Sales & Operations Planning for Small Teams: Aligning Clinical Supply

By Tom Walls, Principal and Founder, Axon Bridge Consulting

Emerging cell and gene therapy companies face a paradox: they need cross-functional coordination most urgently yet have the fewest resources to achieve it. A Phase 2 trial with 30 patients requires clinical operations to orchestrate patient enrollment across multiple sites while coordinating with manufacturing, supply chain, quality, and regulatory. Unlike commercial organizations forecasting market demand, clinical-stage companies manage protocol-driven demand with inherent uncertainty: patients screen but don't enroll, trials amend mid-stream, and regulatory timelines shift.

For clinical-stage teams, alignment does not come from enterprise systems. It comes from disciplined communication of protocol-driven demand signals and clear decision-making frameworks that allow clinical supply to translate into feasible, risk-aware supply plans.

The companies that master early stage sales and operations planning (S&OP) share a common insight: alignment isn't about tools. It's about shared visibility into clinical demand, clear ownership of decisions, and structured forums where clinical supply can surface constraints before they impact trial timelines and establish decision-making frameworks.

A brief note on terminology: while this article uses the term S&OP, some organizations refer to this process as SC&OP to reflect the clinical context. The distinction matters less than the underlying objective: aligning clinical demand with supply and operational decision-making.

Start With Foundations: Define Before You Plan

Before launching your S&OP process, establish three foundational elements. Remember: S&OP is a continuous business process, not just meetings. The meetings are coordination points within broader planning discipline that runs daily.

Clarify decision rights. Document who owns clinical demand signals (clinical operations for patient enrollment trajectories, analytical development for testing requirements, regulatory for submission milestones), who owns supply commitments (manufacturing, external supply management, supply chain), who translates operational plans into financial impact (finance), and who arbitrates trade-offs (typically a VP or COO). A simple one-page document stating "Clinical ops commits to patient enrollment forecasts by the 5th; finance validates financial assumptions by the 10th; supply chain responds with feasibility by the 15th" prevents ambiguity and finger-pointing. Clinical operations must communicate not just enrollment numbers but the assumptions behind them: site activation timelines, screen failure rates, patient dropout expectations, and protocol amendment impacts.

Create a clinical demand signal framework. Clinical trial enrollment is inherently uncertain, but uncertainty does not mean unpredictability. Clinical operations faces unique challenges: demand is protocol-driven, patient populations are constrained, and regulatory milestones create hard deadlines. Establish a structured way to communicate clinical demand distinguishing between committed patients (enrolled and consented), highly probable patients (actively screening), and pipeline patients (identified referrals or site activation plans). This tiered approach allows clinical supply to plan differently for each category rather than focusing on false precision. Finance can then use these tiers to build scenario-based budgets, while supply chain uses them to balance material commitments against enrollment risk.

Structure your monthly S&OP cycle around three meetings. Run S&OP on a monthly cadence and focus on what has changed from the prior cycle. While demand for studies more than 12 months out may only require quarterly updates, available and projected supply often changes monthly due to yields, stability pulls, or manufacturing variability. For that reason, the S&OP process itself should remain monthly, with clinical operations driving the demand signal.

• Demand Review (Week 1): Clinical operations, analytical development, regulatory, commercial (if applicable), and finance review clinical demand signals. Clinical operations presents enrollment forecasts, trial timelines, site activation status, and screening trends, along with the assumptions behind them, including protocol amendments and regulatory feedback. Analytical development shares testing and stability requirements. Finance validates assumptions and cost implications.
  Output: consensus clinical demand plan.
• Supply Review (Week 2): Manufacturing, external supply managers, logistics, engineering, and finance assess feasibility against the demand plan. Capacity, material availability, and distribution requirements are reviewed, and constraints are identified. Finance models cost and risk trade-offs.
  Output: feasible supply plan with identified gaps.
• Executive S&OP (Week 4) Leadership reviews the integrated demand, supply, and financial plan, resolves trade-offs, and makes go/no-go decisions.
  Output: authorized operating plan.

Small teams can initially skip the pre-S&OP reconciliation meeting that larger organizations use. As complexity grows, adding this step helps ensure leadership discussions remain focused on decisions rather than problem-solving.

Build Cross-Functional Trust Through Translation

The biggest barrier to S&OP success isn't lack of systems — it's lack of shared language and understanding between groups. For example, clinical operations manages protocol-driven demand with regulatory constraints, while supply chain manages lead times and material availability.

Translate clinical demand into supply planning inputs. When clinical operations says "we're targeting 30 patients by Q2," supply chain hears a commitment. When supply chain says "lead time is 16 weeks," clinical operations hears an excuse. Build translation mechanisms.

Clinical operations should communicate enrollment forecasts as ranges with probability assessments: "15 to 25 patients (80% confidence) based on current screen rates; potential for 30 if two delayed sites activate." Supply chain should translate lead times into clinical decision points: "We need enrollment confirmation by January 15 to support April dosing without expedite costs."

