Data Reduction

Using Analytics for Pre-Review Data Reduction

According to RAND, Review typically accounts for about 73 percent of all eDiscovery production costs.

Technology has changed the way we work and live in virtually every other aspect of our lives.  So how can technology help reduce discovery production costs?

Quantum’s initial array of technologies work alongside Office 365 and other mail archiving environments, bringing fast indexing, complex iterative search capability and reporting to bear upon the reduction effort.   We are also able to (very inexpensively) pass reduced copies of original data along to the review stage of the eDiscovery process (see blog post: How Early Analytics Enable You to Count the Cost).

But even after applying traditional metadata filters and key search terms in an iterative fashion (which in our experience reduces the data by an average of 93-94%), a substantial number of non-relevant documents always seems to remain.

Pre-Review Data Reduction

The warning here is that once documents have been put into a review platform, eDiscovery costs immediately escalate.  Here are some of  the fees that kick in right away:

 – Review vendor hosting fees

 – Attorney review fees

 – Premium data storage fees

Purveyors of rigid, assembly line-style approaches to eDiscovery (that do not apply the necessary technical expertise need to defensibly reduce the data further before putting the documents into a review platform) will eventually find themselves at a competitive disadvantage at the corporate level, because corporations typically operate on fixed budgets and are more likely to form relationships with vendors who can help them solve the costly problem of sending tens of thousands of non-relevant documents out for attorney review.  Defensible and objective culling out of non-relevant documents before moving them to a review platform further smooths out the spikes in discovery costs for budget-driven corporations.

The technical challenge is applying objective, defensible methods so that the remaining non-relevant documents are significantly reduced before the documents are put into a review platform.

While there is no “silver bullet” technology that can achieve this in each and every case, we select from an array of technologies that can perform the following objective tasks quickly – before  the documents are put into a review platform (in conjunction with guidance from Counsel, of course):

 – Identify non-relevant clusters of documents

 – Identify non-relevant date and non-relevant time periods

 – Identify non-relevant senders

 – Identify non-relevant domains

 – Identify e-mail with visually-similar attachments

 – Identify e-mail that are To and/or From specific custodians

Founder & Principal Consultant
Quantum E-Discovery

Jeff believes in saving time and money in e-discovery by applying a variety of analytics tools early in a case, well before moving content to expensive final review platforms. Over the past 20+ years he has accumulated a variety of tools that can be applied as needed in specific situations. [READ FULL BIO]