Human-services providers strive to improve the trajectory of people's lives, but the work is often more transactional than transformational. A day at most government human-services offices consists of programmed actions and reactions by workers, data systems and clients. Timely, successful transactions are the main goal: Did we issue food stamps on time? Did we respond to 95 percent of our hotline calls within 24 hours?
These measures are important, but they don't always provide the most meaningful outcomes for clients. Programs aren't asked to consider how quantitative transactions contribute to qualitative changes in people's lives. Output measures do matter, but how can we be sure service agencies do the right work for the right people at the right time?
We're seeing how new technology and methods, along with more sophisticated data analytics, can turn volumes of data into actionable insights and help change this all-too-common pattern. As we outline in a new Deloitte report, we've found three effective ways that agencies are shifting the focus from transactions to transformation:
1. Accelerating self-service: Many states are pursuing "no-touch" eligibility systems that automate medical-assistance applications and processing. The systems use data exchanges and real-time verifications requiring minimal caseworker intervention. No-touch systems determine eligibility immediately, benefits come sooner, and caseworkers spend less time on data entry and more time with clients.
The no-touch approach may not work for all programs, especially those needing some independent verification that what an applicant says is true or correct. Here, some state systems use "low-touch" application processing, still saving significant time. One state realized increased productivity -- realizing a 35 percent to 50 percent reduction in processing times -- using both systems.
2. Redesigning programs to serve unique customer segments: Case managers are often forced to focus on program eligibility for clients rather than the reasons they're in the safety net or how they could bounce off of the net successfully. The challenge here is to understand the best goals for individual clients and then provide the services to help achieve them.
This recognition has given rise to a new wave of experimentation. The overarching goal is to get more individuals and families out of the system, not by redefining eligibility or cutting services but by applying the right services and benefits to help them achieve self-sufficiency or at least to improve their lives when self-sufficiency is not possible.
In 2011, Washington, D.C.'s Department of Human Services Economic Security Administration started overhauling its Temporary Assistance for Needy Families (TANF) program using an assessment of specific client needs. The assessment is solution-focused and designed to uncover what has and has not worked in the past. Typical questions include: "How did you get by every day?" "What changed to bring you here?" "How have you tried to address your problems?" "What worked and what didn't?"
The result of the assessment is a customized profile that helps the agency categorize the client into one of four segments that offer a specific suite of services: job placement; work readiness; barrier removal and work support; and barrier removal and financial support. The assessment drives an individual responsibility plan, a contract negotiated with the client, and the service referrals the customer receives. Early evaluation shows a tenfold increase in work activity among TANF recipients.
3. Transforming practice through analytics: Thanks to advances in technology, data capture and analytics, focus is shifting from hindsight indicators to predictive factors. In Camden, N.J., for example, residents in just two buildings accounted for nearly $30 million in services. By better coordinating these clients' health care and addressing their social circumstances, the Camden Coalition of Health Care Providers cut these costs by more than half. And the Florida Department of Juvenile Justice uses predictive analytics to identify juvenile offenders most likely to commit new crimes. The aim is to reduce recidivism by using predictive factors and placing offenders in specific rehabilitation programs.
Will these methods solve all of the issues surrounding government's delivery of human services? No. But properly applied technological advances can do a lot more than simply reducing paperwork. They can enable caseworkers to provide intensive, specialized services for clients that produce what everybody wants: better outcomes.