I have many examples of hyper-efficient systems, but I lack examples of hyper-effective systems. I’ve found one, though, in the Grand Cayman airport. Chronically overcrowded, horribly organized, and highly unstructured, it is also incredibly malleable. Both the structure and the staff seem able to accommodate nearly any situation and adapt to it easily. It doesn’t matter how late the flights are getting in, or how slow the security checks are, or how hot it is, or how far out into the parking lot the check-in lines are, the staff seems to just spontaneously come up with ways of jigging things to work out.
Some might complain that the staff were witlessly unprepared for the utterly predictable stampede of vacationers leaving for home on that one day after New Year’s and before school starts again. But I wonder if they didn’t realize instead, at least in some collective unconscious, that there’s no point trying to plan for the unpredictable, and that a better course of action is to remain loose and flexible to the needs of the moment.
If they’d committed to a plan to handle the exit rush, they would have been more efficient, but only if the plan had predicted actual events quite closely, of if they’d built a significant redundancy into their plans. Either way, implementing such a plan would have cost significant resources at the meta (planning and management) level. Instead, virtually all their resources were deployed “on the ground,” workers who actually did things directly to move people through the airport. They used an extremely flat management pyramid.
And it worked. In the end, it didn’t matter that our ride to the airport was 20 minutes late, or that there was an 800 ft queue winding from security right out into the airport parking lot, or that the check-in agent took an eternity to re-fold each of our boarding passes in a particular, presumably better, way. Somehow everything got done just in time, and the delayed arrival of our plane added an extra (unneeded, I should stress) time buffer to guarantee that we got properly bored waiting at the gate.
I can summarize this with the phrase “island time” – the notion that everything works to it’s own schedule – and not your schedule – in certain Caribbean cultures.
Many people to whom I’ve spoken have been surprised by how well things get done on “island time,” no matter how disorganized they may seem to those unacquainted with the practise. These people invariably come from societies that revere efficiency rather than effectiveness.
Similarly, many people I’ve met from “island time” cultures find the hyper-efficient and management-heavy ways of the “developed world” laughably inept.
I must say, however, that “island time” is not without its faults. While the main goal of getting people into planes was achieved well, it could have been more accommodating of the needs of the passengers. It was evident that they’d already tweaked the structure of the airport with clearly marked “temporary walls” to route people in a winding path through security and airport control to maximize space usage and minimize chaos. But wayfinding was negligible and the gate area was poorly designed. The result: a system that can accommodate high variability from the point of view of the staff but not from the point of view of the passengers.
Of course, this isn’t a problem only for hyper-effective systems; hyper-efficient systems can also often ignore user needs.
The real issue here is that being “too effective” means being too flexible. A system that’s too flexible can handle variations that just won’t actually happen. And that’s always a waste. By narrowing a system’s effectiveness to match the extent of variability in its environment, one can improve efficiency without affecting effectiveness in any measurable way.
This assumes, however, that one has (a) the means to measure the range of variability and (b) the capacity to revisit those measurements regularly and change the system’s flexibility when the variability changes. The work needed to do these things removes resources from the pool of resources dedicated to actually execute the system’s primary function – in the case of the airport, to get passengers into planes comfortably and safely. But some resource loss in this way can also increase overall efficiency. Where exactly the balance point is between resource (effectiveness) loss on the one hand and efficiency gains on the other hand will vary from one situation to another.
This is where design and systems thinking come in. Systems thinking gives us the means to analyze situations and model the richly interacting entities that provide desired function. Design gives us the means to use those models to create new ways to provided the needed functions so that effectiveness and efficiency are balanced.
So in the end, it doesn’t matter if your too efficient (and not flexible enough) or too effective (and not efficient enough), the global optimum – the sweet spot that gets you a product that is perfect for its situation – is going to arise through careful design.
I think I’ll get in touch with the Grand Cayman airport and see if I can help them find that global optimum.