The defense acquisition system isn’t an engineering problem

A couple days ago I discussed how difficult in practice it is to collect data merely on where dollar outlays go. That seemingly simple case of relating cost accounting to a hierarchy of system end items is the the most basic aspect of what has to be a much larger system of data collection if “performance” and “returns on investment” are to be calculated.

I am not saying that data and analytics are of no use to the Department of Defense. They are incredibly useful. For example, satellites generate tons of data that can be usefully analyzed for military purposes. Logistics systems allow us to route material more efficiently. And so on down the list of applications.

But what analytics cannot do is provide some objective measure of performance. It cannot allow us to perform an economic analysis, allowing us to optimize resource allocation across a vast array of alternatives. The questions of what lines of effort should be started, or cancelled, or ramped up, inevitably requires anticipations of an unknowable future, fraught with uncertainty.

Here is a good explanation from Don Boudreaux on why economic systems — even if they can be described by data inputs and mathematics — cannot be directed by the implications of an objective analysis. The economy is not an engineering problem, even if it is made up of many different engineering problems:

[The] Austrian insight is not that the mathematics of economic calculation is so difficult as to be impossible in practice. Instead, this insight is that the challenge of economic calculation is to incite multitudes of strangers to act productively in response to an inconceivably vast number of dispersed, often conflicting, and frequently fleeting bits of information. Coordinating the plans and choices of individuals spread across the globe, and even across time, requires that information about the consumption preferences of individuals – as well as of availabilities of billions of different inputs and of the likely relative values of a practically uncountable number of different input combinations – somehow be transmitted far and wide and in ways that prompt each of these multitude of strangers to make both production and consumption decisions in ways that yield something approaching maximum possible economic output.

 

This problem is not one of getting the mathematics correct; it’s one of information collection and use, where much of the information is not even in principle quantifiable.

 

A system of prices reckoned in terms of money and set in competitive markets for private property rights is the only known ‘mechanism’ for eliciting enough such information, transmitting it in readable form to where it is most useful, and then prompting individuals – consistently if never perfectly – to act on this information in ways that raise over time the standard of living of nearly everyone.

 

That the general features of this astonishingly complex system of economic coordination can be usefully described with mathematics is beyond doubt. That it is fundamentally impossible for knowledge of mathematics to substitute for the information-generation and information-processing achievements of competitive markets is, however, even more certain.

For more on this perspective, check out my guided reading of FA Hayek’s The Meaning of Competition. What this means for the Department of Defense, which is not likely to reflect private markets any time soon, is an open question.

One crucial aspect, however, is that the DOD currently attempts to act like a monopsonist, obsessed with optimizing the entire portfolio of allocation. A preferred system is a diverse collection of combatant commands, system commands, and technology labs whose interactions with eachother and with industry can generate something akin to a price mechanism — based on subjective valuations, reputation, and deal making rather than objective cost analyses.