EDITOR'S NOTE
LSL
6
LIFESCIENCELEADER.COM JULY 2014 CMO SUPPLEMENT
good job of managing Big Data. Further, they
don't know how to analyze it in ways that
enhance understanding and then make chang-
es 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 busi-
ness and how can you apply Big Data to make
evidenced-based decisions? UPS is an interest-
ing example. The shipping company tracks data
on more than 16 million packages per day for
nearly 9 million customers from telematics sen-
sors 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 mil-
lion gallons of fuel by cutting 85 million miles
off of daily routes. Not only does this improved
efficiency make UPS "greener" and more sus-
tainable, 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.
l
Don't Let Big Data
Analytics Prevent You
From Being Brilliant
At The Basics
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J U LY 2 014 V O L . 6 N O. 7
R O B W R I G H T Chief Editor
hen 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 seem-
ingly 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 mas-
sive amounts residing below the water's sur-
face. 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 regula-
tors. Like a majority of the research and discus-
sions 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 ris-
ing 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 ship-
ping. Who cares how stylish a car is if it doesn't
start?
A December 2013 Harvard Business Review
article noted that most companies invest-
ing in data scientists, data warehouses, and
data analytics software have little to show for
their efforts. Why? Most companies don't do a
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