“We are like dwarves standing on the shoulders of giants,” Bernard of Chartres.

“Good artists borrow, great artists steal,” Picasso, or, more likely, TS Eliot.

You’re “stepping all over Apple’s IP,” Steve Jobs.

Let’s get one thing straight. There aren’t any truly original ideas out there. Even the most astonishing scientific breakthroughs are built on the foundations of others’ work. Innovation, even great innovation, is frequently recombination of existing piece parts along with a twist or two, perhaps a different business model, core market, geographic focus.

Most of the literature on the subject, though, treats innovation as a sacred search for the truly different and unique, and diminishes the role of imitation. As such, it does a disservice to business – an audience that fails to appreciate the critical importance of not reinventing the wheel. [You could argue that reviewers and bloggers have enabled this innovation-worship, including this one.]

Oded Shenkar’s new book, “Copycats: How Smart Companies Use Imitation to Gain a Strategic Edge,” goes in the other direction. Shenkar celebrates corporate imitation. At the outset, he describes the biological conditions that favor imitation as a survival mechanism in all species. Then he points out that most innovative products spawn several followers who become long-term successes (often at the expense of the first mover). Southwest has been spectacularly successful, but so have EasyJet and Ryanair. Wal-Mart borrowed many concepts from Sol Price’s long-gone FedMart (Price, an amazing retail innovator, went on to found another innovative concept, the Price Club shopping warehouse, only to be swallowed up by imitator Costco in 1993).

Through his case studies and skewering of the innovation-worshiping business culture, Shenkar seems to be advocating against doing anything new. But as the book goes on, his overarching theme becomes clearer. Sheer imitation can only get you so far. Imitation combined with tightly-focused innovation (a combination Shenkar calls “imovation”) is the best strategy possible. In other words, take the best of what others have done–don’t be the first into a new market, or be the first widget out there–but nonetheless add some distinctive capability.

What Shenkar advocates is more nuanced than the summary just presented. But as I read “Copycats,” and got more convinced of his point, I was unconvinced that this approach needs a new name. To my eyes, innovation (at least successful innovation) does involve this intense borrowing of existing concepts and adding something unique and valuable, whether it be integration, business model, user experience, or (as Roberto Verganti would assert) the meaning users attribute to the product.

But this is quibbling. “Copycats” goes against the grain of the current innovation literature, much to its credit. It deserves to be read by anyone trying to innovate or imitate – and perhaps those should be the same people.

Related posts:
Roberto Verganti – innovation via changing the meaning of a product
Various innovation-worshipping posts

When I first started working for GTE, I went to a seminar where different operating divisions discussed their businesses with a group of recent hires. The highlight of the afternoon was the lighting division, where the presenters highlighted their contempt for their arch-competitor, General Electric, by smashing a four-pack of GE lightbulbs under their feet.

I was working for the Government Systems group at the time, on a long-term project, and felt light years away from competitors. I envied my colleagues for the intense loyalty they displayed.

More recently, an executive at a company I know sent an email to all employees outlining his displeasure that certain employees were using competitor products instead of the company’s. Using the company’s products was a matter of loyalty. He made it clear: competitor products were banned from the workplace, and suggested that employees who didn’t agree were perhaps working for the wrong company.

In Oded Shenkar’s provocative new book “Copycats: How Smart Companies Use Imitation to Gain a Strategic Edge,” he writes this:

Innovators must focus their efforts on a few core features, and even then they may produce a novel and creative recombination of imitated and innovative elements. This combination will surely be resisted by innovators that despise imitation and view it as anathema to their vision statement and claims of corporate leadership; but unless these companies accept imitation on equal terms, they may drown in “invented here” risks and costs while watching their competitors fuse innovation and innovation into a winning formula (p.182)

The lesson: you can’t figure everything out yourself, and shouldn’t. The same pride that causes you to smash your competitors’ lightbulbs under your feet can prevent you from using your curiosity and problem-solving skills to thoroughly understand companies who have the same issues and perfectly good solutions that you could adopt – rather than relying on your own skills to solve every problem.

Is loyalty of the type expressed by lightbulb smashing and the executive’s email bad? No. But it has side effects, and those can be significant. The balance between loving your own products and being curious and respectful about what others (even competitors) have done is very delicate, and executives, no matter how intense their own loyalty may be, must manage this balance.

