In the previous post, Create a Team for Audit Analytics? Part 2, I explored the pros and cons of expecting all auditors to develop a level of data and analytic proficiency.
These auditors would continue to do audit testing that involves analytics as well as testing that does not involve analytics. In addition to keeping up their business skills, they would be learning and upgrading their data analytic skills.
In the first post of this series, I reviewed some of the pluses and minuses of creating a dedicated analytics team.
However, a third option exists, which is sort of a hybrid between having dedicated analytic auditors doing all the analytic work and requiring everyone to increase and develop their data and analytic skills.
Let’s explore the hybrid method in this post, and wrap up the series with a few final thoughts.
This is the third post of a 3-part series…
In the previous post, Create a Team for Audit Analytics? Part 1, I explored the pros and cons of developing an analytics team.
This team consists of analytic auditors who are dedicated to analytic projects; they would NOT typically manage audits or testing that did not include analytics.
In this post, let’s explore another option for managing and growing analytics in an audit department — expecting all auditors to develop a level of data and analytic proficiency.
This is the second post of a 3-part series…
A recent IIA article on building an analytics function in internal audit is dead wrong.
At least on one major point, anyway. And it’s a big one.
As the tombstone reads, this point is D.O.A (dead on arrival, or more specifically, dead on analytics).
The article, Building a data analytics program, requires IIA membership to view, and is located at https://iaonline.theiia.org/2017/Pages/Building-a-Data-Analytics-Program.aspx (that’s actually good, as it means a lot fewer people will ever read it).
Your management says it wants more analytics, but does it really support analytics? Here’s 10+ signs that indicate that your mgmt:
- Does NOT knows what it takes to get analytics off the ground
- Believes that analytics multiply like rabbits, naturally
- Is NOT willing to make the adjustments required to deliver and sustain real value.