Client name withheld under a non-disclosure agreement.
The challenge
The group runs hotels and resorts across the Eastern Mediterranean. Its properties used different property management, point-of-sale and finance systems. Every Monday the finance team exported data from each one and stitched the weekly report together by hand.
Properties also defined occupancy and revenue figures in slightly different ways, so meetings started with arguments about whose numbers were right. Each property forecasted in its own spreadsheet, and head office had no group-level forecast at all.
What we delivered
- Business Intelligence Platforms. One data model across the property management, point-of-sale and finance systems, with shared definitions for occupancy, average daily rate and revenue per available room. Dashboards for the group, each property and each department, plus a weekly report that reaches management automatically on Monday morning.
- Revenue & Growth Analytics. Occupancy and revenue forecasts for each property up to 90 days ahead, refreshed daily, with variance tracking against budget and the same week last year.
Timeline
- Weeks 1 to 4: source system connections and agreement on shared metric definitions
- Weeks 5 to 9: data model, dashboards and the automated weekly report
- Weeks 10 to 12: forecasting models, testing with property managers and handover
Outcomes
- 1 to 2 days saved each week on group reporting
- All properties now report on the same metric definitions
- Head office has a rolling group forecast for the first time, accurate to within 5 to 10% for the following 30 days