Reflections on Risk

In many cases, the only risk quantified in development project investment cases is PTRS (Probability of Technical and Regulatory Success). While technical failures are leading reasons for project cancellations, other critical risks often go unaddressed.

Here are three additional types of risks we discussed in the presentation:

👉 Operational Risks

These include delays in timelines and increases in development costs. Timeline delays harm project value by delaying revenue and pushing out breakeven points. While cost overruns also reduce value, their impact is typically smaller than missed milestones.

👉 Commercial Risks

These involve uncertainties around pricing, market access, market share, and revenue. For example, launch timing, reimbursement challenges, or competition can drastically alter a drug’s value. Despite their importance, commercial risks are often modeled using static spreadsheets that project single estimates or, at best, a base, upside, and downside scenario—leaving uncertainty largely unaddressed.

👉 Dependency Risks

Many projects depend on other assets or programs, and these dependencies can significantly influence success and value. Capturing these interdependencies is crucial for making informed investment decisions.

Despite their profound impact on project value, these risks are often ignored. Why? The main reason is the difficulty of modeling these uncertainties using traditional Excel tools. Internal processes also frequently demand single-point estimates. As Sam Savage aptly noted in The Flaw of Averages: “When you are done with your analysis and have great risk assessments, someone will be there with an Excel spreadsheet saying, ‘Give me a number.’”

Why This Matters

Risks such as operational delays, commercial uncertainties, and dependencies exist whether or not we account for them, and they inevitably affect project outcomes. Ignoring them does not eliminate their impact. To make better decisions, we must embrace tools and processes that can model these risks and integrate uncertainty into forecasts, and visualize their impact on timelines, costs, and value.