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 companies spend 6.7% of their marketing budgets 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.3 Analytics is increasingly used in operations management for demand forecasting, inventory optimization, spare parts optimization, warranty management, and predictive asset maintenance. Acknowledging extreme deficiency of data literacy among today's managers, by 2020, 80% of organizations will embark on data-literacy initiatives.15
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 controlling—in four business functions? In 2015, we conducted a survey of 197 mid-level U.S.-based managers in finance (49), marketing (50), HR (49), and operations (49) functions on their current and future use of various analytics applications.
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