still need some people-based filtering as well.
    • Encourage enhanced serendipity: this is an idea from Ross Dawson, and it’s also discussed in The Power of Pull. It involves building your networks (both online and personal) to maximize your exposure to new ideas and novel viewpoints. One of my personal rules in this area is that on twitter I always follow people that follow me if they come from outside of Australia, North America or Europe. And I follow nearly all of the people that run into from Europe too. This is one way to run across new viewpoints.

    In order to innovate we have to generate new connections between ideas. We can’t do this if all of our routines only expose us to viewpoints that are very similar to our own.

    To innovate more effectively, we have to break out of the innovation filter bubble.

  • Make Little Bets for Innovation Success

    To succeed at innovation, you need to be making a lot of little bets. What are little bets? According to Peter Sims in his excellent book called Little Bets, they are:

    A small, affordable action that anyone can take to discover and develop ideas.

    Here is a more complete explanation in an interview with Andrew Keen:

    When I was in Silicon Valley a couple of weeks ago, there was a huge buzz going around about the book, and I was fortunate enough to hear Peter talk about it at a TEDxBayArea event. Interestingly, two different people who had read the book used almost identical words to describe it – they both said something like: “If you’ve been reading the research there isn’t anything new here, but he pulls it together really well.”

    That doesn’t sound like the highest of praise, but it actually illustrates one of the main points of the book perfectly: that ground-breaking ideas don’t always look ground-breaking when they launch, instead, they tend to build up out of a series of experiments. Sims has done a great job of connecting up a bunch of ideas that were already out there in a novel way, and building an important new idea out of them. This is the essence of innovation.

    He includes a great quote from Steve Jobs that explains the importance of connecting up ideas:

    Creativity is just connecting things. When you ask creative people how the did something, they feel a little guilty because they didn’t really do it, they just saw something. It seemed obvious to them after a while. That’s because they were able to connect experiences they’ve had an synthesize new things. And the reason they were able to do that was that they’ve had more experiences or they have thought more about their experiences than other people… Unfortunately, that’s too rare a commodity. A lot of people in our industry haven’t had very diverse experiences. So they don’t have enough dots to connect, and they end up with very linear solutions without a broad perspective on the problem.

    There are several key actions that you can take based on reading this book that will make more innovative, including:

    • Focus on what you can afford to lose, rather than what you might gain: This is similar to my suggestion that you do as much as you can get away with. The critical point of little bets is that they are little – so if they don’t work, you don’t lose too much. Don’t try to figure out the net present value of a potential idea based on growth projections in which no one can ever have any confidence. Just find a way to test your idea as quickly and cheaply as possible. This is central to any little bets approach.
    • Build as much diversity into your personal network as possible: the best way to make these creative, novel connections between ideas is to have a diversity of experience, and to encounter a diversity of ideas. One great way to accomplish both is to consciously build links with people that don’t think in the same way that you do. Tom Peters sums this up perfectly: Hang out with the freaks. Peters has been making this recommendation for a long time – find the people that are outsiders, that don’t fit, and spend time talking to them. It’s the easiest way to start making novel connections between ideas.
    • Don’t expect to have a great big idea come to you in perfect form: the reason that Sims marshalls all of the evidence that he has is to show us that big ideas don’t spring fully-formed from peoples’ minds. Instead, they build over time. As Linus Pauling said, the best way to have a great idea is to have a lot of ideas. The belief that we have to have a great idea in order to start something is a myth, and one of the main ones that Sims is trying to dispel. If you won’t start until you have a great idea, you won’t start. Instead, it is better to execute an idea, any idea, figure out what works, and build from there (he expands on this idea in an excellent interview with Nilofer Merchant).

    It’s no coincidence that John and I have used the word “experiment” in 103 different posts on this blog. We keep talking about it because it works, and anyone can do it. To innovate, you need to figure out how much you can get away with (how much can you afford to lose?), figure out how to test an idea within the scope that provides you, learn from your experiment, and build on it.

    That’s a little bet.

    That’s innovation.

    If you want to learn more about the book, here is Sims’ talk as part of the Authors @Google series:

  • An Innovation Challenge: Learning From Failure

    I’m still working my way through Being Wrong by Kathryn Schulz. It’s a very interesting book, and nicely written. I’ll tell you more about it when I’m done. In th meantime, I’d like to share a fantastic quote from Schulz, which is in her review of Join the Club: How Peer Pressure Can Transform the World by Tina Rosenberg.

