About the Customer
The Jollibee Food Corporation (JFC) is a fast-growing global restaurant company that operates across 32 countries with over 9,500 stores. With a mission to deliver exceptional food and a joyful eating experience, they manage 19 different restaurant brands. The company is dedicated to staying ahead in a competitive industry by embracing innovation and improving operational efficiency across its locations worldwide.
Challenges
The Jollibee Food Corporation (JFC) faced several challenges with its outdated legacy systems, which were hindering agility and slowing down innovation. Key business challenges included:
- Lack of Self-Service Reporting: Business users lacked the ability to independently create reports and access real-time insights without relying heavily on IT teams. This resulted in delays and limited data-driven decision-making.
- Fragmented Reporting: Existing reporting was based on Rolling Base KPIs, which only offered partial and incomplete views of the business. This led to inaccurate understanding of critical metrics and decision-making delays.
- Data Gaps: There was no direct access to data from Non-Traditional Stores, creating significant gaps in business intelligence and preventing holistic analysis across all operations.
- Inflexibility of Legacy Systems: The legacy system’s rigidity and inefficiencies made it difficult to respond quickly to changing business needs, limiting the company’s ability to innovate and scale rapidly.
Solution
Blazeclan worked closely with the customer to create a cutting-edge data architecture by implementing the following solutions:
- Data Audit: A comprehensive audit of all essential baseline data to ensure accurate and complete migration to a modern system.
- Data Migration to Snowflake: The company migrated its POS and Labor data to Snowflake, enabling a more efficient, scalable, and cloud-first data infrastructure.
- Global Data Model: A unified global data model was deployed, providing standardized reporting and dashboards across all regions and business units.
- Standardized Reports & Dashboards: Blazeclan helped create enterprise-wide, standardized reports and dashboards, ensuring consistency and accessibility of data across departments.
- Transition from RAD to Snowflake: The existing reports and data integration points were rationalized and migrated from the legacy RAD platform to Snowflake, streamlining the data pipeline and reducing vendor lock-in.
- Automation & Alerts: The solution included automating incremental data migration for approximately 188 stores and added features such as email notifications for missing files and predefined quality checks, ensuring data accuracy and timely updates.
- End-to-End Documentation: Comprehensive documentation of the entire system, processes, and integrations was provided, enabling smoother operations and future scalability.
Results
The new data architecture delivered the following key outcomes:
- Reduced Vendor Lock-in: A 10% reduction in vendor lock-in by transitioning from RAD to Snowflake, enhancing flexibility.
- Improved Data Pipeline Efficiency: A 10% reduction in SLA for data pipelines, speeding up information flow and decision-making.
- Empowered Business Users: Real-time self-service dashboards and standardized reports enabled faster, data-driven decisions.
- Enhanced Visibility: Consistent, reliable data improved insights, strategic planning, and operational visibility.
Conclusion
By embracing cloud technologies like AWS and Snowflake, Jollibee Food Corporation (JFC) successfully modernized its data management systems, reducing inefficiencies and empowering teams across the organization. This transformation enabled faster decision-making, more accurate insights, and a scalable infrastructure that supports future growth. The new system has not only improved reporting and data accessibility but has also fostered a culture of data-driven decision-making that aligns with the company’s mission of bringing joy to every meal.
The project underscores the importance of modernizing legacy systems to remain agile and competitive in today’s fast-evolving, data-driven business landscape.
Tech stack that was used:
- Snowflake
- DBT
- Matillion
- AWS S3
- Git
Use Cases: Data Warehousing, Data Engineering, Data Lake, Data Science