Turning impact research into an open calculation toolkit
Translating stakeholder needs and impact research across people, natural and built environments into data structures, calculation logic and a phased product roadmap.
Case record
The same seven questions, every time.
- Context
- Impact work spans different kinds of evidence across people, the natural environment and the built environment, each with its own definitions and data requirements.
- My role
- Data Scientist & KTP Research Associate — leading the design and delivery of the toolkit.
- Constraint
- A technically elegant structure is not useful if it asks for unavailable data or hides the assumptions behind an output.
- Decision
- Resolve definitions, data requirements and calculation rules before the interface, and sequence delivery around evidence and dependency rather than feature count.
- Artefact
- Explicit data structures, calculation logic, success measures and a phased technical roadmap, forming a common working model for research, delivery and product decisions.
- Result
- Approximately 30% less data-preparation time, and a clearer route from research evidence to an open calculation tool that people can interrogate and extend.
- Boundary
- The measured improvement applies to the structured workflow used in this ongoing programme, not to every future dataset or implementation. Current evidence supports the foundation and delivery path, not a finished product.
Evidence ledger
What the work can show.
- Scope
- People · natural · built environmentsOne toolkit has to carry several evidence types without hiding their differences.
- Process evidence
- ≈30% less preparation timeThe measured improvement belongs to the structured project workflow.
- Status
- Ongoing programmeThe current evidence supports the foundation and delivery path, not a finished-product claim.
The challenge
Impact work spans different kinds of evidence across people, the natural environment and the built environment. Turning that research into a toolkit means resolving definitions, data requirements and calculation rules before an interface can make them feel simple.
The product also has to work for its stakeholders. A technically elegant structure is not useful if it asks for unavailable data or hides the assumptions behind an output.
Planning the toolkit
I translated stakeholder needs into explicit data structures, calculation logic and success measures. This created a common working model for research, delivery and product decisions.
A phased roadmap separated what needed to be proven early from what could be extended later. That made dependencies visible and reduced the risk of building breadth before the calculation core was coherent.
- Map stakeholder questions to the outputs the toolkit must support.
- Define the minimum data and provenance required for each calculation.
- Make assumptions visible at the point they affect a result.
- Sequence delivery around evidence and dependency, not feature count.
The result so far
The structured workflow has reduced data-preparation time by approximately 30%. More importantly, it provides a clearer route from research evidence to an open calculation tool that people can interrogate and extend.
The work is ongoing. The current value lies in a stronger technical foundation and a delivery plan grounded in the realities of the data and the people who will use it.
Connected evidence
Where this sits in the rest of the work.
- Impact calculation toolkit in Selected SystemsThe homepage system entry, with its evidence instrument and boundary.
- Planning, in the working methodThe Planning stage this programme is the worked example for.