    Schulz uses the review to critique Big Idea Books, and her argument applies to a majority of business books too. Here is one of the key issues that she raises (I added the emphasis):

    Solutions are not one size fits all—they are, in fact, maddeningly bespoke. That’s because neither problems nor people are fungible. Rosenberg is a brilliant reporter, but here she exhibits the characteristic blind spot of the blind-spot-obsessed Big Idea books. Like totalizing religious or political stories, these books promise to hand over the master key that will unlock our lives. Or, more precisely, they tell us that we have had the key all along, but that we have been holding it upside down.

    To which I say: key-shmey. There is no rule, process, peer group, leader, or best seller that can absolve us of the responsibility of thinking our way through life on our own two feet. What irks me most about this infinite parade of gigundo solutions isn’t their glibness or even the borderline theology (of some) and borderline Babbitry (of others) involved in promising audiences easy, happy, profitable ideas. Nope. What irks me is that when you rigidly apply grand theories to everybody, sooner or later everybody feels like nobody, whether you’re in Communist Belgrade or the local DMV. There is a reason we call such systems soul-crushing: They ignore or annihilate individual difference and inner life.

    This is the problem we have in dealing with complex systems. There are no one-size-fits-all solutions. If anyone tells you that there is, beware.

    Furthermore, there in complex systems, there are nearly always unintended consequences to action. These two things together make it very difficult to plan out actions in advance.

    This is why I like Schulz’ advice to think our way through life on our own two feet – it’s the only way to go. A big part of this is experimenting. One of the themes of Being Wrong is that wrongness is a natural state. We can learn from error, in fact, we must learn from error as this is the only way to improve.

    I ran across a great website today called Admitting Failure. They are trying to use the site to help international development efforts learn from things that don’t work in other contexts. Here is their reasoning:

    The development community is failing… to learn from failure. Instead of recognizing these experiences as learning opportunities, we hide them away out of fear and embarrassment.

    No more. This site is an open space for development professionals who recognize that the only “bad” failure is one that’s repeated. Those who are willing to share their missteps to ensure they don’t happen again. It is a community and a resource, all designed to establish new levels of transparency, collaboration, and innovation within the development sector.

    Get involved – share failures, build knowledge and encourage others to do the same – so we all benefit, today.

    We have to take failure seriously precisely because there are no one-size-fits-all solutions to problems. Contexts are always slightly different, so not all lessons will transfer from one arena to another. Nevertheless, if we embrace the messiness of the world, we’ll see that we don’t need grand theories. We just need to try things, and learn from what works and what doesn’t.

    I’m pretty sure that this approach will work for, well, nearly everyone.

  • Good Innovation Managers are Simply Good Managers

    What happens when the people that are supposed to be creative and innovative in your organisation are neither?

    I ran across an interesting quote from one of the people interviewed in the new book Herding Cats: Being Advice to Aspiring Academic and Research Leaders by Geoff Garrett and Graeme Davies:

    The biggest thing that I have found through the years is that many people in research are actually bureaucrats. I would have expected them all to be interested in the future, wanting to change the world, brimming over with enthusiasm to get on with the job and deliver useful results. This took me a long time to realise and I think I would have been much more effective if I had understood that there are a lot of people who really do not want to see much in the way of change, and that includes a lot of people in R&D.

    How do you deal with this?

    It’s actually a really tough question. This is why effective change management is a critical part of innovation management. It’s also why in research studies, innovation success correlates with so many other good outcomes – higher profits, better firm survival rates, more engaged employees and so on.

    The reason for this is that all of these things are driven by good management.

    Garrett and Davies conclude their excellent book with a quote from another interview:

    I reckon there are five key dimensions to leadership in a research and development or academic environment…

    1. Research leaders must have a vision of where they want the organisation to go – because, if you don’t, no one else will.
    2. You articulate it, and communicate it well, to get your people excited.
    3. You hire the best people you can find.
    4. You create the environment where they can excel, and succeed.
    5. You get out of the way.

    Garrett and Davies undersell their book when they say it is only about managing academic-style research. Those are all the things you need to do to manage effectively anywhere.

    Good innovation managers are simply good managers.