Once upon a time in innovation, there was a general rule: get to market as quickly as you can, meaning you should start on your “long-pole” development activities as soon as possible. But there’s a growing consensus in the innovation community that the best way to succeed isn’t to start developing quickly, but instead to do as much work as possible on paper, to validate assumptions cheaply and quickly, and defer more expensive, riskier (and even long-pole) activities until after some of the basic assumptions are validated.

Part of this thinking encourages innovators to rank their risks – to work on critical assumptions first. In case those assumptions don’t pan out, the entire venture might fall apart: all the better to look at them early. That’s the premise behind the article “Beating the Odds When You Launch a New Venture” by Clark Gilbert and Matthew Eyring in the May Harvard Business Review.

The authors identify three types of risks that should be evaluated early in a new venture’s life:

1) Deal-killer risks – risks that can sink the venture. Often these seem to be marketing and sales related risks: will anyone buy the product we want to build? Given that engineers often start with a product idea, it’s easy to see why market testing is often left to last. However, prototyping and beta launches (common with internet products today) can provide cheap and quick data about a product’s attractiveness to the market.

2) Path-dependent risks – these are situations that could go down multiple paths – for example, a new product that could be useful to consumers or businesses. Committing to one of these paths, and later learning the other path was a better choice, wastes time and money, and risks the venture never fulfilling its potential. The authors recommend entrepreneurs carefully evaluate these alternate paths early on, and consider outsourcing or other ways to cost-effectively pursue both paths until the correct one becomes clear.

3) Risks that are simple and quick to evaluate – validating other assumptions, that may not be as critical as the above two, but which can be simply and cheaply tested, can reduce the overall risk of the venture.

This thinking is similar to ideas put forward in last year’s book “Innovation Tournaments” by Terweisch and Ulrich, which also discussed testing high-impact risks early, before expensive steps like building supply chains.

And, of course, all these efforts owe a debt to the thinking of McGrath and MacMillan, whose book “Discovery-Driven Growth” is the bible of the test-assumptions-first school.

Related posts:
A brief definition of strategy (Clark Gilbert)
When innovating, try more and more varied ideas (Innovation Tournaments)
On “Discovery-Driven Growth”

Scott Berkun did a great job summarizing a talk Ed Catmull gave at a recent Economist conference. In Scott’s post were several transcriptions, one of which stopped me in my tracks:

The notion that you’re trying to control the process and prevent error screws things up. We all know the saying it’s better to ask for forgiveness than permission. And everyone knows that, but I think there is a corollary: if everyone is trying to prevent error, it screws things up. It’s better to fix problems than to prevent them.

W. Edwards Deming must be spinning in his grave. Catmull is saying precisely the opposite of what Deming, Juran and others began preaching in the years after World War II and which became ubiquitous in the 1980s and 1990s. The quality gurus taught us that detecting errors in manufactured products after they had occurred was expensive and wasteful. It was far better to identify problems as they occurred, “pulling the andon cord” if necessary to isolate and solve problems so that superior quality was baked into the product throughout the process, not created in a later inspection step.

This was a brilliant insight and helped revolutionize manufacturing, enabling just-in-time inventory, lean production and Six Sigma. But something else happened. Six-Sigma-like quailty processes were extended to processes like marketing, sales, product development, etc., processes in which variance was not necessarily a bug (in some cases it was a very valuable feature).

Catmull’s business is the polar opposite of the high-precision world of mass manufacturing. As he says in the interview, during the beginning of a film development process, “everything is broken.” You can’t measure conformity with specs because there are no specs. And variability is essential to the process. Only by putting lots and lots of wild ideas into the top of the development funnel do you have a chance to come out the other end with a work of art.

So his words are very helpful to think of when we are working with our business. Is this a conformity-based process? Is error bad? Or is it an artistic process, in which error is inevitable and, in fact, essential? When is it the situation of, “if everyone is trying to prevent error, it screws things up. It’s better to fix problems than to prevent them”?

The entire interview is here (the section I quoted is near the very end):

Related posts:
Processes as art and science
From the Mistake Bank: Make a mistake, get promoted

Lancaster, PA-based entrepreneur Charlie Crystle recently released the initial beta for his product code-named Focus. It’s a product that has grown out of Charlie’s self-described “ADD” tendencies when using the computer (I and many others share these tendencies). Such as: constant switching back and forth between computer tasks, absorption in non-work-related tasks when you should be getting work done (curse you, Facebook!), etc.

