Legal teams are often asked to make major document review decisions before they fully understand what they collected. They may know the overall data volume, but not the characteristics that can materially shape the review: file types, average family size, custodian distribution, timeline activity, duplication, privilege indicators, sensitive information—and most importantly, how many documents may be responsive.
When that information is missing, critical review decisions are forced to rely on historical assumptions, standard workflows, or incomplete information. As mere substitutes for the actual characteristics of the collection, these inputs may lead to review methodologies, staffing decisions, AI and analytics strategies, and cost expectations that are not appropriately tailored to the matter.
The key: Know your review, before you review.
In this OpenText Live, our eDiscovery experts will examine how collection intelligence, AI, analytics, and expert judgment can work together to shape a smarter review strategy before substantive review begins. This will include how to:
- Use AI and advanced analytics to surface matter intelligence earlier, including key documents, themes, likely responsiveness, privilege indicators, and potential risks.
- Translate collection intelligence into review decisions, including methodology, staffing, AI suitability, privilege strategy, validation, and budgeting.
- Build a more defensible and predictable review process, with documented methodology, validation, and cost expectations.
Better review outcomes start with better information. By understanding the collection earlier, you can make more informed decisions, and build a strategy you can explain, defend, and budget with confidence.