Data-Driven Decision Making for Lawyers: Using Analytics to Drive Legal Strategy

This module introduces the concept of data-driven decision-making (DDDM) in the legal field. It explores why data is essential for modern legal practice, how it enhances strategic decision-making, and the key challenges lawyers face in adopting a data-driven approach. The module also provides real-world examples and practical steps to begin using data effectively.

In this module, we explore the different types of legal data, where to source them, and how they can be used effectively in legal decision-making. You will learn how to distinguish between structured and unstructured legal data, access key data sources, and evaluate their reliability.

This module explores how law firms and legal departments can leverage business intelligence (BI) and key performance indicators (KPIs) to drive efficiency, profitability, and strategic decision-making. It covers essential legal KPIs, how to track them, and the role of BI tools in optimizing legal operations.

Description: Discover how artificial intelligence (AI) and machine learning (ML) are revolutionizing the legal sector. This module covers applications such as predictive analytics, case outcome prediction, and document review automation. Key Takeaways: The impact of AI and ML on legal analytics. Use cases such as case outcome prediction and contract analysis. Challenges and ethical considerations of using AI in law.

This module focuses on the crucial role of data visualisation and reporting in legal analytics. It covers the fundamentals of transforming raw legal data into clear, actionable visual insights. Participants will learn best practices for designing dashboards and reports that communicate key legal metrics effectively to stakeholders.

Description: This module focuses on the ethical and legal considerations of using data in the legal profession, including data security, privacy concerns, and compliance with regulations such as GDPR. Key Takeaways: Ethical considerations in handling legal data. Best practices for data security and privacy. Understanding data-related regulations and compliance requirements.