Mack-the-Auditor Gets Audited! Part 3

This is the third of 3 posts; this post describes how I audited the auditors and my perspective on the whole thing.

Read the first post (background) and the second post (audit results).

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Before You Analyze Data

Before you start analyzing data, you need to 1) know you have the right data, and 2) understand the data and the process that produced it.

This post assumes, of course, that you already accomplished some of the hardest tasks already: figuring out what data you need, where to get it, and actually getting the data. Good luck with that. :)

This post is part of the Excel: Basic Data Analytic series.

Steal from Agile to Increase Audit Analytics

To increase the amount and depth of the analytics performed, steal some agile methods, and apply them to your audits.

If you’re not familiar with agile methods, check out the first 5 topics listed here (just click Next at the bottom of each page; the topics are quick to the point and full of pictures).

Briefly, agile projects are performed in cycles, or iterations, rather than in a long, linear-waterfall fashion, which is: do all planning, then field work, then reporting. Each iteration of the project creates some value and includes feedback, which is used in the next iteration to increase the value of the project.

Auditors, Do Data Analytics or Die

If you’re an auditor, you need data analytic skills or you will die.

Or put another way, if you don’t acquire them in the next 1-5 years, you will no longer be an auditor.

Pretty bold statement, isn’t it?

Why You Must Validate Data

Before you analyze data, you must first validate it.

Otherwise, your analysis may not be accurate, and you may miss some important insights or errors.

This post is part of the Excel: Basic Data Analytic series.

Before analyzing your data, you need to check the following:

• Duplicate transactions do not exist.
• Required fields/key fields do not contain blanks, spaces, zeroes, unprintable characters, or other invalid data.
• Date fields contain real dates, and the range of dates is appropriate.
• Amount fields don’t contain inappropriate zero, positive, or negative amounts, and the range of values is appropriate.
• Each field is stored in the correct format. This prevents data from being converted on the fly into something else unexpectantly (e.g., user ID JUL15 becomes 15-Jul).

How to Perform Population Validation

Do you perform appropriate population validation of the data you rely on in an audit?

Population validation is simply gaining confidence that the data you are using in your audit contains all the appropriate data for your audit objectives (e.g., your server list includes all the SOX servers).

For the difference between population validation and data validation, see Why You Must Validate Data.

So how do you do population validation? Let’s look at an example…