With the increasing number of workplace investigations and government regulations, the use of e-discovery technologies is no longer purely a process-specific endeavor. Increased scrutiny of antitrust law, false claims and securities fraud, as well as growing public and investor concerns about personal data breaches have increased the number of investigations that companies face on an ongoing basis.
While e-discovery workflows, both TAR and linear, focus on systematically classifying documents based on discovery requirements for process production, the investigations focus on story development in a more open context, which is typically the search for key documents requires. Therefore, the principles and criteria for conducting investigations are different from those for conducting a responsive review.
For example, rather than using quantitative metrics like precision and recall to track progress and success in finding responsive documents, investigations are largely guided by qualitative assessments of what is continually revealed. Do discovered documents lead to more information about the story? In addition, planning and budgeting often play a completely different role in production reviews than in investigations. While reviews for production typically benefit from a longer schedule and formal planning process, investigations that need to be identified important documents often need to be budgeted and resourced reactively and iteratively because you don’t know exactly which one It takes time to start exploring.
In practice, this means that investigations require agile e-discovery staff and an adaptable e-discovery infrastructure that can be rapidly scaled up or down as the requirements of an investigation change. In addition to agility, specific e-discovery data and technical complexities must also be taken into account when conducting investigations.
Investigations require more than production reviews to be retrieved from a variety of sources beyond email, documents, spreadsheets and presentations, including cellphone data, online chats, audio / video files and content from encrypted devices and files. From a processing standpoint, it is important to have the right technology in place to quickly and comprehensively address these different types of data.
Depending on the industry and the types of data involved in an investigation, various new data protection regulations may be complied with, such as: B. the EU General Data Protection Regulation (GDPR), California’s Consumer Protection Act (CCPA), and the Biometric Data Protection Act (BIPA) is key. Technically, an important aspect of this is the ability to accurately identify personal information (e.g. name, contact information, social security number) and dispose of it appropriately based on the data compliance regime you are subject to.
Linear verification is seldom an ideal option for investigations where the need to quickly locate key facts in large unstructured data sets requires an aggressive approach to isolating and prioritizing the document sets that are most likely to contain useful information. Using clustering techniques early on can help you identify the state of the country, and document classification tools can also be used early to identify structured reports such as logs and quarterly business reports. Especially with email data, threading and thread viewers can help you understand email communication faster and more efficiently.
In general, legal teams are best placed when they can focus on the content of the issues under study – they know who, what, when, where and why. This requires a data infrastructure and tools for quick access to the various files for review, and reliable technology and staff to systematically review and analyze those files. Whether these resources are provided in-house or sourced through a managed service model, once the legal teams are in place and ready, they can gain a full understanding of the issues involved and the risk involved in the investigation.