Data & Analytics

Your Oracle Simphony point‑of‑sale, property management, casino management, membership and accounting systems each hold a piece of the picture. Put together properly, they answer the questions a general manager, a director of F&B or a casino marketing team ask every morning. We build both halves: the analytics people look at, and the data engineering that makes the numbers trustworthy.

Our principal has run analytics and business intelligence organizations at two software companies, so we know what a reporting platform has to look like when it serves hundreds of clients, not just one property.

Analytics operators use

Dashboards and scorecards built around the way a property is actually run, not around whatever the source system happens to export.

• F&B scorecards: net sales, covers, average check and average guest by outlet, day part and server, against budget and prior period, from daily flash to board level
• Player and guest analytics: players versus non‑players, card capture, and guest recency and frequency, so marketing knows who is coming back and who is slipping away
• Comp and promotion effectiveness: which comps and offers bring incremental visits and spend, and which reward guests who were coming anyway
• Menu and pricing: item mix, contribution and velocity, the menu‑engineering view of what to promote, reprice or drop, and what the last price change actually did to covers and check average
• Where the money is leaking: outlet, day part and channel compared side by side, so the underperforming shift or the room‑service channel nobody looks at shows up on its own
• Labor and productivity: covers and sales per labor hour, scheduled against actual, by outlet and shift
• Pace, forecast and real‑time operations: month‑to‑date pace against budget, the run rate for where the month will land, and live production boards during service

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The data engineering underneath

Analytics are only as good as the data behind them. This is the part nobody sees and everybody depends on.

• Pipelines: extract from Simphony, PMS and back‑office systems on a schedule you trust, with monitoring and alerts when a feed fails
• Modeling: a warehouse or lakehouse schema built around how hospitality operators think: outlets, revenue centers, day parts, members, folios
• Reporting layer: Power BI or Tableau on top, with one set of definitions so finance, operations and marketing are looking at the same numbers
• Platform: Microsoft Azure data services (Data Factory, Databricks, SQL) sized to your volume and budget

Why it matters

Most operators already have the data. What they lack is a dependable, understood path from the systems that collect it to the people who make decisions with it. That path, documented, automated and built around your operation, is what we deliver.