In eDiscovery, reviewing legal documents is a time-intensive and expensive proposition that requires attention to detail and diligence that must be sustained throughout the review process. But reviewers are not infallible and end up making mistakes. As this article points out, “A massive Wells Fargo customer data breach was not the work of a hacker, but of the bank's own lawyer who failed to review the bank's entire set of discovery documents, including information about the bank's wealthy customers, before it was shipped to a litigation adversary.”, eDiscovery tools that are not well understood and reviews that don’t follow proper procedures can lead to both financial and reputational impact to institutions.
To ensure these kinds of mistakes do not happen during a review, an eDiscovery administrator needs to ensure the following are in place.
Choosing the correct eDiscovery tool is very important. For review, the tool should be easy-to-understand by the end user and let the user quickly select the correct coding decision. As the product manager of the Veritas eDiscovery Platform, I have consistently been told by so many of our users that the training required for new reviewers is less than an hour because the tool is very intuitive.
The mistake that the lawyer in Wells Fargo case did was this - "What I did not realize was that there were documents that I had not reviewed. I thus inadvertently provided documents that had not been reviewed by me for confidentiality and privilege." Bottom line was that she didn’t have full context on an item and how many items she had to review. eDiscovery Platform puts not just the metadata and content in front of the user but also lets the user know if there are any attachments related to the item and where a particular message stands in relation to the broader discussion thread that it might be part of. This helps a reviewer make an informed and quick decision on the relevancy of an item.
Being able to focus only on the relevant item rather than going through each item in the family helps save time and cost. Coding decisions should be restricted to just the relevant item and upon export, the non-relevant items in the family should be slip-sheeted.
Pro Tip for the Veritas eDiscovery Platform: A reviewer can choose to automatically navigate to the next document after selecting the correct tag. This can be changed by each user through the tagging options:
2. Relevant Data
Right at the start of a matter, attorneys from both sides should agree on the search terms that are relevant. Not adhering to this increases costs to both collect and review the data. Once relevant data is collected, processed and searched, the administrator should use filters to take out the junk. For example, items from wsj.com and other non-relevant domains might have no significance for that case and should be excluded. The ability to see the same data through the lens of the different types of filters allows the administrator to make the right decisions and helps make the searched data more relevant for the end reviewers.
For a review to be successful, all the reviewers should be on the same page on the basic criteria of the facts of the case. The administrator should ensure the following:
Picking the right type of reviewer leads to a successful and effective review. For most matters, a subject matter expertise is required. Moreover, the speed of reviewer decisions will impact the overall cost of the review so picking the right type of review will lead to both cost savings and better quality.
Engage in Early Review Assessment. Instead of waiting for 500 or 1000 documents to be reviewed and then checking for quality, you should start your quality checks much earlier in the process. Specifically, have a Subject Matter Expert (SME) review batches of 100-200 documents for errors in coding decisions and give feedback to the reviewers early on so mistakes or misunderstandings can be fixed and valuable time is not lost re-reviewing large sets of documents.
Human reviewers play an integral role in the eDiscovery process but administrators should think about reducing the amount of data that these reviewers have to see. Predictive coding has been accepted by courts as legally binding and should be a tool that eDiscovery administrators should employ predictive coding to reduce the amount of non-relevant data that is seen by human reviewers. This helps to save not only the legal cost of review but more importantly, time. Some of eDiscovery platform's customers have used predictive coding to check the quality of their reviewers and to show internal stakeholders the utility of utilizing machine learning in legal
There are a lot of steps required to have an effective review but implementing these best practices internally or ensuring the vendor that you are working with has done so can save a company a lot of money in the long run.
What do you think of the above suggestions? Leave your thoughts in the comments.
You must be a registered user to add a comment. If you've already registered, sign in. Otherwise, register and sign in.