Summary
BioTeam partnered with a global biopharmaceutical company to design a sustainable operating model for research IT, spanning HPC infrastructure, cloud strategy, data governance, and specialist staffing. The company’s research organization spanned multiple international sites and relied on a single-site, premise-based HPC cluster managed with Slurm and Bright Cluster Manager, but research-specific IT needs were increasingly outpacing what a centralized, enterprise-first IT function could support. BioTeam ran a structured discovery process across research and IT leadership, compared the current state against evolving research demand, and delivered a multi-year technology roadmap alongside a proposed staffing and governance model to close the gap.
The engagement produced a prioritized roadmap of initiatives spanning data governance, user access management, and cloud adoption, along with a proposed specialist support team structured to sit between central IT and research, closing the divide between the two.
Challenge
The client’s research computing environment had grown organically across multiple sites, with a Slurm and Bright Cluster Manager-based HPC cluster supporting genomics, computational chemistry, imaging, and other data-intensive science. As demand grew, research groups increasingly needed capabilities that fell outside the scope of a centralized enterprise IT function built primarily for business systems and manufacturing.
Priorities included:
- Bridge the research/IT divide. Research teams needed responsive, science-literate technical support, while enterprise IT was organized around business and manufacturing systems with different priorities and timelines.
- Establish research data governance. There was no centralized approach to data standards, access management, or a shared research data repository, making it difficult for teams across sites to discover, access, or reuse each other’s data.
- Modernize user access management. Onboarding and offboarding internal and external collaborators lacked a streamlined, role-based process, creating both friction and compliance risk.
- Clarify a cloud strategy. The organization had cloud capability but no unified, research-informed strategy for when to use it, alongside a growing need to extend on-premises HPC capacity via cloud bursting.
- Right-size a research support structure. Leadership needed a staffing and governance model that could scale with research priorities without duplicating enterprise IT.
Approach
BioTeam ran a structured discovery and design process across the organization’s research and IT leadership:
- Stakeholder discovery. Conducted structured interviews and workshops with senior research and IT leadership, research management, and IT management across multiple global sites to establish a shared understanding of current state and priorities.
- Capability and gap assessment. Mapped current-state research IT capabilities against desired future-state capabilities, identifying gaps across data management, infrastructure, and support services.
- Cross-functional prioritization workshops. Facilitated future-state workshops with dozens of stakeholders across the research and development organization to define and prioritize recommendations, surfacing dependencies and synergies across initiatives.
- Roadmap and staffing design. Translated prioritized recommendations into a phased, multi-year roadmap, and designed a proposed specialist support team model, funded by research but integrated with central IT’s service management processes, to accelerate research-specific initiatives without duplicating enterprise infrastructure.
BioTeam’s Roadmap & Recommendations
- Delivered a phased, multi-year research technology roadmap of prioritized initiatives spanning data governance, user access management, a research data repository, and cloud adoption.
- Identified high-priority initial initiatives, including data standards and governance and centralized user access management, to establish early momentum and value.
- Proposed a specialist research IT support model, with roles funded by research but integrated into the central IT support organization, designed to bridge the gap between enterprise IT and research needs while remaining lean and scalable.
- Recommended a hybrid cloud strategy, including a cloud beachhead and a path to extend the existing on-premises HPC cluster via cloud bursting, to support growing data-intensive science needs without a full infrastructure overhaul.
- Recommended a foundation for centralized research data governance to improve discoverability and reuse of research data across the organization’s global sites.
