📊 The Math Behind Litigation Efficiency
“What gets measured gets managed” — Legal-Tech Adaptation of Drucker’s Maxim
Why Metrics Matter Now
- 73% of e-discovery budgets consumed by review (RAND Corporation)
- 2023 ACC Survey: 89% of legal ops teams prioritize cost predictability
- Emerging Challenge: AI-assisted review alters traditional benchmarks
⏳ Cost Calculation Framework
Key Formula:
<TEXT>Total Cost = (Documents ÷ Review Speed) × Hourly Rate
Variables Breakdown:
| Metric | Industry Benchmark | AI-Augmented Standard |
|---|---|---|
| Docs/Hour | 50-75 | 200-300 (with NLP) |
| Error Rate | 8-12% | <4% (ML-assisted) |
| Privilege Miss | 15% | 6% (Predictive Coding) |
🎯 Three Foundational Metrics
1. Collection-to-Review Ratio
- Target: ≤1:5 (For every 1GB collected, ≤0.2GB enters review)
- Toolkit:
- Near-dupe detection (SHA-256 + semantic analysis)
- Date-range filters with time-zone awareness
2. Reviewer Velocity Index
- Calculation: <TEXT>(Coded Docs ÷ Productive Hours) × Accuracy Score
- Red Flag: Variance >20% between team members
3. Cost-Per-Relevant-Document (CPRD)
- Optimal Range: 0.80−0.80-0.80−1.20 (Standard review) → 0.30−0.30-0.30−0.50 (TAR)
🚀 Modern Optimization Tactics
AI Implementation Roadmap
Budget Defense Checklist
✔ Demonstrate 94%+ cull rate pre-review
✔ Benchmark against Moore v. Publicis Groupe TAR protocols
✔ Document QC cycles in Work Product protection logs
📈 ROI Calculation
Sample Case (500K Docs):
| Approach | Cost | Timeline |
|---|---|---|
| Traditional Linear | $380K | 14 weeks |
| TAR 2.0 | $145K | 6 weeks |
| AI-Hybrid | $92K | 3 weeks |
Assumes $45/hr reviewer rate, 60% responsive rate
🔮 Future-Proofing Your Process
2025 Projections:
- 85% of midsize firms will adopt automated budgeting tools
- ISO 20743-2 for e-discovery metrics standardization
- Real-time budget tracking via BI dashboards
Action Items:
1️⃣ Baseline current metrics within 30 days
2️⃣ Pilot CAL/TAR on next non-critical matter
3️⃣ Negotiate alternative fee arrangements using historical data
(Methodologies align with EDRM Metrics Model v3.1)
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