Frnst &Young TION ${?}^m$

Case studies

Analytics mindset

TechWear

Part II:

Required:

Now that you have your data, you need to perform appropriate analytics techniques to inform your risk assessment for the order$-$to$-$cash cycle for TechWear.

Develop an accounts receivable $($AR$)$ trial balance $($by customer and by invoice$)$ as of December $31,2015.$

Recall that beginning AR $+$ sales $-$ sales returns $-$ cash receipts $-$ bad debt write$-$offs $=$ ending AR$.$ As mentioned in Part I, the beginning accounts receivable balance is zero and there are no returns or write$-$offs in $2015.$

Perform the following analyses relating to collectibility risk $($which is the risk the company won't collect money for its sales$)$ on the December $31,2015,$ accounts receivable balance. For each procedure, provide a brief statement regarding your findings.

$2.$ Display the year$-$to$-$date trend in sales and cash receipts by month for $2015($with dollars on the $x-$axis and months on the y$-$axis$).$ Use a visualization to best highlight any concerns about potential collection issues.

$3.$ Compute the year$-$to$-$date days$-$sales$-$outstanding $($DSO$)$ ratio for each month. Show the results numerically and with a visualization. For the latter, use a column chart, also called a vertical bar chart $($with DSO as the $x-$axis and months as the $y-$axis$),$ to best highlight any concerns about potential collection issues.

DSO$=$ ending AR balance for the period $/$ total sales for the period $($year$-$to$-$date$))*$ number of days in the period $($year$-$to$-$date$)$

Develop an aging analysis by customer and invoice using $30-$day increments $(0-30$ days, $31-60$ days, $61-90$ days and $>90$ days$).$ Display this at the customer level with the ability to drill down to the transaction $($invoice$)$ level. Provide a visualization of the percentage of accounts receivable in each aging category at the company level using a column chart $($with percentage as the $x-$axis and aging category as the y$-$axis$).$