Mastering Enterprise Data at Global Scale

One of the Nation's Largest Quick-Service Restaurant Chains

Context. One of the nation's largest quick-service restaurant chains operated at a scale where small inconsistencies become costly problems — a vast workforce, a wide footprint of locations, and a constantly changing menu, spread across international systems that had grown up semi-independently. Each region had its own way of representing the same essential things: who works where, what a location is, what a menu item costs and contains. The business needed those representations reconciled into one trusted, centralized master — and it needed that master to do real work, including feeding the back end of a then-new customer-facing mobile app. This was not a greenfield build but an exercise in imposing order on a sprawling, living enterprise without slowing it down.

The Stakes. At this scale, master data is not a back-office concern — it is operational physics. A single inconsistency in how an employee, a location, or a menu item is represented multiplies across the entire enterprise, distorting payroll, reporting, and operations at once — and with a customer-facing app drawing on the same data, an inconsistency no longer stays internal: it reaches the guest. Centralized, trustworthy master data is what lets an organization this size act as one company rather than a scattered set of outlets each improvising on its own.

The Challenge. Centralize and master enterprise data — employees, locations, and menu — across the full enterprise footprint, synchronize it across international systems in a rapidly changing environment, and make it trustworthy enough to power both internal operations and a customer-facing app — all with the data quality and reliability that scale demands.

Our Approach.

• Built the master on a governed platform. Led the master-data management initiative on an enterprise MDM platform, centralizing employee, location, and comprehensive menu data into a single authoritative source.
• Connected the international systems. Built custom integration connectors — supporting multiple authentication methods — to synchronize the master across the organization's international systems, so one master could feed many regional environments.
• Built quality in by design. Incorporated a standardized data-quality methodology that generated validation rules automatically from a governed rule set, and developed complex parsing for multi-format source files — because at this scale, quality has to be structural, not manual.
• Made delivery repeatable and resilient. Engineered incremental, multi-file import and export that isolated bad records instead of failing wholesale, strengthened error handling and logging, and established deployment templates and standards — down to the environment setup, configuration, and database migrations behind them.

The Outcome. A centralized master-data backbone serving the enterprise at global scale — synchronized across international systems, quality-enforced by design, and dependable enough to stand behind both back-office operations and the information customers pulled up in the app. Repeatable, resilient delivery kept it that way as the business changed.

From the master to the customer's pocket. One authoritative master fed every regional and international system and kept them synchronized as the business changed. Dozens of automatically generated data-quality rules cut the duplicate-and-error rate to under 1% and markedly improved record-matching accuracy. Standardized, itemized values were mastered across the full menu and its ingredients worldwide — the same trusted data operations and the app both drew on. Deployment templates and automated deployment testing cut migration errors to functionally zero.

What It Demonstrates. The ability to lead master data management at a scale where most approaches break — and to make data quality and resilience structural properties of the system, on a foundation trusted enough to reach the customer's phone.

Capabilities. Large-scale master-data management · enterprise data centralization · custom integration connectors · international data synchronization · data-quality automation · resilient ETL · deployment standardization.