New Unofficial Guide to the Why and How of State Early Childhood Data Systems

Blog Post
Sept. 18, 2017

State early childhood data systems.

Wait! Don’t go – just hear me out. A majority of people, even those immersed in early childhood education, aren’t eager to jump into a conversation about data systems. First of all, there is only a small fraction of us (me, NOT being one of them!), that actually enjoys data. And there are fewer still who have experience building and implementing data systems. But I think we can all agree that access to comprehensive data on state early care and education is critical to improving program access and quality by ensuring that resources and policy changes are directed at strategies that support the health of the whole child and lead to lifelong learning and success.

A recent publication released from the Ounce of Prevention, An Unofficial Guide to the Why and How of State Early Childhood Education, makes the case for why state early childhood data systems are so important and how state leaders can take realistic and manageable steps to implement one. I encourage you to read the entire piece as the author successfully turns a somewhat challenging topic into a light, witty, easily-digestible one.

The cold reality is this: “if your state doesn’t have a unified early childhood data system, the ceiling of what you’re likely to accomplish on any issue is far lower than you need it to be,” the author explains. State early childhood governance structures are typically quite fragmented resulting in any data collected to be disparate, incomplete and difficult or impossible to translate. A unified early childhood data system is the tool that will allow states to connect the data from the multiple state agencies and individual programs within those agencies that currently serve children and their families. In doing so, service providers can manage user needs more effectively; policymakers can better identify interventions that work and support continuous program improvement, innovation, and research; and researchers can conduct higher-quality evaluations.

Imagine a system that allows states to quantify how many students are accessing early care and education options, how effective those programs are, the qualifications of the teachers, and the zip codes each program serves. What if an elementary school principal knew more about her incoming kindergarten students and could ensure that students received appropriate services upon entry? And state policymakers – what if they had access to evidence showing early learning program efficacy beyond student success on a single third grade reading assessments?

But where to begin, you ask?

Setting realistic expectations is an essential first step, the author explains. A data system will likely begin small and grow over time. Experts explain that with a data system grounded in a clear vision and purpose, stakeholders can work slowly “to build policies and a governing structure to accommodate goals and promote ethical and effective use of the data and research as it grows.”

States that have engaged in the work of building data systems have generally followed a standard progression that includes:

  1. Stakeholder engagement. Like any successful broad-scale policy change, stakeholder buy-in is essential. Stakeholders should represent a wide range of possible end users of the final system and those who are likely to have very different ideas about how data should ultimately be used. The author stresses the need to avoid overselling what is possible to stakeholders by ensuring that the intention of the project is well communicated.

  2. Develop interagency agreements to oversee data system. Data privacy and public access to data are each important and should be supported through interagency agreements.

  3. Assess the data landscape. Conduct gap analyses and then prioritize where to focus time and resources.

  4. Build linkages among systems. This requires the technological expertise to actually build the systems that link existing data systems to close identified gaps.

Many states have had success building out quality data systems. Illinois, for example, launched its Illinois Early Childhood Asset Map (IECAM) in 2007 in order to link from Head Start, the private sector and general demographic information. Notably, the project is led by a university, rather than a state agency, an advisory council representing a diverse group of stakeholders guided decisions throughout the development stage and there is now a formalized advisory committee, and the capacity of the IECAM continues to expand beyond its initial purpose. Similarly, North Carolina has an Early Childhood Integrated Data System (NCIDS) that links nine programs and data sources including NC Pre-K, Food and Nutrition Services, and Child Protective Services. Since 2013, they have worked to incorporate Head Start data into their systems. Since early in the process, the state’s efforts have focused heavily on relationship building with each of its 56 Head Start grantees and with a vendor that services the majority of those providers. The NCIDS was able to leverage resources by using the same software as used by other programs in the state.

Yet although states are making great strides, they still have a long way to go before they have access to a complete, comprehensive data portal. Recent analyses indicate that at least 32 states link their K–12 data to some of their early childhood data yet only nine states linked Head Start data to K–12 data, and 12 states linked subsidized child care data to other EC data. Further the last survey conducted by the Early Childhood Data Collaborative in 2013 showed that PA was the only state that could link its state pre-k and child care data to produce a distinct head count. (This wasn’t much different from a report New America released in 2010.)

There is no doubt that building out a comprehensive state early childhood data system is not easy and the author of the report is upfront about that. However, his arguments for doing so are persuasive and cannot be ignored. The report includes valuable examples of how states can unify their data systems including state examples and some questions to get you started. The author also shares a number of resources that can help state leaders throughout the planning and implementation process.