In today’s world, technology is an integral part of data analysis. Data analysis technology provides tools that allow users to sort through mounds of data in order to perform efficient and accurate analysis. These tools are especially useful in performing analysis within accounting departments of colleges and universities. Due to their size and complexity, colleges and universities have a very unique need for data analysis. Colleges and universities process thousands of transactions through their general ledger each month. Data analysis tools can combine data from different sources to allow user’s maximum analysis potential. Proper data analysis tools can assist management in identifying unusual variances, errors, and even fraud.
Below are example analysis procedures that we have found to be useful in our work with colleges and universities. This list is meant to be a series of suggestions to help you understand the capabilities of data analysis tools. Ultimately, the user is only limited by their imagination.
General Ledger
- Identification of manual journal entries for detailed analysis
- Analysis of the number of transactions being entered into individual accounts to determine consistent use
- Search for unusual patterns between individuals initiating transactions and posting transactions
- Analyze monthly fluctuations of account balances
Receivables
- Recalculate the aging of receivables
- Analyze trends in receivables, receipts, and aging
- Search for invalid student accounts (duplicate) included in the receivable balance
- Analyze all manual entries to accounts receivable
- Analyze cash receipts not paired with a receivable
- Search for missing student information
Fixed Assets
- Identify fully depreciated items and assets valued above replacement costs
- Identify items that were not properly capitalized according to the capitalization policy
- Compare assets useful lives by category
- Extract assets with useful lives or deprecation rates beyond established norms
- Compare capital expenditures to budget
- Identify capital projects with large unexpended dollars
Accounts Payable
- Compare voucher or invoices posted against purchase order amounts
- Identify vendors paid more than 12 times in one year
- Identify vendor concentrations
- Search for inconsistent purchase prices of identical items between departments
- Analyze all manual entries to accounts payable
- Identify invoices being applied to multiple purchase order authorization
- Analyze disbursements by department by month for unusual trends
- Search for duplicate purchase orders, invoices, and amounts
- Identify invoices with similar descriptions
- Analyze trends among the individuals preparing purchase orders and approving purchase orders
- Find invoices without purchase orders
- Compare recurring monthly expenses to paid invoices
- Look for lost discounts not taken
- Analyze scheduled receipt date versus actual receipt date
Procurement Cards
- Search for purchases made on the weekend
- Summarize by vendor
- Search for round dollar amounts
- Identify purchases close to dollar limits
A-133
- Analyze factors impacting student eligibility
- Compare actual assistance received to approved amounts
- Search for incomplete data
- Extract transactions of assets funded by federal grants to ensure compliance with grant requirements
- Sort contracts database by contract or cost type to test compliance with government contract terms
- Test whether grant revenue disbursements are properly used
Other
- Compare addresses between databases (payroll, vendors, students)
- Selecting samples
- Calculate financial ratios
- Create custom balance sheets, P&L Statements, etc.
- Compare summaries by major accounts
As previously stated, the procedures listed above are examples of procedures that can be performed using data analysis. This list is intended to serve as a starting point for users as they plan procedures to match their specific needs.
Dean Dorton Allen Ford, PLLC has expertise in data analysis procedures. We have resources available to assist you in your data analysis needs, whether that be coaching staff in the use of data analysis tools, brainstorming procedures, or actually performing the analysis. Please contact Hunter Stout (hstout@ddafcpa.com) or Justin Hubbard (jhubbard@ddafcpa.com) if you would like additional information.