  • Don’t Push Rocks, Roll Snowballs

    Innovation is the process of idea management. One of the critical steps to successful innovation is getting your idea to spread. Hugh MacLeod’s outstanding new book Evil Plans has a lot about how to get your ideas to spread more effectively. One of his tenets is that we should create random acts of traction.

    There are two important parts to this idea. The first is that we need to create social objects that have traction – in other words, we are using a pull strategy. The second part is the random bit – we don’t know in advance which ideas actually will gain traction. So we need to experiment, and try out a lot of different ideas.

    He starts to frame this idea by quoting Doc Searls:

    Tell ya what. I’m fifty-seven years old, and I’ve been pushing large rocks for short distances up a lot of hills, for a long time. Now, with blogging, I get to roll snowballs down hills. Some don’t go very far. But some get pretty big once they start rolling.

    See, each snowball grows as others link to the original idea, and add their own thoughts and ideas. By the time the snowball gets big enough to have some impact, it really isn’t my idea any more.

    Anyway, at this point in my life I’d rather roll snowballs than push rocks.

    Hugh has more great ideas per paragraph than nearly anyone writing these days (he’s in the same league as Charlie Stross) – here is how he follows that point up:

    My friends, Dennis Howlett and James Governor, both technology consultants, certainly understand this. As they can only realistically execute on 10% of their ideas, they don’t seem to mind giving away the remaining 90% for free, via their blogs. If one of their free ideas gets “Random Acts of Traction”, it’s great PR for their businesses. It leads to conversations eventually. Conversations that eventually lead to paid gigs.

    This only works, of course, if you can make your “snowballs” quickly and inexpensively enough. If you spend too much time worrying about it, you lose. If you try to control where the snowballs go after you’ve released them down the hill, you lose.

    “Fail cheap. Fail fast. Fail often. Always make new mistakes.” –Esther Dyson. Words to live by. Exactly.

    There are a ton of important ideas tucked in there. The bit about Howlett and Governor having too many ideas to execute themselves is important. It illustrates why we have to have a good process for selecting ideas.

    The Dyson quote emphasises the importance of experimenting, and then learning from the ideas that don’t work.

    But to me, the important point is that we need to send the snowballs out and see if they gain traction. This is a classic pull strategy. How do we execute this?

    Here is how John Seeley Brown, John Hagel and Lang Davison describe their book about this process:

    In many respects, The Power of Pull can be read as an attempt to reinstate the central role of socially embedded practice in driving knowledge creation and performance improvement relative to the recent emphasis in the management literature of process reengineering. In short, companies need to refocus technology innovation on providing tools to amplify the efforts of communities of practice to drive performance improvement

    If you want to roll snowballs, here are some things to keep in mind:

    • Your idea has to meet genuine needs. Pull strategies are based on ideas that meet real needs for people. If you are going to spread the idea through a community, people need to talk about it. They will only do this if you have created tangible value for them.
    • Pull strategies rely on networks. Which strategy is best for doing this? This is still a controversial question. Many people advocate targeting people within the network that are highly influential. I prefer the “big seed” approach put forward by Duncan Watts. Greg Satell explains this idea:

      As I explained in an earlier post, he calls his approach Big Seed Marketing. His reasoning is that since influence is so hard to track, it is much better simply to start with a lot of reach (i.e. a big seed) and use social media to amplify it. It seems to me to be an incredibly reasonable and sound approach.

    • You need to try out a lot of different ideas. Just as you seed your ideas as widely as possible, you try out as many as you can. As Hugh says, you need to roll a lot of snowballs down the hill.

    Push strategies are attractive because when you are pushing your ideas, it always seems like you are active, and that you are in control of how successful the idea will be. However, this feeling of control is an illusion. Instead of betting everything on one big idea, we’re usually better off trying out a lot of smaller ones – especially if our environment is turbulent.

    So I’m with Doc and Hugh – it’s better to be rolling snowballs than to be pushing rocks.

  • Innovation Lessons from J. Peterman

    The first thing that I ever bought from the J. Peterman catalog was the Otavalo Mountain Shirt:

    I had discovered the Peterman catalog very early in its existence, and after getting a few in the mail, I finally bought the shirt. I quickly discovered that the quality of clothes from Peterman was very high, and all of them were distinctive as well. I bought things when I could afford to, and watched as the company grew incredibly quickly throughout the 90s.

