A Process of Elimination?

Initial analysis of a dataset is one of the most rewarding aspects of the Discovery process both for the lawyer or eDiscovery specialist and, if careful, ultimately for the end-client as well. It is at this stage, prior to instructing your paralegal manager or recruitment consultant on assembling a review team, where modern facets of document review software platforms really come into their own and significant cost savings can be made.

You may be able to make easy data savings. For example, are all file types to be reviewed or shall we just review parent documents and exclude family members? Of course, your data processor should already have carried out a global or custodian-specific data de-duplication and system files should have been removed. Even so, graphic files such as .jpg or .gif files remaining in the dataset are unlikely to be responsive and can be searched for and removed. With any data cull a quality control check can always be undertaken to ensure that any such files really do not contain any responsive material.

Next, basic analytical tools such as email threading could be applied across the dataset. This allows you to prioritise inclusive only emails meaning your review team will only review emails that contain new information and do not separately review each individual email within a chain. It is a simple and effective way of speeding up your review. Using visual analytical tools with your data is a great way of better understanding what your dataset contains. Whether you are using a platform such as Ringtail or Relativity, producing a report of the types of file, keyword specific documents and total data volumes can also save you time later on in the review.

Finally, if you or your client wish to make your review as efficient as possible then predictive coding, context searches and other forms of technology assisted review are highly recommended. By training your system to recognise and code patterns in the dataset, which can then be replicated across the remainder of the set (subject to a quality control check), you really are reducing the need to hire lots of expensive contract attorneys. On the investigatory side, more bespoke options such as a context search using a paragraph lifted from a document or put together manually, can yield impressive results. Your software will search for conceptually similar documents and arrange results in the most logical fashion.

So, in conclusion, it really is all a process of elimination when analysing your new dataset. Simple steps taken at the outset really can have a significant impact later on and help drive the efficiency of your review for the mutual benefit of all stakeholders.

Behind the times?

As the winds of technology change sweep through labour markets, re-shaping how we communicate, hire and do business with one another; one industry seems strangely resistant. I am of course talking about the legal market and, more specifically, litigation support.

Here in London, working in eDiscovery is often still a labour intensive job, as teams of document reviewers beaver away trawling through vast volumes of data, reporting back to several project managers, team leaders and counsel. And that is all before vendor and technical support is brought into the equation.

In our experience, Technology Assisted Review (or “TAR”) has barely scratched the surface of our industry and is certainly yet to revolutionise it in a way that many were predicting it would a few years ago. Perhaps TAR is still too complex a subject matter or too big a leap from current industry norms; or maybe it is mere inertia and a fear of the unknown. Whatever it may be, for the time being, the era of lawyers reviewing documents en masse remains with us.