Mon, May 22, 2023

The explosion in the use of digital channels and the data they produce have caused a corresponding rise in the use of data analytics across organizations. Despite the many accepted benefits of data analytics – increased efficiency and effectiveness, increased breadth and depth of coverage, continuous monitoring, real-time response, and the ability to discover the unknown unknowns – many organizations do not have dedicated analytics staff.

Effective data management and analytics capabilities evaluate and compare data from multiple sources, trace the flow of transactions, and leverage analytical techniques to validate combined data sets to uncover areas of risk and opportunity. Consider the procure-to-pay process, for instance, in which many different data sources play a part. By making data comparisons, users can pinpoint issues like purchase order dates that are later than corresponding invoice dates or other instances of policies’ noncompliance, controls that aren’t enforced or even approaches to procurement that are merely inefficient.

What about smaller enterprises that may not have more experienced departments to learn from? Some are already engaging third parties in either a hybrid model or in a fully outsourced “analytics as a service” (AaaS) model. AaaS providers offer subscription-based software and services to organize, analyze and present data to enable audit teams to get analytics projects up and running quickly, without the upfront technology and capabilities investments. It’s important to keep in mind that access to appropriate and trusted data sets is critical to enabling an AaaS capability. Many analytics initiatives have failed to realize value due to a lack of access to data of the necessary breadth, size and quality.

Check out these KLplus CPE courses related to data analytics: