Article: Q&A: Building Analytic Muscle and Transforming Education Policy in New Mexico
The Experts
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Mitch Herz previously served as director of accountability within New Mexico’s Public Education Department, and staffed the Legislative Education Study Committee (LESC). Mitch knows how to help analysts interpret data, anticipate legislative needs, and craft evidence-based recommendations that shape statewide policy. His work spans early literacy, college and career readiness, assessment systems, resource allocation, and long-term policy design.
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Ryoko Yamaguchi, PhD is a nationally recognized expert in analytic technical assistance, with nearly two decades of experience helping agencies transform raw data into meaningful, actionable insights. One of the earliest practitioners of analytic TA through the Institute of Education Sciences and the U.S. Department of Labor, she specializes in building analysts’ critical thinking skills, data stewardship, and interpretive confidence.
New Mexico is undertaking a major effort to strengthen how its legislature makes decisions about education, and the Southwest Comprehensive Center (Southwest CC) is helping build the analytic muscle to make that possible. Through a structured analytic technical assistance initiative, Southwest CC is developing durable, agency-wide data capacity inside the LESC—the body lawmakers depend upon for evidence-based guidance.
The resulting “Capacity-building Research & Evaluation Workflow” (CREW) project provides one-on-one coaching, monthly Community of Practice sessions, and practical tools that help analysts think critically with data, generate trustworthy insights, and translate evidence into stronger policy decisions.
Over time, Herz and Yamaguchi expect this work to optimize resource allocation in New Mexico, while also helping the state avoid unintended consequences, strengthen systems thinking, and ensure every student has the conditions to thrive.
How did Southwest CC maximize capacity building in this project?
Herz: We focused on underlying principles rather than stances. We quickly identified the foundational elements analysts need to do whatever comes at them. Focusing on principles allows us to talk to anyone in this space and establish guidelines and rules for how best to proceed.
What are CREW’s foundational principles of data analysis?
Yamaguchi: First, principles over products—teaching foundational thinking rather than methods alone. This includes learning how to recognize and overcome what are more than 200 common data tendencies, looking for what data do not measure, who is not represented, and what story the data do not tell. Data simply reflect one moment in time for some population.
Second, humanity behind the data—building trust, empathy, and psychological safety to do this work well. Design thinking and trust building are core to CREW’s approach.
Education has been described as “data rich, knowledge poor.” CREW’s approach is to emphasize people over products. I share my own story to model how analysts should think about data. We use empathy interviews and a design approach, showing up as people first. "Trust and Inspire" is one leadership frame we draw upon.
TA used to be about strategy and practices; now it is about people and building relationships first.
Herz: Organizations often get stuck on statistical methods and skip the foundational parts of meaning-making—connecting data to the people behind it. Asking questions that unearth the humanity behind the data helps us treat data more responsibly.
Is analytic TA typical in the policy analyst space?
Yamaguchi: No. Analytic TA is typically used in research contexts—such as randomized control trials and, What Works Clearinghouse studies. Applying it to policy analysts is unique. In 18 years of doing analytic TA, I haven’t seen it used this way. It’s a new application of the model.
What cross-sector lessons did you carry in from similar work you did for the U.S. Department of Labor?
Yamaguchi: At the Department of Labor, state analysts needed help translating data into analysis. Federal legislation required states to build statistical adjustment models, and analysts needed support to meet those requirements. Many came from data management backgrounds—Oracle database management, institutional reporting—not analytic reasoning.
Helping them shift from reporting numbers to generating insights was essential. That experience informs how I approach LESC’s needs today.
Learn more about how Southwest CC is strengthening legislative decisionmaking in New Mexico here.