The ability to make informed decisions depends on the availability and quality of data. When early childhood data is imperfect, as it often is, how are leaders, administrators, and parents to deliver positive outcomes for the children. As a mission-driven company aiming to benefit all children, 3Si empowers clients with information to serve all families and children, including those who aren’t always visible when data is elusive or nonexistent.
With 3Si’s unique approach, we build a solution based on foundational questions, rather than starting with the conveniently available data. In this blog post, we will explore how our approach helps governments use data more effectively to inform policy-making and other critical decisions.
Focus on Key Questions Regardless of Data Availability
One of the reasons our approach is different is that we focus on the questions that matter most. For example, “Where are the children who aren’t being served?” We then answer these questions by leveraging available data, and when data gaps and inconsistencies exist, we input values and create synthetic records.
For example, 3Si supplements available administrative data with Census data to establish a picture of the full child population. We prioritize child and household characteristics that most typically tie to programmatic eligibility, such as child age, household income, family size, and parent/guardian labor force participation. We pull these data elements together, however imperfect they may be, to provide a more holistic picture of the child population, including which of these children are eligible for which programs.
We maintain all this data as longitudinal data points in the Child Universal Success Platform (CUSP), which allows governments to track and see how key metrics change over time and across regions. This approach supports more effective policymaking and program management.
Another advantage of the CUSP model is its flexibility. The model is designed to take data at a granular level when available but can produce flexible outputs at a more aggregate level. Essentially, the model imputes data when necessary. Data can be flexibly aggregated or cross-tabulated for various levels of analysis. As states improve their data collection and availability, the system does less imputation, which results in higher fidelity in the model.
Making Informed Decisions that Benefit all Children
The CUSP model is designed to represent all children in the state. This includes children who are not served by any formal program with measurable data in the state. Our approach factors in local subject matter knowledge about program policies and eligibility requirements, which frames our understanding of both the served and unserved population. This means that governments can make informed policy, programmatic, funding, and other important decisions that benefit all children, regardless of their status in their state’s early child programs.
Measuring Success Over Time to Improve Outcomes
The longitudinal data points tracked in CUSP provide governments with the ability to measure success over time. With the synthetic records used to model the level of data needed for effective organizational decisions, governments can track how key metrics are changing. This allows them to make informed decisions about where to focus their efforts and investments to improve early childhood outcomes across the state.
Supporting Effective Decision Making
Ultimately, the goal of the 3Si approach is to support effective tool for program management, and other decisions that affect the early childhood field. By starting with foundational questions and developing a flexible model that simulates all children in the state, governments can make informed decisions based on the data that is available. CUSP helps governments identify gaps in data and impute values where necessary, so that meaningful insights can be generated. This approach leads to better outcomes for children and ultimately, stronger communities.
CUSP provides a unique perspective on data-imputation modeling for child development outcomes. By starting with key questions, rather than data availability, the CUSP model creates a strong foundation to support effective decisions. The flexibility of the model allows it to adapt to a range of data granularities, making it valuable for many different states. With its ability to simulate all children in the state, CUSP provides governments with the insights they need to improve child development outcomes, strengthen our communities, and improve lives.