Yesterday we started a multi-part post on the importance of building audit data analytics capabilities, together with some “how-to” tips. Our first tip was how this is actually as much of a people challenge as a technical undertaking. One particular “secret” is that a combination of skills are needed to accomplish these analytics projects, and we see many departments make the mistake of assigning a single individual to carry out a project, without sufficient assistance or at least oversight from colleagues that have complementary skills.
In our data analytics consulting practice, we use a Body of Knowledge framework to identify needed skills for a particular project, and then match at least one “expert” with an “apprentice” that is looking to add to these same skills. Together our teams bring excellent qualifications in each of these domains, but it’s rare that they all arrive in the form of a single consultant. That framework was published here yesterday.
Today’s tip is to “Begin with the business objectives in mind, and map from these objectives to available digital data.” Too often, we see compliance and audit teams request data and begin to interrogate it before understanding the data fully or taking steps to validate control totals and/or data completeness. A related mistake is to exhaustively test a single data file without considering supplemental data sources that may yield greater insight or answer related business questions.
A recent example of why to begin with business questions was a Payroll project that we completed for a retail client. Our team was tasked with searching for “off-the-clock” work. If we had focused only on available data files, we could have answered questions about meal breaks, rest breaks, and overtime but perhaps missed other hours worked but not paid. By focusing on the business question first, we identified badge data and cash register data to identify if employees were in the store and ringing sales, yet were off the clock at the time of badge swipes or point-of-sale,
As such, the first step in any data analytics project is brainstorming. You can think of it as part of project planning. During this step, teams should identify the business questions that they want to answer with their analytics efforts, and cross-reference these business questions against available reports and digital data. If existing report(s) fully answer a business question, then a new query may not needed**. But if a report does not currently exist, then analytics should be considered and understanding data sources becomes a key next step. During brainstorming, it is very important to understand the number and complexity and number of data sources that will be needed, and to focus only on a small enough number of business objectives so that the number of data sources does not get overwhelming. It is better to have a series of “small win” analytics efforts, than a larger, less successful project
Tune in tomorrow for tips on how to understand your data better, and how to explore it before building exception queries. In the meanwhile, comments and suggestions are welcome.
Visual Risk IQ
** Note that some audit and compliance teams may choose to build queries that replicate existing reports, to test the report validity. For important reports, this re-performance can provide comfort or assurance that the original report is working.