Analytics: Where Does it Stand in Life Sciences Industry

Organizations should accept the potential of technology-enabled signaling, identification, and prediction.

FREMONT, CA: Bygone are the days when people used to visit hospitals only when they fell ill. Today's smart consumers have health knowledge at their fingertips. They look at the health industry's professional recommendations and supportive treatment.

Life sciences firms are trying to keep up with the consumer. They switch from recovery to preventive scenarios. But are they doing enough of that? How will they make the most of the critical patient knowledge available to them to manage patient health outcomes? Like other sectors, it is time for life science companies to embrace data analytics and strategically exploit insights to their benefit.

Early identification of trends and strategic intent to achieve real-world objectives is the secret to successful business strategies. Many decision-makers have felt the need to respond to extraordinary shifts in the field of life sciences. This shift has been amplified by innovations such as the transition to sales and marketing models, increased cooperation between regulators across the globe, changing physician-patient dynamics, and an all-important growth direction for emerging markets. Life sciences organizations are transitioning from care to prevention scenarios and patient health results management.

The advantages of analytics in life sciences are apparent in important areas. Fields including early identification of prescribing and care trends, the strategy of the patient's purpose to achieve real world outcomes, and, most notably, the achievement of operational excellence to push through the intellectual path of patient centricity.

The pharmaceutical world needs to reform the existing healthcare system to reduce healthcare costs, increase patient outcomes, and facilitate access to health information. This feature allows organizations to turn from typical pharma players to health players. The slightest improvement in one region has a cascading impact across the entire health care system. Organizations should also accept the potential of technology-enabled signaling, identification, and prediction.

While some analytics have been introduced in the life sciences market, there are still a lot of gaps to be closed. There is certainly a need for improved resources and processes to get market players closer to understanding the needs of their customers. Losing analytics-driven insights impacts the efficacy of their market plans in the real world and, in some situations, translates into heavy losses. Thus, it is time for the life sciences sector to internalize analytics-generated insights into its basic operating model and monitor strategy-based execution.