What the Super Bowl Can Teach About Risk Management

Pause for a moment to consider how adept the NFL has proven itself at proactively addressing logistics and risk management. Whether we’re talking facilities, security, transportation or emergency services, there’s obviously a lot more behind the curtain than we know about.

Suffice it to say that little imagination is required to accept that the NFL sets an interesting, if not teachable, example — not just in terms of how to pull off a mega-event but how to react to most anything that could possibly go wrong. It expects problems and is prepared for them.

While it may miss chip shots on the reputational front, its Super Bowl planners and risk managers have an enviable track record. They have successfully dealt with everything from power outages to facility safety problems, to security breaches, to a number of weather-related nightmares. And they’ve done it under unforgiving pressure.

While it’s always risky to extrapolate lessons from a single event like the Super Bowl, general insights can be gained. For starters, developing the skills required to evaluate and prioritize risk represents less than half the battle. In fact, devoting too much time to prevention is a mistake. Even when accepting that the best risk avoidance plan may fail requires more than knowing how to respond. It’s about reaction time. To borrow a football analogy, it’s not just about making good reads, it’s about calling the right audible in real time during the course of the game.

We have provided a great deal of coverage to sourcing optimization. Mostly, we talk about its game-changing applications, especially in complex sourcing events. What we don’t talk about is how those same combinatorial algorithms can be applied to supply network design via optimized “what if” scenario-based analysis.

Optimization-based decision models are essential and precisely what supply network designers need, especially when acting as risk managers. And the latest tools make it easy to develop and interrogate decision models. The trick has always been about asking the right questions, because if you don’t, you can be assured of getting precisely the wrong answers.

Learn to think about it more simply. Think in terms of using optimization to allocate resources on networks that are invariably encumbered by constraints and preferences that may be intransigent, intermittent or one-timers.

So, if you’re out there assessing the latest and greatest “risk management solutions,” be sure to investigate the level of combinatorial optimization support they provide. Are the algorithms they use hard-wired to specific non-configurable apps? Is the optimization capability generally/separately accessible? Is it sufficiently flexible to accommodate intelligent, ad hoc curiosities? Is the reporting capability relevant to “what if” scenario-based outputs?

Good optimization tools should be accessible to test hunches. They should be business case builders. Don’t settle for less.

Consider it a tip offered in the wake of 1.5 billion chicken wings and an estimated 325 million gallons of beer consumed just a few days ago. To make that happen seamlessly required more than a lot of broad-based supply planning experience. At a bare minimum — at least in Minneapolis — it required someone who was thinking about bathroom capacities.

Congratulations to the Eagles.

Share on Procurious

Discuss this:

Your email address will not be published. Required fields are marked *