Tim Kastelle

Category: book riffs

  • Why You Need to Be Vulnerable to Innovate

    Why You Need to Be Vulnerable to Innovate

    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 until then, I defined myself by how well I did in school.

    So I felt a great deal of shame when I really struggled once I got there.

    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 took a break to reset, and worked in a feedmill.  I saved enough money to pay for finishing up college myself, and when I went back 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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  • Business Needs More Art

    Business Needs More Art

    The tagline in the latest daily email (which is well worth subscribing to) from Hugh MacLeod is: Business needs more art.  I believe that he is absolutely correct.

    In his terrific new book How Music Works, David Byrne starts to explain why:

    A study done by the Curb Center at Vanderbilt University… found that arts majors developed more creative proble-solving skills than students from alost any other area of study. Risk taking, dealing with ambiguities, discovering patterns, and the use of analogy and metaphor are skills that are not just of practical use for artists and musicians. For example, 80 percent of arts students at Vanderbilt say that expressing creativity is part of their courses, while only 3 percent of biology majors and about 13 percent of engineers and business majors do. Creative problem solving is not taught in those other disciplines, but it is an essential survival skill. If one believes, as I do, that creative problem solving can be learned, and is something that can be applied across all disciplines, then we’re chopping our children’s legs off if we slash the budgets for classes in the arts and humanities. There’s no way these kids will be able to compete in hte world in which they are growing up.

    Check out those skills: risk taking, dealing with ambiguities, discovering patterns, and the use of analogy and metaphor. That’s a pretty important list. In fact, I’ve argued before that building a tolerance for ambiguity is the single most important skill in management.

    So, yeah, business definitely needs more art.

    When I think about art and artists, I am constantly fascinated by how the artistic process is often driven by an obsession with solving a particular type of problem.  Jeffrey Davis frames this nicely in a post called The Problem-Solving Paradox:

    Creativity is imagination applied to making situations better – more effective, enriched, beautiful, meaningful, humane. Better.

    Creativity is imagination applied to enriching life.

    To improve a situation, you have to track what’s problematic and apply your imagination to improving or solving it.

    This is what we human beings are biologically and spiritually driven to do.

    So, a work life rich with problems is a gold mine for creativity.

    The other thing about this is that artists experiment, all the time. Experimenting, and making mistakes, is the only way to get better.

    Joe McCarthy put it nicely in a comment here a while back:

    And just to bring it full circle, while I agree that getting it right requires learning and skill, I believe that learning and skill often arise primarily through making lots of mistakes (i.e., being wrong alot … but with an open mind).

    So, yes, business absolutely needs more art.

    Let’s go make some.

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  • Change Your Frame of Reference for Better Innovation

    Change Your Frame of Reference for Better Innovation

    I got a new camera recently, and the interesting thing about it is the features that it doesn’t have.  It has a fixed-length lens, which means that there’s no zoom.  There are some good technical reasons for this, but the interesting thing is that this small change has completely transformed the way that I think about photography.

    Nancy and I are birders, so for us, we’ve always used optics to get us closer to things.  A good pair of binoculars can get us a clear view of a small bird in the top of a tree, or a big bird a long way away.  Zooming means that we don’t have to spend hours stalking closer to get a good view of a bird.  For Nancy, zoom on her camera means that she can get good shots of birds that we can only just make out with the naked eye.

    So I’ve always associated optical gear, both cameras and binoculars, as things that get me closer.

     

    But there’s none of that with a fixed lens.  You actually have to think about where you’re standing relative to what you’re shooting.  It makes photography much more mentally engaging, and a lot more challenging.  So I’ve been learning a lot.

    Here is how Ken Rockwell puts it on his excellent photography blog:

    With a fixed lens, or a few fixed lenses, you already know the camera’s field-of-view as you wander around. With just one fixed lens or or two, you’re already seeing what makes good compositions before you even stop to take a picture. You know what fits in your field-of-view, and you’re in compositional seeing mode as you walk about.

    With a zoom, you’re not thinking as you walk around. With a zoom, you aren’t thinking about how to arrange elements inside a rectangle until after you’ve already stopped for something. Maybe that something will make a good picture, maybe not. You’re not even thinking; you’re just wandering.

    After using a fixed lens for a while, you become intimately familiar with its field of view without having to look through the camera. Since you already know what fits as you walk around, so you can start seeing your compositions in your head as you move about. You can see from different angles and different heights just by moving around, without needing your camera.

    He’s got a lot more to say on the subject, and you should read the whole post (and if you’re interested in photography, it’s a must-read site).

    The bottom line is that changing the frame through which I view things is making me a substantially better photographer.

    The same can be true in business – if you want to innovate, changing your frame of reference is a great strategy.  Nilofer Merchant talks about this in her book 11 Rules for Creating Value in the #SocialEra, where she talks about the value of openness (a topic that Ralph Ohr just addressed here as well):

    Banking on openness is like saying you have hope in people to create.

    I point out this frame because it is so easy for any of us to not realize that this frame changes our vantage point. I ask you to think about what frames you are using to view the world. Frames are simply windows to shape understanding. You may be drawn to one and repelled by the other without even realizing it. But learning to apply different frames and appreciating the difference deepens our understanding. Galileo discovered this when he built his first telescope. Each lens he added contributed to a more accurate image of the heavens. Successful people do the same. They reframe until they understand the issue at hand.

