In many ways, the marine mammal resource type exemplifies the challenge of effectively collecting, combining, and evaluating essential information for decision-making. Cetaceans (whales and dolphins) of the Gulf – particularly those offshore – are complex, long-lived, difficult to study, and ecologically specialized animals. Understanding status, trends, habitat use, life history, and response to stressors are all critical to planning, implementing, and evaluating restoration efforts. In order to operationalize what we know and fill in what we do not, the Deepwater Horizon marine mammal restoration effort has funded a portfolio of projects to understand injured cetaceans, aggregate data, model the cumulative impact of stressors, reduce threats, and evaluate the impact of these investments. What we are finding is that combining biological, ecological, stressor, health, and threat information is difficult to do across the different spatial and temporal scales of measurement with the purely quantitative frameworks that are the norm in marine mammal science. We are also finding that there are opportunities for new synthesis frameworks that support restoration, and the insights from CETACEAN data aggregation, LISTEN GoMex PAM data analysis, PCoMS statistical modeling, large vessel surveys and assessment modeling, SDM restoration evaluation, and other sources can and do come together to paint an incredibly insightful picture of the status, trajectory, and opportunities to restore Gulf cetaceans. This talk will briefly unpack the different aspects of data collection, aggregation, and analysis from the marine mammal resource type in order to set the stage for a discussion of how the hybrid qualitative/quantitative structured decision making model successfully brought all of the restoration information together into a common, exportable framework, and provides an opportunity to widen our regional definition of synthesis in the science-for-management enterprise.