Most chief audit executives (80 percent) want to increase the impact of data analytics in their function, according to new research by Gartner.
The analyst giant conducted a survey of 107 chief audit executives, revealing widespread frustration with the impact of data analytics in internal audit functions. The findings indicate that using data analytics within the scope of an audit engagement only led to materially improved outcomes about half the time.
Data analytics in audit functions
Chief audit executives are increasingly embracing broad data analytics usage for several reasons. A narrow approach often conflicts with their strategic priorities, for instance, many track the percentage of audits leveraging analytics as a key performance indicator.
Additionally, these executives tend to see the identification of data analytics opportunities as something that occurs at the engagement level, which is more detailed than their typical scope of involvement. They may also lack confidence in their technical expertise, whether in data, tools or analytical methods, leading them to rely on data specialists or audit teams to inform them of what’s possible.
“Chief audit executives feel pressure to get better value from their data analytics investments, both to meet growing stakeholder expectations and to secure further budget for continued technology investment and innovation,” said Tegan Gebert, VP, advisory in the Gartner Assurance Practice. “However, to get to greater value, chief audit executives have been focused on better motivating and preparing their teams to use data analytics wherever feasible, which isn’t the right way to improve outcomes.”
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Overcoming data analytics challenges
The problem with trying to use analytics wherever feasible is that not all analytic opportunities are good ones, said Gebert. This broad approach to data analytics quickly hits a point of diminishing returns.
“Once the obvious, high-impact opportunities are addressed, spreading analytics across every audit leads to wasted effort and diluted impact, and it likely puts a strain on the limited capacity of expert digital analytics resources as well.” added Gebert.
In contrast, when chief audit executives deliberately select fewer, high-impact audits and allocate more analytic resources to them, audit teams achieve deeper, more meaningful outcomes.
To improve outcomes, Gartner recommends chief audit executives take personal ownership of data analytics prioritization, using their unique understanding of business objectives, risks and strategic priorities. This involves evaluating potential audit projects not just on the feasibility of applying analytics, but on the necessity and potential impact, specifically whether analytics is likely to deliver significant value or insight.
Chief audit executives should use explicit, structured criteria such as scorecards or qualitative filters to compare and rank audit opportunities based on criteria such as business impact, alignment with strategic goals and the likelihood that analytics will lead to actionable outcomes.
“Once high-impact opportunities are identified and prioritized, chief audit executives should concentrate analytic resources – such as skilled staff, data experts and advanced tools – on these select audits. This enables deeper analysis, higher quality insights and greater overall value,” said Gebert.