Profit & Loss Semantic Models

Profitability is a key metric; any profits can be distributed back to shareholders (owners) either directly or indirectly. A profit and loss (P&L) statement answers high level questions - such as “what was net profit last year?” - and summarises key revenue (i.e., product revenue) and expense (i.e., Research & Development) items. Unlike static reports, a P&L semantic model contains the detail; this allows end-users to ask questions such as “what was R&D spending broken down by a particular research project, fiscal period, or legal entity?.” A semantic model also allows end-users to consume information using Copilot prompts, Power BI reports, or Pivot Tables and formulas in Excel.
In this session, we will go through:

1. Why you should build an income statement semantic model.
2. How to use an accelerator to speed up development.
3. The key questions you need to ask stakeholders.
4. The challenges in building a P&L income statement.

Bio
Chris Barber is a chartered accountant (ACMA, CGMA) and Microsoft MVP. He is the author of income statement semantic models, advises Avanade/Accenture clients on building solutions using the Microsoft BI stack, and runs [StarSchema.co.uk](http://starschema.co.uk/).

Chris's book "Income Statement Semantic Models: Building Enterprise-Grade Income Statement Models with Power BI" will be published on 28th August. You can pre-order it on https://amzn.eu/d/6uxJfu2