Truth, Real Indicators, and Alternative Data

TRIAD develops independent measurement systems for when conventional data sources fail, degrade, or become politicized. The program focuses on identifying observable proxies for economic, social, and security conditions using non-traditional inputs such as geospatial signals, behavioral traces, crowdsourced observation, and machine-assisted verification. Rather than replacing official statistics, TRIAD operates alongside them, testing where traditional indicators break down and constructing reliable alternative signals.

Status: Prototyping

TRIAD is consolidating alternative data types and validation techniques into a structured framework for cross-domain application.

Pillar One: Signal Discovery and Coverage

TRIAD maps where conventional measurement breaks down and identifies the signal classes that can fill the gap. This includes commercial remote sensing, open web exhaust, transactional and logistics traces, and sensor-derived data that can be observed without relying on official reporting. The priority is coverage and continuity: signals that persist through disruption and remain comparable over time.

Pillar Two: Validation, Provenance, and Error

Alternative data is only useful if it can be trusted under scrutiny. TRIAD develops provenance rules, sampling sanity checks, ground-truth strategies, and consistency tests that separate usable signals from artifacts, bias, and manipulation. Outputs include confidence scoring and explicit uncertainty so decision-makers understand what is known, what is inferred, and what is not reliable.

Pillar Three: Fusion into Indicators

TRIAD turns disparate signals into integrated indicators that can be tracked and compared. This includes combining multiple weak signals into a stronger composite, designing leading indicators that move ahead of official data, and building dashboards that show trend, inflection, and anomaly. The objective is not novelty. It is a measurement product leaders can use repeatedly.