Overview
Many of the most consequential decisions in environmental management, public health, and social justice are made precisely where quantitative data are sparse, uncertain, or absent. We specialize in research designs and analytical methods that work in those conditions — combining structured expert knowledge elicitation, narrative and qualitative analysis, and Bayesian approaches to produce rigorous, defensible answers even when traditional data collection is impractical. We guide clients through every stage of a study: framing the right questions, designing a sample or elicitation protocol, conducting analysis, and communicating uncertainty honestly to decision-makers and stakeholders. Our mixed-methods work spans ecological science, organizational culture, public health, and social equity.
Selected Projects
Expert Elicitation for Hydrology Data Layer Review
NC Department of Transportation — ATLAS Sweeping Team
We developed a structured expert elicitation strategy to provide a transparent, quantitative review of ATLAS stream hydrology data layers. The approach was designed to capture practitioner knowledge about data quality, spatial accuracy, and appropriate applications in a format that is auditable and defensible for use in regulatory and planning contexts. The elicitation structure was built to surface disagreement among experts as meaningful signal rather than noise, supporting more honest characterization of data layer uncertainty.
Sense-Making & Organizational Culture Surveys
Spryng.io
We supported the development of data products and analytical frameworks for the Spryng.io platform — an organizational and cultural survey instrument grounded in ethnographic methods and complex adaptive systems theory. Unlike Likert-scale instruments, Spryng invites respondents to recall specific experiences and assign their own meaning through a set of interpretive questions. We contributed to the analytical architecture that surfaces patterns of interpretation across respondents, revealing how individuals understand their roles and experiences in ways that conventional surveys cannot capture. The platform has been applied in contexts ranging from organizational health to community engagement and social justice.
Geometric Morphometrics Research Support
Dissertation Research — Academic Client
We provided end-to-end statistical research support for a landmark-based geometric morphometrics dissertation study involving approximately 1,300 individuals across multiple partner agency collections, each with 86 landmarks per individual. Our work included data import and restructuring into the tps format required for morphometric analysis, assessment and handling of missing landmark data, orientation to the geomorph R package, and guided support through model runs, analysis interpretation, and production of publication-quality figures and tables. This project illustrates our capacity to join complex, specialized research workflows mid-stream as a knowledgeable analytical partner.
Stakeholder-Informed Water Quality Model Development
Upper Neuse River Basin Association (UNRBA) / Brown & Caldwell
For the Falls Lake statistical modeling project, we helped structure the engagement of subject matter experts and regulatory stakeholders in defining model segmentation, objectives, and outcomes. Our role included facilitating iterative feedback loops between the modeling team and UNRBA members to ensure the model framework reflected both the science and the regulatory questions it needed to answer — a process that required integrating quantitative model design with qualitative knowledge about how the model's outputs would be used in policy deliberations.