“Knowledge has become the key economic resource and the dominant and perhaps even the only source of competitive advantage.”
-- Peter Drucker, Management Consultant and Author
According to McKinsey, the top 20 pharma companies collectively spend in the vicinity of USD 60 Billion annually on drug development. Deloitte reports that the average cost to bring a drug to the market, including the cost of failure, stood at approximately USD 2 Billion in 2021, in comparison to USD 1.3 Billion or thereabouts in 2013. As enterprises strive to contain spiraling costs while staying ahead of the competition and accelerating go-to-market, Competitive Intelligence (CI) becomes a key weapon in the pharma armory.
However, in an era where gargantuan amounts of structured and unstructured data are being generated every day, pharma companies need to ensure they have the right CI platform at their disposal – a solution that is comprehensive, customizable, scalable and capable of delivering incisive insights in real-time or near real-time.
The Key Elements of a Holistic Pharma Competitive Intelligence Solution
The life sciences industry has started to witness a significant improvement in the return on pharma innovation. We are seeing agile, cloud-based CI solutions make a considerable difference to pharma companies that are looking for quick and accurate insights amid burgeoning complexities, pricing and regulatory pressures, and evolving customer expectations.
The Agility and Immediacy of Cloud: Cloud-based CI platforms are driving remarkable agility for pharma companies by providing immediate and interactive ways of storing CI data. Cloud makes it possible to readily access crucial insights across a host of devices, including smartphones, tablets and desktops. More importantly, cloud-based solutions are highly customizable, displaying important information such as competitor profiles, sales and pricing through easy-to-use dashboards and layouts.
The Prescriptive Intelligence of AI & ML: AI and ML can help predict key trends and enable pharma companies to pre-empt disruptions and rapidly adapt to evolving markets. By creating granular, precise and timely insights, AI and ML enable enterprises to target unmet customer needs. Cloud computing blended with AI can harvest data from zillions of websites and track competitors’ digital footprint to cull out rich insights. Similarly, through the application of Natural Language Processing (NLP), AI can analyze customer sentiments that competitor brands evoke across social media channels.
The Importance of Data Integration: The ability of a CI tool to securely integrate external datasets such as surveys, social media posts and third-party information is paramount. This amalgamation is critical to measuring the success of an organization’s marketing and sales strategies. Analyses such as Strengths, Weaknesses, Opportunities and Threats (SWOT), perceptual maps and Key Driver Analysis (KDA) can yield interesting business insights when coupled with the external data digitally ingested through the CI solution.
The Effectiveness of User Configuration: Insights prove to be effective only when they are relevant to the particular function or stakeholder using them. User configuration is an important feature of advanced CI tools that allow the creation of different personas within the same license, to cater to the needs of various functions, therapy areas and business lines.
Looking Ahead: CI Innovations in the Offing
The pharma industry has become much more competitive over the past couple of years. The global pharmaceuticals market is expected to reach USD 2,151.1 Billion by 2027, registering a Compound Annual Growth Rate (CAGR) of 7 percent over the 2019-2027 forecast period. CI is expected to provide companies the decisive edge – as they grow in a more intelligent, intuitive manner – by leveraging customized inputs during the drug discovery and development phases. CI platforms are evolving further in the following ways:
Cognitive Analytics: With human-like intelligence, cognitive analytics leverages AI and ML to contextualize information from massive volumes of unstructured data as well as recognize objects within images. It can detect patterns and behaviors, and get smarter over time by continually learning from interactions. Cognitive analytics will trend as the most disruptive technology – not just in pharma but across industry verticals.
Voice-enabled CI: By 2024, customers are expected to interact with digital voice assistants across 8.4 billion devices. Voice assistants can be seen as a critical functional tool in CI. Voice-enabled CI will allow scientists to search data several times faster and more accurately than typed text, and increase the speed of decision-making.
Social CI: Many customer-facing industry verticals deploy social CI for customer engagements and to keep track of their competitors’ initiatives. Given the current regime of strict regulations, the pharma industry is yet to engage in a full-fledged manner on social media. By 2025, social media is expected to attract 4.41 billion users globally. As the drug discovery process becomes more collaborative, social CI can be a game-changer for gleaning and disseminating information.
Pharma companies are constantly faced with novel challenges vis-a-vis new and expiring patents, emerging business models, a fast-paced competitive landscape and innumerable technological advancements. They also expend enormous sums on R&D, which often do not bring in the expected returns. CI, in its advanced, agile and scalable version, can radically transform decision-making with sharp and forward-looking insights and help pharma companies wrest the competitive advantage.