Change Detection

Allocator relevance: Reduces the cost of acting on stale information and improves targeting accuracy in allocator coverage and outreach workflows.

Expanded Definition

In allocator intelligence, the highest-cost failures often come from stale facts: outdated decision-makers, changed mandates, moved geographies, or expired emails. Change detection focuses on identifying what changed, when it changed, and how confident the system should be—so teams can prioritize verification and action.

Change detection is distinct from data refresh cadence: a refresh updates data, while change detection flags deltas and routes them through validation and downstream systems.

How It Works in Practice

Systems monitor sources, compare new signals to prior records, and surface structured “diffs” (what changed + timestamp + source). High-quality change detection ties each update to a verification status and source confidence, and supports auditing.

Decision Authority and Governance

Governance defines what qualifies as a “material change” and which changes require validation before being treated as confirmed. Without clear rules, change detection can create noise and undermine trust.

Common Misconceptions

• More detected changes always improve data quality.
• Change detection removes the need for verification.
• A refreshed record is automatically accurate.

Key Takeaways

• Change detection improves speed and focus, not certainty.
• Pair changes with last verified, verification status, and source confidence.
• Materiality rules prevent alert fatigue and noise.