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5 Essential Tips To Get The Most Out Of Audit Data Analytics

Data analytics a game-changer for organizations that want to better manage risk.

 

Internal audit departments are increasingly using advanced audit software tools to leverage the vast quantities of financial, operational, and other data now available in their organizations.

 

For too long, internal audit has been greeted with shrugs of indifference in the C-suite. Enter data analytics, and it now has the potential to change that perception and help elevate the function to a new, strategic role in the organization.

 

Most departments have a great deal of work to do in reaching this goal, of course. Vision, commitment, discipline, and the right expertise are all required. Yet, fully 25 percent of the more than 1,100 respondents to Protiviti’s 2019 Internal Audit Capabilities and Needs survey have still not taken their first steps on the audit data analytics path. 

 

It’s time to get moving.

 

In this article, we look at five key considerations for departments, whether they are simply planning their first steps or seeking to embed data analytics more deeply.

 

1.  Raise awareness around the role of internal audit

 

According to the Protiviti survey, “Fewer than one in five organizations report that their audit committee is highly interested in the internal audit group’s innovation and transformation activities.”

 

Clearly,  Chief Audit Executives (CAEs) have their promotional work cut out for them.

 

According to the global consulting firm, it is “incumbent on CAEs to convey the internal audit department’s commitment to innovation and transformation to audit committee members through effective and efficient information-sharing practices and persuasive presentations.”

 

In light of this, CAEs are well-advised to:

 

  • Win buy-in and support for data analytics’ deployment from key stakeholders.

  • Demonstrate the capabilities of data analytics in ways that can be readily understood by non-financial or audit professionals.

  • Raise awareness not only of the benefits of investment and forward movement but of the budget, resource and other constraints faced by internal audit. 

 

2. Establish a shared audit data analytics vision and roadmap

 

Along with C-Suite support, businesses need a clearly-defined strategy for data analytics.

 

The strategy should include:

 

  • A business case
  • A plan for investments in training, tools and skilled resources
  • Expected returns on investment
  • Identification of first-deployment areas in the organization 
  • Measures of success
  • Staff utilization targets

 

3. Will it scale? But seriously…

 

We all know this is one of the most common and sometimes misplaced questions in business, but it’s important to ask here. Internal audit departments are well-advised to effect a staged transition and to budget several years for full implementation. This allows for lessons learned at one stage to be incorporated into the approach for the next. 

 

Start with a pilot audit that’s low in complexity but high in value. Many groups start with a process in procurement. The data’s all there, generally of good quality, and the use of analytics will generate returns on investment that are tangible and, just as important, visible. 

 

Carefully selected and well-planned pilot programs will go far in demonstrating the capabilities of analytics, and the merits of continued investment.

 

4. Ensure access to quality data

 

Your group’s access to complete and accurate data is paramount. This is what enables your in-depth analysis of in-scope business processes. Yet, this is often the most challenging barrier to overcome when adopting data analytics.

 

The heavy lifting is at the front end — identifying data, ensuring accuracy, completeness, and availability, and standardizing it, as needed.

 

Leading internal audit departments often begin with a single business process (e.g. procurement) and work with IT to understand the data. They leverage business intelligence tools, data warehouses, and other tools already in use in other parts of the business to deliver data to internal audit on an ongoing basis.

 

5. Prepare your team

 

Some are concerned about job losses in internal audit as a result of new technology tools (automation) and the specialists needed to support them.

 

Rest assured, the internal auditor’s role is secure. There is no substitute for their experience and judgment, nor is there ever likely to be. 

 

That said, auditors must have a solid understanding of data and a capacity for critical thought. They need to be able to grasp new business processes quickly and use data analytics to create procedures to address the risks they’ve identified. And they must be trained in analytics tools and software.

 

Best-in-class internal audit groups have different approaches to building an analytics-ready internal audit team and incorporating needed specialists. But every auditor on the team should have enough expertise in data analytics to carry out basic data analytic tasks independently for each audit. 

 

The road ahead

 

Data analytics has the potential to transform internal audit and promote the function to a senior strategic role in the organization. CAEs, however, must take pains to ensure that implementation is done in a measured, deliberate and well-planned manner, supported by the right technology tools, personnel, and training.

 

If you are starting the audit data analytics journey, now is a great time to download Unlocking The Power of Data Analytics, your first steps on the road to audit transformation.