215 pages | 30 B/W Illus.
For increasingly data-savvy clients, lawyers can no longer give "it depends" answers rooted in anecdata. Clients insist that their lawyers justify their reasoning, and with more than a limited set of war stories. The considered judgment of an experienced lawyer is unquestionably valuable. However, on balance, clients would rather have the considered judgment of an experienced lawyer informed by the most relevant information required to answer their questions.
Data-Driven Law: Data Analytics and the New Legal Services helps legal professionals meet the challenges posed by a data-driven approach to delivering legal services. Its chapters are written by leading experts who cover such topics as:
In addition to providing clients with data-based insight, legal firms can track a matter with data from beginning to end, from the marketing spend through to the type of matter, hours spent, billed, and collected, including metrics on profitability and success. Firms can organize and collect documents after a matter and even automate them for reuse. Data on marketing related to a matter can be an amazing source of insight about which practice areas are most profitable.
Data-driven decision-making requires firms to think differently about their workflow. Most firms warehouse their files, never to be seen again after the matter closes. Running a data-driven firm requires lawyers and their teams to treat information about the work as part of the service, and to collect, standardize, and analyze matter data from cradle to grave. More than anything, using data in a law practice requires a different mindset about the value of this information. This book helps legal professionals to develop this data-driven mindset.
Introduction: Data Analytics for Law Firms: Using Data for Smarter Legal Services. Mining Legal Data: Collecting and Analyzing 21st Century Gold. Deconstructing Contracts: Analytics and Contract Standards. The Big Move Toward Big Data in Employment.Computational Law, Symbolic Discourse, and the AI Constitution. Quantifying Success: Using Data Science to Measure the Accuracy of Technology-Assisted Review in Electronic Discovery. Quantifying the Quality of Legal Services: Data Science Lessons. Uncovering Big Bias with Big Data: An Introduction to Linear Regression.