    I wasn’t studying innovation at the time, but it was clearly an innovative company. Here is how John Peterman describes their idiosyncratic catalog (Owner’s Manual) in his book Peterman Rides Again:

    The direct-marketing expert… [said] “Your catalog hasn’t got a chance, John. There are rules in this business, you know. You’ve managed to break just about every one of them.
    Guilty as charged.
    The Owner’s Manual had an odd, oblong shape, 5-1/2″ x 10-1/2”, and wasn’t even identified as a catalog. “Consumers won’t understand what an ‘Owner’s Manual’ is, and they’re not sitting around waiting to solve puzzles.” Our use of artwork to show products raised eyebrows. “Consumers don’t trust drawings, they want to see photographs of what they’re buying.” Long copy instead of short, to-the-point product descriptions was risky. “Consumers don’t have time to read; besides, their attention spans are short, anyway.” And selling one item per page was suicidal to the “square-inchers”- the guys who try to calculate profit per square inch of catalog space. “You need 2.7 items on a page if you want to make any money.”
    Now, there may be an element of truth to all that if you’re selling familiar, standardized stuff. But we were offering uncommon things to people who to be willing to be different – people like ourselves. So we took a deep breath and went with an approach that appealed to us.

    And it worked. The company went from selling a few thousand dollars worth of their only product in the first years, a cowboy duster, to selling $75 million across a wide variety of things in less than 10 years.

    They did by selling stories. Here is how the 37 Signals blog describes the copy:

    Of course it’s ridiculous. But it sure does make J. Peterman stand out from the pack. And there’s a lesson in that for anyone who wants to decommoditize what they sell: The story you surround your product with is a great way to differentiate it from competitors. Banana Republic sells you a jacket. J. Peterman sells you a tale.

    Then it all blew up. This report from MSNBC explains how it happened:

    Visit msnbc.com for breaking news, world news, and news about the economy

    The company went up to $75 million in sales, overextended and went bankrupt. As I said yesterday, being wrong is the only way to learn, and Peterman seems to have learned from his. After buying the company back (in a deal that included money from John O’Hurley – the man that played “J. Peterman” on Seinfeld!), Peterman has taken a more measured approach to growth.

    I think that one of the reasons he has succeed is that he always seems to have had a balanced view of failure. He is an ex-pro baseball player and a successful entrepreneur, so Peterman is clearly driven. Yet he is pretty open about the necessity of learning from mistakes. One of his quotes in the book is “If you don’t make any mistakes, you’re probably not doing your job right.” He also included this set of quotes that he collected about failure:

    A mistake may turn out to be the one thing necessary to a worthwhile achievement. – Henry Ford
    Failures, repeated failures, are finger posts on the road to success. One fails forward toward success. – C.F. Kettering
    Success is 99 percent failure. – Soichiro Honda
    the man who makes no mistakes does not usually make anything. – W.C. Magee
    The greatest mistake you can make in life is to be continually fearing that you will make one. – Elbert Hubbard
    Do not fear mistakes, there are none. – Miles Davis

    Going bankrupt is devastating. And yet, Peterman has managed to learn from the mistakes made and bounce back. This is the kind of resilience that we need to innovate. There are a few innovation lessons in the Peterman story:

    • You don’t have to embrace failure, or even like it. But if you are able to learn from it, you are much more likely to succeed.
    • Telling a compelling story is a great way to get your idea to stand out.
    • Making mistakes is part of trying to do something different.

    Oh, and there’s probably one more. I still have that first Otavalo Mountain Shirt that I bought over 20 years ago. So in addition to doing things that make your idea stand out, it’s also smart to execute the idea as well as you possibly can. Quality goes a long way towards making your new ideas work.

  • Being Wrong is the Only Way to Learn

    “Who knew doors only cost $30?”

    Jason Potts said that to me last week when we were talking about the work he’s doing on his house. The house was severely damaged in the flood in January. For the past few weeks, Jason has been working on rebuilding it. He was telling me about how he’s learned to do a lot of the work – simply through experimenting.

    Being wrong is actually an essential part of learning – as Jason’s experience with doors shows. Three months ago he didn’t know anything about installing handles on doors, and now he’s good at it. And the cost was much lower than he expected.

    This is common error – we nearly always overestimate the cost of experimenting.

