The Audit Analytics formation

(Source-ACL blog Author- Mr John Verver)

During the past decade, much of the interest around using data analysis in internal audit has stemmed from some great successes that a relatively small percentage of audit teams have managed to achieve.

The majority of audit leaders want their teams who are still at a very basic level of usage to do far more with data analysis and achieve similar success. So, what’s stopping them?

There are several factors that usually need to be addressed in order to derive transformative and sustainable benefits from data analysis.

In my experience, one of the most critical success factors is a recognition that audit analytics should be a team sport.

In many audit teams, a certain level of success has been achieved—but it is overly dependent upon one or two individuals. Don’t get me wrong, the role of audit analytics “champion” and data specialist who just somehow manages to do impressive things with data analysis is very important. But the picture needs to be bigger than that. For audit analytics to be really beneficial they need to be integrated throughout the audit process. The analytics specialist has an essential role to play, but ultimately it should be one of enablement of others who are less technical—allowing them to avoid the practical challenges and get directly to using data analysis to achieve audit objectives in a better way than ever before.

Technology also has a very big role to play in making audit analytics a team sport.

Not all data analysis products do a very good job of supporting team-based analytics. Spreadsheet tools have obvious limitations in this area, as do some powerful statistical analysis engines. Even looking back within ACL’s own customer base will show a historical pattern of many users working more or less on their own with a single user version of the desktop analysis tool.

Standalone desktop data analysis software has been around for a long time but does have some inherent limitations when the objective is to support a typical modern, collaborative working environment in which team members have widely ranging abilities in using analysis technology. The objective today for audit teams is now often to both share analysis results within the team, as well as with other stakeholders within the organization and to do so in an insightful, visual way.

What does a successful team-based analytics model look like?

1. A technical specialist or “power user” is responsible for developing sustainable processes for:

   • Acquiring and managing data that is securely housed within a centralized audit analytics platform
   • Building and managing a secure library of audit analytics that can be scheduled to run automatically on a regular basis, or on demand when needed by a non-technical team member
   • Harnessing the power of the engine of the audit analytics to access, manage and process very large amounts of data, independently of corporate systems and applications.

2. The non-specialist audit team members use the non-technical , visually driven functionality of the same platform to:

   • View and collaborate on the results of analytics and tests
   • Perform their own analysis, using current generation visual analysis capabilities, to explore and gain insights into data
   • Share findings and results, in a secure fashion, with stakeholders both within and outside internal audit

This approach means that the knowledge and skillsets of the power users are harnessed and preserved for the benefit of the rest of the audit team. The audit team as a whole finally gets to integrate data analysis throughout the audit process.

The benefits of this modern technology-driven model seem clear and solve a problem that has existed in many audit teams for a long time.

It is difficult to play a team sport if all you have are a couple of star players who are unable to pass the ball effectively, which means that others in the team never get to run with the ball!