This talk will focus on specific methods and case studies of applying information technology in incremental layers across multiple businesses to improve the value of the organization's investment in experimentation. • The difference between laboratory data management and laboratory "workflow", and why both are important in developing effective research IT systems. • How R&D organizations have developed an overall architecture to bring together sample and data management, analytics, and laboratory and document workflow. • How to balance multi-year grand-vision architecture plans and achieving near-term measurable benefits.