Commercial forecasting built on clearer assumptions.
Commercial forecasts rarely fail because of arithmetic. More often, they fall short because the commercial framework behind them was never strong enough in the first place.
Markets are defined too loosely. Competition is simplified. Pricing and access are treated as secondary. Adoption curves are applied without enough thought about how physicians, patients and payers will actually behave. By the time those weaknesses become visible, the forecast is already being used to support an important decision.
DSX helps leadership teams strengthen the commercial framework behind a forecast before too much weight is placed on the numbers.
Forecast architecture is the work that sits behind the model. It brings structure to the commercial logic that drives the output: who is in the market, how the opportunity is segmented, how competition is likely to evolve, where pricing and access will shape uptake, and which assumptions matter most to the result. The aim is not to make forecasting more complicated. It is to make it more realistic, more explainable and more useful in decision-making.
The framework
A strong forecasting framework usually needs to answer six questions clearly.
What is the market?
The forecast should start with a clear view of the treated population, including epidemiology, diagnostic flow, eligibility and meaningful patient segmentation. This defines the real commercial opportunity before adoption assumptions are layered on top.
How will competition change over time?
Markets do not stand still. Pipeline entrants, label expansion, mechanism competition and competitive response all shape future share and market dynamics. A useful forecast needs to reflect how the market is likely to evolve, not just how it looks today.
How will pricing and access affect uptake?
Adoption is shaped by far more than clinical value alone. Pricing, reimbursement, HTA timing, payer behaviour and regional access constraints all influence how quickly and how fully a product can penetrate a market. These factors need to be built into the forecast from the start rather than added late as secondary adjustments.
How will adoption happen in practice?
Forecasts need a realistic view of physician behaviour, treatment pathways, switching patterns and evidence development. Rather than relying on generic penetration curves, DSX focuses on how uptake is likely to happen in a real market setting.
How sensitive is the answer to key assumptions?
A single forecast number rarely tells the full story. Scenario work helps leadership teams understand how outcomes change when core assumptions move, whether around timing, competition, pricing, access or adoption. That gives a clearer view of risk and a more practical basis for discussion.
What decision is the forecast supporting?
Forecasting is not an end in itself. The real purpose is to support a decision, whether that means indication prioritisation, launch sequencing, portfolio trade-offs, external opportunity evaluation or investment planning. The framework should therefore be designed around the decision it needs to inform.
What is forecast architecture
DSX typically supports forecast architecture work in situations such as building the first commercial forecast for an emerging asset, reviewing and strengthening an existing model, comparing opportunities across indications, assessing launch timing under competitive pressure, or supporting BD&L and investment discussions. The output may include forecast models, assumption libraries, scenario analyses, competitive modelling and supporting materials that make the forecast easier to explain and use.
DSX also brings an international commercial perspective to this work. Commercial assumptions do not travel neatly across markets, and forecasts are often weakened when they rely too heavily on a single-country view. Experience across US, EU and UK pricing and access environments, rare disease pathways, HTA timing and launch sequencing helps ensure the forecast reflects how markets behave in practice.
At its best, forecast architecture gives leadership teams more than a model. It gives them a clearer view of the market, a sharper understanding of the assumptions that matter, and a stronger basis for making an important commercial decision.