In today’s economy, success is synonymous with technological innovation. Technology is driving rapid change in every sector of business. Machine learning, artificial intelligence, the Internet of Things, cloud computing, drones, bots, and blockchain are transforming not only the nature of work but the means of survival. In the new innovation-driven economy, the continued relevance of a given job, department, company, or industry is guaranteed only insofar as it embraces and capitalizes on the opportunities afforded by these advancements. Every possible competitive edge—from talent to timing to intelligence—can be maintained only through the speed, efficiency, and breadth technology delivers. Only those who welcome rather than ignore or hide from our technology-driven future stand a chance of succeeding in it.

Innovation-fueled organizations need innovation-fueled internal audit functions. Indeed, the risks and complexity introduced by rapidly changing business environments have placed increasing demands on internal audit teams, often without accompanying increases in resources. Fortunately, the same technology driving the need for more and better auditing can also enable teams to meet these demands.

In particular, “big data” allows auditors not only to do more of the work they have always done but to do it better and faster. Organizations—and their audit teams—now have access to a fount of information that would have been unthinkable a decade ago. Yet even though technology now enables us to view and analyze the full picture, a majority of internal audit teams continue to rely on methods like sampling. Whether this tendency is due to a lack of support or an unwillingness to change, it means that these internal audits are not maximizing their potential or delivering the value their organizations need.

In order to begin to address this gap, this paper introduces the benefits of data analytics and outlines some initial steps internal auditors can take to leverage current technologies and move toward a more data-driven approach to auditing. It argues that with the proper tools, support, and training, data analytics can be an effective way for organizations to expand their auditing capabilities while also freeing auditors from much of the burdensome task of gathering information. This in turn gives auditors more time for the work that adds the most value to their organizations, risk assessment, and analysis.

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