Don't Let Big Data Analytics Prevent You From Being Brilliant At The Basics
By Rob Wright, Chief Editor, Life Science Leader
Follow Me On Twitter @RfwrightLSL
When I think of the potential Big Data presents for the field of life sciences, it reminds me of The Rime of the Ancient Mariner — “Water, water, everywhere, nor any drop to drink.” Like the salt water ocean surrounding a thirsty sailor adrift, we are seemingly surrounded by Big Data yet struggle to tap its potential. Worse yet, from my perspective, most of those in our industry are only viewing the tip of the iceberg when it comes to looking at how to use Big Data — ignoring the massive amounts residing below the water’s surface. The McKinsey Global Institute estimates the application of Big Data strategies could generate up to $100 billion in value annually across the U.S. healthcare system by optimizing innovation, improving the efficiency of R&D and clinical trials, and providing new tools for physicians, consumers, insurers, and regulators. Like a majority of the research and discussions surrounding the application of Big Data in the pharmaceutical and biopharmaceutical industries, the focus seems to be on that which garners the most attention (e.g., skyrocketing drug discovery and development costs or rising healthcare costs). It seems little attention is paid to the potential value that could be created in the U.S. healthcare system by being brilliant at the basics, such as manufacturing or shipping. Who cares how stylish a car is if it doesn’t start?
A December 2013 Harvard Business Review article noted that most companies investing in data scientists, data warehouses, and data analytics software have little to show for their efforts. Why? Most companies don’t do a good job of managing Big Data. Further, they don’t know how to analyze it in ways that enhance understanding and then make changes in response to new insights. Jeanne Ross (MIT Sloan Center For Information Systems Research), Cynthia Beath (University of Texas at Austin), and Anne Quaadgras (MIT Sloan Center for Information Systems Research) say that until a company learns how to use data and analysis to support its operating decisions, it will not be in a position to benefit from Big Data. In other words, what is your core business and how can you apply Big Data to make evidenced-based decisions? UPS is an interesting example. The shipping company tracks data on more than 16 million packages per day for nearly 9 million customers from telematics sensors in over 46,000 vehicles. Why? To be able to determine trends (drop-offs and pickups) in real time and reconfigure the most efficient route of navigation. What kind of impact can this have? In 2011 UPS reported saving more than 8.4 million gallons of fuel by cutting 85 million miles off of daily routes. Not only does this improved efficiency make UPS “greener” and more sustainable, but it also translates into significant savings. UPS estimates saving just one daily mile driven per driver saves the company $30 million.
In order to help you improve your efficiencies in selecting a strategic partner for your drug development and manufacturing needs, we decided to put together some Big Data trends of our own via this special supplement. However, please don’t let this data-driven research and analysis by Nice Insight prevent you from being brilliant at the basics. For example, when you are on a site tour, don’t let a presentation on how a CMO is using Big Data analytics to improve manufacturing efficiencies prevent you from asking — “ So, when was the roof last replaced/inspected?” Big Data, without application of intellect, doesn’t make a good business decision model.