Clinical operations should also articulate what drives forecast changes, such as protocol amendments that increase testing requirements or reduce effective capacity. Finance translates these scenarios into dollar impacts, including material commitments and risk exposure.

Create shared visibility of clinical demand signals. Maintain one master planning data repository that clinical operations updates monthly with enrollment status, site activation timelines, screening pipeline, and protocol milestones. Planning discussions should reference this single source of truth. Clinical operations owns enrollment forecasts and site data, finance owns financial projections, and supply chain owns material availability and lead times.

Surface clinical constraints early. Avoiding enrollment challenges creates risk when manufacturing commits to capacity that clinical operations cannot utilize. Establish a culture where raising constraints early is expected. A simple red/yellow/green status system can communicate enrollment risk clearly, with finance tracking cost implications at each level.

Focus On Metrics That Drive Behavior

Small teams resist metrics as bureaucratic overhead. The right metrics, however, create alignment by making invisible trade-offs visible, particularly around clinical demand accuracy. Finance should own the metrics dashboard to maintain objectivity.

Measure clinical demand alignment, not just performance. Track clinical demand alignment metrics: enrollment forecast accuracy (actual vs. forecasted enrollment by cohort), site activation timing variance, decision lag time (days between clinical operations identifying an enrollment constraint and supply chain providing alternatives), and communication reliability. Finance tracks plan adherence: actual spend versus approved S&OP budget, with attention to clinical demand variance impact on material commitments.

Keep your dashboard ruthlessly simple. Limit it to five KPIs maximum. Focus on: (1) patient enrollment vs. forecast (by cohort and site), (2) material availability for upcoming clinical milestones, (3) inventory days of supply relative to enrollment trajectory, (4) clinical constraint resolution time, and (5) plan vs. actual financial performance. Present in a single-page monthly report using red/yellow/green indicators. Finance owns this dashboard and presents it at executive S&OP, with clinical operations commentary on enrollment drivers.

Use metrics to trigger conversations, not assign blame. When clinical operations' enrollment forecast variance increases or supply chain faces material constraints, metrics should prompt discussion about what has changed and how planning assumptions need to adjust. Finance’s neutrality helps keep the focus on process improvement rather than accountability.

Know When To Scale Up

Manual S&OP processes work until they don't. Teams should recognize when clinical demand management has outgrown simple tools and manual tracking.

Volume indicators. Manual planning becomes difficult when clinical operations manages multiple concurrent trials, multiple manufacturing sites, or a growing patient population across protocols. Breakpoints often appear when adding a second therapeutic program or as a patient volumes approach roughly 80 to120 active patients. At this stage, maintaining enrollment forecast accuracy across trials becomes increasingly difficult.

Complexity indicators. Geographic expansion, particularly international trials with country-specific regulatory requirements , multiple product configurations, or the introduction of commercial supply alongside clinical, creates complexity that simple tools struggle to support. Maintaining separate enrollment trackers by trial, site, and cohort that should be integrated is a clear signal that better systems are needed. Frequent protocol amendments that materially alter demand profiles further increase this complexity.

Frequency indicators. High volatility is another signal. If enrollment forecasts require frequent updates or emergency planning meetings begin to outnumber scheduled ones, the manual process has reached its limits. When clinical operations spends a significant portion of time coordinating forecasts rather than executing trials, technology can help restore focus.

The good news is that strong process discipline prepares teams to scale. Organizations that implement integrated business planning (IBP) without first establishing clinical demand management fundamentals often struggle despite sophisticated software.

Putting S&OP Into Practice Without Enterprise Tools

Effective S&OP for clinical-stage teams requires rejecting the assumption that alignment demands enterprise infrastructure. S&OP is fundamentally a business process, and for clinical-stage companies, it centers on managing protocol-driven demand and communicating clinical enrollment realities across functions.

Organizations that successfully coordinate clinical trials, manufacturing, and supply chain operations share common practices: Clinical operations defines demand signals with clear assumptions, teams use simple demand frameworks, communication is structured and disciplined, finance is integrated throughout, and planning metrics focus on demand alignment rather than precision.

A manual planning process isn't a compromise — it's appropriate technology for the current scale. The discipline developed through articulating enrollment assumptions, communicating forecast changes promptly, and collaborating on constraints builds organizational muscle that the enterprise later augments rather than replaces.

Start with process, add technology when complexity demands it, and remember that in S&OP, the "O" stands for operations — the daily execution of clinical trials that no software can manage for you.

About The Author

Tom Walls is principal and founder of Axon Bridge Consulting, specializing in Advanced Therapy Medicinal Products (ATMP) supply chain planning. With over 20 years of life sciences supply chain experience, he previously served as Head of Supply Chain Planning at Spark Therapeutics and has published in Cell & Gene Therapy Insights. He is the author of "A Practical Guide to ATMP Supply Chain Planning and Orchestration Excellence" and developed the R3M (Risk Measurement, Monitoring & Mitigation) framework for ATMP supply chains. Contact: tom@axonbridgeconsulting.net.