Under the Bloomberg administration, New York City has been a national leader in evangelizing open data, making the people’s data available to the people with the goals of improved transparency, accountability, insight into performance, and citizensourcing better ideas or processes along the way.
A longstanding open question for this observer, however, has been how well the Big Apple was consuming its own data, particularly with respect to how the city allocates resources and responds to public safety issues. …
…[T]he approach that [Mike Flowers, the director of analytics for the Office of Policy and Strategic Planning in the Office of the Mayor of New York City] and his team have taken to detecting financial fraud and other crimes or problems is interesting - but the outcomes from it are notable. According to Flowers, applying predictive data analytics towards “preemptive government” in New York City has resulted in:
- A five-fold return on the time of building inspectors looking for illegal apartments
- An increase in the rate of detection for dangerous buildings that are highly likely to result in firefighter injury or death
- More than doubling the hit rate for discovering stores selling bootlegged cigarettes
- A five-fold increase in the detection of business licenses being flipped
- Fighting the prescription drug epidemic through detection of the 21 pharmacies (out of an estimated total of 2,150 in NYC) that accounted for more than 60% of total Medicaid reimbursements for Oxycodone in the city
[In the interview on O’Reilly Radar], Flowers explains more about how his team achieved these results, what’s necessary to go beyond performance measurement, and what’s next for the application of predictive data analytics in New York City.