What we build

Decision frameworks and analytical methods

The Institute's applied work turns research questions into methods that people can use. A decision framework defines the choice, the available options, the criteria for comparison and the evidence needed to proceed. Its value lies in making the reasoning explicit enough to challenge and improve.

Useful outputs can include an opportunity assessment, a dependency map, a decision brief or a set of indicators for monitoring change. Each should state its intended use, the information it requires and the limitations that a reader must understand.

Scenarios, models and prototypes

Scenarios explore how different conditions could affect a decision. Models make selected relationships explicit so that assumptions can be varied and consequences compared. Prototypes test a narrower question: whether a proposed method or workflow can work with the information and constraints available.

For example, an AI opportunity assessment can compare the frequency of a task, the cost of error, the quality of the available data and the need for human review. A scenario exercise can then examine how changes in those conditions affect the case for adoption. The output supports judgment; its assumptions remain open to inspection.

Make the work understandable and testable

A practical tool needs clear inputs, traceable calculations and an explanation of its outputs. Testing should include ordinary use, incomplete information and cases in which the method could give a misleading answer. Documentation should explain how to interpret the result and when further analysis is needed.

The same discipline applies to a one-page framework and a software prototype. Define the problem before selecting the technology, keep the method proportionate to the decision and revise it when evidence reveals a weakness.

To discuss an applied research question, contact the Institute with the decision, intended users and practical constraints.