Focus is a PC-resident product that installs a daemon process to monitor which programs, web sites, etc., you access and for how long. Its user interface app then presents this information in a series of graphs and allows you to tag and score activities. The program also calculates a productivity score – to give you something to shoot for. As you can see here, my score, 41, can use improving.

This screen shows how my computer use is spread across various applications – and how my productivity shifts based on which app I’m using. Not surprisingly, “iexplore” has a lower productivity score than Excel.

This screen shows other stats, in this case how often I switched applications per day.

The tool is really easy to use – at a glance, on the main screen, you get a snapshot of what you’re doing. The more granularly you tag, the more useful the score is. I created separate tags for Work-Client (score: 100), Work-Administrative (40), Networking (35), etc.

If you want to probe how you work on the computer more deeply, you can spend some (productive) time analyzing the charts Focus provides, and deciding how you want to change your computer work habits. It’s a fascinating tool, and I haven’t seen anything like it before (if you have, please leave a comment).

The New Tech Meetup of Central PA played a role in Focus’ development. Last fall, Charlie demonstrated an early prototype of the product at a meetup, with a lot of interesting discussion about platforms, functions, etc. It was fascinating to see a good idea at such an early stage, and fascinating too to see it evolved into an actual product. Charlie also demoed the beta version just before its release. If you’re near Central PA developing a tech product and would like to get feedback from a group of fellow travelers, I’d encourage you to join the Meetup and come to our monthly sessions. We’re always looking for interesting new products to showcase.

If you’d like to try the Focus beta, you can visit Charlie’s site to sign up.

Related posts:
Report from Silicon Pasture
Report from Silicon Pasture 2
What In Hell is Collectivus?

[Disclosure: I am the organizer of the New Tech Meetup of Central PA]

Dan Ariely’s monthly column is one of my favorite changes in the Harvard Business Review redesign.

In the April issue, he muses over “Why Businesses Don’t Experiment.” Naturally (perhaps I should say “Predictably“), he looks at behavioral reasons–companies seeking to avoid creating discriminatory situations (i.e., being unfair), or preference for action over insight leading to reliance on expert opinion–”Do this.”

There’s probably some pretty rational fear at work, too: the fear of making a career-limiting mistake. Relying on others helps to distance us from situations that don’t turn out right.

I experienced one more reason. I was in a large meeting with a client in which they were discussing whether certain actions by their staff were impacting revenue.

It was a plausible hypothesis, but it was a volatile moment in the industry & there could have been many factors contributing to the revenue loss.

Plus, even if the staff actions were the cause, what impact would changes make? What side effects would ensue?

It seemed to me a situation ripe for an experimental approach. But it was not to be. Action was needed–the shortfalls amounted to millions of dollars. “Come up with a plan by next week & start rolling it out.”

So, another impediment to experimentation: time pressure, real or perceived. We can’t wait for the results of an experiment; we need to act.

Since that experience, I’ve been thinking about what I can do to make a better case to my clients for experimentation. One requirement, I think, is to detect problems earlier, to buy a little time to put a mechanism in place to measure the effectiveness & side effects of a change.

Are there other steps to take to make experimenting easier?

Related posts:
On the HBR redesign
Dangerous job: change agent
To make progress in complex environments, experiment

The Harvard Business Review this month features a fascinating piece by Jeffrey Dyer of Brigham Young University, Hal Gregersen of Insead, and the omnipresent Clayton Christensen, entitled “The Innovator’s DNA.” The authors have completed a six-year study, summarized in the article, involving an in-depth analysis of 25 innovators and a further survey of 3,500 others who were connected to innovation in some way. The study attempted to identify key skills that separated great innovators from the rest of us.

The authors found five key innovative skills – Associating, Questioning, Observing, Experimenting and Networking.

In the article, a chart compares four iconic modern innovators (Michael Dell, Pierre Omidyar, Scott Cook and Mike Lazaridis) with noninnovators, in each of the five skills. The innovators are much above the noninnovators in each dimension, but in two skills the difference is stark: Associating (according to the authors, “the ability to successfully connect seemingly unrelated questions, problems or ideas from different fields”) and Questioning (”ask[ing] questions that challenge common wisdom”). Noninnovators fell below the 50th percentile on these dimensions, while the icons were with one exception above the 95th percentile of those studied.

Related posts:
Smart World
The Opposable Mind
On Experimentation

I’ve been reading the book “Innovation Tournaments” by Christian Terwiesch and Karl Ulrich of the Wharton School. The book sets out a methodology (the “tournament” of the title) for companies to generate and systematically winnow down innovation ideas to eliminate all but the most exceptional opportunities.

