Commercial intelligence and demand forecasting

- Commercial decisions on rate, inventory and channel depend on reading daily reservation data against history, against budget and against the forward book. Today that data sits across several disconnected systems and spreadsheets, and turning it into a usable daily picture is slow and manual. - A commercial analyst can spend a large part of each morning assembling the report before any decision is taken, and across three properties this repeats every day. - The result is that insight arrives late, forecasting stays intuition-led and inconsistent between properties, and shifts in booking pace and cancellations in the forward book are often seen only once the moment to act has passed. - The Anam needs an AI system that ingests the daily data, forecasts demand by date and by segment, and returns a clear performance read with recommended commercial actions, so the team decides rather than compiles.

- Produce the daily commercial read in minutes rather than a morning of manual work. - Create a consistent forward demand forecast across three properties. - Catch booking pace shifts and cancellation spikes while there is still time to act.

At present the work is done in Excel only, drawing data manually from the property and reservation systems into spreadsheets, with no dedicated forecasting or commercial intelligence tool in place. The analysis depends on the analyst's own structure and judgement, which makes it slow to produce and inconsistent across the three properties. The group has not deployed a purpose-built solution for this before, which is why it is brought as a use case.

- At present the work is done in Excel only, drawing data manually from the property and reservation systems into spreadsheets, with no dedicated forecasting or commercial intelligence tool in place. - The analysis depends on the analyst's own structure and judgement, which makes it slow to produce and inconsistent across the three properties. - The group has not deployed a purpose-built solution for this before, which is why it is brought as a use case.

- Commercial, revenue and reservations teams across the three properties, who would act on the forecast and recommended commercial actions daily. - Operations teams, who plan staffing and resource against expected occupancy. - General Managers and Group Commercial leadership, who read the forward picture for decisions on rate, channel and budget.