iStock 000046596412Small resized 600(This blog series will introduce emerging trends in sales planning that every commercial operations department must prepare to face in the future.)

While many industries, such as retail, financial or travel and tourism, have relied on big data for years to improve competitiveness, life science has been slower to incorporate data into its planning beyond pure sales and customer attributes. But with many factors outside of pure sales driving today’s complex environment, we have started to recognize big data’s potential impact.

We are grappling with issues of access, control, influence and perception. Luckily, the opportunity to find the answers is huge, with more data than ever before, in more formats (structured and unstructured) and from more places offering insight into these new questions. Gartner predicts that unstructured data will grow 80% through 20151, or 15 times the growth rate of structured data2.

The Role of Unstructured Data in Life Sciences
For life science companies, new systems and repositories of valuable data emerge every day: Medicare and Medicaid databases, electronic medical records repositories and aggregators, social networks like Doximity and PatientsLikeMe, not to mention quickly accumulating internal data, such as repositories of video and audio interactions with customers, outcomes databases, closed-loop marketing clickstreams and many more.

A lot of this data can offer clues to answers to questions we’ve been struggling with for the past decade: Who are the most influential and authoritative key opinion leaders (KOLs)? What are their opinions and concerns about our medicines? To extract the right answers will require considerable mastery of this data and the ability to put it together.

Harnessing the Data
So what are life science companies doing to harness this data? One company sought to understand important influencers for a new drug it was about to launch. To identify the greatest authorities and their academic employers, ZS helped that company pull data from the PubMed citation database, with 24 million citations from Medline, journals and books3.

The data was filtered by citations and articles related to the relevant therapeutic area and further graphed and analyzed based on authority score, a composite of the number and influence of those who refer to one’s articles. The process identified KOLs in the field, as well as their colleagues, co-authors and the academic institutions most influential in that particular area. Ultimately, this led to a small but powerful list of KOLs to coordinate with before launch.

This is just one small example of how to harness the power of this new, unstructured data. The challenge then becomes, are you prepared to harness this power to drive a positive impact on your sales planning operations, and ultimately help deliver a better customer experience?

The next trend we will explore focuses on how analytics can help unlock the potential contained in the data.

Topics: big data, sales, call planning, territory management, Maria Kliatchko, Key Opinion Leaders, Sales Planning, Life Sciences, Commercial Operation