Cost-Benefit Tool Helps New York Target Funds to Evidence-Based Programs

Analyses ensure more decisions driven by data

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Cost-Benefit Tool Helps New York Target Funds to Evidence-Based Programs

In 2012, the New York State Division of Criminal Justice Services (DCJS) partnered with the Pew-MacArthur Results First Initiative to conduct formal cost-benefit analyses to help policymakers ensure that limited state resources are allocated to evidence-based criminal justice programs.

Before that, officials could not be certain that the state was funding programs that work or determine what outcomes to expect from the more than 200 community justice intervention services provided. So the division built an inventory of programs and conducted cost-benefit analyses using the Results First model—a tool that measures a program’s return on investment—to produce detailed calculations of how each program could affect recidivism, criminal victimization, and government spending.

The state’s initial report, published in 2013, summarized results from simulations for 58 programs to determine the likely effects on specific offender populations. To ensure this work would resonate with policymakers, the state focused on gross benefits to the government over five years.

For each program, the findings included: 

  • The projected change to the recidivism rate over five years.
  • Gross benefits, in dollars, per program participant.
  • The estimated reduction in crime victimizations per 100 program participants.

A second cost-benefit analysis performed in 2014 expanded the number of simulations to 67 and added program delivery costs and a calculation of net monetary benefits to the mix. Based on these analyses, New York identified several incarceration- and community-based programs that were likely to have positive impacts on public safety and reduce correctional spending, with some projected to return more than $4 for every dollar spent (the returns ranged from -$0.75 to $5.26).

While evidence-based employment and cognitive behavioral programs had been state priorities already, the ability to model the quantifiable impact on crime and spending solidified the importance of these interventions in New York’s criminal justice portfolio—and helped secure new funding for programs that could be demonstrated to be effective.

As the state was conducting its cost-benefit analysis, about $3.5 million of funding from the federal government through the American Recovery and Reinvestment Act (ARRA) for alternatives-to-incarceration programs was set to expire. DCJS requested $5 million from the state’s general fund to replace the federal money and boost spending, proposing investments in evidence-based programs that would return savings over the long term. Early cost-benefit calculations played a critical role in persuading policymakers to approve this request.

Now, the commitment to evidence-based policymaking has expanded to other state agencies. New York’s Department of Corrections and Community Supervision has used these analyses to rethink how to address problems and make sure resources are directed to effective programs.

State leaders say the strength of the Results First work helped New York win a more than $11 million “Pay for Success” federal grant in 2013 to expand evidence-based employment programs for parolees under state supervision. Including this grant, New York has allocated more than $95 million for effective programs driven by data and analysis in the six years since it joined Results First. During this period, the proportion of state spending dedicated to evidence-based alternatives-to-incarceration and re-entry programs increased from 25 percent in fiscal year 2012-13 to nearly 80 percent in fiscal 2016-17.  

Convincing policymakers to embrace this approach took time and effort, but New York’s experience demonstrates that an initial investment in using evidence to inform decisions can yield monetary benefits and spur activities that promote data-driven decision-making.

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Sara Dube is a director and Mariel McLeod is an associate with the Pew-MacArthur Results First Initiative.