Reading the Signals
Applying Pharma Productivity Benchmarks to Competitive Intelligence
Industry-wide performance themes
Scenario One: A CI lens on the application of speed of innovation benchmarks
Scenario Two: The dynamic nature of development risk
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These are the top-level findings of Norstella’s 2026 Pipeline-to-Patient Productivity Index (P3i), an industry-wide benchmark launched in 2026. Industry-level benchmarks capture these shifts well, but at such a high level, they are only directional. Knowing what they mean for a specific indication or a specific competitor is the harder part.
That translation is the work of competitive intelligence. Knowing that median timeline from Phase I to approval is 9.3 years is fine, but a CI team responsible for projecting when a particular competitor will file cannot answer with an industry median. Competitive intelligence teams need to extrapolate trends proactively and recognize divergence between competitors.
This paper shows how to make that move, using insight from the P3i. We use two worked examples in oncology covering speed of innovation and development risk to show how high-level benchmarks can be translated into competitive intelligence.
Along the way, the examples show what a thinning early pipeline can signal, why Eli Lilly’s speed looks like a repeatable capability and how company-level Phase I data separates a therapy area signal from portfolio-wide discipline.
P3i follows 25 leading biopharma companies across four connected stages: speed of innovation, development risk, market access and commercial return. Each stage has two core measures. The index is built on Norstella's integrated data engine, which brings together pipeline and clinical development data, portfolio investment and commercial forecasts, and market access and formulary intelligence.
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