In the dynamic global biopharma landscape, competitive intelligence (CI) is as indispensable as ever. Too much of the competitive research conducted by companies today, however, can be described as reactive: seeing an update in the news on an asset in a competitor’s pipeline, and jumping in to log all of the details. Developing a CI approach that is predictive instead, that gives a company a vision of what is coming ahead, can deeply inform how R&D strategy and priorities are established and can spell the difference between first-to-market success and being blind-sided by a swiftly moving rival.
Here are some approaches to competitive intelligence along a classical maturity curve – from ad hoc to visionary – and the reduction in risk seen as companies evolve from reactive to predictive CI.
Ad hoc: By ad hoc, we mean research that is conducted in “look-up” mode as companies respond to industry news. CI assignments are distributed among scientists and others who have other jobs and are not CI specialists. This kind of research relies on canned syndicated reports and other less established information sources.
Risks: The risks for companies that take an ad hoc approach are numerous: they are unable to monitor the competitive landscape pro-actively; they constantly react to more mature players that influence the CI landscape; and they can’t place the intelligence into a pan-R&D context.
Emerging: In this approach, companies license some, but not all, commercial CI data and tools. CI assignments here are channeled through a small knowledge management or library team. There is still a strong reliance on syndicated reports.
Risks: Companies with an emerging approach are still less aware of the pan-R&D landscape and decision-making still relies on multiple ad-hoc research efforts from less well-defined, less comprehensive sources, often times presenting conflicting paths from multiple misaligned sources.
Capable. Here, companies are licensing most forms of commercial CI. Small CI teams may be augmented by external consultants, and are able to support projects as assigned. They still may lack a seamless flow of CI to decision-makers and are constrained by the scope of the licensed sources and tools.
Risks: A biopharma company here may miss opportunities in decision-making not covered by the commercial sources and tools it is using and may be limited to canned reports and data dumps to support decisions.
Tactical: Companies that have developed a tactical approach to CI have the breadth of information sources covered with internal teams or external consultants. They have the resources in place to support all projects, yet do not have a sophisticated monitoring or surveillance network and have not developed an analytics capability for predictive scenarios.
Risks: Decision-makers and users in the tactical approach are reliant on project requests and delivery and CI is not operating in real-time, so decision-makers experience longer than desired turnaround times and have difficulty considering what-if scenarios.
Strategic: Here, the approach to CI has matured to the point where the company has full breadth and depth of data covered. Teams of internal and external experts are using surveillance and monitoring techniques and some analytics, but the company is not yet fully advanced in surveillance or real-time CI distribution and may lack a coherent vision.
Risks: Despite this more rigorous approach, decision-makers and scientists may not catch CI in time to avoid wasted R&D investment or be able to relate specific scientific concepts through tags to real-time CI.
Visionary: Companies that have developed a visionary approach to CI have mastered all the full breadth and depth of industry data and have processes in place to adapt to changes in market dynamics and anticipate evolving research and disruptive innovation. These companies have the greatest ability to perform what-if analyses and therefore influence the CI landscape, and to bring differentiated drugs to market faster than competitors.
Risks: A mature, well-developed, visionary approach to CI creates the least risk to decision-makers.
There are several key characteristics higher performing CI teams achieve, including: the ability to perform holistic analyses of the research and drug R&D pipeline rooted to scientific and commercial strategies; informatics expertise to aid in the curation, integration and delivery of real-time CI; and a higher form of emerging data analytics expertise using statistical and machine learning approaches to inform predictive CI scenarios.
To help measure CI competency within both major pharma and emerging biopharma, Clarivate Analytics has developed a CI Diagnostic survey and independent, objective analysis to assess CI maturity, measuring these critical characteristics to help support new CI strategy and operations.
Attending the BIO International Convention (BIO) in San Diego, CA? Join David Thomas, BIO’s Senior Director of Industry Research, and Richard Harrison, Chief Scientific Officer at Clarivate, for “State of the Innovation Industry” on June 19. Presenters will provide a detailed account of current licensing and M&A trends across the biopharma sector. Learn more.