Ari Kaplan interviews James Bickley, managing director at Ankura Consulting and ACEDS advisory board member, about how e-discovery has changed, what litigants need to recognize about the new normal of data, best practices for advanced planning, and strategies for engaging in proactive e-discovery.
How has e-discovery changed?
The Data Estates of our customers have become increasingly more sophisticated and complex as the technology we develop has evolved to help us connect and share information and ideas seamlessly from anywhere. We are also faster, smarter, and more available than ever before, which means data is everywhere, so the sheer volume is often hard to comprehend. Technology continues to advance, and data storage, security, privacy, and document management continue to be at the forefront of our minds. Structured data has also started to take center stage in the e-discovery process because it is not just about email anymore. One can find a tremendous amount of useful information in many non-traditional data sources, which often help to prove what some may suspect after reviewing a small portion of emails. This information can be and often is more valuable than the emails themselves.
Have those changes impacted the cost of discovery?
In many instances, the costs of discovery exercises have become prohibitive, even as unit rates continue to compress across the industry. The sheer volume and the diverse nature of today’s data sources alone create considerable challenges when factoring the time, value, and costs. While volume and data sources are significant drivers to the cost discussion, it is essential to note that technological advancements also require highly skilled professionals to create and deploy solutions to address the myriad of challenges coming from the tools we develop to enhance our productivity.
What do litigants need to recognize about the new normal of data?
Sometimes it is best to walk before we run. The devices and products we use every day are designed to be plug-and-play; however, working with them on the backend can take some creativity. Software updates, versioning, and permissions, for example, can play a significant role in determining “the how” at the initial stages of collection. While companies routinely share similar products running various functions of their businesses behind the scenes, each has its own set of rules and policies based on the needs of their business. This affects how data can be identified, preserved, and managed throughout the e-discovery process. The environments may appear similar on the surface, but there will be subtle differences to consider.
What is required beyond processing emails and collecting information from random computers?
Where do I begin? Data collections and processing are just a small part of the overall endeavor. They are incredibly important, but practitioners have a great deal more to consider when evaluating e-discovery needs. For example, how will you review and eventually produce this information, especially if it is not email? Does analytics help us here? No e-discovery matter is truly the same, so it is essential that you start the process and plan from the beginning to ensure you’ve considered all of the potential items throughout the e-discovery process.
What type of advanced planning is required to engage in modern e-discovery?
Get your discovery partners involved early and often. Connect with the partners you trust, ask for their thoughts and experiences related to your situation, and talk to their colleagues and available experts. This simple process allows everyone who may potentially be involved to be aware of the particular nuances of the matter, data environments, needs, and requirements of the discovery request. Even if the case does not materialize, everyone will have benefited from the conversations. It is always free to have a conversation about a potential engagement, and the call is always welcome.
What are some best practices for being proactive in e-discovery?
Talk with your partners and collaborate with them as much as possible – outside of the active matters. Take time to understand your data estate before there is an event to be sure you know what you are going to be dealing with before you execute. Take notes from your past experiences and don’t make the same mistakes twice as they are avoidable with proper planning.
How do you avoid misrepresentation?
Ask lots of questions, engage experts, and experiment with your providers to get a sense of what they are capable of doing to add value to your process.
What type of communication is required to avoid confusion in your approach?
Early and often, period. Do not just assume that everyone is on the same page or someone “understands” their assignments without a discussion. Not everyone has the same view on how things should be done, and while the provider might have an abundance of experience, your specific request may be unique to the team.
How much certainty is there in e-discovery?
In my opinion, there is minimal certainty in e-discovery. While we know a GB is a GB, not all GBs are the same. We all have a set of what we would consider acceptable industry standards to apply for budgets at the onset of any project, but as result of the myriad of ways a company can manage, store, and secure their data, and the uniqueness of every discovery request, we are now seeing how these slight differences impact the e-discovery process and cost.
Is waiting until “later” too late?
Often, yes. However, that is, unfortunately, a real problem across the industry. In concept, the solution to an issue may seem easy, but the nuances behind creating and deploying the solution can take considerable time, testing, and planning to ensure the results are accurate. Functions across the e-discovery process are often tied to another. So, if we wait until later at the wrong point in the process, we can create significant timing and delay issues that may be hard to overcome, especially since it is difficult to make the technology go faster in the moment.
Where do analytics fit into one’s litigation support strategy?
Data analytics is a powerful tool and can be deployed in many different and useful ways to add value to your discovery strategy. Analytics help remove the ambiguity of the information during the review, and you can find and present more useful information swiftly. You can also streamline the understanding and classification of documents quickly, accurately, and in a manner that can pivot rapidly off of newly discovered information. Also, analytics can and often does help drive the strategy tied to the review and production of information.
What changes in technology are driving change?
Society continues to advance technology to enhance our lives professionally and socially while giving people the flexibility to work (and play) in environments where the information across all of their platforms are connected and can be shared with others. We have a platform for this and a platform for that, and sometimes they talk, and sometimes they don’t, but in many instances, these environments contain valuable and potentially discoverable information. So, we are forced (and welcome the challenges) as an industry to tackle the latest and greatest technology of today, and many of us are already thinking about the problems tomorrow.It goes without saying, but every single day presents new obstacles. Sometimes they are tied to something we have considered before, and others are entirely new.
Why are teams leveraging technology differently?
Not all technology providers are created equal. Some people simply have a deeper bench of professionals who have experience with a particular set of tools and or have been exposed to more advanced environments and technology development. With that exposure, those who have the resources can experiment to test and create unique approaches to solving some of our most complicated data challenges.
