During a July 6th webinar on how to become an expert analyzer, Andy Hines, an Audit Partner at Whitley Penn, shared valuable insights into how his firm has successfully embraced audit data analytics (ADA) technology. Below are excerpts from the webinar.
Partner Insights: Audit Data Analytics with Andy Hines of Whitley Penn
What do you see as the most compelling reason for adopting and advancing the use of audit data analytics at your firm?
We started down this road about three years ago at Whitley Penn. We focused on elevating our audits, bringing technology into the audit, and incorporating some of these data analytics in our everyday procedures. One of the biggest drivers behind that was efficiency, trying to gain some realization from our audits and knowing there were areas in our audit taking more time than was necessary. And there were better ways to do it. That's where we started to look for how we can facilitate those better ways.
The other thing is the value, just the time that we could be spending on more valuable work, increasing efficiency and reducing sampling by increasing the use of tests that have a higher likelihood of actually finding error or fraud. You could pick 50 transactions out of thousands. Or you can perform an analytic test that will do a better job of finding that needle in a haystack via anomalies and outliers. That was the biggest reason we went down the path of analytics.
What approach have you taken to implement audit data analytics at your firm?
At first, we did have had the auditor doing everything, deciding when to apply, determining how to apply, and running with that. It didn't work out very well. We did that for one busy season before we decided to look into utilizing champions and then the auditors running it. And we've had a lot of success with that. We have a champion / super-user group that develops the actual workflows and standard set of tests that will be done on each audit. The team then runs it, and the team evaluates the results with the clients.
We have advanced training given to a small set - that super-user / champions group. It's very in-depth, usually a full day where we often bring in a third party, like CCH or TeamMate. We like to some training from the people that make the tool. We also do training each year at least once, sometimes twice, for staff, seniors, managers, and other partners on how to use the tool. It's not quite as intense and in-depth as that superuser group.
The most important thing about the training, especially at the manager and partner level, is understanding what the tool can do, what it's capable of. At the staff and senior level, the training is how to do it and the clicks needed to accomplish that test.
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Thinking about the skill levels of your team members, how many potential data analytics champions do you think you have?
We took the approach of "throw it out to everyone, and see who has a passion for this." If you like working with the data, working with the tools that we have, and it's something that excites you, that's the people that we want to be on that champions team. We used to think that those team members needed 2-3 years of experience in audit to understand. I've gone back forth on that; I don't think that much experience is necessary. I have some staff at Whitley Penn for one busy season, but they like data analytics, the tool, and doing the analysis. That's what we need - the team is the one evaluating the results. It works out better that way anyway because our newer staff are the ones that usually have more time to help.
What advice would you give a firm that’s looking for an analytics tool, such as TeamMate® Analytics?
One of the first things we did was reach out to some of our other firm contacts and asked them, "hey, what are you doing, are there tools that you would point toward." That was our first step in getting an idea of the landscape and what is out there. From there, we liked the idea of a tool that was already Excel-based because everybody was already using Excel.
Interested in learning more about how leveraging Audit Data Analytics (ADA) can provide your clients with insights from teamwork, speed, history, probabilities, consequences, and trust?