eDiscovery and Data Analytics

We bring value to our clients in the following ways:

• eDiscovery Advice: At the intersection of law and technology, it can be hard to keep up. What’s more, the decisions that companies make today could have unexpected consequences down the road. Clients across all industries seek the advice of our lawyers in navigating the dynamic challenges of the eDiscovery space. We help companies identify unforeseen risks and ensure that their actions are defensible in the future.
• Discovery Counsel: eDiscovery continues to emerge not only as a body of law but also as an area of practice requiring specialized skills. In bet-the-company litigation, clients are increasingly retaining dedicated discovery counsel. Sidley is recognized as one of the world’s elite law firms at handling large-scale discovery.
• Litigation Readiness: Thinking about eDiscovery needs ahead of time reduces the number of fire drills and significantly reduces costs. We help clients evaluate their eDiscovery needs across their entire litigation portfolio, rather than focusing on a single case. We work with clients to identify areas where they can improve and then help them implement a step-by-step playbook tailored to their unique systems and data.
• Data Analytics: In almost every matter, relevant data is held in structured data sources such as web applications, data warehouses, CSV files, and enterprise systems. Traditional eDiscovery tools built primarily for email fall far short. But when properly extracted, scrubbed, analyzed, and visualized, structured data can be the key to the case. We work with clients to identify these data sources at the outset. We then analyze the data intensively and shape the results into compelling, data-driven legal arguments.
• Defensible Disposition: In the event of litigation, companies may find themselves spending vast sums to sort through massive accumulations of irrelevant data — so-called “digital debris.” Our lawyers help clients implement data disposition in a structured, defensible, cost-effective, and documented manner that can withstand later scrutiny, if necessary.
• Machine Learning: In recent years, machine learning algorithms — sometimes called technology assisted review (TAR) or predictive coding — have fundamentally altered the approach to large-scale document reviews. We understand machine learning at its core and, as a result, are not reliant on a single tool, algorithm, or approach. Companies cannot simply “press the button” on the latest technology and expect satisfactory results. That is why we work with clients to develop a custom approach designed to meet their data and goals.
• Pathogenic Data: Being able to quickly quarantine and eliminate unwanted data resulting from information leaks and premature disclosures can prevent small problems from becoming big ones. We repurpose many of the traditional tools of eDiscovery and data analytics to help clients make informed decisions in a defensible manner.