E-Discovery & Data Analytics: A Q&A With Stephanie Giammarco, Forensic Technology Services Practice Leader at BDO Consulting and a Member of BDO’s Board Of Directors
Why data analytics and visualization in e-discovery?
Applying data analytics and visualization across the Electronic Discovery Reference Model (EDRM) enables companies to identify and focus on the relevant data throughout the life of a case, instead of just at the review phase. E-discovery is not immune to “Big Data.” Applying data analytics upstream and downstream in the EDRM is the evolutionary shift needed to potentially reduce the amount of data moving through the process and thus reduce the overall cost of e-discovery, while increasing the overall efficiency and effectiveness of the process.
Taking this holistic approach helps manage the increasing volume and variety of data in the context of e-discovery. It enables us to defensibly identify, collect, process, review and produce relevant, electronically stored information (ESI) in a timely fashion during a litigation or investigation.
How to be smart about data analytics and visualization?
The old adage that time is money is true, and in the legal community, this reality requires counsel to resolve cases faster and more efficiently. While the concept of slowing down by applying data analytics and visualization across the EDRM, including pre-collection and pre-processing, may seem to stand in contrast to that objective, it can result in significant efficiencies in the subsequent phases of e-discovery because the processing and review is ultimately much more targeted.
While there are many points at which you can apply data analytics across the EDRM, pre-collection and pre-processing are critical to having a positive impact on cost. Pre-collection is where the initial framing and culling occurs to determine what ESI needs to be collected, and pre-processing is where prioritization and strategy analytics are used to determine what ESI needs to be processed. On the other end of the spectrum, we can apply data analytics to adversary productions to prioritize the information in a way that reduces the amount of documents for review.
Can we talk ROI?
We had a case with 2.7 terabytes of data. To put all of that data—much of which may not have been relevant—through the e-discovery process would have been prohibitively expensive; however, we applied pre-collection analytics, meaning we analyzed the data in place prior to collection, and determined that two-thirds of it was unnecessary to collect. This resulted in significant cost savings for the client.
The other critical point to mention is that data analytics and visualization is an interactive and real-time process that leverages solutions to help you see, in real-time, the impact of different filters on your data—it's not reliant on vestiges of the past like the slow process of sending back and forth emails or sorting through cumbersome excel documents.
Additionally, data analytics and visualization can help shape an e-discovery strategy early in the case by forcing you to create a risk profile based on the timeframe and the relevant custodians, among other factors, to determine what information should ultimately be collected, processed, reviewed and produced.
Stephanie Giammarco leads the firm’s Forensic Technology Services practice and is a member of BDO’s Board of Directors with 20 years of experience in accounting, information technology and criminology. She has worked with organizations and their counsel on many financial frauds, garnering significant media attention, and has led teams to develop data-driven solutions to achieve litigation or investigative objectives. She can be reached at email@example.com.