3 Essential Tips To Get The Most Out Of Audit Data Analytics
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.
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.
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. It’s time to get moving.
In this article, we look at three 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. 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 audits on an ongoing basis.
Connevate makes audit analytics accessible to every level of user in the audit team – from advanced users, as well as Excel users – with advanced analytics capabilities and easy to use features. Our Audit Analytics reduces the time it takes to maintain and support analytics being deployed throughout the audit department.