Despite increasing adoption of new technologies in the legal space, the vast majority of legal teams are still not implementing analytical tools in a way that can truly make a difference to alleviating their overall e-discovery burdens and growing expenses. Many attorneys remain unsure of how to properly apply these tools or transition to new workflows, and are weary of completely abandoning their long-trusted process of linear review.
Linear review is extremely time consuming and costly, and can lead to either under-collection or over-collection during e-discovery, both of which limit the ability to extract insights from the data and conduct a matter efficiently. But it continues to be the relied upon approach for almost all e-discovery matters.
With the right approach, and knowledge of what’s available in the market, attorneys can benefit from analytic review workflows at the outset and through the duration of a matter, without paying a premium to do so. Furthermore, proper implementation of analytics tools does not require a complete 180-degree shift away from everything attorneys have grown to know in linear review. In a recent InsideCounsel article, I outlined steps e-discovery teams can take to transition toward standardized use of analytics and improve linear review efficiency and e-discovery budget predictability.
The full article covers the following steps:
Step 1: Identifying (Only) Documents of Interest
At the outset of a case, analytics tools can be applied to help identify all of the documents attorneys may be interested in at all for a matter. This step happens the first time data that is known to be relevant to the case is collected, and ideally would take place before the first meet and confer to ensure that the team has a strong understanding of the dataset from day one.
Step 2: Narrowing the Scope
Once the set of documents that have confirmed correlation with relevance have been identified, analytics can be applied to further narrow down the scope of what actually matters to the case. In this step, analytics are used to group similar documents together, and search terms and other criteria can be cross-referenced with the coding from the sample to understand their correlation with responsiveness.
Step 3: Bringing Documents into Focus
Once the documents are properly grouped and actual review begins, analytics can make a big impact on determining how the documents are read and reviewed. By looking at the documents in groups, it is easy to see them in order to determine chronology of events and find facts faster.
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