Create a Team for Audit Analytics? Part 2

In the previous post, Create a Team for Audit Analytics? Part 1, I explored the pros and cons of developing an analytics team.

This team consists of analytic auditors who are dedicated to analytic projects; they would NOT typically manage audits or testing that did not include analytics.

In this post, let’s explore another option for managing and growing analytics in an audit department — expecting all auditors to develop a level of data and analytic proficiency.

This is the second post of a 3-part series…

 

Develop Analytic Skills of All Auditors

This option doesn’t mean that all auditors should master all the skills of those on an analytic team, but that all auditors should have a baseline of data and analytic skills, some should be intermediately skilled, and others should be experts. And all auditors should be continuously advancing their skills.(See Note 3)

Most of these PROs/CONs below are just the opposite of those listed for creating a team, with a few twists.

PROs

• Auditors add analytic expertise to their vast business process knowledge, which results in better insights. If they need analytic help, many others are available to help.
• The more highly skilled analytic auditors maintain their business process knowledge.
• No auditor is left behind; auditors sharpen each other and share their insights and expertise, which creates cohesiveness.
• All auditors build their analytic skills to stay relevant and marketable. And they are more valuable to the company.
• The amount of analytic work is spread throughout the department, keeping project loads more in line with auditor capacity.
• More people will have (or will be developing) the skills to audit the analytics of business partners.

CONs

• Auditors have to juggle completing audits while trying to develop and maintain analytic skills. When push comes to shove, the analytics are often dropped or reduced.
• Because some audits do not lend themselves to analytics, auditors may not practice their analytic skills enough to maintain them, or not have enough opportunities to develop new skills.
• All auditors have to deal with the ‘churn and learn’; not all auditors have the interest or capability to deal with the technology. Some auditors will find other jobs.
• During the early stages of the analytic journey, less analytics will be performed as most auditors struggle with the learning curve. As a result, the analytics may not be as accurate or in-depth.
• The more experienced analytic auditors are constantly helping less experienced auditors with their analytics. As a result, the experienced auditor cannot focus as much on completing their own work in a timely manner.
• Creating, executing, monitoring, and adjusting a plan to increase the analytics skills of all auditors take a lot time and effort.
• One or more people have to be fully or partially dedicated to increasing the skills of all auditors, which reduces their personal productivity.
• Management has to do more leading and managing.

If this path is taken, management must decide what constitutes the baseline of data and analytics skills that all auditors must develop.

Personally, at a minimum, I believe all auditors should be proficient in basic and intermediate Excel procedures such as loading and transforming data, intermediate Excel formulas, pivot tables, and Excel fuzzy lookup (this is not an exhaustive list).

I would also expect them to progress from there.

In the final post of this series, I address a third option for managing audit analytics–a hybrid approach. See #3 here.

 

NOTES

 

(3) Think of a baseball team: They all have to be able to catch, throw, and bat a ball (that’s the baseline).

But some have additional throwing skills (pitcher and outfielders) and catching (catcher and outfielders), but everyone has to be an expert in their assigned location (1st base, 2nd base, 3rd base, etc.).

To be successful, you need a mix of basic skills and expert skills, and some people can play multiple positions (purple unicorn).

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