Advanced Data and Analytics in Life Sciences: The Winning Prescription
In the new normal, digital channels have become the core channels of customer engagement, but everyone is using the same channels. Doctors are being swamped with content, and push sales techniques are not working anymore. Pharma needs insights from customer behavior to understand what will work, and a high degree of personalization, with messages tailored to the individual HCP. It is necessary to consider the reaction of customers quickly, analyze the impact, and optimize the customer journey in real time, which requires a much more data-driven approach.
Today, stakeholders, whether patients or physicians, are much more actively involved in the journey. The data strategy influencing content strategy, insight strategy, and activation needs revisiting from this angle. Now, analysts are being challenged to use data to anticipate, rather than forecast. When there is confusion and trends do not match historic data, there are risks in making real-time decisions. Without digital, there is no real-time data and historic data may not provide an accurate picture. Agility requires not only speed but also new ways of sourcing and reviewing data, which must include digital channels, if foresight is essential.
The analytic cycle can be accelerated using agile analytics to allow leaders to make fact-based decisions faster. Agile analytics comprises 3 components. First, it is fundamental to have the right data platforms to address questions with data insights in real time. Second, people with analytic consulting capabilities are required as they can facilitate discussions about the data in real time among decision makers and enable them to make choices quickly. Good analysts spend almost as much time with stakeholders defining the objective of the analytics, as they spend in implementing the methodology. Analysts need to be sitting at the table and helping the organization to achieve better outcomes. They must be articulate about whether the company has the right objective and improve its efficiency with the best use of the analytics. Third, the process is accelerated by drawing together a focused team to develop insights and facilitate actions. All stakeholders should confer regularly to agree on the actions necessary to achieve the goal. This is a cyclical approach. After each action, performance should be assessed, and problems should be addressed in real time, before the next set of insights is decided. Such agility accelerates data-driven insights and leads to success, both in terms of decision-making and outcomes.
Now is a time for experimentation. Pharma can use new data sets to gain insights into how the human HCP persona is behaving. Time-restricted experimental pods can be set up and given the freedom to use different paths to build trust through insights and performance. New ways of engaging the data, such as social listening about brands and physicians, can provide different paths to performance.
Pharma is held back by its legacy data footprint. It has 3 problems in this regard. First, the industry does not talk directly to the consumer. Second, it lacks real-time data and is not set up to get information as it occurs, as is possible in the consumer environment. This means there are data lags.
Third, a stimulus-response methodology, whereby an action is taken, and its effects can be measured, is critical for successful analytics, but the industry does not have that luxury as it cannot readily use stimulus-response.
However, now the technology is available to integrate data sets. This enables organizations to move from a data acquisition and data reporting mentality to a data strategy and data decision frameworks. This is a significant migration for pharma. Its legacy data sets can be integrated and augmented with market research, for example. This provides answers to the ‘What?’ and the ‘Why?’ in the same place, enabling quicker decision-making, which is increasingly important. Now it is possible to activate a marketing mix, promotional optimization, and dynamic targeting.
The use of augmented analytics enables better connection of the dots across data, when one flow of analytics may not be providing the information needed. While this is not real-time data, it does offer a higher level of accuracy from streams that pharma has not tracked traditionally. For example, when payer data drops off or changes frequently, the social media footprint can provide a lot of useful information.
As the work environment continues to change, it is critical for the analytics function to be embedded in the organization. The analysts need to know the latest business challenges so they can react fast and ensure they are addressing the questions the company wants to answer. They can also make certain that queries are not repeated and processes are standardized and made more efficient. Every function within the business needs to be listening to feedback first-hand, with the goal of reacting and changing processes quickly, in response to what the customers say.
Chief Technology Officer
Tarun has over 27 years of experience and has been associated with Indegene for the past 17+ years. He leads the technology domain at Indegene and his responsibilities include development of technology-based solutions focused on the healthcare industry. His strengths lie in his technological expertise and business acumen, which help in developing various platforms and next-generation IT solutions.