Enabling real-time distribution of 700K+ spare parts worldwide
Volvo enables real-time visibility into spare parts inventory with Databricks Delta Live Tables
Efficiency gains after Databricks Delta Live Tables deployment
Reduction in pipeline latency
The Volvo Group Service Market Logistics (SML) team manages and distributes a massive spare parts inventory for Volvo Group worldwide across the entire chain, from supplier to truck dealer. With roughly 200,000 new Volvo trucks sold yearly (and millions more on the road) and hundreds of thousands of spare parts spread across warehouses globally, keeping track of every spare part — and ensuring each one arrives on time at the dealership that needs it — is daunting. Following the implementation of the Databricks Data Intelligence Platform and Delta Live Tables (DLT), the team has visibility into how and where to stock their inventory for immediate needs and predictive scenarios.
Siloed data systems put the entire supply chain at risk
When trucks break down, deliveries get delayed, supply chains slip and consumers and manufacturers feel the pinch. “Our main target is to have spare parts available close to our customers,” said Ingmar Rogiers, Digital Product Manager at Volvo SML. “That’s what SML is doing to secure good service for our customers.”
Knowing what spare parts are where and even predicting what should be where is critical to the flow of the entire Volvo SML system. But hitting that target wasn’t always easy. Before their Databricks implementation, Volvo’s data stack was usable but had room for improvement. Years of mergers and acquisitions created a scattered application landscape containing several legacy systems. Instead of being managed from a centralized hub, inventory planning occurred individually, warehouse to warehouse, with limited visibility into what resources could be shared.
“We had a great opportunity to improve the integrated planning and coordination,” explained Rogiers.
The Volvo SML team needed a central platform to gather and integrate all their data sources. They knew that if they could steer their operations from that platform, monumental gains were just around the corner.
Improving systems to near real-time data ingestion and automation
During the discovery phase of Volvo SML’s cloud journey, they experimented with other solutions, including Azure Data Factory (ADF). However, they quickly realized that the Databricks solution was the only way forward for their unique needs.
The first step in the transformation was to adopt the Databricks Data Intelligence Platform. This critical first move brought Volvo’s previously separate spare parts data sources together under a single, unified platform.
From there, the team deployed Databricks DLT and Databricks Workflows to ingest and process Volvo’s huge amounts of data in near real-time, a new capability for the organization. It was a game changer and the primary reason for adopting DLT and Workflows.
“That’s where it all started, because a planning and supply-chain business is very fast moving,” said Rogiers. “Your data is quickly outdated. So the expectation is that every minute counts.”
What once was triggered in minutes could now be triggered in mere seconds. “With just a simple click, we can effortlessly transition our metadata scheduling from triggered to continuous and back again, all without the need to dive into complex code, which saves us a considerable amount of time,“ recounted Bruno Magri, Senior Data Engineer at Volvo SML.
Armed with these new capabilities, the team then rolled out the DLT automated operation features to bolster processes and improve efficiency around routine tasks, including automatic checkpointing, background maintenance, table optimizations, infrastructure autoscaling and more.
“Now we don’t need to worry because of the optimizations and maintenance jobs that run in the background,” offered Bruno. “If you need to refresh the table you can do it with a few clicks. Whether it’s data type chains or schema chains, Databricks DLT can handle those things almost automatically. It’s a nice feature.”
For data orchestration, the team switched from ADF to Databricks Workflows. “Workflows has been a great orchestrator for us,” continued Bruno. “We can query all the data using database APIs and build a monitoring report to see if a job is failing, how much time it’s taking on average and if it’s taking more than the average for that job.”
Benefits beyond inventory visibility
Since the DLT deployment, Volvo has realized new capabilities and efficiencies, from global reporting and end-to-end order tracking to real-time inventory processing. The Volvo SML team now has unprecedented access to automated operations, autoscaling and the unifying benefits of the Databricks Data Intelligence Platform built on lakehouse architecture.
“Today, we get an integrated view of where spare parts are, the value of spare parts across warehouses and the potential costs involved in shipping parts from warehouse to warehouse or dealers,” touted Rogiers.
Real-time data ingestion and processing also helps Volvo SML plan for expansion. “We have a task in our organization that we call ‘footprint design,’ where we identify where our next warehouse should be located or which warehouse should be responsible for which particular markets and brands,” added Rogiers.
With up to 40% efficiency gains across many routine database tasks, the Volvo SML team can now look to the future with confidence, knowing Databricks DLT and Workflows are helping make a major difference across the organization.
