The February 2007 issue of Harvard Business Review (HBR) had a cover article that caught my eye: “Breakthrough Ideas for 2007”. This is their annual survey of twenty emerging ideas that are considered important, or at least provocative, by the editors, the World Economic Forum, and in one case, the HBR readership. Each idea was presented by a short essay by a subject matter expert.
The least interesting ideas to me were the most technical ones. Most high technologies fail in the marketplace, and even the successful ones have a half-life of maybe five years. I’m more interested in the ideas that cause me to doubt my whole world view, question my basic assumptions, and, in the best cases, cause me to have a crisis of faith. Of course I viewed all of them through a lens polished with thirty years of engineering experience. Here’s my take on some of the HBR’s breakthrough ideas. These are all strictly filtered through my perspective; I encourage you to read the article for yourself and see if any of the ideas rock your world. (Any opinions or analyses expressed are strictly my own and not those of the authors.)
The Accidental Influentials
Duncan J. Watts
In his book The Tipping Point, Malcolm Gladwell applies the epidemic theory of disease to the spread of ideas. These self-replicating ideas are called memes. One of his pivotal distribution mechanisms is that of the connector, someone who knows a lot of people, to whom is paid a lot of attention, and who makes it their business to disseminate memes, sort of the cognitive equivalent of Typhoid Mary. Popular bloggers (for example, not me) frequently serve as connectors.
Watts argues against this model, and instead says, based on studies of actual meme distribution, that memes are spread most effectively by a critical mass of people who are willing to be easily influenced. That is, the network model of meme distribution depends not on those willing to influence, but on those willing to be influenced. If a meme encounters resistance just a couple of degrees away from the connector that is spreading it, its propagation slows or stops all together. The mechanism of meme distribution depends not on Typhoid Mary but on having a lot of victims with depressed immune systems, a susceptibility to what has been called viral marketing. The special ability of connectors is “mostly an accident of location and timing”.
For folks (for example, like me) trying to become known through their blogs, this does not bode well. It means if it happens at all, it is because a critical number of my readers are willing to believe whatever crap I write, not because of the quality or insightfulness of anything I write.
Well, now that I put it that way, it sounds like a good thing.
Brand Magic: Harry Potter Marketing
Frederic Dalsace, Coralie Damay, David Dubois
The idea here is simple. You don’t design a product for a particular market segment. You design it for a particular demographic cohort. And you evolve the product over time so that it consistently appeals to this same cohort.
The example in the article is cosmetics. You start out designing and marketing a line of cosmetics for women in their 40s. Over a decade you evolve the same brand so that it fulfill the needs of women in their 50s. Then, over another decade, for women in their 60s. Presumably over the span of a couple more decades, the same brand is altered and marketed to funereal cosmetologists.
The economics behind this has been stated before: it is a whole lot cheaper to keep existing customers than to acquire new customers. So if the needs of the demographic cohort to which you market your product changes as it grows older, your product, sold under the same brand, changes too. Meanwhile you introduce the same formulation as before under a different brand name in an effort to attract new customers from the subsequent demographic cohort.
My telecommunications equivalent of this would be to sell the same phones decade after decade but with volume controls that go higher and a typeface that is larger.
Algorithms in the Attic
I have no idea if this is true, but I love the concept: Schrage says that Google’s page rank algorithm was actually invented in the 1800s, the Perron-Frobenius theorem. And that many other algorithms that have similarly revolutionized high technology languished for years or even decades because at the time they were invented, they were computationally intractable.
In a past article (“It’s Not Just About Moore’s Law”) I’ve talked about how the power of different portions of an architecture grow at different rates, making designing a scalable system with a long life-span challenging. This is the flip side of that: those same growth curves suddenly make possible what was once thought impossible. This makes possible a whole new field of algorithmic archeology, where scientists and engineers try to find modern applications of old algorithms. What was once old is now new again.
When something amiss occurs in an embedded system, most don’t have the luxury of just logging an error message or throwing an exception. They have to find a way to soldier on, perhaps in a reduced capacity. I’ve designed and implemented error recovery sub-systems for two commercial telecommunications products to do just that. I’ve often thought that borrowing something from the Game Theory playbook to implement a more general solution would be an interesting idea. Maybe I should revisit that intuition. Embedded systems may now have the available horsepower to exploit more complex algorithms. I’ve made the same argument about the evolution of embedded programming languages, which have transitioned from assembly, to C, to C++, and now (as I argued in “If Java is the new COBOL, is C++ the new assembly?”) to Java.
