The System-Level View That Sound Market Access Decisions Are Missing

Market access teams can make individually sound decisions on pricing, coverage, contracting, affordability and commercial execution yet still produce a suboptimal overall outcome. The problem is rarely the quality of decision-making within each function. More often, decisions rest on different assumptions and are made without a clear view of their effects across the system. As market conditions become more interconnected and change more quickly, organizations need a system-level view of how those choices interact across the product lifecycle.

Why Well-Run Functions Still Produce Suboptimal Outcomes

When a payer tightens its utilization management, the affordability program feels it within a quarter, and a launch price set for the opening negotiation shapes the contracting position for years. Annual planning cycles, each with distinct owners, data and reviews, move more slowly than the market they are meant to govern.

Within each function, the approach often appears sound. Pricing teams evaluate comparable products and establish launch price ranges. Contracting teams balance access against rebate competitiveness. Affordability teams focus on patient starts, abandonment and persistence. Each optimizes the metrics it is accountable for. But when those decisions rest on different assumptions, an outcome that is right for one team may create unintended consequences elsewhere. This disconnect is less an organizational failure than an analytical one, and it widens as the organization grows.

Because no single scorecard captures the combined effect, the shortfall is easy to miss. For example, teams supporting the same product launch may develop substantially different estimates of the eligible patient population, because each is working from a limited view of the available data. In some cases those estimates vary widely, which leads to fundamentally different pricing, access and affordability strategies.

The Hidden Cost of Siloed Decisions

When one team optimizes its own position, the impact is often felt elsewhere. Formulary access provides a clear example. Reaching a preferred formulary tier at launch usually requires deep rebates, and a high list price paired with significant concessions can help to achieve short-term goals of access and uptake. However, those same concessions may reduce net revenue and, in the United States, can also have implications for Medicaid best-price calculations. Recent policy changes, including the Inflation Reduction Act of 2022 and most favored nation pricing, add further variables that a launch decision now needs to account for. The combined effect may not become fully visible until nine to 12 months after launch.

Because the impact appears in another function’s results, it is often interpreted as an execution issue rather than the result of an earlier strategic decision. The original assumptions and trade-offs are rarely revisited, so the same patterns carry forward from one launch to the next. Organizations that can trace outcomes back to the decisions behind them can apply what they learn to future launches.

What System-Level Thinking Asks a Team to do Differently

Many market access teams associate system-level thinking with better dashboards, forecasts or shared data platforms. The real shift is in what gets modeled. System-level thinking models how payers, providers, patients, channels, policy and competitors influence one another over time, including the delays, feedback loops and threshold effects that most strategies leave out. The question itself changes, from how a decision affects this year’s result to how decisions and behaviors interact across the product’s lifecycle. A product’s commercial life can run 10 to 15 years, so a policy change in year six matters to a launch decision made today.

A model built on that foundation helps teams understand how the market is likely to respond under a defined set of conditions. Key assumptions are made clear, aligned across functions and assigned to a specific owner. The model is then calibrated against historic analogs, meaning earlier products that faced comparable conditions, so that its assumptions about how payers and providers behave rest on what actually happened. On the payer side, that record now runs to roughly 64,000 health technology assessment reviews and reimbursement decisions across more than 30 countries.¹ Against that record, rebate and access strategies can be tested and refined before they are committed. Provider adoption and prescribing behavior are then layered in to produce realistic growth curves. The result is a whole view of a launch, from the first month on the market to the eventual loss of exclusivity.

Most important, the model gives teams something concrete to discuss before decisions are made. Surfacing conflicting implications early, while assumptions can still be revised, is often more valuable than increasing the precision of any single scenario.

From Reporting What Happened to Deciding What to do Next

A retrospective dashboard can show what happened, but it cannot help teams evaluate what may happen next under different assumptions. Dynamic simulation allows teams to test scenarios and understand the trade-offs among speed to market, breadth of coverage, net price, affordability and long-term value before committing to a strategy. The team can then recalibrate as real-world signals arrive.

Spreadsheets have traditionally carried this work but cannot hold a large patient population modeled across many interacting factors. Artificial intelligence, including agents that rebuild a model whenever an input moves, changes the speed and scope of that work. Instead of waiting a week or more for a model to be rebuilt, a team can adjust a single input and see its effect within minutes. The path from insight to action shortens from weeks to a single day, and the time that gives back to the team is worth as much as the answer itself.

Policy change is where the difference between reporting and deciding shows most clearly. Policies such as the Inflation Reduction Act and most favored nation pricing can change the value of a strategy agreed on today. When one product in a market basket is drawn into a pricing rule, the effect can spread to every product in that basket. A working model can be rerun under the new conditions in the time the change allows. Simulation earns its place when it changes a decision. A scenario set that only confirms the existing plan has cost the team time it could not spare.

Governance and Shared Assumptions Come Before a Platform

Before selecting a platform, organizations need to establish the governance, ownership and data foundations that support continuous decision-making. Human judgment should be built into the workflow from the start, not added at the end. The assumptions behind pricing, access, evidence and financial decisions should be explicit, documented, owned and shared, so that every team involved is working from the same foundation. Connected access, claims and patient and contract data make that possible, with reviews that adjust as evidence and policy change instead of once a year at planning time.

With the current process, updating one decision can require two to four weeks to gather data, update spreadsheets and rerun the model. When an executive compares scenarios A and B, that process cannot deliver answers quickly enough to act on them. The further a single decision reaches, the more that speed matters. Within the European Union, the joint clinical assessment process, in force for new oncology and advanced therapy products since January 2025, means an evidence decision taken once now carries consequences across many national markets at the same time.^2,3

Governance also sets a boundary. What-if questions are endless, and no model can forecast a competitor’s launch four years ahead, so the governance structure decides which scenarios are worth running, and the model supports decisions instead of delaying them. Market access will keep behaving as one system regardless of whether it is managed as one. Organizations that model it that way can see the downstream cost of a decision before it is made instead of a year after. The question for a leadership team is which decision from last quarter would have changed with that view and what the next launch stands to gain from having it.

Matthew Champion is a director at IQVIA. Kunal Akwalia is a senior director at IQVIA.

References

1. IQVIA. Market Access Insights: A Clearer Path to Market Access. IQVIA fact sheet. Published November 7, 2023. Accessed November 4, 2026. https://www.iqvia.com/library/fact-sheets/market-access-insights
2. IQVIA. JCA Success With One Partner. EU-Wide. IQVIA EU HTA Solutions. Accessed November 4, 2026. https://www.iqvia.com/solutions/real-world-evidence/health-economics-and-value/eu-hta-solutions
3. IQVIA. EU HTA in Action: How Health Technology Developers Can Prepare for a Successful JCA. IQVIA white paper. Published November 6, 2025. Accessed November 4, 2026. https://www.iqvia.com/library/white-papers/eu-hta-in-action