How a Logistics Company Transformed Last-Mile Execution with Databricks
Industry
Logistics
Overview
The client is a leading last-mile delivery provider specializing in large format goods. They operate a complex technology landscape spanning SAP, warehouse management, transportation systems, and field operations, supporting enterprise partners such as Home Depot.
Challenge
As delivery volumes grew, Temco faced a widening gap between the data it generated and the intelligence it could act on. Systems operated in silos, creating fragmented visibility across planning, execution, and partner reporting. Decisions were delayed, KPIs were inconsistent across teams and partners, and exceptions were managed reactively rather than prevented.
Unifying fragmented data across SAP, WMS, TMS, telematics, and partner systems Eliminating conflicting KPI definitions between Temco and Home Depot Replacing manual, Excel-driven reporting with real-time, trusted insights Building predictive capability to get ahead of delivery failures before they occur
The Solution
Sigma Solve implemented a Databricks-powered data and AI platform to establish a unified, real-time intelligence layer on top of its SAP ecosystem. The architecture enabled direct access to SAP data, seamless integration with external sources, and the operationalization of advanced analytics within core workflows.
- Zero-copy SAP data access via native SAP-Databricks integration, eliminating ETL pipelines, reducing latency, and removing the root cause of data inconsistencies
- Unified data foundation blending SAP transactional data with routing schedules, telematics feeds, crew performance history, and external signals such as weather and traffic
- Bi-directional data exchange using Delta Sharing to keep SAP and all downstream systems continuously synchronized, ensuring no system operates on stale data
- ML-driven delivery risk models trained on order attributes, distance, product mix, crew history, and historical exceptions to flag at-risk deliveries before dispatch
- Proactive decision systems surfacing risk alerts directly into operational dashboards and scheduling tools, enabling interventions before issues escalate
- Depot-level forecasting models for inventory positioning and delivery capacity, with recommendations automatically fed back into SAP and TMS for execution
- Enterprise-grade governance through Unity Catalog, providing consistent access controls, lineage tracking, and compliance coverage across all users and systems
Outcome
Temco established a real-time, intelligence-driven operating model, enabling proactive decision-making, consistent performance measurement, and synchronized execution across its delivery network. Decisions are driven by data, not instinct. And every stakeholder, from depot managers to enterprise partners, works from a single, real-time version of the truth, turning last-mile delivery from a reactive challenge into a precisely orchestrated competitive advantage.