Practical guide
How analysts can reduce information overload
Define the measure and decision first. Resolve figures to primary data, normalize units and periods, group commentary by assumption, and preserve dissent that can falsify the working conclusion.[1][2]
Why this gets difficult
Analysts can collect more reports than they can reconcile. Duplicate figures, incompatible definitions, revised data, and consensus commentary then create the appearance of depth without a clean analytical base.[1][2]
A practical way through
- Write the metric, population, period, and threshold that would change the analysis.[1][2]
- Resolve every important figure to a filing or named data series.[1][2]
- Separate observed data, estimate, forecast, and interpretation.[1][2]
- Stop collection when the coverage rule is met and record missing evidence explicitly.[1][2]
An example
The situation: Several reports cite market growth using different geographies, currencies, and category definitions.[1][2]
What changes: The underlying sources and definitions are reconciled, incompatible measures remain separate, and commentary is mapped to the figure it actually uses.[1][2]
What you get: The analyst avoids a false consensus and identifies the specific data gap that still matters.[1][2]
What to watch for
Sources worth keeping
How Scottie helps
Scottie can group selected filings, data releases, and specialist reports around the analyst's questions while preserving links and visible exclusions.[3]