The Leader from Hope
Harry Hutson, Barbara Perry
One of my favorite quotes is from Napoleon Bonaparte: “A leader is a dealer in hope.” I have found this to be true on the battlefield of product development, and it makes me think that this idea, while important, is not new, and shouldn’t be provocative.
An Emerging Hotbed of User-Centered Innovation
Eric von Hippel
This article talks about how in many industries, innovation is increasingly being customer driven, from the point of view that it is the end-user doing the innovating, not the producer of the product.
This is a very open-source or hacker kind of model, where innovation is the result of a grass roots effort and not of corporate or government initiatives. It is also not a terribly new idea even in the manufacturing arena. Harley-Davidson routinely sends representatives to motorcycle rallies to examine how customers have customized, modified, and improved their products. The best ideas show up on subsequent models.
Certainly every time I have ever visited a customer site and seen a product I’ve helped develop in use, I learn something new. Most of the time it is “Boy that’s a lot harder to use than I anticipated.” But sometimes it is “Wow, I never thought of using it that way!” Just one more reason why developers should get out more (whether they like it or not).
As corporate policies like forced-ranking, sixty-hour works weeks, and always-on Blackberries continue to squelch corporate innovation (my opinion), user-centered innovation is going to become increasingly critical for global competitiveness as R&D organizations can no longer be counted upon to meet the innovation needs of their customers. (See my comments below on Innovation and Growth: Size Matters and In Defense of Ready, Fire, Aim for other takes on this topic.)
Living with Continuous Partial Attention
Stone talks about the backlash against the tyranny of always-on Blackberries, and how continuous partial attention differs from multitasking, where the tasks generally have low cognitive requirements. See my comments above on An Emerging Hotbed of User-Centered Innovation to see where I think this is going.
Innovation and Growth: Size Matters
Geoffrey B. West
This one really caused me to think. The author looked at scalability issues as they relate to population size. Civilizations exist because of economies of scale: not every one has to raise crops, hunt game, or rear children. The cumulative effort of these tasks scales sub-linearly, making labor available for other things, like blogging. What was unexpected, both to me and apparently the author, was that innovation scales super-linearly. The larger the population, the disproportionately larger the amount of innovation that occurs.
This sounds like a page from James Surowiecki’s book The Wisdom of Crowds, which talked about how studies of juries revealed that a diversity of opinion yielded more subtle and nuanced decisions, or how scientists who were more widely collaborative were ultimately more successful in their research. West conjectures that this may be why organizations like Bell Labs “in its heyday” were so creative. (Speaking as someone who worked at Bell Labs during its decline, “ouch”.) This is really counter-intuitive to the stereotypical lonely genius in the garage that permeates American culture as a high-tech equivalent to the American cowboy, but it rings true.
On a more ominous note, his model also predicts that “in the absence of continual major innovations, organizations will stop growing and may even contract, leading to either stagnation, or ultimate collapse.”
Although Fraser doesn’t specifically cite the “Green Movement”, where consumers preferentially choose products from environmentally friendly companies, it is a great example of what she is talking about. Fraser describes stealth consumers who buy your product but would rather not, and only do so because they have no choice. While sales may continue to be strong, there is a growing resentment towards the brand held by consumers who are just waiting for an alternative that is more palatable.
The gist of this is that companies can get by with violating the values of their consumers as long as they have a captive market. This may seem kind of obvious. But the real message is that such companies cannot afford to become complacent, assuming that their current customer base will always be there. Things could suddenly turn ugly. Not only might consumers find a replacement product from a more acceptable source, but in some cases they may simply decide to do without.
So I imagine a web site in which disgruntled Baby Boomers post their feelings about subtle age discrimination in hiring by companies whose products they consume. These are the same Baby Boomers who are poised to retire in droves and whose retirement funds will ultimately control most of the wealth in United States. Is a day of reckoning is upon some of us? Our memories may be bad (and getting worse), but they’re not that bad.
Why U.S. Health Care Costs Aren’t Too High
Charles R. Morris
Mrs. Overclock, also known as Dr. Overclock, Medicine Woman, remarked to me the other day about an unintended side effect of the mandatory motorcycle helmet law in California. It resulted in a shortage of organs for transplantation. Folks that had never been on a motorcycle in their life died because some biker had to wear a helmet. This is like something right out of the book Freakonomics.
I was reminded of this by Morris’ observation that the costs of individual medical procedures in the U.S. are not increasing. If anything, they are decreasing. It’s just that we’re living longer to need more of them. We live longer, and hence require more care. “The people who used to die of heart attacks now live on to consume expensive medications, visit specialists, and contract cancer or Alzheimer’s. Does that mean we should stop saving heart attack victims?”