    Openness is a frame that helps us understand the social era. After all, we can continue to hold ideas tightly, but we must realize that this means they can’t be shared ideas. The remain alone, isolated, and separated so that they can’t be built upon, refined, and shaped into something bigger.

    Reframe.

    Right now, think about a frame that you take for granted.  What assumptions lie underneath this frame?  How does the world look different if you look through a different frame?

    Reframing makes me a better photographer.  Reframing makes us better innovators. Reframing helps us understand how business works now.

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  • Are You Ready for the #SocialEra?

    Are You Ready for the #SocialEra?

    A few months ago, Facebook bought Instagram for $1 billion.  Instagram had 13 employees at that point in time.  How is it possible for 13 people to create a company worth $1 billion?

    On the face of it, this might seem impossible.  But if you read 11 Rules for Creating Value in the #SocialEra by Nilofer Merchant, it starts to make a bit more sense.  It turns out that Instagram was doing nearly all of the things that she recommends in this terrific book.

    Here is how Nilofer defines the Social Era:

    Here’s the simplest way to define the Social Era: the industrial era primarily honored the institution as a construct of creating value. And the information age (inclusive of Web 1.0 and Web 2.0 phases) primarily honored the value that data could provide to institutional value creation. It allowed for greater efficiency to do the same things that were done in the industrial era. The Social Era honors the value creation starting with the single unit of a connected human. That shift in focus has profound implications for business, and those implications are the subject of this book.

    There are several important issues that Nilofer raises in the book:

    •  Social is not just “Social Media.” If your employees are disinterested, and you run a top-down hierarchy, and the only real purpose that customers serve you is to give you a bunch of money, then adding a Facebook page doesn’t make you social.  Nilofer describes the impact that social can have on every aspect of an organisation – the social era of business changes HR, service, finance, products, distribution, supply chain management, sales, marketing and innovation. The implications of this are significant, and Nilofer does a great job of drawing them out.  If you’re going to take this seriously, then you need to think about how to use social tools across all of these functions.
    • It’s not just about the tools.  This is not a book that answers questions like “should we be on Pinterest?”  I was re-reading the book today, and realised that it addresses some of the same issues that I am trying to get at with The Innovation Matrix.  Here is how I pictured it in #SocialEra:If you want to make your organisation more social, it requires tools and culture to work together. Tools by themselves will never fix your problem. This is a point that Terri Griffith also makes very well in The Plugged Manager – that successful management these days requires strong interaction and interdependencies between people, technology, and processes (and if you want to read a good, more traditional review of #SocialEra, Terri’s is excellent).  To really become social, it’s not enough to pick the right tools – you have to change your culture as well.  This is huge.  It means that:
    • Changing the culture means changing the business model. When you take social seriously, you end up needing to change nearly everything about how you operate. Here’s Nilofer again:

      These 800-pound gorillas are feeling the Social Era all around them, but are failing to notice how significant a change it has produced. Perhaps that is because it has shown up in bits and pieces, sometimes wrapped up in technology whiz-bang-ness. You might have seen it arrive via freemium models, crowdsourcing, online communities, virtual workforces, social networks, co-working locations, and so on. Each of these on its own is interesting but not the central idea; each on its own is only an example of how value is created with others, allowing seemingly disparate individuals to create value in a way that once only centralized organizations could.

      When we look at all the parts together, we can see how it affects everything.

      So for your Facebook page to work, you need to change the way you distribute decision-making to push accountability down the hierarchy, and you need to hire differently to have people sufficiently skilled to handle this. Your relationship with customers changes, and so on. Your business model needs to be internally consistent. Business models based on social are going to be significantly different than those based on economies of scale, or big data.

    The big question here is “what do you do if you’re already big?” It’s relatively easy to build nimbleness in to a small startup. It’s another question entirely if you’ve been around for a while and have been reasonably successful. Chuck Eesley talks about #SocialEra does this:

    My favorite analogy in the book is between 800-pound gorillas and quick, nimble gazelles. While many of us who teach and study entrepreneurship have given up on making the 800-pound gorillas more nimble and accepted a world where startups continually disrupt old industries while creating new ones, Nilofer’s book outlines how even larger organizations can become more nimble and quick moving by breaking down walls and barriers, pursuing social purpose, leaving traditional strategy behind and changing the way they approach strategy in the #SocialEra.

    One of the tricks here is to think about what you would do if you were building your business from the ground up, starting now. Dave Gray said in a tweet today:

    You can’t turn the New York Times into Instagram. I’m not even sure you’d want to. But the NYT is competing against companies like that – ones that were born in the Social Era, and which embody it.

    If you’re an 800 pound gorilla, that’s something you’ll need to think about.  More importantly, it’s something you’re probably going to need to act upon.

    Welcome to the #SocialEra.

    Disclaimer: I know and like Nilofer, and I received a free copy of the book. I also bought my own copy. I’m writing about the book because of its quality, not because of who wrote it or how I got it.

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  • Apple is a Manic Pixie Dream Firm

    The Manic Pixie Dream Girl

    Nancy and I saw Ruby Sparks last night, and really enjoyed it. It’s written by Zoe Kazan, who also stars, and it absolutely skewers the Manic Pixie Dream Girl trope.

