This past Monday, we partnered with Databricks to host a webinar on Supply Chain Intelligence. The session highlighted the real challenges organizations are facing across manufacturing, automotive, and industrial sectors, and demonstrated how the Databricks Data Intelligence Platform is changing the way supply chains operate. One of the key highlights was a live demo of our Supplier Performance Scorecard built on Databricks AI/BI.
Organizations today are facing mounting pressure: missed OTD and OTIF targets, slow planning cycles, disconnected data systems, and a heavy reliance on manual spreadsheets. At the same time, customer expectations continue to rise, external disruptions are more frequent, and supply chain risk is becoming harder to identify. During the webinar, we explored how companies can overcome these challenges by unifying data, applying AI responsibly, and empowering teams to self-serve insights through natural language.
The Live Demo: Building a Supplier Performance Scorecard
During the session, we walked step-by-step through how the Supplier Scorecard is built using the supply chain data model, which includes tables such as supplier_master, supplier_sourced, and warranty_claims. The goal of the scorecard is to create a single, trusted view of supplier performance that sourcing teams can rely on for decision making.
We highlighted four critical KPIs:
- On-Time Delivery (OTD): Measures how reliably suppliers deliver by the expected date.
- On-Time Ship (OTS): Measures whether shipments leave the supplier on schedule.
- Lead Time Adherence: Determines whether suppliers meet their promised lead times.
- Defect Rate: Identifies quality issues by measuring warranty claims against sourced volumes.
Each KPI is calculated in SQL, governed in Unity Catalog, and brought together into a single supplier_scorecard view. That view powers the Databricks AI/BI dashboard used in the live demo.
The dashboard included KPI cards, supplier ranking tables, trend visualizations, and regional or category filters. We also demonstrated how Databricks’ AI capabilities can produce narrative explanations of performance trends. During the webinar, attendees watched how AI/BI could answer questions such as:
Which suppliers are showing declining delivery performance over the last three months?
Which suppliers contribute the highest warranty claim costs?
What is causing rising lead times in specific supplier tiers?
This demonstrated how quickly teams can get answers without building reports manually or waiting on IT.
If you missed the live webinar, you can build it yourself by clicking on the link to the artifacts and using the Databricks Free Edition, just import the notebooks into the workspace to generate the data and sync the dashboard.
Why Supplier Intelligence Matters
Databricks also provided broader industry context showing why performance measurement is becoming mission critical. Many companies still suffer from disconnected systems, long report cycles, and difficult-to-govern data landscapes. Challenges such as data quality, lack of skills, and the need to modernize legacy systems continue to slow AI adoption. At the same time, companies need faster planning cycles, real-time insights, and the ability to respond quickly to logistics delays, demand shifts, geopolitical disruptions, and warranty trends.
The Supplier Scorecard fits directly into this picture, giving organizations a reliable foundation for supplier risk, quality, and delivery intelligence.
Beyond the Scorecard: Supply Chain Intelligence Use Cases
We also discussed the broader set of use cases that organizations are delivering on the Databricks Data Intelligence Platform, including:
- Inventory optimization to reduce carrying costs while maintaining service levels
• Demand forecasting using historical trends, BOM structures, and market drivers
• Delivery time prediction to improve ETA/ETD accuracy
• Supplier risk monitoring with n-tier supplier mapping
• Automated quoting and order processing through AI agents
• Sustainability and low-carbon analytics
• Quality and warranty insights for post-delivery performance
These use cases are enabled by having trusted, governed data products in Unity Catalog, scalable analytics and machine learning on Delta Lake, and conversational analytics through Databricks AI/BI.
A New Standard for Supplier Performance
The core message from the webinar was simple: organizations win when their supply chains operate intelligently. A supplier scorecard is more than a dashboard—it is the starting point for building a data-driven, AI-powered supply chain.
By unifying data, governing KPIs, and enabling AI-driven self-service, companies can achieve:
- Faster planning cycles
• Proactive supplier risk management
• Better sourcing decisions
• Real-time operational visibility
• Improved OTD and OTIF performance
• Reduced costs and reduced manual work
• A more resilient supply chain model
