Kubrick helped a global pharmaceutical company reduce delays, environmental impact and risks in its supply chain.
- 01
The challenge: legacy data architecture preventing real-time insight
A global pharmaceutical company were dealing with excessive storage and shipping costs, wasted product, and inconsistent logistics that made the supply chain unreliable.
The data environment was fragmented, slow and costly, hampering advanced analytics needed to optimize the supply chain; reduce delays, environmental impact and risks.
The company needed to modernize its entire supply chain data architecture, enable advanced analytics with a scalable AI-ready workforce to deliver quickly.
- 02
The approach: an all-in-one solution supplying near-real-time data
Our Accelerator program, composed of 30+ Data Engineers, first delivered a proof-of-concept in two weeks to unlock budget and partner funding for the R&D team.
We then delivered:
- A modern Snowflake data architecture: We rebuilt all data into Snowflake’s Data Lake capability, creating real-time data ETL from all data sources into a single platform to improve data accuracy and access.
- Advanced analytics with Neo4j: We used graph technology to reveal the interconnectivity and inefficiencies across the supply chain, connecting 1bn data points to enable the team to detect patterns, eliminate duplicate orders and map dependencies.
- 03
The impact: enhanced supply chain transparency
The project helped the client improve decision‑making, mitigate risks, streamlined logistics and reduce operational inefficiencies.
- Rebuilt 100% of legacy reporting with unified, real‑time, Snowflake‑powered dashboards.
- Delivered a 25% decrease in time spent producing reports
Reducing product waste, shipping delays and storage inefficiencies helped increase the resilience of our client’s supply chain.
