Decision-making cycle times and differences in risk profile

 From Social Psychology and Business by Arnold Kling, his review of The Geek Way by Andrew McAfee.  

In the middle of the last century, the American economy was dominated by heavy industry, making automobiles, steel, and other manufactured goods for the mass market. The business culture that evolved in those industries stressed planning and top-down control, as John Kenneth Galbraith argued in The New Industrial State. The leaders of such firms were allocating massive amounts of capital in irreversible ways, as in the decision to build a new plant. Needing to get these decisions right, corporate leaders relied on a cumbersome evaluation process in which each proposal was examined by a cadre of division managers and their staff analysts.

Today, much of the capital in American business consists of software systems, not physical plant and equipment. Managed correctly, this software capital can be acquired—and changed—much more quickly than physical capital. This environment rewards an entirely different management culture, what McAfee calls the Geek Way, that today’s successful business leaders have arrived at.

I have not read The Geek Way.  However, I do frequently focus on the S-curve of innovation and adoption.  In 1900, if you were to introduce some new technology such as electric refrigerators, it would take 40-50 years to reach market saturation (and commoditization).  In 2000 it was more like 10-15 years.  Now it is perhaps 5-10 years.  

Very early in my consulting career I became attuned to the articulation that as a project manager, you should never let the mean time of implementation exceed the mean time of business and technological change.

Given a set of problems for which it is a solution, if you are implementing an IT solution that will take five years to become operational but the technology, market demand, and competitive threats are on shorter cycles, then you are guaranteed to be in trouble.  The solution has to be in the market before the change.

And that is increasingly hard to do.  

The quoted section above is I think a usefully true description of what has happened but there is a slightly different way of considering it.  The mean time of implementation in the real world of big capital projects which are physical have longer lead times than capital projects which are essentially digital/conceptual.  

The conclusion is probably the same but I think there is a nuance.  In both cases, the cycle time of decision-making is shortening (with all sorts of ramifications.)  Management techniques and tools have to accommodate that.

But the nature of what is being decided upon (physical assets versus digital/conceptual assets) also invite different approaches independent of the cycle times and more related because of the difference in their respective risk profiles.