Digital Isn't The Strategy: What Actually Drives Value In Clinical Supply Transformation

By Irena Maksimovic, Ph.D., CSCP cell therapy and drug product operations performance lead, Bristol Myers Squibb

Clinical supply teams are buying more technology than ever before. New dashboards appear, analytics platforms expand, automation promises speed. Yet many organizations still struggle to reduce waste, control amendments, or consistently improve timelines to patients. The problem is rarely the software itself. More often, the issue sits upstream in decisions and processes that were never redesigned before the tools arrived. Technology tends to magnify whatever operating model already exists. If the foundation is fragmented, digital tools simply make fragmentation more visible and faster.

Industry research supports this reality. A global survey by PwC found that nearly 80% of healthcare and pharmaceutical executives felt they were not realizing the expected value from digital investments, and most pointed to process readiness and workforce capability rather than technical limitations.¹ Bain & Company reports a similar pattern across large transformations, where organizational alignment and role clarity are stronger predictors of success than technology selection.² In other words, the gap is rarely inside the platform. The gap is inside the operating model.

A Simple Framework: Design, Source, Plan, Decide

Clinical supply performance is shaped long before the first kit is packed or the first shipment leaves a depot. Four upstream levers drive most cost, risk, and timeline variability:

• Design: protocol structure, visit schedules, kit configuration, amendment discipline
• Source: comparator strategy, supplier relationships, negotiation timing
• Plan: integration of short-term operational planning with long-term portfolio planning
• Decide: governance clarity, accountability, and decision speed

Digital capability supports each of these levers, but it cannot replace them. When they are addressed early, technology compounds value. When they are ignored, technology compounds inefficiency. This first article in this two-part series focuses on strengthening these foundations. The second article explores how digital and AI accelerate results once the basics are stable.

Protocol Design: Where Complexity Becomes Cost

Many of the most expensive supply problems originate during protocol design, often because supply representation is late or symbolic. Once a protocol is approved, complexity becomes embedded cost.

Benchmarks from the Tufts Center for the Study of Drug Development show that Phase 3 trials frequently experience amendment rates above 75%.³ Publications in Applied Clinical Trials estimate that a single substantial amendment can cost several hundred thousand dollars and introduce multi-month delays once regulatory updates, relabeling, packaging revisions, and site communications are included.⁴ Each amendment sends ripples through forecasting, depot allocation, and manufacturing schedules.

At the same time, optimization studies consistently show that 20% to 30% reductions in material waste are achievable simply by refining visit schedules, kit logic, and packaging configuration before study launch.⁵ These gains come from better design decisions, not better reporting tools.

Practical Actions

• Give supply chain leaders formal authority in protocol design forums.
• Require structured supply impact assessments before approval.
• Model amendment sensitivity during feasibility.
• Treat supply feasibility as a core design constraint rather than a downstream check.

Comparator Sourcing: A Commercial Decision, Not A Logistics Task

Comparator sourcing is one of the most predictable cost drivers in clinical supply, yet it is often addressed too late. Delayed engagement leads to inflated pricing, constrained availability, and secondary market risk that no system can fully correct afterward.

Industry analyses indicate that comparator drugs can represent 40% to 50% of total clinical supply costs in oncology and rare disease programs.³ This is not primarily a visibility problem. It is a negotiation and planning problem. Case studies from McKinsey & Company show that earlier commercial engagement, preferred supplier frameworks, and selective insourcing can reduce overall clinical supply costs by around 10% without major technology investment.⁶

Practical Actions

• Start comparator strategy at program initiation rather than study start.
• Establish preferred supplier agreements and direct manufacturer relationships where possible.
• Integrate procurement into cross-functional governance.
• Model alternative sourcing scenarios alongside enrollment projections.

Technology can show inventory with precision. It cannot renegotiate contracts signed under pressure.

Cross-Functional Planning: Connecting Today And Tomorrow

A frequent source of inefficiency is the disconnect between short-term operational planning and long-term strategic planning. Tactical teams manage weekly shipments while strategic teams forecast multiyear capacity, often with limited interaction. The result is misalignment where daily decisions undermine portfolio strategy and strategic plans ignore operational realities.

