Despite the fact that data analytics has been part of the audit conversation for almost 30 years, most audit departments are still struggling with implementing an effective data analytics strategy. The two main contributing factors causing this problem are software and culture. To help everyone understand this issue and how we can all be part of the solution, let’s look at this as if it were an issue in an audit report.
Demystifying data analytics
Auditors are not using data analytics effectively and consistently.
- Criteria - If we consider audit as a process, we have a risk associated with sampling, and our control is the use of data analytic tools to test full populations. Guidance from The IIA requires auditors to have an understanding of data analytics and the associated tools ( GTAG 16 - Data Analysis Technologies).
- Condition – Most audit departments have not established a data analytics strategy or fully adopted the strategy they’ve set.
- Cause - Many departments have failed in their attempt to adopt data analytics because of the software they purchased. Some products require extensive training and constant retraining for users to remain current in the software. We cannot afford to spend our entire continuing education budget on data analytics training year after year.
- Effect - Complicated tools have harmed the audit industry and held the use adoption of analytics back for the last 30 years. They have established a sub-culture of analytics specialists who speak their own language and are often set apart from the rest of the audit team. The vast majority of auditors are not even exposed to data analytic tools.
To help your department embrace the use of data analytics, first establish an effective data analytics strategy:
- Reset the idea that analytics is a complicated mystery
- Provide the entire staff with an easy-to-use, cost-effective tool
- Promote the use of data analytics whenever applicable
- Require justification when data analytics is not used
Corrective action plan
Again, data analytics is not a new topic. Auditors have been talking about it for almost 30 years. We speak to audit departments every day that are trying to figure out how to get their staff to embrace the use of data analytics. Since the two main contributing factors that are causing this problem are software and culture, we can address both of these topics with a corrective action plan.
Data analytics can seem incredibly intimidating to many auditors, but there is really no need. It is not some mysterious skill that only a few select individuals possess. Put simply, data analytics is nothing more than understanding data using a structured approach. The good news is that there is software readily available to do most of the work for you. The bad news is that some software tools are very expensive and too hard for everyone to use.
Not all software packages are created equal, and many departments have failed in their attempt to adopt data analytics because of the software they purchased. Some products, like ACL Analytics, require extensive training and constant retraining for users to remain current in the software. In the real world, our staff is made up of people with varying skill sets, and we cannot afford to spend our entire continuing education budget on data analytics training year after year. Other tools, like TeamMate Analytics, take a much simpler approach. Your department has limited resources, so the application is built with easy-to-complete guides that walk you through the applicable options. To illustrate the point, consider a common analytic test used to find statistical outliers in a data set. Here is the 3 ½ page test script you need to write in ACL Analytics to extract the outliers compared to the same guided test in TeamMate Analytics. For anyone who is not tech savvy, the idea of scripting can be terrifying, so choose an application that everyone can grasp.
A department’s culture also has a huge impact on the adoption of an analytics program. Some will embrace the new methodology, and others will resist. The first step in preparing your department to use data analytics is resetting the idea that analytics is a complicated mystery. The IIA, in GTAG 16 - Data Analysis Technologies, does not say that only 2 or 3 people should be using data analytics. Anyone and everyone should be able to use simple analytic tools.
By perpetuating an aura of mystery and an idea of exclusivity around the use of their complicated tools, software providers like ACL have harmed the audit industry and held the adoption of analytics back for the last 30 years. They have established a sub-culture of analytics specialists who speak their own language (ACL = Audit Command Language) and are often set apart from the rest of the audit team. Many times, when we present a simpler solution, like TeamMate Analytics, to a department with an existing ACL user, the first thing I hear is “oh shoot, I may be out a job”! From a tone at the top perspective, we should promote the use of data analytics on every audit. Even further, we can require audit teams to provide a justification when they do not use analytics. Auditors will have a very hard time trying to justify a less effective testing methodology when an easy-to-use tool is available.