Agricultural Biotech

The client runs a wide range of R&D projects powered by complex, unstructured data—genome maps, field monitoring data, etc. But most of this data is scattered across silos and fragmented initiatives, with no clear governance, ownership, or workflows. Add to that hybrid cloud and on-premises architecture, creating additional complexity.

As a result, data lacks credibility, and R&D projects get dragged out for years. This slows down seed research and the release of new products. Instead of focusing on real scientific work, biotech experts spend most of their time sourcing and sorting out data.

We analyzed the client’s data assets, infrastructure, and use cases, and proposed a platform design and governance to consolidate data initiatives and improve the traceability, reliability, and quality of data. 

The team delivered a suite of score sheets identifying optimal architecture, infrastructure approach, tech stack, and governance tools based on the client’s priorities. Plus, a TCO calculation template for cloud and AI tools, implementation, and internal training to make informed investment decisions. 

By implementing the data platform, the client could: 

• Create structured R&D workflows with clear data ownership and governance
• Speed up seed research by 4x and accelerate time to market for new products
• Improve credibility, collaboration, and access to data across the organization
• Reduce risks and better secure sensitive research data and know-how
• Make data-driven investments in new seed products and research