Strategy Lab - Hotel group displacement analysis and minimum acceptable rate

When performance metrics, pace insights, and market benchmarks live in separate tools, revenue teams struggle to agree on the right move. In this Strategy Lab, Blake Reiter and Daniel Foreman show how working from a shared data foundation speeds up group displacement decisions — using a fictional wedding block RFP as the example: 10 rooms for 2 nights on a weekend a 60-room boutique hotel is already forecasting to sell out.

Using Lighthouse, they walk sales, revenue management, and operations through the same numbers at the same time: current pace, forecast validation, displaced revenue, and a minimum acceptable rate — then show how the same analysis runs in Ernest, Lighthouse's AI workspace, in a fraction of the time.