RSI conducts vulnerability and capacity assessments using a mix of quantitative indicators and qualitative inputs. It emphasizes local knowledge and stakeholder engagement, particularly in climate adaptation and health equity contexts. RSI’s integrated approach ensures findings are used to inform practical and just resilience-building strategies.

RSI uses predictive modeling in public health forecasting, emergency preparedness, and scenario planning. It combines machine learning, regression models, and simulation approaches tailored to each risk domain. RSI emphasizes not only accuracy but explainability, ensuring that decision-makers can trust and act on the forecasts provided.

RSI supports alignment through pre-event planning workshops, messaging templates, and interagency coordination protocols. The firm helps map messaging chains, test consistency under time pressure, and document roles. RSI draws from its expertise in both risk communication and governance to build systems that are timely, clear, and coordinated.

RSI designs and runs workshops that draw out both expert and operational perspectives on emerging or systemic risks. Its approach combines participatory mapping, guided brainstorming, and pre-read materials. RSI ensures that identified risks are captured systematically and translated into inventories, matrices, or models that feed into larger risk processes.

RSI facilitates risk prioritization workshops using tools such as risk matrices, MCDA, and facilitated consensus. Its approach balances technical input with participatory deliberation to create shared understanding and buy-in. RSI ensures that prioritization outcomes are documented, traceable, and integrated into planning and resource allocation processes.

RSI designs and deploys visualization tools to make risk intelligible across technical and lay audiences. It uses participatory design, evidence mapping, and digital prototyping. RSI ensures that tools are intuitive, scalable, and aligned with communication objectives, particularly in cross-sector contexts.

RSI uses systems mapping to support integrated risk strategies, particularly in multi-sectoral or cross-jurisdictional contexts. Its approach combines expert elicitation, participatory design, and software tools to create clear, actionable maps. RSI ensures maps serve as living tools for analysis, communication, and decision support.

RSI applies data science to enhance its modeling, surveillance, and synthesis capabilities. The firm integrates open-source tools, custom scripts, and commercial platforms to analyze diverse datasets—including textual, geospatial, and time series data. RSI’s approach emphasizes transparency, reproducibility, and integration with domain knowledge to ensure data science outputs are not only innovative, but also responsible and relevant in high-stakes decision-making.

RSI supports signal detection in safety surveillance, environmental monitoring, and early warning systems. Its teams configure thresholds, monitor trends, and use algorithms or human-in-the-loop processes to flag concerns. RSI emphasizes the integration of signal detection with context interpretation, ensuring appropriate responses and sustained vigilance.

RSI applies MCDA in high-stakes risk decisions, helping clients define criteria, score options, and test robustness. Its facilitators engage stakeholders in structured deliberation to ensure diverse values are reflected. RSI documents assumptions and uncertainty transparently, providing a defensible foundation for risk-based choices.