The problem is not lack of information
The first failure in opportunity research is often category confusion. A sourced market number, a recurring qualitative observation, a simulated scenario and an intuition can all be useful. They are not the same kind of evidence.
The purpose of the protocol is therefore not to eliminate uncertainty. It is to label uncertainty before it enters a decision.
Four evidence states
Fact
A fact is an observation that can be traced to a source, dataset, document or directly observed event. A fact should carry provenance and, when relevant, a date and scope.
Signal
A signal is directional. It indicates that something may be happening consistently enough to deserve further investigation, but it is not yet sufficient to support a strong causal claim.
Model
A model is constructed. It may be useful for exploring scenarios, prices, allocation mechanisms or system behavior, but its outputs must remain visibly separated from observed data.
Hypothesis
A hypothesis is a proposition waiting for validation. It is valuable precisely because it can be tested and potentially rejected.
Why this matters for opportunity design
A Digital Opportunity Broker works upstream of product development. The decision is not initially how to build, but whether a friction is real, recurrent and economically meaningful enough to deserve a system around it.
That requires disciplined separation between what the market has shown and what the designer believes the market might support.
Publish the thesis. Show the method. Label the uncertainty.
Operational rule
Every quantitative element in an FT dossier should eventually answer four questions: source, update date, method and confidence. Until those fields can be completed honestly, the visual should be labelled as a signal, model or placeholder rather than presented as observed market data.