Pilot quality is an experimental-design and operations problem, not simply a matter of collecting more data.
Inconclusive results usually begin before installation: the question, baseline, comparison, sensors, or decision rule was never made explicit.
That distinction matters because irrigation decisions cross several boundaries: a water record becomes a physical delivery, a delivery becomes a hydraulic condition, and that condition becomes a root-zone response. A number at one boundary cannot automatically prove performance at the next.
The mechanisms to keep visible.
Changing configuration mid-run can destroy comparability unless versioned.
Sparse sensor placement can confuse local anomalies with system performance.
Maintenance, weather, crop stage, and operator interventions can be unrecorded confounders.
Turn the pain point into a defined operating question.
Run a preflight review that can stop or redesign the pilot before hardware deployment.
Start with the decision the analysis must support. Then identify the smallest set of inputs capable of changing that decision. Keep source facts, calculations, model outputs, estimates, and operator observations distinct throughout the workflow.
Make the result reviewable.
Use protocol versioning, synchronized records, calibration checks, field notes, and predefined missing-data rules.
What this analysis cannot establish by itself.
Some uncertainty is irreducible; an honest inconclusive result can still improve the next protocol.
SIM treats an honest limitation as part of the result. Where evidence is incomplete, the correct status is inconclusive or unverified—not a more confident sentence.