Rewiring an oncology portfolio to hit the growth target

The story

An established oncology business faced a simple problem with hard edges: the revenue curve it had promised to the street outpaced what its pipeline could credibly deliver. Competition intensified, payer scrutiny rose, and internal tools could not compare multi-indication bets on a common basis. Teams argued asset by asset. No one owned the whole.We rebuilt portfolio management around three moves.

‍Foundation
‍We interviewed R&D, commercial, medical, manufacturing, and finance leaders to map decision pain points. We audited the existing scorecards and models. Gaps were obvious: inconsistent risk assumptions across programs, no way to value indication sequencing, and no line of sight from strategy to budget.

‍Redesign
‍We stood up a two-lens system. Top-down: define the “point of arrival” in priority diseases and the capabilities required to win. Bottom-up: value each asset/indication with explicit probabilities, timings, COGS and promo intensity, then pressure-test scenarios (label breadth, access, competitor moves).
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Between the two, we introduced a “mutual-fund” allocator that optimizes the mix for return vs. risk, resource, and timing—shifting capital across discovery, early development, and late-stage bets. A single portfolio dashboard rolled up NPV, risk-adjusted revenue, headcount, and manufacturing slots. Governance changed too: a quarterly Portfolio Council with clear decision rights, common discount rates, and pre-agreed stop/go rules.

Implementation
‍We embedded the tools in annual planning and mid-year refreshes. Templates became lightweight and mandatory. One development leader owned the fund model and kept assumptions synchronized. Functions used the same view to align trial starts, tech-transfer windows, and launch sequencing. The model also quantified where selective in-licensing could close the shortfall fastest.

The company moved from “favorite projects” to funded strategies. Capital reallocated toward three disease areas with the best risk-adjusted return; lower-yield indications were paused or sequenced later. Discovery spend shifted to mechanisms that reinforced those disease theses. Late-stage programs with weak odds lost budget; two external assets were added to fill timing gaps. The dashboard gave executives a single source of truth, and the Council cut decision cycle time.

‍Results
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– Revenue gap addressed with a three-year plan that combined reprioritized internal assets and two targeted in-licenses.
– 15–20% of R&D spend reallocated toward higher-return programs with clear milestone gates.
– Portfolio risk-adjusted NPV up 8–12% versus baseline; peak-year variance reduced.
– Decision latency halved; cross-functional alignment improved as supply, medical, and commercial planned against one sequence.
– Adoption stuck: one leader was assigned as “fund manager,” and the dashboard became the default view in budget reviews.

The oncology story is now simple enough for investors to underwrite: a concentrated set of disease theses, a sequenced launch plan, and a governance model that keeps capital flowing to the best odds.