    Nathan Rabin defined Manic Pixie Dreams Girls (MPDG) in his review of Elizabethtown:

    The Manic Pixie Dream Girl exists solely in the fevered imaginations of sensitive writer-directors to teach broodingly soulful young men to embrace life and its infinite mysteries and adventures. The Manic Pixie Dream Girl is an all-or-nothing-proposition. Audiences either want to marry her instantly (despite The Manic Pixie Dream Girl being, you know, a fictional character) or they want to commit grievous bodily harm against them and their immediate family.

    You can identify a MPDG because she:

    • Is beautiful, uninhibited, and usually kooky. Or weird.
    • Likes the hero of the movie for no real apparent reason.
    • Has no obvious inner life, career aspirations, or desires of her own.

    Examples are the characters played by Natalie Portman in Garden State, Audrey Hepburn in Breakfast at Tiffany’s, and Melanie Griffith in Something Wild, to pick three examples from three different eras. If you’re still not clear on the concept, this might help:

    Ruby Sparks quite cleverly sends up this trope by making the title character explicitly the creation of a writer’s imagination. Then every time she tries to express a desire or need of her own, he freaks out.

    The Manic Pixie Dream Firm

    As Nancy and I talked about the film today, I realised that Apple is a Manic Pixie Dream Firm.

    Last week we saw Bob Sutton moderate a talk by Geoffrey Nunberg, discussing Nunberg’s new book Ascent of the A-Word. During the discussion, Sutton talked about his theory that Steve Jobs is a Rorschach Test. The piece about Jobs in Wired that came out last week quotes Sutton, and says:

    Sutton now thinks that Jobs was too contradictory and contentious a man, too singular a figure, to offer many usable lessons. As the tale of those Chinese CEOs demonstrates, Jobs has become a Rorschach test, a screen onto which entrepreneurs and executives can project a justification of their own lives: choices they would have made anyway, difficult traits they already possess. “Everyone has their own private Steve Jobs,” Sutton says. “It usually tells you a lot about them—and little about Jobs.”

    Like the Manic Pixie Dream Girl, Jobs is a projection. One consequence of this is that peoples’ view of Apple is often a Rorschach test as well – it becomes the firm that they want it to be – a Manic Pixie Dream Firm.

    A post by Jessica G. argues that the Manic Pixie Dream Girl trope is dangerous, because it creates unrealistic expectations of what women should be. I think that the Manic Pixie Dream Firm is equally dangerous.

    How to Identify a Manic Pixie Dream Firm

    You can identify a Manic Pixie Dream Firm because it:

    • Never Makes Mistakes: the Manic Pixie Dream Firm understands its market perfectly. So it never has to deal with uncertainty, and it never does anything wrong. It is a beacon of stability and hope in a world filled with chaos.
    • Does things by magic: the MPDF usually springs from genius. This means that the things that it does will never work in a normal firm. It is so far out of the norm that there is no point trying to do the same things in your firm.
    • Makes everyone happy: because it is perfect and never makes mistakes, a MPDF makes its customers, employees and fans happy. All the time.

    Why Manic Pixie Dream Firms are Dangerous

    The Manic Pixie Dream Firm trope is extremely dangerous, much like the Manic Pixie Dream Girl is. The latter takes all the responsibility out of the hands of the movie hero. The MPDG exists to make him happy, and to enable him to do his creative work. In most of the movies with a MPDG, she fixes things for the hero, whether they end up together or not.

    But that’s not the way that real relationships work. No one makes you happy – you’re responsible for yourself.

    It’s the same with work. The Manic Pixie Dream Firm trope is dangerous for two reasons. The first is that it creates an unattainable ideal for firms to reach. This is part of what I am trying to get at with The Innovation Matrix – because not everyone can (or should) be Apple, Google or Procter & Gamble.

    We need to understand how real firms work, because this how we undertake evidence-based management. We actually know a lot about what makes firms work – but we often don’t use this knowledge. In part, we don’t use what we know because it doesn’t fit with the distorted view of what a perfect firm should be created by the Manic Pixie Dream Firm idea.

    The second problem with the MPDF is that it takes responsibility away from managers and workers for making their firms better. If a MPDF never makes mistakes, and does this by magic (or genius, same thing), then there’s no hope for the rest of us. Which means that if our firm isn’t as great as the Manic Pixie Dream Firm, then it is our firm’s fault for being inadequate.

    But it’s not our firm’s fault – it’s ours. Firms are made of people, and we determine how our firms work.

    The movie hero really needs to take control of his own life, instead of relying on the Manic Pixie Dream Girl to fix everything for him. And we need to take control of our work lives, instead of relying on the Manic Pixie Dream Firm to fix everything for us.

    Goals based on illusions can’t be met. The clip below from NPR concludes by saying that the Manic Pixie Dream Girl is a wonderful character, but not a real person. Believing that she’s real is the danger.

    In the same way, the Manic Pixie Dream Firm may be a wonderful character in a business book, but they’re not real either. If you spend your working life looking for one, you’re bound to be disappointed. That is why the way that we often talk about Apple, Google, and, for quite a while Toyota, can be dangerous. We end up describing idealised fantasy firms built by untouchable geniuses. Hoping to somehow work for a firm like this is dangerous, because they don’t exist.

    It’s better to do what you can to make your own firm great.

  • Why Your Business Model Must Evolve

    Nancy and I were talking about business models today. She is trying to figure out how to use her knowledge of ageing to have the biggest impact. As we discussed the possibilities, and it was clear that she wants to work out the best plan in advance.

