Twilight of the Obliterati Means Sunrise for Developers

Opinion: The old work model that defined success as a relative lack of failures is imploding, destroyed by its own insistence on mediocrity and lack of creative response to customers.

As yields from the offshoring and globalization fads fade and fall below the event horizon, business and governments inevitable kiss-off of the decade-long model will be scary to most of those whove been shaping their organizations to play that game.

For those that optimize their success by repetition and not change, theres an assured crisis.

An insightful thinker has written a little about the reasons for the decaying of the status quo. And hes delivering the good news and the better news.

The good news is hes written in detail how organizations can thrive. The better news is the professions most likely to benefit from the skill sets required for the replacement model both work in IT.

As it happens, truly good analysts and truly good programmers have the best work styles and personal aptitudes to build the organizations that will survive the implosion of the old model.

What those skill sets are, and why they are so vital Ill explain in Part II, but its important to first understand how we got to where we are and where were likely headed.

The work of Roger L. Martin, dean of the University of Torontos School of Management, is the most illuminating (and enjoyably readable) short treatise on the subject. A copy of his original article is here (PDF) and I encourage you to read all if it, but Im going to summarize it here so I can explain a few things he doesnt mention, including why the future trend is so promising for good IT people.

He calls out three words to help describe his view: mysteries, algorithms and heuristics.

Mysteries, he suggests, are those events around us that are observable but that we cant explain or predict variations on. Mysteries are the early triggers for human systems. Perceptive medieval observers could see that objects without support always fall. But other objects, like birds or leaves in a strong wind, dont.

Concerned observers hadnt inherited coherent systems to explain gravity, wind resistance and aerodynamics to explain the phenomena.

But even without knowing the precise physics of these effects and without instruments to measure them, people were able to fashion explanations based on a number of observations. Sometimes they got closer to predictive heuristics; sometimes they went down blind alleys like Sir Bedevere in Monty Python & The Holy Grail. But eventually, groups of humans came to understand the heuristics of a phenomenon.

The economy of most of the 20th century, according to Martin, was based on creating value by turning heuristics, intrinsically loose guidelines, into algorithms, to promote mass production and the scope of their organizations.

So, he asserts, most of the last decades initiatives, from supply chain management to cost controls to CRM were executed to further the very Taylorist road map large organizations have favored for more than 80 years.

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The basic view: A headquarters-driven, expansive leviathan that creates wealth by getting ever more efficient at doing the same thing.

Martin antes up McDonalds as a poster corporation for the model. Lots of restaurants made hamburgers, many produced them in a low-formality, to-go delivery mechanism, but McDonalds turned every step into a precise factory-floor process.

The product was not as good as most competitors average, but it had fewer complete failures, was more consistent and cheaper to make and gave McDonalds the chance to use price as a competitive advantage.

He cites Procter & Gamble as the algorithm-builder for brand management and EDS for codifying systems integration.

Next page: Growing a business doesnt necessarily make it better.