A 2014 IDC report predicted that by 2020, the digital
universe—the data we create and copy annually—will
reach 44 zettabytes, or 44 trillion gigabytes.
10 With the
explosive growth in organizational data, there is
increasing emphasis on analytics that can be used to
uncover the “hidden potential” of data. A 2014 Society
for Information Management survey found analytics/
business intelligence to be #1 among the top 15 most
significant IT investments in the prior five years.
12 It is
not surprising that business analytics is increasingly
central to managerial decision making within business
functions: finance, marketing, human resources,
and operations. For example, cash-flow analytics,
shareholder-value analytics, and profit/revenue analytics
are increasingly important aspects of
the finance function. A 2017 survey of
chief marketing officers found compa-
nies spend 6.7% of their marketing bud-
gets on analytics and expect to spend
11.1% over the next three years.
16 A 2017
Deloitte survey of HR managers found
over 71% of the surveyed companies see
people analytics as a high priority.
lytics is increasingly used in operations
management for demand forecasting,
inventory optimization, spare parts
optimization, warranty management,
and predictive asset maintenance. Ac-
knowledging extreme deficiency of
data literacy among today’s managers,
by 2020, 80% of organizations will em-
bark on data-literacy initiatives.
As analytics becomes central to
decisions across finance-, marketing-,
HR-, and operations-related work, it is
also increasingly viewed as central to
current and future continuous learning efforts within organizations. In the
context of analytics-related continuous learning within different functions, managers need to better understand the trends in how different
types of analytics applications are
being and will be used for function-specific decision making. We thus focus on this research question: What
current and future use of different
types of analytics applications—static
reports/interactive dashboards, descriptive analytics, predictive analytics, prescriptive analytics, and big data
analytics—can help support different
dimensions of managerial work—
planning, implementing, and control-
Work in finance, marketing, human
resources, and operations increasingly
relies on analytics—with more to come.
BY VIJAY KHATRI AND BINNY M. SAMUEL
˽ A variety of analytics applications are
needed to support the various dimensions
of managerial work in four business
functions: finance, marketing, human
resources, and operations.
˽ The future use of analytics in these functions
will employ increasingly sophisticated
types of analytics applications.
˽ To help business managers derive value
from the data in the digital economy,
analytics preparedness, as well as the
design of data-literacy programs, will
have to be function- and work-specific.