Examine social and historical contexts to identify root causes of disparities, inform data collection and use, and develop data-driven solutions.
To assess and address disparities along the pre-K-to-workforce continuum, data users must understand the local historical and social context behind these disparities. Root cause analysis equips decision makers with the essential contextual knowledge needed to understand how disparities are produced, not only that they exist. Too often, data users analyze data on outcomes without deeply interrogating the structural causes of the disparities they observe, such as historical events, racist and other unjust policies, misinformed interventions, and oppressive social conditions. Without an understanding of these root causes, data projects and intervention strategies can fall short of creating lasting change and may even perpetuate racist structures.
Root cause analysis is a data-driven inquiry process with three overarching steps: identify a problem, identify root causes of the problem, and identify strategies to address the root causes. Data users must spend time developing an understanding of system conditions and other contextual factors that might be contributing to disparate outcomes, pulling data and information from existing sources, if available, to avoid duplicating efforts and placing undue burden on community members. Grounding data work in historical and societal context can also involve conducting an organizational reflection, equity audit, or environmental scan. An equity audit is a study of the fairness of an institution’s policies, programs, and practices. Equity audit tools can help data users critically examine policies, programs, and practices that directly or indirectly affect students or staff related to their identity. An environmental scan involves gathering information about a community and its relationships to understand the systems and institutions in place that affect how people behave, and the landscape in which the community operates.
Direct engagement with people with lived experience is key to conducting reflective root cause analyses that seek to identify systems drivers of disparities—not symptoms—and solutions to dissolve them. After an initial assessment of disparities, data users should convene groups of people with different perspectives on the problem—such as practitioners, students, and parents from priority communities—to brainstorm possible explanations that, if addressed, ought to reduce or prevent disparities in the future. Groups should prioritize potential root causes until they reach consensus on a few of the most actionable factors most likely to drive disparities. This process should not only inform the development of solutions, but also decisions about which data to collect and analyze to further validate the hypothesized root causes and monitor progress.
Involving community to identify and address root causes
Disaggregated test score data for Marguerite Montgomery Elementary School in Yolo County, California, showed that students in the school’s English-only program scored significantly lower than their peers in the two-way bilingual immersion program in every grade, regardless of whether students were emerging multilingual learners. The school held multiple staff and parent engagement activities in both Spanish and English to uncover the root causes of this disparity. They found systemic disproportionalities in the students enrolled in the two programs. They also learned that the school community valued bilingualism, and that research showed that students in dual language programs did as well or better than their peers in English-only programs. As a result, the school decided to transition into a fully dual immersion model, holding planning sessions that continued to engage both staff and community members as part of a new continuous improvement cycle (California Department of Education, 2021).
Applying this Principle
Identify key historical events, policies, and processes that provide context for the observed present-day disparities. You can conduct an historical analysis through an equity audit, an environmental scan, or organizational reflection, such as a visual timeline activity that maps trends in outcome data against policies and other changes over time.
Vet research questions and data collection plans for a root cause analysis with the groups of people most affected by the identified problem of practice. Community members can provide input on whether the right problem of practice has been prioritized and which data points should be collected and from whom to explore its root causes.
Engage multiple colleagues in dissecting the chosen problem by asking them to answer the question, “Why is this the case?” five times. Tools like a fishbone diagram or root cause tree can aid in this step. Focus on systems and structures, eliminating explanations that are not within the control of E-W decision makers, are not consistent with the available data, or cannot be tested. Reach consensus on the most likely and actionable root causes.
Seek community reactions to and interpretation of findings to illuminate root causes not otherwise surfaced. Co-create action items—including potential data-driven solutions to address the root causes—to promote change through advocacy.
- Who is affected—positively or negatively—by the disparity in question? Why? How?
- Do our analyses identify historical structures, policies or practices, and institutions involved? What social conditions contribute to the problem?
- Do our analyses go far enough, or are we attributing an equity disparity to contributing factors rather than root causes? Are there alternative explanations that fit better?
- What opportunities have we provided for community members to lead and drive contextual understandings to support project goals?
Be On The Lookout
Be careful not to mistake contributing factors for root causes. Contributing factors are conditions that allow the identified disparity to occur or persist. A root cause is a factor that prevents it from occurring if taken away. Removing a contributing factor (for example, expanding Advanced Placement course offerings) can improve disparate outcomes, but will not eliminate them. Addressing root causes (for example, educator bias, misplacement of Black students in noncollege preparatory courses) makes it more likely that solutions will be successful in promoting equitable change.
- How to Embed a Racial and Ethnic Equity Perspective in Research. This guide by Andrews et al. offers practical guidance to researchers and data users alike on how to dissect and use data through an equity lens. The authors pay particular attention to understanding the contextual and societal factors behind the issues of access and opportunity a community may face.
- Race Equity and Inclusion Action Guide. This Annie E. Casey Foundation resource provides guidance on key steps to advance and embed racial equity and inclusion in organizations. It provides questions to guide data users through a systems analysis of root causes of inequities and to identify strategies to address root causes.
- The State and District Role in Root Cause Analysis. This resource provided by the Office of Elementary & Secondary Education links to tool kits that state and district education agencies use to conduct root cause analyses while supporting school improvement efforts. It also offers guiding questions and facilitation tips for districts and states.
- How We Should Talk About Racial Disparities. This article by Spievack and Okeke discusses why and how researchers and data users can examine contextual factors to avoid perpetuating racist structures and eliminate bias in reporting.
The framework's recommendations are based on syntheses of existing research. Please see the framework report for a list of works cited.