As David Leonhardt wrote in The New York Times yesterday
, it's possible to discern some glowing embers among the ashes of federal and municipal government inefficiency.
"When the federal government is good, it's very, very good. When it's bad (or at least deeply inefficient), it's the norm," according to Leonhardt, who quotes as support a dismal statistic from a new book by Peter Shuck, Why Government Fails So Often: "Less than 1 percent of government spending is backed by even the most basic evidence of cost-effectiveness."
Those glowing embers represent data-driven, fact-based policy decisions -- the kind that big data analytics makes increasingly practicable. And what better use for data-based solutions than accelerating interest in social impact bonds?
SIBs are essentially a mechanism for driving private capital in the direction of persistent, intractable social problems. They're relatively risk-free for the government, too, since repayment is usually triggered only when savings accrue as a result of the program. This approach, also known as "pay for success," has already been taken up by New York City and other authorities keen to turn measurable effectiveness into dollars. It has its critics, too.
New York has focused on using SIB funding to combat recidivism among young offenders emerging from the Riker's Island detention center. A 2012 agreement with Goldman Sachs secured a $9.6 million loan, which will be repaid according to the program's success -- the city, of course, saves money if offenders don't return repeatedly to jail.
In a failed initiative, however, the Children's Aid Society sought a "pay for success" partnership with the city to support its Lasting Investments in Neighborhood Connections (LINC) program aimed at keeping young people out of the juvenile justice system. The proposal ran into problems with metrics. It could not overcome obstacles in determining things like:
- The exact target population for the program
- Expected outcomes for that population, absent the program
- The precise cost of failure (repeat offenses), and which agency bears the cost
- The most effective interventions
- The cost of the interventions
There have been criticisms of the SIB approach. Some argue against the privatization of social programs, complain about the ROI expected by sponsors, and point out that the emphasis on funding proven programs shows SIBs to be -- predictably -- risk averse.
However, the fundamental challenge for the SIB strategy lies in driving clean, unambiguous data against both the problems and the possible solutions. The good news is that, even in the last two or three years, analytics has increasingly measured up to the task of capturing and interpreting troves of complex data. As Leonhardt says: "The explosion of available data has made evaluating success -- in the government and the private sector -- easier and less expensive than it used to be."
It's too soon to write off the SIB experiment.
— Kim Davis , Editor-in-Chief, UBM Future Cities