Imagine for a moment that your job was to build a bridge across a raging river and it had to withstand conditions you’d never seen before. Perhaps untold levels of traffic or weight, perhaps local weather phenomena that swung from desert heat to arctic cold every day, with the odd typhoon thrown in for variety. And it needed to be done faster and with a tighter budget than you’d ever imagined. Under these circumstances, would you have a few truckloads of girders dropped off and just start welding? Maybe you’d sketch it first on a napkin, discuss that in a meeting for a couple of hours, then begin?
Unfortunately too many business strategies are formed in just this way. We’re trying to do more with less. We’re trying to out-think and outrace our competition, who we’re certain have more resources than we do. We’re pushed into new frontiers and launching innovative ventures in an effort to capture blue ocean markets and greater share in the rest. We’re awash in uncertainty.
As a young boy, I built many a bridge with my Tinker Toys and through an informal trial-and-error process, I eventually learned the practical basics of physics and engineering such that my GI Joe’s and model tanks were able to safely cross treacherous imaginary chasms.
Real-world civil engineers in the bridge-building business also have a few tricks up their sleeves to reduce their uncertainties and mitigate risks and among the most important is this same idea of modeling. In the old days, this literally meant constructing a scale-model of their bridge concept and subjecting it to stresses, wind-tunnels, load tests and so on in an effort to understand where the structural limits were and to identify and improve the likely failure points. Nowadays, the physical models have been replaced by computer simulations, but the purpose is the same: to create an environment in which the engineers can safely experiment with their designs and learn more quickly, cheaply, and efficiently. Ultimately this translates into a better finished product with substantially lower likelihood of failure.
The same tools that lead to better bridges are just as applicable to the novel, high-stakes business problems we find ourselves in. Computer simulations have been applied in far-reaching business domains ranging from understanding the dynamics of project/program management (teaser: the things we reflexively do to get ailing projects back on track typically make the problems worse), to pharmaceutical new-product launches, to optimizing manufacturing processes. A simulation encodes the salient points of the business problem under investigation and enables decision makers to experiment with the different policy levers are their disposal (e.g. budgets, staffing levels, product attributes, etc. — whatever is germane to the problem at hand) and see how this impacts the trajectory of business performance. Through this experimentation, decision makers form new insights about cause-and-effect relationships, strengths and weaknesses of specific levers, nonlinear responses (e.g. saturation effects) and more, all without risk to the business itself.
Moreover, by playing out strategies in the face of a number of possible future scenarios, managers can devise strategies that are robust to the unknown, strategies that are resilient to unforeseen changes in the business climate (much like designing a bridge to withstand extreme conditions).
The next time you’re facing a strategic problem, consider taking a page from bridge builders (both professionals and six-year olds with Tinker Toys) and model it first.