Challenge

With 800+ locations and 8 franchise brands, Sizzling Platter needed a way to manage facilities at scale while keeping costs in check. The team faced mounting complexity, balancing inhouse and outsourced repairs, tracking service-level agreements, and maintaining a massive fleet of equipment across multiple regions. Rising inflation only added pressure, forcing them to rethink how they managed repair and maintenance spend while supporting continuous growth.

Strategy

Sizzling Platter needed more than a work order system, they needed a smarter way to run facilities. After evaluating multiple platforms, they chose Ecotrak to centralize maintenance operations, streamline technician deployment, and track asset data across every location. The goal: shift from reactive repairs to proactive cost control, using real-time insights to improve decision-making, extend asset life, and protect margins in a challenging operating environment.

Solution

Sizzling Platter chose to switch their facilities management to Ecotrak’s Computerized Maintenance Management System (CMMS). The “seamless transition” to Ecotrak allowed the organization to tackle multiple priorities with one software solution:

• Manage service tickets daily to deploy technicians for repairs and maintenance at scale, for equipment from HVAC to ovens and grease traps.

• Support hybrid regional facilities management model, deploying in-house technicians when it is cost effective and outsourcing other repairs to local vendors.

• Minimize operational disruptions at franchise locations through preventative maintenance schedules and timely service responses.

Results

• Successful “air traffic control” of estimated tens of thousands of technician work order tickets per year, tracked against the budget set.

• Greater insight into facilities KPIs, tracking equipment, building, and maintenance cost trends over time with integration into Power BI.

• Value savings from tagging serial numbers, warranty data, and service history for all assets in every acquired or opened store.

• Better repair/replace decision making, powered by fleetwide data set and detailed analysis (with plans for leveraging new AI tools).