Indicator definitions and pipelines
Indicators are written down, versioned, and calculated by tested code instead of by hand.
Service
Research Monitoring & Evidence Systems
Traceable data systems for research programs, surveys, monitoring, and evidence reporting.
We build the data layer behind your indicators, from collection integration and quality checks to dashboards and recurring reports.
When teams need this
Situations this service is built for
- Indicators are recalculated by hand each reporting cycle from several exports.
- Survey data arrives with duplicates, out-of-range values, and skip-logic errors.
- Partners submit data in different formats that cannot be reconciled easily.
- Funder reports must be regenerated every period and the process is slow and error-prone.
- A dashboard shows numbers that nobody can trace back to their source.
What we can deliver
Capabilities
Monitoring databases
A structured database that holds program and survey data with clear keys and documented tables.
Data collection integration
Ingestion from the export files and APIs of the collection tools your team already uses.
Data quality assurance
Automated checks for duplicates, ranges, skip logic, and missing data, with exception reports your team can act on.
Dashboards
Dashboards where each indicator links to its definition and data source.
Reporting automation
Periodic reports generated from the validated data rather than assembled manually.
Tangible artifacts
What you receive
Deliverables are agreed in the scope. Typical artifacts for this service include:
- Indicator reference (definitions, formulas, sources)
- Monitoring database schema and loading code
- Data quality exception reports
- Dashboard and automated report templates
- Operations runbook for each reporting cycle
Typical workflow
How the work usually runs
- 1
Discover & scope
Agree the indicators, data sources, reporting cycle, and who needs what, along with data permissions.
- 2
Implement
Build ingestion, validation, and indicator calculation, then the dashboard or report on top of them.
- 3
Validate & review
Test indicators against hand-checked samples and review exceptions and definitions with your program team.
- 4
Document & hand over
Deliver the system with documentation and a runbook for each reporting cycle.
Rigor and constraints
Evidence, design, and limits
- Research design, sampling, and causal evaluation require qualified domain leadership. We build the data systems that support that work.
- A monitoring system tracks indicators. It does not by itself show that a program caused an outcome, and we do not describe it that way.
- Indicator definitions are owned by your program team and recorded in the system.
- Handling of participant data is assessed per engagement. Please do not send participant data in the initial inquiry.
Who this is for
Teams we typically support with this service
FAQ
Questions about Research Monitoring & Evidence Systems
Can you evaluate our program's impact?
Impact evaluation needs qualified research design and methods. We build the data systems that support it and can work alongside your evaluators.
Can you work with data collected in the field?
Yes, through the export files or APIs of your collection tools, subject to your data-sharing arrangements.
How are indicators kept consistent over time?
Definitions are versioned alongside the code, and changes are recorded so past reports can be explained.
Who can see the dashboard?
Access arrangements are decided with you during scoping, based on the data involved and your policies.
Discuss this with us
Tell us about your data and goals. The service is preselected in the inquiry form.