    Part of this is because we don’t realise how cheap it is test most ideas. But the bigger problem is psychological – one big problem with experimenting is that we might be wrong. In her excellent book Being Wrong, Kathryn Shulz explains why this is such a problem for many people:

    In our collective imagination, error is associated not just with shame and stupidity, but also with ignorance, indolence, psychopathology, and moral degeneracy. This set of associations was nicely summed up by the Italian cognitive scientist Massimo Piattelli-Palmarini, who noted that we err because of (among other things) “inattention, distraction, lack of interest, poor preparation, genuine stupidity, timidity, braggadocio, emotional imbalance,… ideological, racial, social or chauvinistic prejudices, as well as aggressive or prevaricatory instincts.” In this rather despairing view – and it is a common one – our errors are evidence of our gravest social, intellectual, and moral failings.
    Of all the things we are wrong about, this idea of error might well top the list. It is our meta-mistake: we are wrong about what it means to be wrong. Far from being a sing of intellectual inferiority, the capacity to err is crucial to human cognition. … Thanks to error, we can revise our understanding of ourselves and amend our ideas about the world.

    In other words, being wrong is the only way to learn.

    That’s one of the things I’ve been spectacularly wrong about recently. We’ve had a persistent leak in our basement, which became a torrent during the rains that led to the flood. Ever since I first noticed the leak, I thought that it was from a broken drain pipe. My presumption was that the pipe was underneath the bricks, and that we would have to get plumbers in and dig up the whole front of the house to fix the leak.

    During the rain, I took a close look at the leak, and realised that my idea about its source had to be completely wrong. So I developed a new idea: that the water was leaking through the gap between the sidewalk and the bricks.

    To test this idea, I tried the experiment you can see in the picture. I bought $20 of sealant, and did the world’s messiest caulking job along the two gaps that I thought might be the source of the leak.

    Since then, not one drop of water has gone into the basement. My experiment worked. Now that I know what the problem is, I can work on coming up with a solution more elegant that my two messy lines of sealant.

    There are some general lessons in all of this home improvement work:

    • If things aren’t working right, examine your basic assumptions: I thought my leak would require a lot of time, money and expertise to fix. Jason thought the same about putting in doors. We were both wrong – but we only knew this once we actually tested those ideas.
    • Experiments are a lot cheaper than you think: Who knew that doors only cost $30? People that had already tried to experiment with them, I suppose. My new idea about the leak could have been wrong, but the $20 of sealant was a lot cheaper than calling in a plumber to test out my first hypothesis. Find a way to test out your ideas as quickly and cheaply as possible.
    • Being wrong is the only way to learn: Schulz’ point is exactly correct – being wrong is not a moral failing, or a sign of intellectual inferiority. It is the only way we can figure out how to do new things.

    Experimenting isn’t just for fixing stuff around the house either – experimenting is a critical step in innovating. Earlier this week Jose Baldaia pointed to an excellent post by Amir Khella called How I launched a profitable product in 3 hours. Khella recounts how he developed a new product called Keynotopia which is, beautifully, a rapid prototyping (experimenting!) tool.

    Here is part of what happened:

    It had been less than a month since I wrote about how I’ve been using Apple Keynote to prototype iPad applications. I debated whether or not I should publish the post, thinking there was nothing new or useful about it. Yet, I decided to do it for the fun of it. What I didn’t expect, though, was for the post to be picked up by some of the most respected bloggers, becoming popular among the design and iPhone communities. In less than three weeks, the post generated more than 10,000 visits and 500 downloads of the iPad keynote templates I posted along.

    Khella had an idea, but wasn’t sure if it would work, or even if it was any good or not. Instead of sinking a lot of further thought into it, he ran an experiment. He put together a website just to see if the idea would fly.

    And it did. It’s great when your experiments work out this way. But what if it didn’t?

    If no one had gone to the page, or if Keynotopia wasn’t useful for people, or if it didn’t work right, or if something else had gone wrong, he would have learned something – and for a pretty small investment, just three hours. If no one tried it out, then he’d know that the idea didn’t create value for people. Then he could move on to his next idea/experiment. If they had complaints about how it worked, then he’d know that the idea creates value, but his execution needs to be better. Then he could fix the problems and make the idea better.

    In both of those cases, he would have been wrong about something. And much better off for knowing it.

    Being wrong is the only way to learn. If you have a great idea, find a way to test it out. Experimenting is usually a lot cheaper than you think. Just remember Jason and the doors.

