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Three don’ts for helping the neediest families

Get families to economic sustainability faster with human services analytics.

Overview

Human services agencies cannot be truly effective if families most in need—those with annual gross incomes of less than 50 percent of federal poverty guidelines—stay that way. But the neediest families can be the hardest to help. Human services analytics can provide more individualized help faster.

By starting to collect outcomes data such as time to employment, wages earned when leaving eligibility for assistance, and integrating child support payment data with assistance eligibility data, human services agencies can develop pathways out of poverty for families with common characteristics.

Background

While most agencies have yet to act on the full potential of human services analytics, most see its value. Data insight allows agencies to get more nuanced and prescriptive in helping people than ever before. What better group to focus on than families that need the most help?

With data insight into the dimensions that contribute to a family’s characteristics, human services practitioners can identify its unique strengths and barriers and develop strategies to deliver the most promising interventions. Characteristics to analyze include:

  • Family size

  • Education, employment and criminal history

  • Immigration status

  • Health and disability status

  • Skills gaps

Analysis

Getting started means moving past commonly held assumptions that can stand in the way of using human services analytics to deliver outcomes to needy families.

  1. Don’t assume that a family’s need “in the moment” is their only struggle. Multi-program dependency means that the economic struggles of these families are not one dimensional. Their struggles are rooted in a complex mix of socio-economic, behavioral and cultural factors, some of which may cross multiple generations.

  2. Don’t assume its takes a lot of time and money to measure success. It is also important for agencies to measure the effectiveness of these interventions. By focusing on specific, short-term outcomes, complex and extended longitudinal assessments can be avoided, which saves time and money.

  3. Don’t assume the barriers to sharing data are insurmountable. Getting the necessary data for analysis is a must for developing and measuring interventions for the neediest families. There are strategies and tools that human services agencies can use to get traction in data sharing. After all, to comply with federal regulations, agencies must report certain data—and there are legal strategies for sharing it, especially de-identified data.

Recommendations
Human services analytics is not new. As practitioners focus on delivering public service for the future, helping the neediest families through scalable data segmentation of family characteristics is a practical way to help get more from human services dollars spent. Further, identifying communities with deeper levels of significant need can lead to the development of a community strategy to help improve the well-being of many families collectively.

Podcast

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Get Families to Economic Sustainability Faster with Human Services Analytics: Human services professionals know that the neediest families can sometimes be the hardest to help—and the journey to economic sustainability is different for each of them. But what if your agency could improve outcomes for the hardest-to-help families—getting them to economic sustainability faster? The good news is that it is possible to provide more individualized help to families faster with human services analytics.

We’ve heard a lot about human services analytics. Agencies are working hard to make the most of using data insight, especially in individualized siloed programs. What’s exciting is that by starting to collect outcomes data—such as time to employment, wages earned when leaving eligibility for assistance, and integrating child support data with assistance eligibility data—you can uncover pathways across siloed programs out of poverty for families with common characteristics. Some agencies seem excited about the prospect of working this way, However, many seem paralyzed to act. These agencies may be making false assumptions about the abilities and capabilities of families in their caseload. They may lack the needed data maturity to help them find the new and meaningful pathways out of poverty for the families they serve. Listen to Howard Hendricks, director of Human Services Business Strategy, on this podcast as he discusses getting families to economic sustainability faster with analytics.

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