Creating a Winning Recipe for a Hyperefficient Supply Chain: A Case Study on Barilla
Technology Category
- Functional Applications - Manufacturing Execution Systems (MES)
- Functional Applications - Warehouse Management Systems (WMS)
Applicable Industries
- Consumer Goods
- Retail
Applicable Functions
- Logistics & Transportation
- Maintenance
Use Cases
- Predictive Maintenance
- Supply Chain Visibility
Services
- System Integration
- Testing & Certification
About The Customer
Barilla is the largest pasta producer in the world, with over 300 different food products made in more than 90 factories and distributed across over 100 countries. The company has a diverse ecosystem of production sites, raw material vendors, distribution centers, and thousands of retailers serving markets from Asia to Europe and into the Americas. Barilla has long been at the forefront of technology innovations in an effort to deliver the best food products to the masses. However, as their distribution expanded to support the growing demand for their products worldwide, it became clear they needed to modernize their data to allow analytics at scale.
The Challenge
Barilla, the world's largest pasta producer, faced significant challenges due to unpredictable crop yields and rising raw material costs caused by climate change. These disruptions led to product shortages and quality issues, necessitating a more sustainable and resilient supply chain strategy. However, Barilla's legacy on-premises data warehouse was unable to scale their operations effectively, creating silos that hindered their ability to navigate these external threats. The company's supply chain and logistics needed to maintain high-quality standards while maximizing revenue in a low-margin business. As Barilla's distribution expanded to meet growing global demand, it became clear that they needed to modernize their data to enable analytics at scale. With over 1TB of data ingested daily, data analysts struggled to integrate and analyze the necessary data, leading to delays and inefficiencies. Additionally, Barilla's large European footprint required processing sensitive consumer data for GDPR compliance, necessitating a robust data governance plan.
The Solution
Barilla adopted Databricks Lakehouse as their data strategy, upgrading their monolithic, mainframe-based infrastructure to Azure Databricks and Power BI for departmental reporting and dashboarding. This transition propelled Barilla's data-driven transition, with 90% of their business now running on Databricks Lakehouse. Barilla uses Databricks for their entire ML practice, delivering intelligence that guides manufacturing, improves operations, and drives their environmental sustainability efforts. With manufacturing cost deployment models, staff can extract and allocate industrial costs and quantify plant losses. They can also better predict machine failure and schedule maintenance windows proactively. To streamline supply chain management, Barilla implemented a traceability system using Databricks. By analyzing supplier performance through BI dashboards, they can assess supplier risk. Barilla's marketing teams use Databricks Lakehouse to understand customer behavior and preferences, identify new markets, and segment customers to drive more revenue opportunities.
Operational Impact
Quantitative Benefit
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