  • Three Types of Models: Simplistic, Complex and Simple

    I was watching some MBA presentations this week, and they reminded me of a section of “On Exactitude in Science” by Jorge Luis Borges. In this short story, Borges describes a map the size of the world (From Jorge Luis Borges, Collected Fictions, Translated by Andrew Hurley Copyright Penguin 1999):

    . . . In that Empire, the Art of Cartography attained such Perfection that the map of a single Province occupied the entirety of a City, and the map of the Empire, the entirety of a Province. In time, those Unconscionable Maps no longer satisfied, and the Cartographers Guilds struck a Map of the Empire whose size was that of the Empire, and which coincided point for point with it. The following Generations, who were not so fond of the Study of Cartography as their Forebears had been, saw that that vast Map was Useless, and not without some Pitilessness was it, that they delivered it up to the Inclemencies of Sun and Winters. In the Deserts of the West, still today, there are Tattered Ruins of that Map, inhabited by Animals and Beggars; in all the Land there is no other Relic of the Disciplines of Geography.

    Suarez Miranda,Viajes de varones prudentes, Libro IV,Cap. XLV, Lerida, 1658

    A map is a type of model, and any time you make a model, you have to leave things out for the model to be useful. Otherwise you end up with a map the size of the world.

    World Map 1689 — No. 1

    The MBA talks got me thinking about the models that we make when we study business. We can classify these models based on how they reduce the system that we are trying to describe down into some kind of (ideally) more coherent set of ideas. In doing so, we are trying to follow Albert Einstein’s advice that “Everything should be made as simple as possible, but not simpler.”

    In the MBA presentations, I saw three types of models:

    1. Simplistic: these are the most common types of models in business, and they don’t follow Einstein’s advice – the actually make things simpler. These are models or frameworks that lack depth. Because of this, the ideas being put forward often fail to include critical information. In most cases, simplistic models are not just inaccurate, they can be dangerous to take seriously. One example of a simplistic model is “house prices can only go up.” We’re still trying to sort out the results of many people taking this simplistic model too seriously. That’s the danger of simplistic models. The good side of simplistic models is that these are the type of models that you get when you approach things with a Beginner’s Mind. So simplistic models can be useful for finding underlying assumptions that experts overlook or assume away.
    2. Complex: these are models that are closer to “map of the world size”. They add in a lot of details – a whole lot. Complex models are the ones that lead to the creation of powerpoint slides with 250 words of text on them. Complex models are often better than simplistic ones, because they include more of the relevant details. However, the trade-off for this increasing accuracy is a reduction in clarity.
    3. Simple: you get simple models when you really understand a topic. I used to do industrial water treatment consulting. I would design treatment programs for plants, but on a day-to-day basis these programs had to be executed by the plant’s operators. Usually these were people with limited education, and often with English as a second language. Despite these obstacles, my manager used to say that if you couldn’t explain the principles of our programs so that the operators understood what we were trying to do and why, then you didn’t understand it yourself. He wanted us to be able to explain simple models – ones that really were as simple as possible, but not simpler.

    What I observed while working with the MBA students is that the presentations would work their way through all three types of models. We would start with simplistic ones. Sometimes these would provide unique insight, but usually they were too basic to be useful. In response to this, the students would load them up with every fact and idea that they could generate, leading to complex map of the world type models. These were better, but difficult to understand. Eventually, they could take these facts and ideas and distill out the critical points. That is when they got to simple models.

    Two people that have done some great thinking on how to effectively deal with complexity in business are Dave Snowden (example here) and Ralph Stacey (example here). They both worry that most business models are simplistic, and they try to develop ways of seeing and acting that avoid this problem.

    When you think of how the world works, are you using a simple model or a simplistic one? The difference is important. You can only get to simple with a deep understanding of the system you are trying to picture.

    (picture from flickr/Chuck “Caveman” Coker under a Creative Commons license)

  • Why Experimenting Beats Benchmarking

    In his excellent new book Why the West Rules – For Now Ian Morris tells many great stories while trying to explain the trends in human history from around 14,000 BC to now. One of them jumped out at me – the story of the rise of Portuguese sea power on the back of guns in the early 16th century (emphasis mine):

    Dozens of Portuguese ships followed in da Gama’s wake, exploiting the one advantage they did have: firepower. Slipping as the occasion demanded among trading, bullying, and shooting, the Portuguese found that nothing closed a deal quite like a gun….

