Tag Archives: Data analytics

Statistics are critical to our program

Colorful bar graph through a magnifying glassI just learned (via the U.S. Census Bureau) that 2013 is International Year of Statistics. A page full of statistics can be scary to some, but statistics is one of my favorite words. In OCSE, we have a division of dedicated staff members who collect and analyze statistics—a critical component of our program. Because we audit program data (through another OCSE office of dedicated auditors), we have program data that we trust.

Why do I like statistics? Well, first of all, child support statistics have given us the tools we need for measuring and presenting the efficiency and effectiveness of our national program to the public. The fact that we can measure our performance, and do so with audited, accurate data, has helped us demonstrate program accountability, identify program trends, and correct course when those data identify performance problems.

Statistics are critical, too, as we train our own staffs. In the February Child Support Report, New York City Director Frances Pardus-Abbadessa describes the need to get buy-in from every staff member to understand the culture of change in our program, including the importance of treating both custodial and noncustodial parents fairly in every case.

We pay attention to statistics published at various times of the year to understand trends in our caseload and improve our outreach services. For example, see the articles in the same Child Support Report on Teen Dating Violence Awareness Month, the Latino Resource Center, and the IRS Earned Income Tax Credit; they all contain pertinent statistics.

But most importantly, statistics gives us a window on the families we serve. What does our caseload look like? What are the demographic factors we need to understand? And what does data tell us about effective strategies for reaching our goal: obtaining consistent child support payments for families? An example of how data changed the way we thought about arrears management is the series of state studies conducted several years ago by the Urban Institute that found that 70 percent of noncustodial parents who owe child support arrears had reported incomes below $10,000 per year. (You can find the report on the HHS website.)

Here are some statistics that are worth repeating because they play an important part in the program’s success:

  • Child support provides about 40 percent of family income for the poor families who receive it, and 10 percent of income for all poor custodial families.
  • Child support is a critical program for poor families; about half of families in the program are below 150 percent of the poverty level, while 90 percent are below 400 percent of poverty. The child support program is one of the “big three” income support programs (along with Earned Income Tax Credit and SNAP) that provides a safety net for poor families.
  • The child support program demonstrates a high return on investment. In FY 2011, the program collected $5.12 for every dollar it spent.

I look forward to two new OCSE reports this year that will give us a deeper understanding of those and other statistics in our program. The first is a “Story Behind the Numbers” fact sheet that analyzes the Census Bureau’s “Child Support Supplement to the Current Population Survey.” We expect to publish the fact sheet soon.

The second report will delve into data analytics. Over the last year, we have been collaborating with a contractor to assess our various data sources so we can use them more easily and effectively. We are developing a conceptual design document and requirement specifications to build an internal child support dashboard framework that will allow us to analyze our data in more robust ways. As many state and local child support programs know, dashboards are great tools for tracking outcomes visually through devices such as bar charts, time series trends and pie charts. They help us to tell the “story behind the numbers.” In addition, users will be able to quickly aggregate data from our data sources and drill down for further analysis. We expect to complete this project in late spring, and we’ll keep you posted.

I hope that many of you will share my focus on statistics this year, as we use data to help us improve ways we manage our program and provide services to all parents and families we serve.

 

 

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