Physicists have spent centuries studying the three-body problem—a classic puzzle showing why systems with three interacting gravitational bodies become unpredictable, unstable, and extremely difficult to model over time. Two bodies can be calculated. Add a third, and small changes cascade into chaos.
Life sciences IT leaders are facing a modern version of that problem.
Research teams rely on one cloud for compute and AI workloads. Regulated data platforms live in another because of vendor alignment or compliance requirements. Contract manufacturers and partners operate in a third. On top of that, on-premises systems still anchor critical workflows. Individually, each environment makes sense; together, they create a system whose complexity grows faster than traditional governance models can manage.
The result isn’t just technical sprawl—it’s governance instability.
Multi-cloud adoption in life sciences is rarely accidental. It reflects real needs: flexibility for R&D, resilience, access to best-of-breed services, and support for global partners. At the same time, cloud investment keeps accelerating. Worldwide spending on public cloud services is projected to more than double between 2024 and 2028,¹ with end-user spending reaching $723 in 2025.²
Yet governance maturity often lags behind that growth. Most organizations now appear to be in a steady state rather than a transition. Roughly 70% operate across at least one public and one private cloud,3 making hybrid and multi-cloud complexity a permanent operating condition.
When governance doesn’t keep pace, predictable failure modes appear:
Individually, these challenges can be managed. Collectively, they erode confidence, especially during audits, regulatory reviews, or executive reporting cycles.
At the leadership level, the challenge becomes a balancing act. R&D demands speed, scale, and experimentation. Quality and compliance require consistency, traceability, and defensible controls. Finance demands predictability, while risk leaders need transparency.
When governance fragments, executives end up choosing between false tradeoffs: agility or compliance, speed or control. The best organizations reject that framing. They recognize that governance doesn’t slow motion—it makes motion predictable and safe.
This distinction matters. More than 50% of organizations will fail to achieve expected outcomes from their multi-cloud strategies by 2029,⁴ most often due to interoperability challenges, inconsistent controls, and governance gaps, not technology limitations.
In physics, unstable systems require stabilizing frameworks. In life sciences, multi-cloud environments require the same. A unified governance model doesn’t eliminate cloud diversity—it makes it operable.
The most effective approaches share four core elements:
Clear Accountability
Governance fails fastest when responsibility is diffuse. Executives must define ownership for cloud policy, risk acceptance, exception approval, and cost accountability, distinct from day-to-day administration. Decisions should be deliberate, documented, and visible.
Standardized Policies Across Platforms
Define core policies—security, data classification, access management, logging, validation, change control—once, and apply them consistently across environments. Cloud-specific implementations may differ, but policy intent cannot. Consistency enables compliance at scale.
Practical Exception Handling
Exceptions are inevitable in regulated industries. Mature governance doesn’t eliminate them. It manages them transparently. Time-bound approvals, clear rationales, and executive visibility turn exceptions into controlled decisions rather than hidden liabilities.
Executive-Level Visibility
Governance only works if leaders can see its impact. Executive dashboards should connect operational cloud activity to business outcomes: compliance posture, risk exposure, and cost trends. When metrics are fragmented or overly technical, governance becomes performative instead of operational.
Effective multi-cloud governance translates technical complexity into business-level insight. Leaders should be able to answer, with confidence:
When governance enables those answers, it stops being a constraint and becomes an enabler.
The three-cloud problem isn’t disappearing. As cloud and AI adoption accelerate, life sciences organizations need governance that scales with complexity, without slowing innovation.
NexusTek helps life sciences organizations address this by treating multi-cloud governance as an operating model, not a toolset. NexusTek brings clarity and accountability across public cloud, private cloud, and on-premises environments, aligning policy, risk management, and executive-level visibility so complexity never outpaces control.
NexusTek helps organizations:
The three-cloud problem doesn’t erupt all at once. It emerges quietly—in policy drift, inconsistent controls, or unanswerable questions. Left unchecked, small instabilities compound over time.
The organizations that thrive aren’t those that eliminate motion or consolidate to fewer clouds. They design governance that lets innovation, compliance, and cost control move together. The three-cloud problem is not solved by choosing fewer platforms. It’s solved by governing them as one system.
Sources:
IDC, Worldwide Spending on Public Cloud Services Forecast to Double Between 2024 and 2028, IDC Spending Guide
Gartner, Gartner Forecasts Worldwide Public Cloud End-User Spending to Total $723 Billion in 2025, November 2024
Flexera, 2025 State of the Cloud Report, July 2025
Gartner, Gartner Identifies the Top Trends Shaping the Future of Cloud, May 2025