Evidence Decay
The rate at which information becomes stale or unreliable over time, varying by field type and entity characteristics.
Understanding decay rates determines re-verification schedules and confidence adjustments—using 2-year-old role data without decay accounting leads to targeting errors and wasted outreach.
Expanded Definition
Decay rates vary by field type: high-decay (roles: 12-18 months, contact info: 6-12 months, active mandates: 12-24 months), medium-decay (strategic focus: 24-36 months, AUM ranges: 24-36 months), low-decay (founding dates: permanent, legal structures: rarely change, historical allocations: permanent).
Entity characteristics affect decay: high-growth firms have faster role turnover; mature organizations have slower changes. Individual factors matter too: senior executives stay longer than junior staff; founders outlast hired management. Geographic and sector patterns exist: tech sector has faster role decay than traditional industries.
Signals & Evidence
Decay pattern indicators:
- High-decay fields: Current role, email/phone, active allocation targets, near-term investment readiness
- Medium-decay fields: Strategic sector focus, geographic preferences, team structure, AUM tier
- Low-decay fields: Founding date, legal jurisdiction, historical track record, wealth origin
- Acceleration signals: Rapid growth, frequent organizational changes, high turnover industries
- Deceleration signals: Mature organizations, long-tenured leadership, stable industries
Decision Framework
- Re-verification scheduling: High-decay fields every 6-12 months; medium-decay every 24 months; low-decay only on change triggers
- Confidence adjustment: Reduce confidence progressively as data ages without re-verification
- Change detection: Monitor for role changes, firm transitions, strategy shifts that accelerate decay
Common Misconceptions
"All data decays equally" → Decay rates vary 10x between high-decay (roles) and low-decay (founding dates) fields. "Recent = accurate always" → Recent data can still be wrong if source quality is poor; recency ≠ accuracy. "Decay is linear" → Often step-function (stays accurate until change event) rather than gradual deterioration.
Key Takeaways
- Decay rates vary dramatically by field type—prioritize re-verification for high-decay fields (roles, contacts, mandates)
- Age data confidence scores based on field decay rate and last verification date
- Monitor change triggers (role changes, firm transitions) that accelerate decay beyond normal patterns