This makes me wonder if mandatory helmet laws actually drive health-care costs up. Instead of leaving a good looking and mostly intact corpse, motorcycle accidents may now create victims that require expensive medical care.
Morris cites that health care is the single largest industry in the United States, now 16% of the GDP. He projects it will rise to be 25% to 30% in the next two decades based on shifting demographics alone. He likens this to how, in 150 years, agriculture went from being 50% of the GDP to a tiny 3%, and in the last fifty years the workforce went from being one-third employed in manufacturing to 10%.
Wake up and smell the disinfectant: things change! Health care becoming a major industry may not be a problem, and even if it is, what is to be done about it? Morris says that that paying for health care is an issue of financing, not affordability, and that there are no quick or easy fixes.
I’m reminded that we really have no frackin’ clue as to all the impacts of the Baby Boomer retirement wave.
In Defense of “Ready, Fire, Aim”
“The cost of trying to prevent bloggers from saying stupid or silly things… would be high, whereas the cost of allowing anyone to publish anything is low.” Thank goodness. This is another article right from the pages of The Wisdom of Crowds, and from the open source movement. Let a thousand flowers bloom. Let a thousand schools of thought contend.
Except Mao didn’t really mean it. And Shirky points out that out of 100,000 open source projects on SourceForge, most are inactive. While we know about the high profile successes, like Linux and the Apache web server, the vast majority of open source projects are stillborn. Linux and Apache are notable because they are the highly publicized exceptions to the rule.
Never the less, Shirky promotes open source as a path to innovation because the cost of failure is low. Large companies insist on embarking on huge boil the ocean projects where the economic cost of failure is counted in six figures or more. Open source allows thousands of tiny projects to be planted in the hopes that a few of them might sprout and fewer still survive the first winter. What we need is a good way to filter successful projects from failures as quickly as possible.
As two-time Nobel Prize winner Linus Pauling said: “You aren’t going to have good ideas, unless you have lots of ideas and some principle of selection.”
The Folly of Accountabalism
Holding people accountable for their actions is one of those things that sounds (to me anyway) like a no-brainer. For one thing, you only learn from your mistakes (this is never truer than it is in software development), so if you are not held accountable, you never learn anything.
Weinberger argues that accountability assumes that there is a right and wrong answer to every question, that performance can be measured exactly, that systems go wrong because of individual actions, and that if we only knew the appropriate set of controls to put in place, the system would be self correcting. It assumes perfection can be achieved.
In an era of Six Sigma process controls, this is a very seductive idea. The problem is that in everything but the most mechanized of processes, accountabalism, as Weinberger calls it, is “blind to human nature”. It reflects a very engineering mindset (which may be why it sounds so appealing on the surface to people like me): it tries to treat people like machines. Although, as Weinberger points out, this doesn't even work all that well with machines, thanks to entropy: even machines wear out and misbehave. People are just a lot more clever and subtle about it.
This is a recurring theme. People that hang around me are tired of hearing me trot out Robert Austin’s book Measuring and Managing Performance in Organizations, but it really did change my world view. Austin presents a model based on Agency Theory (an offshoot of Game Theory which is the basis of much of contract and labor law) that shows that no incentive plan can be perfect unless all metrics of success can be accurately measured. Then he argues that this is impossible in any information-based industry.
Weinberger is making the same argument from a different perspective. Punishing (offering negative incentives in Austin-speak) people for taking risks and failing means that people will cease to take risks. Just like in the stock market, the higher the risk the higher the potential payoff (and the greater the potential loss). Becoming completely risk averse brings a halt to innovation because people will only apply what is guaranteed to work, meaning only that which has been done before.
But Weinberger is arguing something more than that: that complete accountability is impossible, in the same sense that Austin argues that perfect incentives are impossible. Weinberger’s accountabalism is another form of Austin’s measurement dysfunction.
“Breakthrough Ideas for 2007”, Harvard Business Review, February 2007, pp. 20-54
Robert D. Austin, Measuring and Managing Performance in Organizations, Dorset House, 1996
Malcolm Gladwell, The Tipping Point, Little, Brown and Co., 2002
Steven D. Levitt and Stephen J. Dubner, Freakonomics: A Rogue Economist Explores the Hidden Side of Everything, William Morrow, 2005
James Surowiecki, The Wisdom of Crowds, Doubleday, 2004