    I told her that this is impossible – instead, your business model must evolve.

    It reminded me of one of the biggest failures I was ever involved with. I was working for a startup, and we had a product with some problems. Before I joined up, they had built a database development tool which you could use to build websites. It was particularly well-suited for e-commerce sites.

    When it came time for me to sell it, I ran into some problems. The main one was that the majority of people that needed to build such websites were already using PHP. Since PHP was free, and ours wasn’t, this was a problem. However, in talking to potential customers, I discovered that our software did one unique thing, that had some potential value.

    Our software could use one query to interrogate multiple databases, and return an integrated answer. This ability had huge potential value for anyone trying to integrate a legacy database application into a new system.

    I tried to get our CEO and our owner to redesign the software to attack this market. I failed.

    Not too long after that, so did our software.

    Compare that story to this one: Caterina Fake and Stewart Butterfield were running a company building a game called Game Neverending. As part of the game, one of the engineers wrote a photo-sharing module. They quickly realised that this module had more commercial potential than the game. More importantly, the photo-sharing could be brought to market more quickly, which was crucially important because they were running out of cash.

    Their photo-sharing module became Flickr.

    This is a textbook example of a pivot – something that we even have conferences about now:

    Pivot Conference 2011

    Fake and Butterfield were able to move from their original idea to one with greater potential. My startup couldn’t. According to Clayton Christensen, the need to pivot is more common than we think:

    Professor Amar Bhide showed in his Origin and Evolution of New Business that 93 percent of all companies that ultimately become successful had to abandon their original strategy—because the original plan proved not to be viable. In other words, successful companies don’t succeed because they have the right strategy at the beginning; but rather, because they have money left over after the original strategy fails, so that they can pivot and try another approach. Most of those that fail, in contrast, spend all their money on their original strategy—which is usually wrong.

    93% of successful companies pivot!!

    This is why business models must evolve – because our original one is probably wrong.

    John Mullins and Randy Komisar talk about how to address this in their excellent book Getting to Plan B: Breaking Through to a Better Business Model. Their primary recommendation is use dashboarding to track the development of your business model. They use a more restricted view of what a business model is than other current models of business models do, but their approach is very useful.

    Mullins and Komisar recommend using analogs and anti-logs to develop your original idea. Analogs are companies or products that you want to be like, and ant-logs are the opposite – examples of what you want to avoid. These will help you build your first business model.

    The next step is identify the leaps of faith – what are assumptions that must be correct for your business model to work? If there is no previous data to help you test these, then you have a leap of faith. The last step is to figure out ways to build and test hypotheses that will be determine if these assumptions are correct or not.

    If they aren’t you need to evolve your business model to a new version.

    The best resource I’ve run across to help you build and test business model hypotheses is Ash Maurya’s Running Lean: Iterate from Plan A to a Plan That Works.He uses a modified version of the Business Model Canvas. Maurya says that building a viable business model is actually the primary objective when you launch a new idea. In other words, “your product is NOT ‘the product‘ – your business model is ‘the product.’”

    Here’s what he says about hypothesis testing:

    Once you know what you need to learn, the final step is then setting up a series of experiments designed to uncover some answers as quickly as possible. The tactics that you use is highly dependent on the stage of your startup. For instance, the period before Product/Market Fit is usually riddled with qualitative learning (customer interviews/usability tests), while the period after Product/Market Fit tends to be more quantitative.
    …
    As entrepreneurs we view the world with a strong solution bias. Once we acknowledge that the solution is not the whole product and that we don’t need to pretend to believe our made up answers, we shift from pitching to learning – from other people.

    I believe the true benefit of creating a business model/plan is only realized when it facilitates learning from other people.

    Effective business models are dynamic. The odds of getting yours right on the first go are low. So your first business model is a starting point.

    You need to identify the things you don’t know, and build experiments that will help you learn what will work.

    That’s what Butterfield and Fake did with Flickr, and that’s what I should have done in my startup. You can bet that’s what I’ll do while Nancy and I work out a business model for her, and when I launch new ideas in the future.

    The business models that win are not those that are the best right out of the box. The business models that win are the ones that evolve quickly and effectively. Building them to change is the best way to try to build one that will last.

    (Photo from flickr/thekenyeung (of course!) under a Creative Commons License)

  • Culturematic by Grant McCracken Makes a Great Case for Experimenting

    Experiments are a critical innovation skill, and it’s one that you can use to build your Innovation Competence. A culture of experimentation is one of the elements that distinguishes highly innovative firms from those that arene’t quite as good at it.

    The best thing that I’ve run across recently on the importance of experimentation is Grant McCracken’s new book Culturematic: How Reality TV, John Cheever, a Pie Lab, Julia Child, Fantasy Football . . . Will Help You Create and Execute Breakthrough Ideas.

    Here is how he defines a Culturematic:

    Eventually, I found an idea that helps explain these oddities. I call it Culturematic. A Culturematic is a little machine for making culture. It is designed to do three things: test the world, discover meaning, and unleash value.

    And here is a video where he gives a bunch of examples:

    I’m in the middle of reading a string of outstanding books right now, and this is one of my recent favourites. Here are some quotes from it about experimenting:

    Start-ups are inclined to put all their eggs in one basket, all their bets on a single idea. And this is wrong. If nothing else, it’s an evolutionary error. What we want instead is a Culturematic cluster, a bundle of experiments, investigating the world in a variety of ways, defined with enough intellectual generosity that several outcomes—some of them quite different—are possible. Are there venture capitalists out there who understand the Culturematic proposition? Are there people looking to fund ingenuity bundles instead of this-one-idea-take-it-or-leave-it? I hope this book will encourage a new approach.

