AI for Multiple Matters: Reusing Work Product
What It Is
Work product reuse is the process of recalling and learning from old datasets to make document review more efficient and consistent from matter to matter.
In traditional eDiscovery, legal teams start from scratch on each new matter, regardless of how similar it is to the last one. Often this means reviewing and coding the same data again and again, as if for the first time. Not only is this redundant but, as data volumes grow, it’s becoming downright unfeasible.
Over the last decade, work product reuse emerged as a way to avoid the burden of repeated review. Until recently, the process was limited: Documents had to be identical between matters in order for teams to reuse coding.
Today, advancements in AI technology enable teams to reuse work product much more flexibly and effectively. Legal teams can unleash advanced AI to identify, reuse, and learn from the work product in millions of previously coded documents archived in old databases.
Why It’s Valuable
Even if documents are not identical among matters, past data and decisions are still a gold mine of knowledge.
This is especially true for classifications that generally stay the same from matter to matter, like junk, privilege, and sensitive information (e.g., privilege, personally identifiable information (PII), and trade secrets). Analytic tools that use advanced AI get smarter by analyzing previous attorney review decisions, metadata, language use, and other aspects and artifacts. This powers more precise assessments and recommendations when it encounters new documents.
When one of these documents comes up for review again, advanced AI uses that information to predict likelihood that it falls into one of the noted categories and can resurface its classification history along with it. Review attorneys are armed with historical and predictive data, making faster, data-driven decisions to apply document coding.
In the Real World
Using advanced AI analytics across matters enabled counsel at a global pharmaceutical company to save on document review and make strategic decisions sooner.
Inspired by the efficiency they achieved with advanced AI on a single matter, the company proceeded to use it on an additional 5 related matters. Each one proved to have thousands of documents in common with past or concurrent matters—more than 30,000 overlapping documents in some cases.
Past attorney work product was reused to reduce eyes-on review and improve consistency and accuracy:
Further insights followed, with immediate payoffs for review and case strategy. These included:
- 20K documents from one custodian were collected and processed across multiple matters, but only 10 documents ever actually made it to eyes-on review as potentially responsive documents.
- Another custodian’s documents were reviewed and produced across multiple matters and were classified as privilege 0% of the time.