Create a Team for Audit Analytics? Part 1

Once your audit team has proven the value of doing analytics consistently, the next question is: Do we create an analytics team and have the team do all (or the majority) of the analytics?

Or should we expect all auditors to develop some levels of analytics proficiency?

Of course, this question often comes a bit further down the trail on the analytics journey, but I think the sooner it is decided, the better.

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

First, Define ‘Analytics’

I don’t mean define it in the sense of whether pivot tables or filtering is analytics; I mean in terms of the entire life cycle of an analytics project, which consists of steps like these:

• Develop testing ideas
• Obtain data
• Do population validation, data validation, and data profiling
• Develop analytic procedures
• Perform analytic procedures
• Validate results
• Review and interpret results
• Create analytic work papers and report findings

When auditors think of ‘analytics’, too many of them think of only developing and performing analytic procedures. For the purposes of this post, I’m referring to the entire process.

In the Beginning…

When a department first launches their analytics capability*, it is usually just one or two people.

*Analytics that go beyond simple Excel procedures like filtering, Text-to-Columns, Remove Duplicates, and simple formulas.

So the ‘team’ really isn’t a team; it’s more of an island, and they are busy trying to figure out how to complete their current project, and don’t have capacity to help others learn analytics; also, they usually have other audits to do too.

So in the beginning, I think, is the best place to start thinking about whether you want to train a few–or have everyone learn analytics together, but at different paces, as projects and opportunities allow.

In other words, do you want 1-2 auditors blazing the trail, and once blazed, try to bring the others along (‘drag the others along’ is probably more appropriate).

Or should you work at increasing everyone’s skills, bit by bit?

In this series, when I refer to ‘analytic auditors’, I mean auditors that are dedicated to doing analytics; they don’t do ‘normal’ audits, only analytic projects. And yes, they do exists in some companies.

Create a Team?

Here’s some pros and cons of creating an analytics team and having the other auditors ‘throw their analytic work over the wall”.

PROs

• Analytic auditors are focused, and have only one job: analytics. They don’t have to juggle audit deadlines which often don’t fit neatly into an analytics project.(See Note 1)
• Analytic auditors get frequent opportunities to learn new skills and sharpen existing ones. They use the same analytic tools and methods frequently.
• Auditors can toss work over the analytic wall, and focus on non-analytic testing or other projects while the analytics are being performed.
• Only a few analytic auditors have to deal with the constant technology ‘churn and learn’ instead of all auditors (who may not have the skills or the interest).(See Note 2)
• More analytics are performed; they are usually more accurate and/or more in-depth than if the entire department was trying to learn and perform analytics.
• This process is easier to execute and manage, as each auditor has a specific and well-defined role: auditor or analytics auditor.

CONs

• Analtyic auditors usually don’t have (or can’t develop or maintain) the deep understanding of the business process that the auditor has. As a result, key insights can be missed.
• Auditors are disconnected from the data, and could miss key insights (and audit issues) that a business auditor would identify by obtaining the data, doing all the validation, and developing/performing analytic procedures.
• Some auditors can feel excluded from the ‘inner circle’.
• Throwing work over the wall can lead to disconnects and misunderstandings, which delay completion of the analytics, and the audit.
• Audits are becoming more data rich, data driven, and technical. As technology, business processes, and cost-reduction efforts (including automation) continue to advance, the amount of non-analytic work in an audit will continue to decrease. Non-analytic auditors will be less marketable, eventually, and potentially less valuable to the company.
• Analytic auditors quickly reach their capacity limits and stay too busy to take on more projects. As a result, key analytic reviews are not performed.
• When the analytics of business partners need to be analyzed, only the analytic auditors can do a decent job, but they are too busy with their current slate of analytic work.

If you go this route, what you DON’T want to do is have one auditor develop the test ideas, obtain data, do all the validation and profiling of the data, and then have the analytic auditor do the analytics, and then the original auditor completes the work paper and does the reporting.

For best results, both (or all the involved) auditors need to have at least a high level of understanding and input into each step. All of the work, including the analytics, tend to be better when the entire team is involved start to finish, at least on a high level.

In my next post, I’ll discuss the pros and cons of requiring all auditors to develop a level of data and analytic proficiency. Read  Part 2.

NOTES

(1) Analytics are hard to complete in an audit for the following reasons: 1) Planning is not started early enough, 2) the data is not requested early enough, 3)  too little time is allotted for analytics, and 4) people too frequently give you the wrong data at least once (that’s a topic of its own).

(2) While most auditors have to deal with technology changes, I’m specifically referring to the churn associated with analytic tools, techniques, and  developments and changes in network, application, file, database, and cloud technology (and topology) that impact obtaining data and analyzing it.

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