    Their tiny numbers meant that Portuguese ships were more like mosquitoes buzzing around the great kingdoms of the Indian Ocean than like conquistadors, but after a decade of their biting, the sultans and kinds of Turkey, Egypt, Gujarat and Calicut – egged on by Venice – decided enough was enough. Massing more than a hundred vessels in 1509, they trapped 18 Portuguese warships against the Indian coast and closed to ram and board them. The Portuguese blasted them into splinters.

    Like the Ottomans when they advanced into the Balkans a century earlier, rulers all around the Indian Ocean rushed to copy European guns, only to learn that it took more than just cannons to outshoot the Portuguese. They needed to import an entire military system and transform the social order to make room for new kinds of warriors, which proved just as difficult in sixteenth-century South Asia as it had been three thousand years earlier, when the kings of the Western core struggled to adapt their armies to chariots.

    Here is my take on lesson of this story: benchmarking doesn’t work.

    The problem with benchmarking is the basic assumption that a particular tool or process will function in the same way in your firm as it does in its original context. This is rarely true.

    Just as the kings around the Indian Ocean didn’t just need guns, they needed entirely new military processes and personnel, firms trying to change can’t just copy a tool that a successful firm uses, like Google’s 20% rule (discussed here), they need to support the tool with different processes and people.

    So rather than trying to copy tools through benchmarking, you are better off putting in place a system that supports experimentation. Matt Perez raised this point in a comment on yesterday’s post:

    “Bad ideas come from bad structures. One of the best ways to eliminate bad ideas is to build new, better structures.”

    Oops, how would you know if they are “better?” I would say that to show up bad ideas for what they are, build new structures and EXPERIMENT like your life depended on it (because it does).

    As discussed yesterday, one of the difficulties in managing in uncertain environments is that hierarchies often don’t function well in these circumstances. They respond slowly to change.

    This is important to innovation, because it means that you can’t simply say “we need to be more innovative” in response to competitive pressures. You actually have to change the way you do business – much as the kings around the Indian Ocean had to change their entire military systems in response to pressure from the Portuguese.

    I’ve talked about Steve Denning’s ideas in this regard a few times. He has a set of prescriptions for changing your management systems to deal with such threats. They are well worth exploring.

    He says that experimenting is a key to building such systems, just as Matt suggests. He quotes The Power of Pull to show how self-managing teams can do this:

    Organize work in short cycles: As the authors of The Power of Pull point out, one proceeds “by setting things up in short, consecutive waves of effort, iterations that foster deep, trust-based relationships among the participants… Knowledge begins to flow and team begins to learn, innovate and perform better and faster.… Rather than trying to specify the activities in the processes in great detail…specify what they want to come out of the process, providing more space for individual participants to experiment, improvise and innovate.”

    When you are faced with competitive threats that change the playing field, you can’t respond by simply doing more of what you’re currently doing. Furthermore, you usually can’t copy what the new competitors are doing either – their systems and contexts are often too different, which means that even if you can copy what they’re doing, it won’t work the same way.

    To succeed, you need a system that supports experimentation – that’s what really provides firepower.

    Experimentation beats benchmarking.

  • Contrasts Drive Innovation

    In his thought-provoking new book Whole Earth Discipline, Stewart Brand has this interesting passage:

    In Peter Ackroyd’s London: The Biography (2000), he quotes William Blake – Without contraries is no progression” – and ventures that Blake came to that view from his immersion in London. “Wherever you go in the city,” Ackroyd observes, “you are continually being assaulted by difference, and it could be surmised that the city is simply made up of contrasts; it is the sum of its differences.” What drives a city’s innovation engine, then – and thus its wealth engine – is its multitude of contrasts. The more and greater the contrasts, and the more they are marbled together, the better. The most productive city is one with many cultures, many languages, and more kinds of urban experience available than any citizen can keep track of.

    London skyline. Skyline de Londres.

    This seems about right.

    We know from the work of Jane Jacobs and others that cities drive economic growth and innovation. We know from the work that Scott Page and others that differences increase creativity. So it makes sense that the increased diversity that you get in cities, especially big ones, will drive innovation.

    And if it’s true for cities, it’s probably true for firms too. It’s something to think about if you’re trying to improve innovation efforts.

    (photo from flickr/J. A. Alcaide under a Creative Commons License)