Two brief observations:

One, the authors suggest that almost any company’s innovation performance would be helped by increasing the number of ideas going into the top of the funnel. Early-stage evaluation (a la “Discovery-Driven Growth“) is cheap and fast, so the cost of, say, doubling the number of ideas reviewed isn’t significant when compared with an overall innovation budget.

[It was interesting to read today's post by tech venture capitalist Fred Wilson, in which he outlined his approach to finding new opportunities: (1) making public his strategies, ideas, and passions so that entrepreneurs know in advance what he's looking for, and (2) meeting with as many people as he can, every day. In short, a strategy to add lots of opportunities to the top of his funnel.]

Two, along with the sheer number of ideas, the variability of the ideas is important. High variability increases the possibility that a truly outstanding idea is found (given that truly outstanding ideas, like 7-footers with great athletic ability, are few and far between). In that event, increasing the number of ideas coming into the funnel increases the likelihood that a truly outstanding idea is looked at.

Ironically, methodologies like Six Sigma seek to limit the variability of processes. When (mis)applied to disciplines like innovation, they are very successful at impeding the success of the effort.

Related post:
On Discovery-Driven Growth
Processes as art and science

“The Design of Business: Why Design Thinking is the Next Competitive Advantage,” by Roger Martin. 2009: Harvard Business Press, 190pp.

When did you read it? November 2009.

Subject: Hot on the heels of Tim Brown’s “Change by Design,” Rotman School dean Roger Martin, author of “The Opposable Mind” discusses how design thinking can help businesses balance exploration (the search for new solutions) and exploitation (extracting value from existing solutions) to improve their innovative capability.

Did you like it? How many stars would you give it (1-5)? 4

Summary: Martin describes the process of innovation in three steps, something he calls the “knowledge funnel”: (1) staring into a mystery; (2) coming up with a heuristic, or rule of thumb, that allows you to address the mystery; (3) systematizing your solution – in Martin’s words, turning the heuristic into an algorithm. This process, to Martin, is design thinking.

He spends time discussing the preference business has for reliability (i.e., consistency and repeatability) over validity (meeting a desired objective). Validity is the starting point for innovation – the discovery of something new that helps illuminate a mystery. Since validity is not predictable or repeatable, and tends to rely on qualitative, intuitive assessments (i.e., pattern matching), companies that rely on quantitative measurement struggle with it. It was easiest for me to understand validity, as Martin uses it, as a synonym for “right-brained” or “artistic.” Successful businesses balance the desire for reliability with a relentless search for new validity.

As Martin described this process – taking mysteries, developing heuristics and then refining algorithms from it, it seemed quite simple. Why doesn’t every company do this? But I also thought that there are lots of mysteries that don’t lend themselves to heuristics, and lots of heuristics that can’t turn into algorithms. There are lots of failures on the way to the next great business algorithm. Not only that, there are lots of successful businesses built on heuristics alone [for example, your favorite restaurant, assuming it's not part of a chain]. Martin’s point, which is not stated explicitly, is that you can’t build large businesses without this transition to algorithms. You can’t have McDonald’s without a cooking and serving system. You couldn’t have Wal-mart without its distribution model.

There’s not a discussion of the cost of algorithmized businesses to society. On my last trip to downtown Boston I was hard pressed to find a business that was not part of a national chain; much different from when I Iived there in the 1990’s. But I digress – Martin isn’t writing as a social critic; he’s a business professor.

Favorite quotes:

“Vice President of Marketing” denotes a permanent position with a set of ongoing tasks…. As well suited as that construct is for running known heuristics and algorithms, it is not an effective way to move along the knowledge funnel. That activity is by definition a project; it is a finite effort to move something from mystery to heuristic or from heuristic to algorithm. pp.118-119

Designers produce prototypes for feedback, but managers are accustomed to delivering final products. p.121

Status comes from running large, high-revenue business units whose operations have been reduced to reasonably reliable algorithms that product results on time and on budget. Those are the highest goals, that is, the ones that command the highest compensation. That is why most executives prefer the known to the unknown. p.125

Was it similar to anything you have read before? Of course, there are echoes of “Change by Design” (Brown’s earlier HBR article is referenced). And the idea of “staring into mysteries” reminds me somewhat of “changing the inherent meaning of a product” from Roberto Verganti’s “Design Driven Innovation.” 2009 is definitely the year of design thinking in business!

