Module 7

Learning from your negotiations: scorecards, calibration and responsible use of data and AI

Experience does not automatically produce expertise. Many lawyers negotiate for thirty years and are no better at estimating what a case is worth than they were in the first five, because they never check their estimates against results, and memory rewrites the past to flatter the present. Learning from negotiations needs a deliberate loop: record what you expect before you start, record what happened, compare the two without excuses and change what you do. This module describes the tools of that loop: a preparation sheet, an outcome scorecard, a measure of how much of the available zone you captured, a post-mortem that avoids hindsight and outcome bias, and a calibration check on your own probabilities. It then deals with the data itself: how to build a dataset that is useful and confidential, and how to use AI tools for preparation, drafting and practice without trusting them for facts, breaching confidentiality or letting them decide. It closes the course with a note on professional conduct. All the examples are invented, and the habits apply to any area of practice.

General education on using data in negotiation, with invented companies, people, disputes and figures. It states common practice in simplified form and does not describe any one country's law or professional rules, which differ and change; rules on candour, misrepresentation, confidentiality and settlement in particular vary. The tools organise your own estimates and cannot predict the result of any real negotiation. It is not legal advice, and it does not replace advice from a qualified lawyer on a real matter.