Overflowing with data.

Photographer: Victor J. Blue/Bloomberg

Finding Data in the Trash

Megan McArdle is a Bloomberg View columnist. She wrote for the Daily Beast, Newsweek, the Atlantic and the Economist and founded the blog Asymmetrical Information. She is the author of "“The Up Side of Down: Why Failing Well Is the Key to Success.”
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Last night, I had the privilege of having dinner with Karen Freeman-Wilson, the mayor of Gary, Indiana, who discussed the challenges of reviving a city that has been hit hard by the same manufacturing declines that have plagued many of the Midwest's industrial towns. I learned a lot from our conversation, much of which will probably appear in future posts. But here's one tidbit that I thought was worth sharing: how she addressed a really basic data problem. That is, figuring out how many people you have in your city.

"Census!" you will say, but a lot of areas, especially high-poverty areas, have problems counting all their residents. Abandoned properties attract squatters; families in distress surf from couch to couch with friends and family and may miss being counted. So how do you figure out how many residents you're trying to serve?

The answer is trash cans. Even if people aren't answering surveys, they're still generating garbage. And as Freeman-Wilson said last night, "They're not putting out the cans if they're not there." A growing number of trash cans means a growing number of residents, no matter what the census figures say.

There's no moral to this story exactly; I just wanted to highlight an innovative way to get around a data problem. It would be nice if we could have all the data we want. But we can do a surprising amount with the data we actually have.

This column does not necessarily reflect the opinion of Bloomberg View's editorial board or Bloomberg LP, its owners and investors.

To contact the author on this story:
Megan McArdle at mmcardle3@bloomberg.net

To contact the editor on this story:
Brooke Sample at bsample1@bloomberg.net