What is common to a banker who intends to determine which of her
customers are at a greater risk of account-takeover fraud and a retailer
intending to reach out to a prospective customer who happens to be in the
vicinity of the retail outlet? The answer lies in big data analytics. Big data
is the buzz word today. The old idea of data residing in rows, columns, reports
and purchase transactions is passé. The form of data has evolved and now, it
also originates from tweets, videos, click streams, sensors used to gather
climate information, posts to social media sites, cell phone GPS signals and
various other unstructured sources.
IBM estimates that every day we generate
2.5 quintillion bytes (1018 bytes or 1000 petabytes) of data leading
to creation in last two years itself, of 90% of all data available. Eric
Schmidt, the CEO of Google, took everyone by surprise in a conference in 2010
when he declared that we create as much data in two days now as we did from the
dawn of civilization until 2003. Therefore, it is called as big data. Doug
Laney of Gartner, Inc. defined big data as “high-volume, -velocity and –variety
information assets that demand cost-effective, innovative forms of information
processing for enhanced insight and decision making.” It promises to companies
not just information, but insight. It provides an opportunity to unravel the
mysteries in the past, present and future when explored using tools e.g.
modeling, experimental design, prediction, optimization and simulation. For an
organization, it translates into more objective yet speedy decision-making. Big
data is already influencing the way companies approach customers. The outcomes
are evident in the form of new concepts floating around as well as cases of
profitable execution. For example, location based advertising (LBA) is rapidly
gaining traction. LBA has gained significance due to use of social media and
its features e.g. location. LBA allows focused marketing communication with
specific reference to location. With rise in m-savvy customers and availability
of technology to track, LBA is being pitched as one of the top high-value
mobile services to achieve mass adoption. Fraud detection is another area where big data
is turning out to be of help. Ruchi Verma and SR Mani of Infosys reported a
case wherein GE Consumer & Industrial Home Services Division saved about US
$5.1 million in the first year of using SAS to detect fraudulent claims by
unscrupulous service providers from within the organization.
Big data and
analytics may not be inexpensive, but it is definitely proving to be
cost-effective by resulting into insightful decisions. The companies which
believe in engineering the future are gaining new insight through big data
analytics and thereby, adding value to their processes and outputs vis-à-vis
their stakeholders.
-Dr. Manit Mishra
Assistant Professor
Marketing, IMI-B
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