Business Intelligence & Financial-Operational Systems for a Multi-Location Hospitality Business
A connected set of financial, operational, and analytical models built to bring structure and clarity to a growing hospitality operation spanning restaurant, catering, and event service lines.
Financial Planning & Cost Control
Models built to give leadership a forward-looking, assumption-driven view of financial performance — turning "should we do this?" and "where is margin leaking?" into structured, testable questions.
Lunch & Delivery Initiative — 18-Month Financial Projection Model
In active use · Month 1 of 18Projected monthly revenue — 18-month ramp
Seat occupancy growth — weekday vs. weekend
Original KPI milestone one-pager — recreated
Sanitized recreation of the actual leadership one-pagerLunch service was running at roughly 7% of weekday seating capacity and 27% on weekends — a fraction of what the space could support. Leadership needed a structured, assumption-driven way to evaluate whether the daypart could be revived, and what a credible path back would actually require.
Built a capacity-driven projection model — Available Seats × Occupancy % × Average Spend per Order — rather than a top-down revenue guess. Occupancy climbs in a straight line from today's actuals to leadership's target over 18 months, so the plan shows a month-by-month ramp instead of a single end-state number.
- Seat inventory reconciled by zone (indoor and outdoor separately), since outdoor seating closes for winter and temporarily cuts total capacity by roughly a third
- Starting occupancy calculated directly from a full year of point-of-sale data, split by day of week — not estimated
- Average spend per order pulled per day of week from a year of transaction history, rather than one blended average, since weekday and weekend guests spend differently
- Delivery modeled as a percentage of walk-in revenue, net of platform commission, flagged as a placeholder assumption pending the delivery platform going live
- Cost structure (food, labor, overhead) applied as a percentage of revenue to roll the model up into a monthly profit projection
A linked spreadsheet model (capacity assumptions → monthly projection → quarterly summary), a one-page methodology brief explaining the formula and every input in plain language, and a milestone summary used directly in leadership review meetings.
Model went into active tracking at the start of the initiative. Early weekly checkpoints (Weeks 4, 8, and 12) are being compared against the projection to catch drift early, rather than waiting for a full-quarter review.
Cost of Goods Sold (COGS) Model
In active useWith three distinct revenue lines — restaurant, catering, and events — each carrying different recipe costs and vendor pricing, leadership lacked a clear, consistent view of true food and beverage cost as a percentage of revenue by line and by location.
Built a model to calculate theoretical COGS from recipe-level ingredient costs, compare it against actual purchasing and usage data, and surface variance so cost leakage could be caught early rather than discovered at month-end close.
- Recipe-level ingredient costing rolled up to a theoretical COGS % per revenue line
- Actual vendor invoice costs compared against theoretical to flag variance
- Breakout by location and by revenue stream (restaurant / catering / events) rather than one blended number
A spreadsheet-based COGS tracking model with a monthly variance report used in operational reviews.
Gave leadership visibility into COGS variance by location and revenue line for the first time, surfacing where actual cost was drifting from recipe-based expectations.
Purchasing Cost-Saving System
In active usePurchasing decisions across multiple locations and vendors weren't being systematically compared, making it difficult to know whether the business was consistently getting the best available pricing and terms.
Built a system to standardize how purchasing costs are compared across vendors and locations, surfacing savings opportunities and inconsistent pricing on the same items.
- Vendor price comparison across shared/common items purchased at multiple locations
- Flags locations paying above the best available negotiated price for the same item
- Consolidation recommendations where volume could be combined across locations for better terms
A spreadsheet-based comparison model with a recurring savings-opportunity report.
Identified specific vendor and item-level pricing inconsistencies across locations, informing renegotiation and consolidation decisions.
Inventory & Pricing Intelligence
Models built to keep pace with a business where input costs and stock levels shift constantly across multiple locations and revenue streams.
Inventory Analytics
In active useInventory levels across multiple locations weren't consistently visible, making it hard to tell overstock, waste, and stockout risk apart from normal operating variation.
Built an analytical view of inventory usage and par levels by location, so patterns in waste and shortage could be caught and addressed rather than treated as one-off incidents.
- Usage trend tracking by item and location against set par levels
- Waste and shrinkage flagged where usage doesn't reconcile with sales-driven demand
- Location-level comparison to separate one-off issues from systemic ones
A spreadsheet-based inventory tracking and analysis model with a recurring waste/variance summary.
Improved visibility into where waste and overstock were concentrated by location, supporting adjustments to ordering and par levels.
Price Tracking System
In active useVendor pricing on key food and beverage inputs shifted frequently and wasn't consistently tracked, creating a risk that menu pricing would fall out of step with actual cost and quietly erode margin.
Built a system to track vendor price movement over time on key inputs and flag when changes were significant enough to warrant a menu pricing review.
- Ongoing tracking of vendor price changes on core ingredients over time
- Threshold-based alerts when a price move is large enough to affect margin materially
- Direct link from price movement to affected menu items, to make pricing review decisions faster
A spreadsheet-based price tracking model feeding a recurring vendor price movement report.
Gave leadership earlier visibility into cost pressure on key menu items, supporting more timely pricing decisions.
Workforce Optimization
A model built to align labor with actual demand across dayparts, locations, and service lines — the largest controllable cost in a hospitality operation.
Staff Scheduling Model
In active useLabor scheduling across dayparts and locations wasn't closely tied to actual demand patterns, creating a mix of overstaffing during slow periods and understaffing during peak periods.
Built a demand-based scheduling model that ties staffing levels to sales and traffic forecasts by daypart, rather than scheduling off a fixed, historical template.
- Historical sales and traffic patterns by daypart and day-of-week as the demand baseline
- Labor hours recommended per shift based on projected demand, not a static template
- Labor cost as a percentage of projected sales tracked against target by location
A spreadsheet-based scheduling and labor-cost model used to guide weekly schedule building.
Improved alignment between scheduled labor hours and actual demand, supporting better labor cost management across dayparts.