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

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.