Effective planning connects time horizons and functions. Short-term planning focuses on immediate study needs and site inventory. Long-term planning focuses on manufacturing capacity, depot networks, and portfolio allocation. When planning cycles are synchronized and cross-functional teams collaborate regularly, organizations balance agility with efficiency instead of trading one for the other.

Practical Actions

• Establish integrated planning cycles linking tactical execution with strategic forecasting.
• Form cross-functional planning teams spanning clinical operations, supply chain, regulatory, and procurement.
• Use rolling forecasts that reconcile near-term variability with long-term commitments.
• Define explicit handoff points between tactical and strategic processes.

Without collaboration, planning becomes a collection of isolated forecasts that optimize individual functions while suboptimizing the system.

Visibility And Governance: Turning Data Into Action

Clinical supply visibility has improved dramatically. Many organizations now operate near-real-time dashboards showing enrollment curves, shipment status, and inventory levels. Yet faster visibility does not automatically mean faster decisions.

Benchmarking from McKinsey & Company indicates that pharmaceutical and biotech companies already achieve on-time delivery rates close to 97%.⁶ The persistent challenge is not awareness but authority and speed. When dashboards highlight regional imbalances, delays usually stem from approval pathways and cross-functional negotiation rather than missing data. Bain & Company research shows that a small number of roles often generate a large share of transformation value, yet many organizations struggle to identify and empower those mission-critical positions.²

Practical Actions

• Map high-impact decision pathways before adding new visibility tools.
• Define explicit ownership for redistribution, overage, and forecast adjustments.
• Establish escalation timelines and preapproved thresholds.
• Align performance reviews with amendment reduction, cost avoidance, and forecast accuracy.

Where To Start: Strengthen Foundations, Then Scale Technology

Transformation gains momentum when leaders focus on a few high-impact entry points rather than broad modernization programs.

• Map the decisions that most influence cost, waste, and timelines.
• Build cross-functional alignment linking short-term execution with long-term strategy.
• Make accountability tangible through named metric ownership.
• Realign incentives toward transparency and accuracy instead of silent buffers.
• Pilot with purpose using use cases tied to measurable patient or financial impact.

Best-in-class clinical supply organizations consistently achieve double-digit cost savings and meaningful cycle-time reductions through early collaboration and disciplined upstream decisions.⁶ Digital tools and AI become powerful only after these foundations exist. Predictive analytics strengthen forecasts when protocols are designed for supply efficiency. Machine learning optimizes inventory when decision rights are clear. Dashboards drive action when governance removes approval bottlenecks.

The message is simple: Transformation begins before system implementation. Strengthen upstream decisions first, then allow technology to multiply the results. Part two explores how digital and AI function as accelerators of a strong clinical supply strategy rather than substitutes for it.

References

1. PwC. How Digital Supply Chains Can Drive Transformation and Growth in Health, Pharma and Life Sciences. 2023.
2. Bain & Company. Why Transformations Fail and How to Beat the Odds. 2024.
3. Tufts Center for the Study of Drug Development. Protocol Amendment Benchmark Reports. 2023–2024.
4. Applied Clinical Trials. “Shining a Light on the Inefficiencies in Amendment Implementation.” 2024.
5. N-SIDE Life Sciences. Clinical Supply Optimization Studies. 2023.
6. McKinsey & Company. Clinical Supply Chains: How to Boost Excellence and Innovation. 2021.

About The Author:

Irena Maksimovic, PhD, CSCP is a global supply chain leader dedicated to bringing clinical innovation to commercial scale. She integrates deep technical expertise in CMC and IMP development with extensive experience in manufacturing networks and product strategy across small molecules, biologics, and cell therapies.

Known for turning complex strategy into execution, Irena strengthens governance and drives operational excellence in high-stakes environments. She possesses a unique understanding of how business decisions ripple through operations to shape patient outcomes. By building resilient supply capabilities and high-performing teams, Irena ensures life-changing therapies are delivered faster and more reliably.