    This is a fairly novel view of startups, but it has some merit. It certainly applies to larger, more established firms that are trying to innovate. Build a bundle of experiments, test them out, and amplify what works.

    Another quote:

    The search for the future is an exercise in edge finding. We don’t know what we are looking for. We are not even sure what it is when we find it. We are working by instinct, by intuition. We are flying by the seat of our pants. To find the innovation that returns lots and lots of value, we will have to try many things that return next to nothing. It’s the nature of the hunt.

    Experimenting is another tool that helps us when we are faced with a mystery rather than a puzzle. Mysteries are typified by large amounts of uncertainty, and in these situations, we must tools built for that – like Culturematics.

    Innovation is a messy, multiple business. There is no single method. The sensible approach is to keep trying stuff—to provoke the world and let it start talking to you. As Sims puts it, invention and discovery emanate from the ability to try seemingly wild possibilities; to feel comfortable being wrong before being right; to live in the world as a careful observer, open to different experiences; to play with ideas without prematurely judging oneself or others; to persist through difficulties; and to have a willingness to be misunderstood, sometimes for long periods, despite the conventional wisdom.

    The reference there is to Little Bets: How Breakthrough Ideas Emerge from Small Discoveries,by Peter Sims. That was my favourite book last year on experimenting – these two books fit together quite nicely.

    We know two things. First, we are obliged to innovate. This is the only way to survive the killing fields of the contemporary marketplace (where only 14 percent of the Fortune 500 survive for more than fifty years). Second, we’re hard-pressed to tell which innovations will flourish and which will die. Sometimes, we are not even sure where to start. In a world like this, we want lots of little experiments. So says the IPO prospectus for Google in an almost perfect expression of the Culturematic logic: We will not shy away from high-risk, high-reward projects because of short-term earnings pressure. For example, we would fund projects that have a 10 percent chance, [placing] smaller bets in areas that seem very speculative or even strange. As the ratio of reward to risk increases, we will accept projects further outside our normal areas, especially when the initial investment is small … Most risky projects fizzle, often teaching us something. Others succeed and become attractive businesses.

    There’s not a whole lot more to add. Experimenting is a crucial part of innovation. If you want to improve your innovation capability, improving your capacity for experiment is a great first step to take. It’s probably more effective than the more symbolic steps, like making it a core value or integrating innovation with strategy (though you’ll eventually want to do both of those too).

    We talk about experimenting a lot here, because it’s so important.

    If you want to make your organisation better right now, what’s an idea that you can go out and test? If you can’t think of one, Culturematic will give some excellent suggestions about where to start.

    So go to it.

  • Are You Solving a Puzzle or a Mystery?

    Innovation is all about coming up with new solutions to solve problems.

    But here’s an interesting question: is the problem that you’re trying to solve a puzzle or a mystery?

    The distinction was made by Gregory Treverton and highlighted by Malcolm Gladwell in a piece he wrote on Enron a few years ago.

    According to Treverton, a puzzle is a problem that can be solved if you have more information (or the right information). On the other hand, more information doesn’t help with a mystery, which is characterised by high levels of uncertainty, and the need for judgement. Here’s Gladwell:

    The national-security expert Gregory Treverton has famously made a distinction between puzzles and mysteries. Osama bin Laden’s whereabouts are a puzzle. We can’t find him because we don’t have enough information. The key to the puzzle will probably come from someone close to bin Laden, and until we can find that source bin Laden will remain at large.

    The problem of what would happen in Iraq after the toppling of Saddam Hussein was, by contrast, a mystery. It wasn’t a question that had a simple, factual answer. Mysteries require judgments and the assessment of uncertainty, and the hard part is not that we have too little information but that we have too much. The C.I.A. had a position on what a post-invasion Iraq would look like, and so did the Pentagon and the State Department and Colin Powell and Dick Cheney and any number of political scientists and journalists and think-tank fellows. For that matter, so did every cabdriver in Baghdad.

    The distinction is not trivial…

    If things go wrong with a puzzle, identifying the culprit is easy: it’s the person who withheld information. Mysteries, though, are a lot murkier: sometimes the information we’ve been given is inadequate, and sometimes we aren’t very smart about making sense of what we’ve been given, and sometimes the question itself cannot be answered. Puzzles come to satisfying conclusions. Mysteries often don’t.

    Puzzles are attractive because, as Gladwell points out, they come to clean conclusions. Ironically, by these definitions, all of the Agatha Christie books are puzzles, not mysteries – they can always be solved if you just pay attention to the right information, which is all there for you.

    We are strongly drawn to puzzles because of how clear-cut they are.

    Unfortunately, many of the big problems that we face are not puzzles, but rather mysteries. Mysteries are messy, and the methods that solve puzzles don’t work for mysteries, and they might actually make them worse.

    Jeanne Liedtka and Tim Ogilvie pick up on this distinction in their outstanding book Designing for Growth: A Design Thinking Toolkit for Managers.

