Customer demand can change quickly, creating challenges for efficient inventory management and supply chain operations. SAF-Holland uses SAP Business Data Cloud and Databricks to better understand customer ordering behavior, turning more than 100 million SAP records into actionable insights. By accelerating analytics by 5x, the company is helping teams make more proactive supply chain decisions while building a foundation for AI-powered operations into the future.
Understanding the demand behind every order
For years, SAF-Holland relied on reporting platforms that provided visibility into business operations and helped standardize decision making processes. SAP Analytics Cloud and SAP Datasphere became important building blocks in the company's reporting landscape, delivering transparency and consistency across the organization. But the business needed more than visibility into what had happened. Teams wanted to identify emerging demand patterns and ultimately predict what would happen next.
The organization wanted to move beyond understanding what had happened and begin answering what would happen next. Teams needed more flexibility to explore data, identify patterns and support forward looking decisions. “We had a very complex data environment spanning multiple SAP environments and regional business units,” explained David Gund, Senior Manager of Global Digital Intelligence at SAF-Holland. “Accessing and preparing SAP data often took significant effort before analysis could even begin."
One challenge quickly emerged as an ideal proving ground. SAF-Holland's customers submit scheduling agreements that forecast future demand for products weeks or months in advance. While these agreements provide planning certainty on paper, customer call-offs and order changes often fluctuate significantly as delivery dates approach. Those changes can impact production planning, inventory levels, supply chain operations and customer service. SAF-Holland wanted to understand those patterns more deeply and determine whether historical behavior could help predict future demand.
Turning SAP data into proactive planning insights
SAF-Holland saw an opportunity to extend its SAP landscape with SAP Databricks rather than introduce another disconnected analytics platform. The company uses SAP Business Data Cloud and SAP Databricks together to create a unified environment where data could move seamlessly between systems. Teams can now share SAP data products directly into SAP Databricks, enrich datasets and return insights back into SAP environments where business users already work.
"One of the biggest advantages of Databricks is the seamless integration with SAP," said Gund. "We can share a data product to Databricks, use it, enhance it, and then share the data back into a common solution for the business."
SAP S/4HANA serves as the system of record for core business processes. SAP Datasphere provides a governed layer for integrating and sharing business data products, while SAP Analytics Cloud delivers reporting and operational visibility across the organization. Databricks complements these capabilities by providing a unified, governed environment to enrich, analyze and operationalize trusted enterprise data for analytics and AI, then make those insights available back within SAP environments.
Now, SAF-Holland can easily analyze more than 100 million SAP records spanning scheduling agreements, delivery data, customer information and material data. These insights help teams identify which customers are most likely to adjust orders, enabling more proactive production planning, inventory management and customer engagement. Using Databricks, the team can align customer demand signals with actual deliveries, helping uncover patterns in customer ordering behavior that had previously been difficult to identify.
Databricks also provides the analytics team with a faster way to experiment. Rather than spending significant time building and maintaining complex scripts inside traditional reporting tools, analysts can use interactive notebooks to quickly test ideas, iterate on logic and collaborate. According to Gund, implementing similar analytical workflows elsewhere would have taken at least five times longer.
Optimizing supply chain operations for the future
The combination of Databricks and SAP has demonstrated how advanced analytics can help teams make more informed decisions. Now business users can see what's possible when trusted SAP data is combined with modern analytics capabilities. New ideas are already emerging across the organization, including inventory optimization, production analytics, IT ticket analysis and demand forecasting.
For SAF-Holland, the transformation is about creating a trusted data foundation to build upon with confidence. "Opening the SAP data ecosystem to Databricks has unlocked better analysis for our internal teams and ultimately helps us deliver better outcomes for our customers,” said Gund.
As SAF-Holland continues its data transformation journey, the company sees Databricks as a strategic enabler for continued innovation. By connecting trusted SAP data with machine learning and AI, SAF-Holland is evolving from traditional reporting toward more predictive, AI-powered operations —helping teams anticipate demand, improve operational performance and transform data from a record of the past into a guide for the future.