I receive regular e-mails from a few employment websites, but by far my favorite is Jobing.com, which is local to the Denver metro area. I usually spend a small amount of time skimming the highlights of these e-mails, and then quickly delete them. However, some marketing genius named Scott Birkhead wrote an article for Jobing entitled fail faster, and given the context, I had to read it. Kudos to you, Mr. Birkhead! Just a heads-up, though: It’s a sales pitch.
…[Heck,] Most political garbage in a company comes from people trying to cover themselves from a past, current or future failure. After all, they tell us what to do. And often how to do it. When you think about it, they just want what the teacher in 6th grade wanted – for us to regurgitate the answers they think are right. If we can’t do it, we’re “bad.”
The problem with that mentality comes you’re suddenly acting in open space, with no rules or acceptable steps to success. Like when you’re an entrepreneur. Or a job seeker in a market like today’s, when the things that got you a job even five years ago are no longer working.
Anyway, the article reminded me of a fairly basic concept in economics: creative destruction. A concept introduced by Werner Sombart, and made popular by Joseph Shumpeter. Which states that innovations in technology that increase our wealth, necessarily destroy previous generations of technology that preceded them.
However, the article also made me think about a concept in complexity economics that I believe is even more powerful than creative destruction, and that is the evolution of networks and technology.
The concept flows from the logic of evolution; the blind search for optimizing traits given an evolutionary design space. In an economy, it is entrepreneurs that do the searching of this space (although not completely blindly). As the article states, entrepreneurship is mostly defined by failure in searching this design space. The role of firms is to create business plans to differentiate physical and social technologies that they develop using the tools of this evolutionary search. The role of markets is to select for optimal designs given consumer preferences, and amplify successful business plans. In a smoothly-function evolutionary system, successful innovations in a certain design space will follow a Sigmoid curve.
- The bottom of the S curve represents emerging new technologies. In this phase, there are a multitude of competing designs and designers, searching both for the most efficient way to create a technology, but also the most efficient form the technology can take. To take the example of cars; during this phase, people were experimenting with different types of energy generation (i.e. steam, electric, internal-combustion), and different driving configurations. You may be surprised to see old pictures of cars with all sorts of different drive configurations! It wasn’t always pedals and steering wheels.
- The upswing of the S curve represents finding the optimal production and technology model that both consumers want, and that provides a profit. This is the market’s selection and amplification mechanism. Keeping with our car analogy, when it was decided that foot-gas-and-brake, wheel steering, and internal combustion was the optimal configuration for car technology, that layout was rapidly copied, replicated, and improved both in cost and efficiency measures.
- The top part of the S curve represents the limits of growth in the design space for a given technology. During this time, price likely falls close to marginal cost, and many generic products become available because replication cost is so low. Have we reached this phase? At least the beginning?
During the top of the S curve, generally new technologies that started their own S curve will begin hitting their own stride, and eventually overtake the old product’s market share — eventually driving the old technology out of existence. Think vinyl > 8-track > cassette tape > CD > mp3.
Many times, the efficiency of the failure mechanism in economies is just as important as the efficient initial search function. To tie this in with current events; many people commenting on how we should go about “re-regulating” the financial sector wish to make the sector more resilient to failure (through regulation). Not only is this a monumentally impossible task…but it is also prone to catastrophic failure. In contrast, I believe that we should seek to design the “bare bones” of a market which allows financial firms to fail faster (i.e. more efficiently), and allows the market to be easily fixed through intervention (like resolution) and innovation. It would also be nice to allow the every person protection from downside risk (like deposit insurance, even though it makes banks ugly).
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Circling back the article, the title is provocative, and the information salient. In our job search, we should “fail fast, cheap, and get on to what words quickly”, like the entrepreneurs of the 19th and 20th centuries. This allows us to search the design space of employment seeking strategies more efficiently, experiment with differentiating ourselves, and select for and amplify the strategies (employment seeking business plans?) that bring us success.
P.S. I have long held a pet theory that people who are interested in the same subject think about similar topics, usually at the same time. Or at least, coincidence would lead you to believe something like that. Leigh Caldwell provides more proof! (Also, I humbly thank Leigh for linking to my blog in his post about the smallness of the blogosphere =]).
But interesting things happen when a model turns out to be accurate – or if people think it’s accurate. People start to use it. People making decisions about the economy use the model to decide what to do. And the more accurate it seems to be, the more likely they are to use it.
Remember your Hayek!