A global hotel management company operating more than 200 properties across Europe and the Middle East ran its operations in fragments. Property management systems, food and beverage platforms, maintenance and work order tools, and finance systems had all been acquired or built independently over time. They did not share data.
Regional directors made decisions without cross-portfolio context. When a property underperformed, there was no benchmark to compare it against. Maintenance teams operated reactively, responding to failures rather than anticipating them. Corporate forecasting was done in spreadsheets, assembled manually by the finance team each week. The executive reporting pack took seven days to compile and was out of date by the time it landed.
BASAWE designed and built an Azure Synapse-based operations intelligence platform, connecting all six source systems through a unified data pipeline layer. Python-based ETL processes handled schema normalization across systems with incompatible data models, a common challenge in hospitality technology stacks built through acquisition.
A unified property performance model was built at the core, enabling regional directors and corporate leadership to benchmark any property against cohorts, regions, or the full portfolio. KPIs including occupancy, RevPAR, F&B margin, and maintenance cost per room were standardized and made available in real time.
For maintenance specifically, BASAWE built predictive models using 18 months of historical work order data combined with equipment age and utilization signals. The models identified equipment approaching failure before breakdowns occurred, allowing the facilities team to shift from reactive repairs to planned maintenance. A real-time executive dashboard replaced the weekly PDF pack entirely.