    They say that incremental innovations are puzzles. The parameters are basically known, we just need to find the right information to develop the innovation that will solve the problem. But then:

    There’s another category of problem called mysteries, where there is no single piece of data, there is no level of data disclosure that will actually solve a problem. In fact, there might be too much data and it’s about interpreting all the data that’s there. And that’s a richer, harder problem that requires more systems thinking, that requires prototyping and piloting. That’s really where the designers are often most adept.

    Their contention is that the high levels of uncertainty in mysteries requires a different, more experimental approach. Their solution to this is design.

    Third, design is tailored to dealing with uncertainty, and business’s obsession with analysis is best suited for a stable and predictable world. That’s the kind we don’t live in anymore. The world that used to give us puzzles but now dishes up mysteries. And no amount of data about yesterday will solve the mystery of tomorrow. Yet, as we’ve already noted, large organizations are designed for stability and control, and are full of people with veto power over new ideas and initiatives. They are the “designated doubters.” The few who are allowed to try something new are expected to show the data to “prove” their answer and get implementation right the first time.

    The bulk of the book is taken up with describing tools and processes that you can use to implement design thinking. This is how they picture the process:

    If you look at this model, it maps onto the idea management process model that we have discussed here on numerous occasions.

    Their model is based around four questions. The first – What Is? – is the place for problem definition.

    The next step is asking “What If?” This is idea generation. And it’s the same question that Grant McCracken identifies is critical in his book Culturematic – discussed here. This is the divergent step in the process.

    Question three is “What Wows?” This is the idea selection step. Liedtka and Ogilvy outline an method for assumption testing and rapid prototyping here. In other words, experiments.

    The final question is “What Works?” This is the execution and diffusion phase of the process. This is where you co-develop with your customers to converge on a solution.

    The approach in Designing for Growth is sound. It is a very practical book, with clear instructions on how to implement design thinking in your innovation process, and with plenty of examples and case studies to make the ideas real.

    The problems that lead to disruptive innovations are often mysteries. This means that we need a different toolkit to solve these problems than we use when we solve puzzles. Experimentation and design thinking are two excellent approaches to use when facing a mystery.

    Which kind of problem do you face right now?

  • How to Improve Your Innovation Competence – Experiment!

    Note: This is part of a series of posts explaining the individual parts of The Innovation Matrix. See this post for a description of the full model and what can be done with it.

    I presented The Innovation Matrix at a conference last week. After the other three speakers in my session had given their talks (all excellent!), the first question we got threw me for a bit of a loop. The point that was raised was that the guy thought that everything that we had presented was very linear, and not very systems-oriented.

    This made me realise that I didn’t make one of the key points that underpins The Innovation Matrix – it’s actually based on complex system thinking. And the key insight that I get from it is this: there is a (sometimes huge) disconnect between the effort you put into innovating, and the return that you realise. The relationship between the two is non-linear.

    You can have an extremely high level of Innovation Commitment, and sink large amounts of time and resources into it, and still be lousy at innovating.

    The whole point of the matrix is that this non-linearity exists, it surprises people, and we need to be aware of it.

    What is the best way to address this?

    The most important skill to deploy in complex systems is experimentation. When faced with high levels of uncertainty, and systems that respond non-linearly, we can’t predict in advance which ideas will succeed.

    This is why building a culture of experimentation is an essential part of Innovation Competence. This is the approach that is outlined by Peter Sims in his excellent book Little Bets: How Breakthrough Ideas Emerge from Small Discoveries.

    I just read another equally outstanding book that discusses a similar approach. It’s by Grant McCracken – Culturematic: How Reality TV, John Cheever, a Pie Lab, Julia Child, Fantasy Football . . . Will Help You Create and Execute Breakthrough Ideas.

    In his last book, Chief Culture Officer: How to Create a Living, Breathing Corporation,McCracken explained why it is important to pay attention to culture. In Culturematic, he outlines how to undertake cultural innovation.

    Nearly all of his examples come from popular culture (the Old Spice campaign, Andy Samberg on Saturday Night Live, etc.), but the approach that he outlines is actually a general one. Here is how he describes it:

    Eventually, I found an idea that helps explain these oddities. I call it Culturematic. A Culturematic is a little machine for making culture. It is designed to do three things: test the world, discover meaning, and unleash value.

    Why does Samberg’s standalone production studio work so well for SNL?

    It was to give SNL a little spaceship that could go places and do things out of the range of the SNL players. At 30 Rock, no one invests so much as a second in something that might not work. Because the clock is ticking. But The Lonely Island can try stuff until something works. Here, failure is acceptable, because, as Michaels puts it, it’s the guys, not the cast, who “take the risk.”
    …
    Many Culturematics return nothing. This is not to say they fail. They tell us that this is a tree up which we no longer wish to bark.

    That’s experimenting! And that’s how we innovate.

    Here is how McCracken describes innovation at Unilever – think about where this would put them on The Innovation Matrix:

    British researcher John Kearon recently looked at the innovation record of Unilever, a Dutch-British corporation. The results were surprising. Unilever has a great track record, creating not just new brands and products but entire categories in the U.K. consumer market: laundry powder, fabric softener, margarine, and moisturizing soap. Kearon noticed that none of these discoveries came from the innovation centers Unilever set up in the 1990s. Everything about the innovation centers looked right. They hired the best people. They spent real money. They centralized Unilever’s creative efforts. And as Kearon explains, by and large they failed: The innovation center model is good at creatively farming existing brands and has added significant value to the likes of Dove, Lynx and Flora. However, as a model of innovation it is too centralized, too evidence-based, too marketing-science orientated to have the freedom and contrariness to originate new categories that can create even greater value. Kearon recommends another approach. If you want to innovate as Google, Apple, and Red Bull have, he says, you should follow a couple of rules: Don’t look for big ideas. Seek small ideas that can grow. Fail fast. Fail often. Keep learning and never give up. Excellent, very Culturematic advice.

