Prepared For
Marco Ricci
A diagnostic of current AI & automation readiness across six operating pillars — with a prioritised 90-day plan, tool stack, and projected ROI tailored to your business.
+2 points above the Hospitality SMB median of 46. You're tracking ahead of peers, with measurable upside in Data and Process.
The Anchor is running the operating model of a venue that is growing faster than its back-of-house systems. Square is the till, OpenTable is the reservation book, and a rostering spreadsheet ties the two together once a week — by hand. There is no customer database, no link between a Friday-night booking and the bill it generates, and no view of which dishes drove the night. The data exists; the venue is just not yet harvesting it.
The single biggest lift here is in Data Readiness and Process Maturity. Stock counting, supplier ordering, and rostering all still happen on paper or in a single shared spreadsheet, and two of those three are touched by the owner directly. AI Use-Case Fit is genuinely strong — demand forecasting for rostering and automated review responses are well-trodden moves in the Australian hospitality market — but the foundation needs a layer of automation first.
The 90-day plan connects Square and OpenTable via Zapier (week one), introduces an AI rostering tool that learns from the booking data (weeks two to six), and finishes with automated Google review responses that protect the 4.3-star rating. Combined that is around $28k–$54k of recovered revenue and reclaimed manager hours per year, against a tooling bill well under $400/month.
Transactional data is captured cleanly in Square, but no one has ever exported, joined or analysed it. There is no customer database, no menu-mix view, and no linkage from a booking to its bill. The raw material is excellent; the harvesting tools are absent.
Needs work — data silos are the bottleneckRostering lives in a spreadsheet, stock count is on a clipboard at end-of-week, and supplier orders are still placed by phone. Front-of-house service runs well — the gap is back-of-house process discipline, which is where the owner's time is currently going.
Needs work — manual effort is the constraintSquare POS and OpenTable are both modern, capable, and well-supported in the Australian market. The problem is that they are not connected to each other or to Xero. Even a light Zapier footprint would do most of the integration work without a replatform.
Needs work — stack gaps blocking AIThe owner-operator is moderately tech-confident and the two floor managers can both operate Square and OpenTable comfortably. Seasonal casual staff are the wildcard — any new tool needs a 10-minute onboarding story for someone who will only work eight shifts.
Solid foundation — training will unlock fastThree strong candidates map directly onto current pain: demand forecasting for rostering, automated Google review response, and menu engineering from POS data. All three are peer-validated in the Australian hospitality market with clear ROI signals.
Solid foundation — scope and prioritiseNo password manager, POS PIN shared across all floor staff, and no backup of reservation data outside OpenTable itself. None of this is expensive to fix; all of it must be in place before customer-facing automation is deployed.
Needs work — address before scaling