SEE THE UNOBVIOUS
O
ne thing I always felt pretty confident about during my acquisition career was the ability to see the obvious.
Tat may not sound like much, but believe it or not, you’ll encounter a lot of people who don’t have this skill. However, seeing the unobvious … Ah, now that was the ability of only clairvoyants and psychics, I thought.
But guess what: Te right investment by the program manager (PM) in model- ing and simulation (M&S) can help you do just that. How can this be? After all, the primary weakness of all models is the same as their strength—simplicity.
Seems a real balancing act. Philosopher William of Ockham (see Ockham’s Razor, or Occam’s Razor) advised us to keep things as simple as we can. Einstein voiced the same caveat with, “Tings should be as simple as possible, but no simpler.” It was mathematician Norbert Wiener who said, “Te best model of a cat is another, or preferably the same, cat,” while statis- tician George Box advised, “Essentially all models are wrong, but some are useful.”
Tese fellows weren’t telling us not to model or simulate. They were simply warning us against excessive elaboration or build-out when modeling or simulating a product or system, since no system can be exactly represented by a simpler model.
So, how can a model that is not too complex and not too simple give us addi- tional information we need to make technical or financial decisions?
I’ll provide some examples. But you should know upfront that modeling and simula- tion can support you in your management decisions through all phases of the acqui- sition life cycle. In the main, M&S will likely do this by reducing your sample size
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of test articles, saving you money, as well as providing early discovery of technical anomalies. And yes, just like the modeling and simulation evangelists tell us, M&S will help you reduce time and risk as well, while increasing the quality and readiness of the fielded system.
Tose are the expected payoffs to your investment. Still have some doubts? I don’t blame you.
granularity or detail, these efforts can actually save us from some misery.
We’re probably all familiar with flight simulators, helping to train pilots in the operation of their systems. But along the development path, we have no finished system to emulate or simulate. So that’s when the benefit of M&S can seem a little vague. And when you’re having trouble achieving some key performance param- eter, the last thing you want to hear is that
If done right, it’s going to help you see the unobvious before disaster strikes—and save you time and money as well.
QUANTIFYING THE UNKNOWNS Tere are any number of models across various knowledge domains: cost or finan- cial models, models for spare parts and usage of consumables and, of course, the technical components of your develop- ing system. Focusing herein mostly on the latter, it often became apparent to me how many “unknown unknowns” were always lurking out there during any partic- ular phase of development.
It is often said that complexity is best defined as many, different, interconnected parts and their interactions. A key compo- nent of complexity is the uncertainty of those interactions, and that’s where model- ing and simulation gives us a hand. If we build our models right, with just enough
October-December 2018
more research, development, test and engi- neering (RDT&E) money is needed for some model when you know that even the actual system probably doesn’t have enough funding. We have to see our investment in M&S as a risk-handling technique, since the worst we can do is proceed into uncertainty with a ready-fire- aim approach.
For example, during development of the Javelin anti-tank missile, engineers were uncertain as to whether the early design of the gimbaled seeker (the rotating assem- bly up front of the missile that “sees” the target) would be able to hold on to the target view throughout its climbing and diving flight pattern for autonomous top attack. Using a scale model of the eventual missile’s front end, the engineers literally
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