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RAPPORT

Behind the data

While organizational analytics can yield powerful insights, they may also be a source of risk.

CAEs and internal auditors just beginning to audit the organization’s use of data analytics may welcome some words of wisdom to ensure favorable results. The experts offer several suggestions:

  • » Consider the advantages and drawbacks to building analytics capability in the existing team versus acquiring talent.
  • »  Engage with management, especially in the planning process. “If they are not involved, the process may get started, but it is less likely to be sustainable,” Rudenko says.
  • »  Start small. Understand the process and break it in to manageable, auditable parts.
  • »  Have realistic expectations.While the internal audit function may hope to spring from level 1 to level 4 with regard to its ability to use data analytics effectively in the audit process, the reality is that it takes a lot of effort just to go to level 2. The level of internal audit’s understanding and capacity to use data analytics does influence how to effectively audit a control process with heavy reliance on similar routines.
  • »  Take the time to work through the false positives that are likely to arise during the initial execution of the audit testing routines.
  • »  Look for a win. “Start by auditing candidates, or processes, where you are likely to gain success,” Windeknecht advises, “then build on that success.”
  • »  Look to local IIA chapters for shared experience/expertise and libraries of data analytics routines and audits of data-analytics- driven control processes. Some have formed discussion groups specific to data analytics.
  • »  Have the end game in mind. “Know who is relying on the data and what they are using it for,” counsels Robert Berry, executive director of Internal Audit at the University of South Alabama.
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