Sampling has existed as a standard for controls testing since controls testing began. We’ve developed algorithms to tell us how many samples we should pull and how many errors we can have and still pass the control. We’ve even developed algorithms to tell us how many more samples we can test if the control didn’t pass the first time. If your goal is simply to do the minimum to pass a SOX audit, then these behaviors should probably continue. If your goals also include really improving the operations of the organization to make it stronger then a more holistic approach is needed, such as analysis on 100% of the population, rather than a small sample. Most controls analytics do not require a degree in data science, but they do require the controls team begin changing its behaviors. Join us to understand what it takes to begin this change, it’s not as challenging as you might think. Learning Objectives Understanding the advantages of analytics vs sampling How to Identify controls where analytics can be applied Real life examples of controls and their associated analytics How to effect a change