City and states are awash with data.

One obstacle to translating that data into information useful for management is an apples-and-oranges kind of phenomenon: Information in one dataset frequently can’t be effectively meshed and analyzed with that in another.

When this challenge is overcome, though, good things can happen, and New York City’s tree pruning efforts illustrate this.

According to Network World, there are about 2.5 million trees in the Big Apple. In order to avoid major storm cleanups and fatal accidents from heavy limbs falling, the trees must be properly pruned. The idea that proper pruning was worth the effort made sense, but there was no statistical evidence to see just how much good it did. The city had lots of data about pruning and emergency calls, but it wasn’t able to see how they linked. When it turned to a contractor with the technological savvy to make both datasets function together, the city discovered that carefully pruning for specific hazards caused a 22 percent decline in the frequency with which the city had to send in an emergency cleanup crew.

“Big data” is all the rage, and we’re thoroughly excited by the notion that super powerful technology combined with huge databases and strong analysis can do a lot to manage well. But we’d throw a little cautionary note into the maelstrom of excitement: Big data by itself won’t do a bit of good for any government unless it’s actually used for management or policy. We’re worried about that given the way mountains of well-done analyses issued by the likes of legislative audit offices, comptrollers and so on have frequently been ignored by decision-makers.

This column is an abridged, edited version of a column originally published by