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“You can have a problem that’s too big for anybody’s mind, but if you break off a piece of it, it’s more manageable,” Bendor says.Evaluating something that’s radically different from the status quo is bound to be fraught with error.Through “recombination,” the problem solvers design a solution.
When faced with a difficult decision, the problem solver, Bendor says, is better off turning to “a toolkit of heuristics that can be deployed separately and combined in various ways.” Bendor’s research shows we actually have more options when it comes to solving hard problems than “Muddling Through” suggested.
“There aren’t just two fixed methods of decision making like Lindblom thought,” Bendor says, referring to disjointed incrementalism and the synoptic method.
“The elements can be broken down and then combined and recombined in new ways.” According to Bendor, the best problem solvers mix and match the cognitive shortcuts to reach their solution.
The idea is growing in cognitive psychology that experts in information-intensive domains, like teaching, chess, or medicine, become skilled because they garner enormous mental libraries of heuristics and patterns, he says.
One could design a patient survey, another examines the efficacy of the appointment reminder notice, another tries to determine the causes of patient drop-off, and another researches what’s worked well for other hospital settings. Some are relatively easy fixes: The receptionist has been notifying patients 72 hours before the appointment, but it turns out a 24-hour notification leads to better turnout.
Others are more challenging: The hospital serves low-income people who lack consistent childcare, transportation, and guaranteed time off work.He introduced the idea of disjointed incrementalism, a package of heuristics that could be used to make small, incremental changes along the way.Disjointed incrementalism rang true for several generations of scholars and problem solvers.In the middle of the 20th century, the standard recommendation regarding problem solving went something like this: Create an extensive strategic plan with a few rigidly outlined logical steps.The synoptic method, as this conventional procedure was known, amounted to a prescription that didn’t actually work well for hard problems.It also helps to include people from varied backgrounds.For example, a team wrestling with a big data problem might consider incorporating a visual artist, cognitive scientist, and computer scientist to bring different insights to the problem solving.“This plan will get us from A to G,” explains Bendor. And then from G we’ll look around and think again and figure out how to get from G to R.Then when we’re there we’ll figure out [the rest].” Having many people working independently on the same problem increases the likelihood of success, Bendor says, referring to what Lindblom calls distributed intelligence.When faced with a tough problem, Bendor recommends choosing among these methods.Carve off part of a big problem and disperse its subcomponents to different groups.