    Very Culturematic, and very Little Bets.

    The question at the conference threw me because I hate linear models – they almost never describe the real world. And The Innovation Matrix is not linear. It actually describes a non-linear problem: that we can’t predictably increase our innovation capability simply by increasing our commitment to innovation, or simply by throwing more resources at it.

    There is always mystery about which ideas will actually work. This is part of what creates the disconnect.

    In a non-linear world, the best strategy is to innovate through experimentation. As Saul Kaplan says: Think Big, Start Small, Scale Fast.

    Figuring out how to do this is the best possible first step if you are trying to change your position on The Innovation Matrix, because it’s the best way to actually get better at executing ideas.

    (And if you want some tips on how to proceed, I can’t recommend the books by Sims and McCracken strongly enough)

  • If Not Excellence, What? Tom Peters & Business Models

    Better business models lead to better businesses. One critical part of building a better business model is getting your value proposition right.

    An excellent value proposition means that you have to be excellent at, well, something.

    But what?

    One framework that John uses a lot in his classes is this from The Discipline of Market Leaders: Choose Your Customers, Narrow Your Focus, Dominate Your Market:

    There’s a nice explanation of the figure here, but basically, it means that you have to choose. You can’t be everything to everyone – you need to build your value proposition around differentiation, customer responsiveness, or lowest total cost.

    One important part of the diagram though, which is often overlooked, are the lines on each bar. These mean that even while you concentrate on excellence in one area, you have to be at least competent in the others. Where this baseline lies will vary from industry to industry.

    Here’s an example, from the engineering company that I mentioned yesterday. They are in a very competitive industry. We evaluated the business model of four of their different business units. This turned out to be a pretty useful application of the business model concept to a large, well-established firm.

    The one common thread across all four business units is that they have customers that are willing to pay a premium for reliable delivery of on-time and on-budget work. They have an opportunity to differentiate in this area.

    However, their industry is fiercely competitive. So the benchmark level of operational excellence that is required just to be in the game is very high. While they are trying to build excellence and differentiation in reliability of delivery, they also have to keep improving efficiency.

    So one way to identify a potential area of excellence is finding the things that your customers value and being fanatical about delivering in that area.

    In his latest book, which, as usual, is excellent, The Little Big Things: 163 Ways to Pursue EXCELLENCE,Tom Peters includes a great quote from an anonymous commenter on his blog about how to do this:

    Excellence can be obtained if you:

    …care more than others think is wise;

    …risk more than others think is safe;

    …dream more than others think is practical;

    …expect more than others think is possible.

    So, to sum up. Better business models are built on excellent value propositions. To build one, you have to avoid trying to be excellent in all areas (differentiation, customer responsiveness, or lowest total cost), because you’ll spread yourself too thin, and get caught in the middle.

    On the other hand, if you are simply competent in all three areas, you’ll also fail because you’re not excellent at anything.

    You need to be competent at a couple, and excellent at one. You can help yourself define what you should be excellent in by thinking about that quote from Peters.

    Excellence requires going fanatically overboard in something. That’s what excellent value propositions are built on, and those are what drive better business models.

  • Innovation is the Source of the Variation that You Need to Adapt & Survive

    Innovation is an evolutionary process. Here is John explaining what that means:
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    Generic evolutionary processes have three parts – generation of variety, selection, and replication. This maps on to the three steps in the innovation value chain. The Innovation Value Chain also has three steps – idea generation, idea selection and execution, and idea diffusion. The connections between the two models should be fairly apparent!

    Innovation as evolution has some interesting implications, including:

    • The ideas that spread are often not optimal solutions to problems, they simply happen to be the best solutions currently available. In other words, our innovations just have to be good enough, not perfect.
    • Consequently, the idea that we’re not looking for a perfect execution of our new ideas is a strong argument in favour of taking a build, launch, tweak approach to getting our new ideas out there. We’re most likely to get to the best solutions to the problems we are interested in through an iterative process, rather than through pure development.
    • This leads to the last point, which is that the evolution of our great ideas is built on collaborative networks. The sooner we can enlist the help of our network (customers, partners, suppliers, etc.), the more likely we are to come up with the best version of our great new idea.

    Another important thing to consider is that innovation creates variation. And the more variation we have in the way that our organisations operate, the better our ability to adapt to a changing environment.

    Here is a series of interesting quotes from The Power of Positive Deviance: How Unlikely Innovators Solve the World’s Toughest Problemsby Richard Pascale, Jerry Sternin and Monique Sternin:

    It is an empirical fact that most of the world’s cities live forever.’ Corporations, on the other hand, live half as long as the average human being. The explanation has to do with the self-organizing and emergent nature of cities as contrasted with companies. True, cities may cycle between decline and ascendance. But the complex interplay between a city’s heterogeneous elements fosters continuing variation and adaptation. Corporations, in the name of efficiency, suppress variation by “getting all the ducks in line.” To optimize productivity, they evolve highly refined and internally consistent operating systems. Payoff results-as long as the music lasts.
    …
    But in the face of nontraditional competitors or major environmental discontinuities, all that streamlining and reengineering limits diversity, suppresses self-organization by those closest to the disruptive change, and curtails a bottom-up emergent response to cope more effectively. We witnessed this at Genentech and Merck. Nothing fails like success. Overadaptive organizations become inflexible. Disruptive change leaves them as helpless as a beached whale.
    …
    The problem is not exclusively technical and requires behavioral or/and social change. • The problem is “intractable”-other solutions haven’t worked. Positive deviants are thought to exist. There is sponsorship and local leadership commitment to address the issue.

