Quote of the Weak – Auditor Judgment

We recently acquired a new data analysis tool in our department, which prompted some of our newbie auditors to share their misunderstanding of auditor judgment and basic data analysis.

A group of less experienced and newer auditors were selected to try out the new tool before it was rolled out department-wide.

 If you’re not familiar with my ‘Quote of the Weak’ series, I described it briefly in About. For a list of posts in this series, see here. If you haven’t seen one of these posts before, it’s because I haven’t had one in a while…

When I heard this tool was coming, I wondered why we are lowering our tools to the level of some of our struggling auditors rather than raise our auditors’ skills to use our current tools, but that’s another topic entirely.

From what I heard, someone in senior management recommended the tool, so we are spending decent money to acquire it and roll it out. A recent rumor says that this tool is the silver bullet to help our newbie auditors. But I digress.

Anyway, this tool hides all the code behind buttons, so the person using it doesn’t know how it works (or whether it works), which doesn’t really matter, because the auditors using it won’t know the difference anyway. The name of the tool doesn’t matter, as several of this type exist in the market.

The auditors were asked to try the tool on live data that they were currently auditing. No specific instructions were given to them other than to “try it out and see what works”.

One team member (slightly more experienced that the rest, and with more common sense–let’s call him Sid) used the tool to redo some of the audit testing that he just completed. He tried most of the options, and in the end, he told audit management that he didn’t see the need for the tool as he could do all the analysis in our existing tools.

During the tool testing, Sid had watched the others in the group do sorts, filtering, sampling, and simple statistics. No joins, fuzzy lookups, or anything other than the simplest of commands.

After one auditor clicked a couple buttons and got immediate results, she said, “Wow, this tool totally eliminates the need for auditor judgment and critical thinking!”


In other words, said auditor no longer needed to understand the data, how fields in the data related to each other, what values are appropriate in some fields, but not others, etc.

She no longer needs to ponder what tests were most applicable to the audit objective and could be performed on the data at hand. No, just load the data and click a couple buttons! So how does she know which buttons to click so their magic appears?

If auditor judgement and critical thinking aren’t needed, then why is she needed? She needs a tool, but no judgment?

Before Sid could respond to auditor #1’s bizarre comment, something else happened. Another auditor ran the statistic command, which resulted in many highlighted fields indicating blank values, negative values, values of zero, summed values, and other items of interest.

“This is cool, but what do I do with this information?” auditor #2 asked, not realizing that he just contradicted auditor #1’s previous statement.

Auditor #1 leaned over and peered at auditor #2’s results, and remarked, “No clue.”

“And I can understand why,” Sid mumbled to himself as he sulked away, shaking his head.



Filed under Audit, Data Analytics, Humor/Irony, Quote of the Weak, Technology

4 responses to “Quote of the Weak – Auditor Judgment

  1. John

    Uhg, it took my second pass to catch quote of the WEAK. Got a good chuckle regardless, both at the scenario and myself.
    Sharing now cause… me. There are always 2 types of people. I am reminded of an audit in which I noticed someone using a bunch of sum ifs in an excel report. I asked why he wasn’t using a pivot. When he blankly stared up, I then showed him how, he was ecstatic at the 2 days a week I had just saved him trouble shooting (Sid). A week later nearly the exact same scenario played out, but the person was upset that they would lose 2 days of this mindless work and be forced to do something more productive (Auditor 1).
    Auditor 2 gets a pass in my book, they knew to at least ask what does this mean.
    Thanks for this blog.


    • John,
      Thanks for your input. I hear you on giving auditor 2 a pass, but I guess I’m not as gracious. I’m thinking one of the first things an auditor should learn about data analysis is how to review the statistics of the data (sums, how many zeros, blanks, negative amounts, which codes a field contains (A, B, D, but not C). If you don’t understand those items, I don’t think you can read the overall story the data is telling you.

      Of course, I know this auditor, how long they’ve been auditing, all the times we have explained simple data analysis methods, etc. So I’m biased with the extra info that I know but wasn’t in the post.

      Did you see the ‘Auditor Struggles’ series starting at https://itauditsecurity.wordpress.com/2019/10/15/auditor-struggles-part-1/? It has more Excel pivot adventures (not).


  2. BLM82

    Interesting I’ve faced a similar scenario. I suppose the reason for exploring the alternative tool is drive usage of data analytics, which is noble, since many “non-technical” auditors get intimidated by the mainstream data analytics tool and hence don’t get the value of analytics. The new tool would probably supplement the existing tool for that kind of auditor, perhaps they can one day graduate to the more advanced tool. There’s no alternative to understanding the data and what you want to do with it though…


    • B,
      You are exactly right; mgmt is trying to drive more data analysis. However, as I have told them many times, it won’t work because they are not addressing the real problem.

      If auditors won’t (or can’t) use Excel to do basic analytics (see my basic data analytic series), they won’t be able to use a tool that makes that analysis easier by pressing a button, and here’s why….

      If you don’t understand WHY you need to do a particular test/analysis, you won’t be able to interpret the results. Also, if you don’t understand your data (statistics and how each field and values in those fields relate to each other (or don’t) and why), your testing will be just that: testing. I did X and got Y, but I have no clue what it means or whether something is broken, stolen, inefficient, or corrupt.

      I think this is generally true, but it holds especially true for the auditors that I refer to in the post. We have provided documentation that explains how to validate the date, do the basic tests you need to do every time, some other tests to consider, and how to do them, and how to interpret the results, and multiple people have walked them through it using THEIR own data in a REAL AUDIT. We also explain that each audit requires an understanding of the data and critical thinking so the results are interpreted correctly.

      They still don’t get it, but don’t seemed to be bothered with that, and they fumble along. I believe data analysis is like drawing; you can either do it or you can’t. Sure you can get better, but if you can’t draw anything that looks like a cat, you probably should focus on other things.

      Trust me, we have worked extensively with this folks. I just haven’t found a trump card yet that makes a difference.

      So to sum up, some people will never understand data analysis, but many are just complacent. If mgmt doesn’t set smart goals for people to get better and hold them accountable, a lot of folks stay pretty much where they are, and the bulk of the hard work gets pushed to those who can do it, which is unfair. If tough goals are monitored, those who can’t do it will find another profession. That’s a tough statement, but those who have done just that are much happier doing a job they understand and enjoy a lot more.

      In the end, the burden is on mgmt, not the auditor, which is what the IIA calls ‘audit supervision’.


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