purpose of this memo is to document plausible trends and expectations for disaggregated revenue data

Disaggregated Revenue Analytics

 Purpose: The purpose of this memo is to document plausible trends and expectations for disaggregated revenue data and to identify specific days and locations that warrant further substantive investigation. 

 Data: We obtained a listing of daily sales by location from the client’s IT system. We tested the details for mathematical accuracy, as summarized in the table below:

Procedures: Based on our risk assessment process, we identified the following assertions as significant risks related to revenues/sales:

·         Recorded sales occurred.

·         Sales are accurately recorded.

·         Sales are recorded in the proper period. 

Because Souper Bowl’s operations are solely in the state of Maine, we obtained disaggregated data that reports daily sales by store location and store type. Based on discussions with management and our review of the board of director minutes, we are unaware of any new store locations or other major changes to operations during the year. Therefore, we expect prior year to be a reasonable baseline expectation for this year’s revenues (e.g., similar seasonal trends). Because the business can also be impacted by weather conditions, which vary by year, we also perform analyses that consider changes in weather patterns to predict expected changes from the prior year’s sales. We performed several analytics to identify unusual trends compared to the prior year’s sales, taking weather conditions into consideration. The purpose of these analytics is to identify specific observations (or specific sets of observations) to select for further substantive testing. The analytics that we performed are as follows: 

·         Visualization Analysis #1: Title

[Provide a description of the relationship you expected to observe in the data, along with screenshots of the visualization results. Clearly identify (using circles, arrows, etc.) the part of the visualization that leads you to believe that a specific location/day is an anomaly. Ensure that all tables and graphics are properly labeled (x axis, y axis, etc.).]

o   Results: [In each of the “results” sections, include a brief summary of your findings so that your manager can see (in words) the way that you interpret the visualization screenshots.] 

·         Visualization Analysis #2: Title

o    Results: 

·         [The number of analyses that you perform is up to you. Remember that you want to impress your manager, but you also know that the manager’s time is valuable. Therefore, each analysis that you report should offer new information and conclusions (e.g., avoid repeating the same type of analysis with different coloring, shapes, etc., if the conclusions drawn are the same.) 

Conclusion: Based on the procedures described above, the audit team will pull supporting sales information to substantively test transactions from the following locations and days:

·       This section of the memo can be achieved using lists or tables, but regardless of the style of presentation, it should clearly describe which item(s) you’re recommending that the audit team look into it further (based on all the analyses above). For each item, you should reference which analysis # the item comes from. The item should be a specific location on a specific day, or a sample of certain days from a set of observations that exhibit the same unusual trend based on your analyses above (e.g., if you identify an unusual relationship for Q4 for location #1001, but you can’t identify one specific day or set of days that is driving the unusual relationship, you may choose to sample from Q4 instead). Remember that it takes time and resources to test each selection, so be strategic in your selections and include justification for your decisions in this section of the memo.