    This is similar to the idea that Jeffrey Phillips advocates – that efficiency and innovation are two quite different outcomes, and you can’t achieve both at the same time very well.

    Efficiency by definition reduces variation. And yet, variation is the one thing that allows us to adapt to uncertain, changing environments.

    The Positive Deviance approach is interesting. Here is a description of it:

    Positive Deviance is based on the observation that in every community there are certain individuals or groups whose uncommon behaviors and strategies enable them to find better solutions to problems than their peers, while having access to the same resources and facing similar or worse challenges.

    The Positive Deviance approach is an asset-based, problem-solving, and community-driven approach that enables the community to discover these successful behaviors and strategies and develop a plan of action to promote their adoption by all concerned.

    In other words, instead of ignoring outliers as we usually do, we seek them out. Once we’ve found them, we try to observe how they are able to perform well in highly constrained circumstances. Then we take what we learn and apply it within the wider population.

    Innovation drives variation, and variety is the key to successful adaptation and survival.

    That seems like a pretty good argument for supporting innovation to me.

  • How to Improve Your Information Diet with Better Filtering

    There’s so much information around these days, how can we possibly deal with it all? Many of us are overwhelmed just by our email, so when you add in everything else (TV, books, newspapers, blogs, twitter, facebook, etc.), it’s just too much.

    And yet, we’ve always been faced with more information than we’re capable of processing ourselves. If we’ve been in a state of information overload for centuries, is that really the problem?

    In his book The Information Diet: A Case for Conscious ConsumptionClay Johnson argues that the answer is “No!”

    The book is very good. Here is how Johnson makes the case on the website to support it:

    The problem of “information overload” isn’t particularly new — it’s a problem older than our nation, and a problem that still has not been solved. You know why? Because the problem isn’t information overload. Trying to solve an overload problem is impossible. Are we obese because we have “food overload”?. Of course not— it is not the poor (mostly) inanimate food’s fault. We’re obese because we have “food overconsumption” and while the abundance may make it easy to be fat, it isn’t as though the food’s mere existence is making us fat. Simply putting Paris Hilton in a room full of Tyson Anytizers won’t make her gain weight.

    The right question to ask is: How do we deal with information overconsumption?

    We’ve gotten dealing with food overconsumption down to a practical science. While there’s 55,000 diet books available to us, they all boil down to the same thing: eat less, exercise more. I think that if you’re interested in improving your focus, productivity, and stress levels, building conscious information consumption and attention fitness into your daily routine seems [eminently] worthwhile.

    To do this, we have to filter.

    I’ve run across two great examples of very different types of filtering recently. The first is my current favourite iPad app – Zite.

    There are at least five forms of filtering, and Zite is a great example of algorithmic filtering. Here is how it works in a picture (made by DDO):

    The explanation in words is pretty interesting, so I recommend reading the full description on the company blog. Here is part of what they say:

    There are tens of billions of web pages out there and more than two million terabytes of text, images and more are created every hour. So, where in this deluge does Zite start looking for what’s interesting to you? Zite observes what’s happening around the social web, because the community, in aggregate, creates a strong signal for what’s interesting. User-generated content, sharing, commenting and bookmarking have overtaken email and web pages in sheer volume of data created and total time spent online – eMarketer expects 115 million people in the U.S. to be creating content by 2013. What’s important is either happening on, or reported through, social media. What’s more, mining the social web makes it possible to personalize content at the moment you start using Zite for the first time .

    The app then tracks what you respond to, and it customises its recommendations so that they are increasingly personalised over time. I’ve been using the app for a month now, and it is incredibly useful.

    It doesn’t replace twitter or my RSS feed, but it is a great addition to them.

    It definitely provides high quality information.

    However, there is a limit to the power of algorithms. There isn’t an algorithm in the world that will tell you first to read Changing the Game by Roger Martin, then A Fine Balance by Rohinton Mistry.

    But that’s exactly what Nilofer Merchant did in the list of books that she put together for the latest TED Conference.

    Maria Popova also put together a great set of books for TED too.

    This is a form of judgement-based filtering – Expert Filtering.

    This form of filtering is based on a few key components including judgement, reputation, and trust. Judgement-based filtering is where you get the out-of-the-blue recommendations – connections that are too obscure or too creative for an algorithm to come up with.

    The upshot for me is that because I trust Nilofer’s judgement, I’ll read Mistry’s book.

    In setting up your information diet, using effective filters is essential. Algorithmic filtering is great. However, to maintain a balanced information diet, you also need to include some judgement-based filtering.

    Howard Rheingold calls building your aggregation and filtering routines Infotention. Since attention is becoming one of the scarcest commodities these days, you need to spend yours wisely.

    If you do, you will consume better information, and your information diet will be a lot healthier.