Scaling Performance Across 20+ Locations

Multi-location Fast Food Brand (Croatia)

20+ restaurants · Centralized operations · High daily transaction volume

As the restaurant network expanded beyond 20 locations, leadership faced increasing difficulty maintaining
consistent visibility across restaurants. While each location generated detailed operational
and financial data, information was spread across multiple systems and formats.

Daily and monthly reporting relied heavily on:

• frequent data exports
• spreadsheet consolidation
• manual validation by operations and finance teams

This made it challenging to:

• compare performance across locations
• align restaurant managers around shared KPIs
• identify underperformance early
• scale decision-making without increasing reporting overhead

As a result, gaining a reliable, cross-location view of performance required
time, coordination, and repetitive effort.

Key operational and financial data was distributed across several systems:

• POS system – sales, transactions, product mix
• Accounting system – financial results and cost tracking
• Hospitality management platform – operational structure and location metadata
• Spreadsheets – targets, bonuses, and internal performance inputs
• Customer feedback platforms – review scores and reputation signals

Each system was valuable individually, but no single source of truth existed for performance analysis.

1. Centralized Data Foundation

Dataspot partnered with the client as both a strategic analytics partner and technical implementer
to establish a unified data foundation.

All relevant systems were integrated into a centralized data warehouse, with standardized definitions for:

• revenue
• costs
• operational KPIs
• performance targets

This eliminated inconsistencies and enabled like-for-like comparison across all restaurant locations.

2. Scalable Reporting Model

A standardized reporting layer was built to support both operational and management-level use cases.

Key features included:

• consistent KPIs across all restaurants
• location-level and network-wide views
• role-based access to dashboards
• automated daily and monthly refresh cycles

Dashboards were delivered through an embedded BI experience within a custom web application,
allowing managers and leadership to access insights securely without relying on manual reporting.

3. Architecture & Integrations

Source systems were connected via custom .NET integrations into a centralized Microsoft SQL Server data warehouse.

Data processing and refresh were orchestrated using:

• scheduled SQL Server jobs
• stored procedures for transformation and validation

Reporting was delivered using Power BI, with dashboards embedded into a custom application
and refreshed automatically.

Role-based access control ensured that users could only see data relevant to their role and location.

The new analytics platform replaced fragmented reporting processes with a
single, trusted view of performance.

As a result:

• manual daily and monthly Excel reporting was fully eliminated
• restaurant performance could be compared consistently across locations
• management gained faster access to operational and financial insights
• accountability across locations improved through shared KPIs

Instead of spending time assembling reports, teams could focus on
improving operational outcomes.

By establishing a scalable analytics foundation, the client enabled
data-driven decision-making at network scale — without increasing operational complexity.

The project demonstrated how multi-location hospitality brands can move from manual reporting to
reliable, centralized performance management, creating the foundation for continued growth.