Scenario One: A CI lens on the application of speed of innovation benchmarks
How can a competitive intelligence team take this high-level insight and apply it to their initiatives? Here, we use a four-step process to achieve that – tapping into Norstella’s broad data assets across the full pipeline journey.
Does the longer timeline apply in oncology? It does, strongly. The oncology median rose from 8.2 years in 2011 to 2013 to 10.8 years in 2023 to 2025. A team using a generic nine-year planning assumption for an oncology competitor is probably too optimistic about its timing. Hematological indications elongate even more, so the gap could be larger still.
Figure 5: Top 25 oncology development timelines: median years from Phase I to approval
An example analysis of nine oncology companies compared the median time from Phase I to approval across two rolling 10-year windows, matching the 2020 and 2025 benchmarks. Company names are blinded here except for Lilly.
The median across the nine rose significantly between the two benchmarks, consistent with the industry picture. Individual companies moved sharply. Company F rose from 8 years to 10.8, while Company C accelerated from 9.5 years to 8.6. Three companies beat the benchmark in both windows. Two of the top three companies experienced lengthening timelines, while Eli Lilly’s timeline did not.
For CI teams, the big takeaway here is that a competitor’s speed and whether that speed is changing should both be considered in your company level threat assessments.
Figure 6: Example competitor set – median years from Phase I to approval
Going deeper in solid tumors
If we go a layer deeper, within solid tumors, Lilly stands out again, with a median of 7.0 years against a 9.2-year benchmark. The phase breakdown shows where the time goes: Lilly's Phase 2 takes 1.2 years against a benchmark of 3.1. A total timeline shows that a competitor is fast. The phase split shows where it is fast, and that is what a team can monitor.
A total timeline shows that a competitor is fast. The phase split shows where it is fast, and that is what a team can monitor.
Figure 7: Example competitor set – median years from Phase I to approval (solid tumors)
Is Lilly fast because of what it chooses to develop, or because of how it executes development? Strategic considerations might include mix of precision oncology, indication selection, accelerated approvals, acquisitions and oncology portfolio focus. If indication selection in oncology, as an example, was the only driver, similar outperformance across other therapeutic areas would be unlikely. Interestingly, Lilly beats the benchmark in every one: by 2.4 years in CNS, 2.3 in cardiovascular, 1.8 in oncology, 1.0 in metabolic and 0.6 in immunology. The pattern points toward a stronger operational capability, with strategic factors likely adding to the effect. That read changes how a competitor is treated in a threat assessment. A repeatable capability for accelerated development means a competitor is likely to be fast in the next indication too.
Figure 8: Assessing the role of strategic choices vs operational advantage – Eli Lilly example
If indication selection in oncology, as an example, was the only driver, similar outperformance across other therapeutic areas would be unlikely.
Timelines are a mission-critical part of competitive intelligence. Six focus areas turn benchmarks like those in the P3i into sharper projections:
Zoom in to compare like with like. Which benchmarks best fit each competitor? Have setting, modality and patient cohort been accounted for?
Assess strategic choices. Is a timeline attributable to biomarkers, combinations or dose optimization? Is the competitor pursuing a broader label with a deliberately long trial design? Is it adept at running parallel trials?
Investigate operational advantages. Which competitors consistently outperform benchmarks, and is it a repeatable capability? Does it come from trial design, enrollment strategies or site networks? How does it affect the threat assessment?
Optimize timeline projections. Is the methodology granular enough, or does it rely on standard or outdated benchmarks? Is it too granular, missing the bigger therapy area trend? Does it incorporate directional signals from across the industry?
Know how your own company stacks up. How does your development timeline compare with the most equivalent peer set, and why? Do internal expectations align with industry-wide trends?
Contextualize new disclosures. Fewer disclosures alongside rising R&D spend point to greater selectivity, so a thinning early pipeline may signal higher conviction.
Teams spend so much time benchmarking competitors that the home company can be left out of the comparison. If an internal plan assumes eight years in solid tumors and the market median is 9.2 and rising, leadership should hear that from the team that owns the timeline benchmarking against competitors.
