The heart of EdSystems’ work is ensuring successful transitions to and through postsecondary and career opportunities for all students, with a particular focus on supporting historically marginalized populations. Data is essential to this vision, informing policy and program designs that effectively support students and guide them toward a successful future. By analyzing data about communities and programs, the team gains a deeper understanding of student needs, tracks progress, and refines our efforts to ensure resources are focused on the most effective strategies.
We are committed to continually improving how we use data to guide EdSystems’ work. Our team is committed to growing our data expertise, recently participating in development opportunities to better support our partners with impactful, data-driven solutions. Our goal is to build our data capacity so we can better address the data challenges our community partners face. This includes improving access to data, helping them find relevant data resources, assisting with data uploads, linking data from different sources, and supporting data interpretation and contextualization.
Key Principles of Our Data Approach
Identifying the Exact Problem
At EdSystems, we base our data strategy on the principles outlined in Learning to Improve (Bryk et al., 2015), which emphasizes problem-specific, user-centered solutions. We start by asking, “What exactly is the problem we are trying to solve?” This question sharpens our focus on the most important issues. The process is collaborative—engaging key participants early and throughout ensures that the solutions we develop are not only relevant but also practical for those who will use them. This approach ensures that our solutions are designed by those who will implement them and those who are most impacted.
Understanding the Context
Another crucial aspect of our work is understanding the variation in performance across different contexts. When considering solutions, we also ask, “What works for whom and under what conditions?” Our goal is to enhance effectiveness consistently across various settings, which requires us to thoroughly understand the current system and observe how local conditions influence work processes. Recognizing variations in contexts allows us to adapt strategies to meet the unique needs of different communities.
A Data-Driven Vision for Change
With these principles in mind, a clear vision for data is essential in driving lasting change. To fully understand variation in performance, we look at macro-level data, like the Success Network Dashboard, and longitudinal data, which reveals patterns of the same cohort of students over time. This helps identify underlying factors that contribute to student success or challenges, giving insight into how different elements of programs are working. By embedding measures of key outcomes at each stage of the process, we can measure progress and adjust our efforts to improve effectiveness consistently, ensuring that resources are focused on making the most impact.
Combining macro-level insights with community-level data also allows us to see how local conditions and implementation strategies influence outcomes, as evidenced by examples from our manufacturing pathways initiatives, such as the STAMP Dashboard and data brief highlighting the resilience of students from high-needs communities in pursuing credential pathways. This comprehensive approach helps us understand the system behind current results and ensure that improvements can be scaled reliably. By measuring, tracking, and adjusting based on these diverse data types, we can adapt our strategies to the unique needs of each community, ensuring continuous improvement and fostering long-term, equitable success.
Data and Equity
In any effort to improve complex systems, having a clear and structured data approach is essential—not only for driving meaningful change but also for informing equity. When data is used poorly, it can harm communities by setting unachievable goals, misdirecting resources to ineffective programs, or focusing on the wrong priorities. Data-driven insights allow us to reveal the challenges students face, assess program effectiveness, and identify areas for additional support.
A strong data approach helps us clearly define the specific problems we’re trying to solve and allows us to measure the impact of our interventions across different groups. By centering our work around the principles of problem specificity, user-centered design, and continuous evaluation, we build a foundation for making informed decisions that lead to sustainable, long-term improvements. This approach also ensures that we can identify and address performance gaps, enabling us to design solutions that are fair and equitable for all stakeholders.
We aim to make our approach a valuable resource for other organizations by sharing insights and lessons learned. By focusing on key principles—asking the right questions, tracking outcomes, and understanding performance—organizations can refine interventions and drive long-term impact for greater equity. We intend to deepen our efforts and share more about our data work with communities, along with current learnings, through future resources and blogs, offering further insights to support meaningful change.
Our Approach: Data for Effective and Equitable Solutions
The heart of EdSystems’ work is ensuring successful transitions to and through postsecondary and career opportunities for all students, with a particular focus on supporting historically marginalized populations. Data is essential to this vision, informing policy and program designs that effectively support students and guide them toward a successful future. By analyzing data about communities and programs, the team gains a deeper understanding of student needs, tracks progress, and refines our efforts to ensure resources are focused on the most effective strategies.
We are committed to continually improving how we use data to guide EdSystems’ work. Our team is committed to growing our data expertise, recently participating in development opportunities to better support our partners with impactful, data-driven solutions. Our goal is to build our data capacity so we can better address the data challenges our community partners face. This includes improving access to data, helping them find relevant data resources, assisting with data uploads, linking data from different sources, and supporting data interpretation and contextualization.
Key Principles of Our Data Approach
Identifying the Exact Problem
At EdSystems, we base our data strategy on the principles outlined in Learning to Improve (Bryk et al., 2015), which emphasizes problem-specific, user-centered solutions. We start by asking, “What exactly is the problem we are trying to solve?” This question sharpens our focus on the most important issues. The process is collaborative—engaging key participants early and throughout ensures that the solutions we develop are not only relevant but also practical for those who will use them. This approach ensures that our solutions are designed by those who will implement them and those who are most impacted.
Understanding the Context
Another crucial aspect of our work is understanding the variation in performance across different contexts. When considering solutions, we also ask, “What works for whom and under what conditions?” Our goal is to enhance effectiveness consistently across various settings, which requires us to thoroughly understand the current system and observe how local conditions influence work processes. Recognizing variations in contexts allows us to adapt strategies to meet the unique needs of different communities.
A Data-Driven Vision for Change
With these principles in mind, a clear vision for data is essential in driving lasting change. To fully understand variation in performance, we look at macro-level data, like the Success Network Dashboard, and longitudinal data, which reveals patterns of the same cohort of students over time. This helps identify underlying factors that contribute to student success or challenges, giving insight into how different elements of programs are working. By embedding measures of key outcomes at each stage of the process, we can measure progress and adjust our efforts to improve effectiveness consistently, ensuring that resources are focused on making the most impact.
Combining macro-level insights with community-level data also allows us to see how local conditions and implementation strategies influence outcomes, as evidenced by examples from our manufacturing pathways initiatives, such as the STAMP Dashboard and data brief highlighting the resilience of students from high-needs communities in pursuing credential pathways. This comprehensive approach helps us understand the system behind current results and ensure that improvements can be scaled reliably. By measuring, tracking, and adjusting based on these diverse data types, we can adapt our strategies to the unique needs of each community, ensuring continuous improvement and fostering long-term, equitable success.
Data and Equity
In any effort to improve complex systems, having a clear and structured data approach is essential—not only for driving meaningful change but also for informing equity. When data is used poorly, it can harm communities by setting unachievable goals, misdirecting resources to ineffective programs, or focusing on the wrong priorities. Data-driven insights allow us to reveal the challenges students face, assess program effectiveness, and identify areas for additional support.
A strong data approach helps us clearly define the specific problems we’re trying to solve and allows us to measure the impact of our interventions across different groups. By centering our work around the principles of problem specificity, user-centered design, and continuous evaluation, we build a foundation for making informed decisions that lead to sustainable, long-term improvements. This approach also ensures that we can identify and address performance gaps, enabling us to design solutions that are fair and equitable for all stakeholders.
We aim to make our approach a valuable resource for other organizations by sharing insights and lessons learned. By focusing on key principles—asking the right questions, tracking outcomes, and understanding performance—organizations can refine interventions and drive long-term impact for greater equity. We intend to deepen our efforts and share more about our data work with communities, along with current learnings, through future resources and blogs, offering further insights to support meaningful change.
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