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Dan Meyer asks, "All other things being equal, which lane is the fastest?"

and answers: the express lane is actually slower after all.

Love the question, the approach, and the model. Meyer explains:

This problem has obsessed me for years. It's my DaVinci code. It's my love for math, for mathematical reasoning, for the relentless deconstruction of something that seems simply intuitive into data, models, and computation.

And why not? As he goes on to say, "You have here a simple question that anyone can access. Doesn't matter that you've never run a linear regression in your life. If you've ever shopped for groceries, if you've ever stood in line with a candy bar, a soda bottle, and a matinee starting across town in ten minutes, you have an opinion here. And I can use that."

I have a "Da Vinci code" of my own: what's the optimal time to leave your house for the airport so that you spend the least amount of time waiting for your flight?

A cursory Google search reveals Carson Chow's methodology. With the assumption that "the only thing we're concerned about is minimizing wasted time," he derives a formula to compute waiting time based on the average time lost to make up for a missed flight.

I'm missing Meyer's approach here, though. I want to be able to use the results in my day-to-day life, and there are simply too many variables to simplify that far! I should be able to determine how much time to add if I expect traffic on the way to the airport, or a 4,000-strong security queue on the Monday after a holiday weekend. To that end, direct observation and field research might be of more use than computation.

I hardly believe that a one-size-fits-all solution is possible (the comments on Meyer's article are a pretty fascinating additional read). And basing a model on my own unreliable habits would probably be a mistake—after all, I can know down to a tee how long the Narita Express is going to take me, but I can't account for my lazy ass up and missing the train.

Still, I think there are a few variables that are more or less predictable, e.g. rush hour traffic and evening flight delays, that could surely be factored into a tentative experiment.

In retrospect (to borrow the title of his autobiography), McNamara was a hedgehog rather than a fox, an engineer rather than an ecologist. The hedgehog knows one big thing, and for McNamara that was rational systems analysis. If he'd been a fox, he'd have brought additional perspectives to America's pressing problems. Like a dogged engineer, he believed that you could model and manipulate the inputs and outputs of any system. Unlike the ecologist, he didn't seem to appreciate the complexity of systems involving living things. If the variables explaining poverty or victory in guerilla warfare were unwieldy or unmeasurable, he simply ignored them.

There were few better at analyzing the small picture, but big-picture thinking was not his strength. Particularly when the variables involved human passions and motivations, his analytical thinking came up short. Only much later would McNamara realize that those variables were missing from the key equations of his professional life.

Judgment consists not only of applying evidence and rationality to decisions, but also the ability to recognize when they are insufficient for the problem at hand. McNamara had a good brain, but not good judgment.