Simulatastic Times

When you don’t know whether you should plunge ahead with that big endeavour…when you fear the consequences of something going horribly awry…the simulation is the universal buffer zone.

But is it the universal solution? The grand panacea? Hardly.

You see, simulations can only cover so much ground, so many what-ifs, so much conjecture… yet they still remain popular. Because they are a de facto (and, in many contexts, de rigeur) testing ground. One would hardly refute the benefits of flight simulations, for example (unless you’re Maverick Mitchell).

Here’s a clever mnemonic device: if our simulation has enough potential, then given enough time ‘t’ we can grant it that ‘t’ in its name, as a stimulation. It is stimulating the go-ahead. It is stimulating greater enthusiasm for something amazing coming to fruition. But let’s just look at it in “quantum” terms, as a s(t)imulation, knowing that one day it could get us where we’d like to go. In a similar manner to my debut book with a quantum title, called “Diamond Min(e)d”.

So, the problem is when we start to think of simulations as the be-all and end-all. This can also fool us in advertising or consumer reports. Think of a typical gas mileage claim of an auto maker; they will claim that their vehicle provides such-and-such mpg (or L/km, if you prefer), but this was undoubtedly obtained under controlled conditions, such as on a test track or vacated lot designed for such a purpose. It did not adjust for factors such as weather and surrounding traffic patterns; perhaps it did for inclines and curves, but those are far more within its control.

Well, heck, even a GPS in a car is essentially based on simulated scenarios of how long it takes to reach a destination, or which route you need to take; and while it can tell you of sudden construction or accident delays in real-time, it is unlikely that it could tell you of things like local ordinances that you can’t turn left here between 3-5pm, or that certain rare events or shows are going to cause big-time bottlenecks along a certain corridor.

But then again, you probably wouldn’t want it to, lest the darn thing ever get released – the adage of “do not let perfect be the enemy of the good” comes to mind. Since, after all, the context is not mission-critical like airplanes or hospitals.

In my debut book Diamond Min(e)d, you will find my quote: “Regardless of your intentions, the number of what-ifs will always exceed the number of how-abouts.”

Beyond the realm of transport, one simulation that I find is mostly good for “game value”, but not any real-world value, is that of financial markets and trading. Such simulated software exists, to show what happens if you trade this stock at time ‘t’ or hedge commodities a, b, and c at the end of the month as opposed to now, and how the market will react – guiding you towards an “optimum” outcome – good luck trying that in the real world. I’m sure 2007-2008 is still fresh in many people’s minds, let alone COVID.

But what really barricades the financial simulation-learning-to-real-world-application journey is, well, other people. (Existentialists will note how Sartre said “hell is other people.”) Well, once you have so many people that are also partaking of this fantastic financial simulation software, guess what? You get what’s called the zero-sum effect. When everyone “benefits”, nobody will in the end. If I’m not mistaken, that’s also a mainstay of game theory.

And all bets are off when it comes to simulations that are part of emergency planning. True, we can have a BCP (Business Continuity Plan) or DRP (Disaster Recovery Plan) in place, as many organizations have done–and this is an excellent habit to maintain (and revisit periodically)–but there are just so many variables, a myriad of combinations (& permutations) of events, that you can only have so many hypothetical scenarios. I’m not saying you shouldn’t devise some mock scenarios, but it is unrealistic to expect those to cover everything. The distinction between “known unknowns” and “unknown unknowns” was made manifest by former U.S. SecDef Donald Rumsfeld.

And finally, to tie up this article, I would be remiss if I didn’t say something about how the monitoring effect of simulations, or of troubleshooting diagnostics in the “real world” can unduly affect your result. You may have heard of the anonymous axiom, “To measure something is to influence it.” This is true to some degree in Windows, when you have to bring up the Task Manager – which consumes just a little bit of processing power – to evaluate where a bottleneck may be occurring on a slow computer. However, the contributory effect could be even more pronounced in more intensive environments, with many nodes (think power stations). Since, after all (& of course), any simulation that you conducted beforehand with load testing was probably subject to the vicissitudes of day-to-day consumption and events.

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