Martin’s book is less ambitious than Verganti’s, but broader (in a good way) than Brown’s. And his ability to create a powerful, memorable metaphor remains intact (I think I’ll be using “knowledge funnel” and maybe even “validity vs. reliability” in the future).

Will this book end up on your bookshelf or in the library donation pile? The bookshelf.

Related posts:
On “The Opposable Mind”
Processes can be art or science
On “Design-Driven Innovation”
Reading journal: “Change By Design”

I listened to a Fresh Air interview with “Omnivore’s Dilemma” author Michael Pollan and couldn’t get this passage out of my head (it comes 14′40″ into the interview):

But it’s very interesting to watch, as the amount of time spent cooking has fallen by about half since the 1960s, you know, obesity has risen dramatically. Now why should that be? Well, there is some very interesting research that correlates the amount of time that a culture spends cooking with its obesity rates, and that when you don’t cook and you rely on corporations to cook for you, you tend to eat more special-occasion food, things like French fries.

I mean, take the French fry. It’s a great example. I mean, the French fry did not become the most popular vegetable in America, which it now is, until corporations relieved us of all the work of preparing them. French fries are a whole lot of trouble to make. You’ve got to wash the potato. You’ve got to peel the potato, slice the potato, fry the potato and then clean up a kitchen that’s going to be a wreck. And, you know, you wouldn’t do that very often, and indeed, people didn’t do it very often.

But now, since corporations are making all the French fries, we can have them two or three times a day, and many of us do. So, you see, when there’s something built into the process of cooking that delays gratification, the work itself makes you think twice before you embark on a cake or French fries or fried chicken. And so as soon as you outsource that work, it becomes possible to indulge in all these special-occasion foods that no longer are special-occasion foods. They’re everyday foods.

And French fries wouldn’t be something we could eat two or three times a day without the Frialator. Rather than pouring oil into a pan, cooking, then discarding the oil, the Frialator allows restaurants to cook many dishes in the same oil, with only occasional filtering of the oil to remove food particles, until the oil is replaced, approximately one to two weeks in some cases.

The Beginnings
In 1918, New Hampshire restaurant equipment manufacturer J.C. Pitman and Sons created a revolutionary high-volume deep fat fryer. In this 1946 letter, company founder J.C. Pitman described the invention as follows:

In 1918 J.C. Pitman and Sons Hotel & Restaurant Equipment Manurfacturers, while attempting to work out a more satisfactory method of frying, made some important discoveries. One was that if the small particles of food which ordinarily settled to the bottom of the French Fry pot (where they collected and burned) could be kept away from the intense heat of that part of the kettle, the quality of fried food could be greatly improved. The Pitco Frialator was invented on this basic principle – and patented. This brought about a complete change in the method of deep fat frying. The fat medium was heated by tubes running through the center of the fat container. This construction permitted all sediment from the food being fried to drip below the heating tubes into a cool zone where it could not carbonize and break down the frying fat.

The importance of this construction is the reduction in fat costs, which exceeds by a wide margin the initial cost of the equipment, its depreciation and upkeep. Thanks to the thousands of Pitco Frialators now in use from coast to coast, deep fat frying has indeed become an art.

The Value Proposition
According to the Proceedings of the American Gas Association, Volume 20 (1938), a gas frialator costing $160 on average saved a restaurant owner $390 per year in oil costs.

Half a million or more in use in US
The National Restaurant Association reported that as of 2009 there were approximately 945,000 restaurants in the US. Estimating that at least 50% of these restaurants use a deep fryer, there are a lot of Frialators out there.

The Impact of “Special Occasion Foods as Everyday Foods”:
McDonald’s French fries have 380 calories per 4.1 oz serving. Eric Schlosser wrote in “Fast Food Nation” that “in 1960 Americans consumed an average of about eighty-one pounds of fresh potatoes and four pounds of frozen french fries. In 2000 they consumed an average of about fifty pounds of fresh potatoes and thirty pounds of frozen fries.” Thirty pounds of French fries equates to about 45,000 calories per person per year, using McDonald’s calorie counts. Meaning 307 million Americans (according to the US Census Population clock) will consume 13.65 trillion calories of French fries in 2009.

Thanks to the Frialator.

Photo: The Pitco Model 1

Related post:
A brief history of wheeled luggage