Today’s pharma landscape is more dynamic than ever. Rapid scientific advancement has brought significant breakthroughs in everything from GLP-1 drugs to gene therapies over the past year alone – and further acceleration is on the horizon. According to McKinsey, technologies like Generative Artificial Intelligence (Gen AI) could soon generate up to USD 110 Billion a year in value for the pharma industry, fast-tracking drug identification, research, development and approval.1
This dynamism is driving industry leaders to prioritize speed and agility. Research from Forrester, in collaboration with WNS, revealed that almost two-thirds (63 percent) of life sciences enterprises considered accelerating their response to business and market changes an immediate priority, ensuring they could stay ahead of fast-moving clinical, competitor and consumer developments.
Currently, many pharma companies are hindered by fragmented intelligence gathering across the enterprise. However, leading organizations are addressing this challenge by re-imagining Competitive Intelligence (CI). They are creating a new paradigm that integrates primary sources, secondary sources and market research into a single source of truth that is accessible to everyone, from researchers to sales and marketing professionals.
Adopting such integrated strategies will see CI evolve into something akin to an ‘insights’ function – responsible for unifying all types of intelligence in one platform. This centralization of intelligence can see existing pharmaceutical insights instantly augmented with extra context and all-new transformational insights unearthed. In this future, one can imagine CI as the pharma equivalent of a streaming service, bringing together myriad genres of data and information from across the enterprise and enabling key personnel to access the multi-source insights they need.
Adopting an integrated strategy will transform competitive intelligence into an ‘insights’ function, centralizing all forms of intelligence within a single platform.
In doing so, CI can help accelerate and seamlessly fine-tune drug development, unlock a holistic, real-time understanding of the competitor and consumer landscape, and empower decision-making across the entire enterprise. Here, we explore how pharma companies can bring this new future to life.
Unearthing New Value with Integrated Insights
The necessity for CI practices to embrace integrated strategies is evident. At present, many pharma companies have their view of the market, competitors and consumers obscured by traditionally siloed intelligence gathering. Just as a single data point alone holds little meaning, assessing primary sources without integrating secondary sources or market research (and vice versa) limits the value derived from data.
However, by adopting an ‘insights’ mindset and creating multi-source intelligence, CI can become an engine of transformation within the enterprise. The intelligence already exists; it’s now a matter of bringing it together in one place. Creating multi-source data sets fueled by cross-functional intelligence can instantly enhance insights and enable confident, rapid decision-making across the entire organization – from researchers working on drug development to marketers optimizing the communication of an approved drug’s potential.
Unifying teams in this way can also help unite information that is fragmented across the enterprise, with data silos driving inefficiencies, leading to duplication and limiting understanding of internal and external conditions. Furthermore, fragmentation also impacts the potential of new solutions that rely on accurate data to thrive, from AI chatbots to cutting-edge data crawling tools.
Enhancing Blended CI with AI and Analytics
Once integrated strategies have been embraced and an agnostic ‘insights’ mindset adopted by CI practices, the instant benefits of augmented insights can be further enhanced through next-generation tools. Standardizing and democratizing this intelligence is one case in point.
AI-led data platforms are already enabling seamless integration and contextualization of data, creating a harmonized single source of truth across the enterprise for enhanced decision-making. Innovative statistical analysis tools, for example, can harness newly unified enterprise data to derive easy-to-digest insights leveraging state-of-the-art machine learning techniques.
Beyond enhanced data capabilities, transitioning from traditional CI to a blended future requires the right use of advanced technologies. Data delivery is as integral as the data itself. Centralizing CI can provide awareness across regions or brands about ongoing work, fully realizing the true value of data.
Paving the way are next-generation cloud-based platforms that offer automated functionality, comprehensive analysis of multiple resources, and real-time information and insights. This means key personnel can access multi-source data sets for greater accuracy, completeness and recency. Intuitive interfaces, meanwhile, ensure insights can be accessed anywhere, anytime, enabling CI to assume a central, strategic and always-on role for pharma companies.
Next-generation cloud-based platforms offer automated functionality, comprehensive analysis of multiple resources, and real-time information and insights.
Partnering to Unlock Transformation at Scale
With 65 percent of industry executives planning to increase their spending on data and analytics, the signs are promising for pharma companies looking to build and enhance such capabilities. Many organizations seek third parties to do so at scale, tapping into AI-enabled tools and comprehensive coverage consolidated for ultimate efficiency.
These partnerships also enable pharma companies to tap into emerging technologies like Gen AI, which may face hurdles in-house. Deloitte research reveals that more than 90 percent of biopharma executives expect Gen AI to have an impact on their organizations this year, with a majority (66 percent) experimenting with the tech to test ideas and build use-cases.2 With PwC data estimating that Gen AI could reduce process timelines by 70 percent and operational costs by 30 percent, these capabilities could prove transformative.3
Since pharma companies have a limited number of dedicated CI professionals, partnering can also help quickly balance any shortcomings in expertise or skills, further helping new ‘insights’ mindsets to flourish. It’s why 43 percent of life sciences companies seek to recruit more people with advanced data and analytics skills while helping deliver the requisite therapeutic and regulatory expertise for innovation to flourish. Further, strategic partners also provide a third-party perspective without any internal biases, combining organization-level thinking with skilled research.
Insights for the Enterprise and Beyond
Once fragmentation is overcome through the right data capabilities, digital tools and domain knowledge, CI practices can begin functioning as an ‘insights’ engine – integrating insights from all sources, viewing them holistically and empowering the right people at the right time with the knowledge they need. This ensures staying ahead of the curve in every aspect of the industry, from clinical developments and competitor progress to consumer mindsets and behavior.
This approach also lays the right foundation for quickly incorporating emerging sources of insights, with technological progress creating myriad new use cases. The industry is talking about everything from integrating social analytics through to brain-scanning healthcare professionals for instant information. While the latter may feel futuristic, progress is occurring rapidly, with every new potential component further augmenting CI’s power.
This impact can extend far beyond the enterprise. Increasingly, pharma companies are collaborating with competitors, embracing a new era of ‘coopetition’ to create more significant outcomes. Re-imagining CI with an ‘insights’ mindset can help companies achieve speed and scale in data sharing internally and externally, enabling them to reach new heights.
About the Author
Mark Halford is a Corporate Vice President in the WNS Life Sciences practice. He has over two decades of experience, leading business engagements for analytics, technology, consulting and BPM services for some of the largest European pharmaceutical organizations.
Click here to learn more about transforming competitive intelligence in pharma for integrated insights.
References
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Generative AI in the pharmaceutical industry: Moving from hype to reality | McKinsey
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2024 Outlook for Life Sciences | Deloitte
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Next in pharma 2024: Reinventing for returns | PwC