Google Cloud Product Bets to Win Pharmaceutical Companies as Customers

You are a PM at Google Cloud, asked to shape its strategy for the pharmaceutical industry. What should Google Cloud build or offer for drug makers, and where would you start? ```hint Follow a drug's path to market Trace the stages a drug passes through, from discovery to clinical trials to manufacturing and sales. Ask where each stage's data and compute problems are most costly, and where Google's strengths give it a reason to win against the cloud providers already inside these companies. ``` ### Clarifying Questions - What is the goal for Google Cloud here: consumption revenue, share taken from the clouds pharma companies already use, or a showcase for its AI products? - Which customers are in scope: large global drug makers, smaller biotech companies, or the contract research and manufacturing organizations that work for them? - Should the strategy span the whole value chain (discovery, clinical trials, manufacturing, commercial) or concentrate on one stage? - Are partnerships with established life-sciences software vendors in scope, or only what Google Cloud builds itself? ### What a Strong Answer Covers - A stated goal for Google Cloud in this vertical and why pharma is worth pursuing, given its R&D spend, data volumes and regulation. - A segmentation of customers and value-chain stages, and a reasoned choice of where to focus first. - Pain points specific to drug development, each tied to a concrete offering and to Google's advantages over incumbent clouds. - A prioritized roadmap with a go-to-market path, including partners and the compliance work buyers will require. - Success metrics and risks such as validation requirements, patient-data privacy and customers' fear for their intellectual property. ### Follow-up Questions - A large drug maker runs nearly everything on a competing cloud. Which workload would you use to get Google Cloud in the door, and how would you expand from there? - A customer worries that its proprietary compound data could improve models its competitors then use. How do you address that in the product and in the contract? - Your discovery AI offering wins many pilots, but few reach production. How do you diagnose why?