1 – Cost Savings
By automatically identifying relevant documents, eDiscovery projects utilizing this technology result in substantially lower billable hours. While a small team of more senior lawyers are still required to “train” the software on what is relevant, traditional eDiscovery techniques require a larger group of less experienced lawyers reviewing a lot more documents and costs more.
2 – Faster Document Review
Since the review process is accelerated via predictive coding, it allows decision makers to have earlier access to pertinent information which might reduce litigation costs relative to if the same issues are identified later in the process. A more recent trend is that the timeline of eDiscovery engagements are getting compressed due to the exponential rise in data usage, so the ability to quickly process large amounts of data is critical
3 – Holistic Pattern Recognition
With manual reviews, individual reviewers see their documents in relative isolation to what their fellow reviewers are discovering. Underlying
connections between separate documents may not be observable. With Predictive coding, initial review is performed through a single lens and certain patterns or consistencies may be identified that would not have been observable to an individual reviewer looking at a relatively small set of documents.
4 – Ability to respond to changes
If the criteria for responsive documents change, predictive coding can be quickly “trained” and re-applied to the document set for the new criteria rather than a manual reviewer having to begin the process anew
5 – Greater Cost Transparency
With Predictive coding, clients are able to determine the number of documents that will require further review. This could enable them to more accurately estimate the cost of engagements.