Deanna's Delights, Inc.: Data Analytics in the Audit of the Procurement Cycle

Abstract

Auditing has increasingly focused on data analysis techniques to examine large data sets. This now occurs in all three phases of a financial statement audit: planning, testing and gathering evidence, and final review. Many audit activities use limited or cleaned data and guide students through routine data analytics processes. This case presents students at various levels of mastery of data analytics, suitable for an introduction to the concept and for more experienced students. It introduces the concepts of auditing and internal control processes to introduce them to the need for critical thinking and problem-solving. Students are given a complex case and determine their own testing procedures. They then perform those tests on the data to learn the value and limitations of data analytics in audit risk assessment.

Headnote

Journal of Multidisciplinary Research

Abstract

Auditing has increasingly focused on data analysis techniques to examine large data sets. This now occurs in all three phases of a financial statement audit: planning, testing and gathering evidence, and final review. Many audit activities use limited or cleaned data and guide students through routine data analytics processes. This case presents students at various levels of mastery of data analytics, suitable for an introduction to the concept and for more experienced students. It introduces the concepts of auditing and internal control processes to introduce them to the need for critical thinking and problem-solving. Students are given a complex case and determine their own testing procedures. They then perform those tests on the data to learn the value and limitations of data analytics in audit risk assessment.

Keywords

audit evidence, data analytics, analytical procedures, risk assessment

Case Information and Implementation

Overview

This case serves as an in-class activity or an outside of the classroom exercise. Students do not need to have completed an audit course prior to completing the activity. However, the case presumes that students understand intermediate accounting concepts as well as risk assessment and internal control concepts.

Faculty or students can complete the data analysis using a number of different programs based on their preference or competence. Most of the solutions provide reference to functions or techniques in Excel. However, this is to guide the instructor to the general type of analysis required. The case is suitable for use with students having a wide range of prior experience with data analytics and related software. The technology used can be as simple as Excel pivot tables for less experienced students. It can also be Power BI, Tableau, Alteryx, or other more sophisticated data analysis software for advanced students.

While instructors can assign the case to students individually, using this as a team assignment is generally more beneficial. This allows the students to discuss data analysis strategies and interpretation of the testing results. Using teams also provides an opportunity for audit brainstorming regarding fraud or other risks in the case. Implementation guidance will presume instructors assign the case to student teams. However, implementation for individual assignments requires minimal adjustment.

Instructors may introduce the case as part of a lecture on these topics or use it to assess the students' mastery of the concepts. Instructors should assign students to teams prior to disseminating the Student Case Materials. One key aspect of this case is that each team can focus on a different concern based upon their own risk assessment and brainstorming. By having a data set covering much of the non-inventory procurement cycle, students can choose to focus on a variety of accounts and transactions.

The assignment includes three basic steps: a preliminary risk assessment and fraud brainstorming step, a data analysis step, and a final step to assess the impact of testing findings on the remainder of the audit. Instructors should assign the first step with enough time for students to read the case and complete their brainstorming prior to working with the data.

In-Class Use

For use of the case as an in-class activity, instructors should provide students with the Student Case Materials in Appendix A at least one class period prior to use in the classroom with the data set to allow completion of Step 1. The more time between introduction of the case and data analysis in the classroom, the higher the expectation can be regarding team brainstorming of risks and means to assess them. Also, the delay between introducing the case materials and the activity allows more time to ensure all students have access to and understanding of the technology that they will use to evaluate the data set.

On the day when students will use the data set in class (Step 2), they should sit together in their teams for discussion purposes. Ideally, instructors can allocate teams in a way that limits the possibility of overhearing other teams. However, the variety of areas to explore within the data set make it unlikely that multiple groups are assessing the same risks using identical means. You can provide the data set through your LMS or links to a faculty or class web page. Instructors should use password or time-access restrictions to ensure that all teams have the same access to the data. At the conclusion of the class or activity time, teams should take time to complete Step 3 and evaluate the analysis they have completed in light of the concerns initially raised in the case materials. The instructor can either use the questions in the case as discussion topics or require a written response. The case asks four questions:

1. What specific aspects of the cycle did you choose for testing?

2. What made those aspects most relevant or in need of testing?

3. What specific tests did you perform on the data and what was the goal of the tests?

4. What are your findings and what conclusions have you drawn regarding additional substantive testing needed in this area?

Outside-Class Use

For use as an outside assignment, instructors should provide the Student Case Materials first, even delaying the release of the data set until students complete Step 1 and plan their strategies. Instructors should encourage teams to brainstorm risk and testing ideas before they gain access to the data set. Instructors may require teams to submit a written planning document or use other methods to assess that students focus on addressing specific audit objectives rather than simply "playing" with the data. Once instructors are satisfied that teams have planned their testing sufficiently, they can provide the data set for Step 2 as with in-class use. Teams should have enough time to complete testing and evaluate results, forming conclusions about the need for additional testing. As with in-class use, instructors may assign Step 3 as a written risk assessment memo or use other means to ensure that teams have completed this last step.

Materials Provided

The case materials present a narrative of the company and its procedures entitled Student Case Material. This narrative enables students to conceptualize the data and assess risk and internal controls prior to working with the data. The case materials provide enough detail for students to understand the overall firm operations as well as the specifics of the non-inventory procurement cycle.

The case also includes a data file in Excel. This file provides several data sets for use in planning and performing the testing:

1. A complete three-year trial balance of Deanna's Delights,

2. A monthly budget of the non-procurement expense accounts for the current year,

3. A list of vendors with vendor codes, names and addresses,

4. list of Accounts Payable employees with employee ID numbers, names and addresses,

5. A transaction set for the current year with over 1,200 entries, including vendor codes, invoice numbers, processing and payment dates, expense accounts, and employee ID for both processing and approving the transactions.

The individual worksheets provide a means of creating relationships for more sophisticated data analysis. The transaction set has enough information to link to vendor and employee data. Depending on the experience and competence of the students working with the data, joining the data may be completed by the instructor prior to using the case or by the students as part of the activity. For simple Excel analysis, =XLOOKUP functions can be used. For Power BI, Tableau, or other software, the tables can be related by unique identifiers.

Regardless of the method of implementing the case, instructors can discuss the general background of the case as explained in the Teaching Notes to help students focus on the overall audit risks, prior to diving into the data set. It is helpful for students to have an understanding of overall risk assessments and more specific control risks within the procurement cycle.

Teaching Notes

This case is an extension of a previous teaching case called The Impossible Interview (Souza et al., 2021). The same fictional company is used, however the focus that case was testing through client inquiry as opposed to data analytics of expense accounts as here.

Case Learning Objectives

The objectives of this case focus on introducing students to the complexities of audit risk assessment and data analytics. The data set, in conjunction with the Student Case Materials, provide students with a more realistic setting to learn the importance and difficulty of developing effective analytical procedures for planning and assessment. While audit firms are continually increasing their use of technology and data analytics, this has caused some concerns for the skills and preparedness of the staff working with them. The American Institute of Certified Public Accountants (AICPA) considers data analytic skills essential to the profession and has included them in the CPA exam (2023). Integrating data analytics into the classroom has become a priority for the AICPA (2022), accrediting bodies (Association to Advance Collegiate Schools of Business - AACSB, 2022), and academia (Falgout et al., 2024; Xu, Liu, & Krahel, 2024; Losi, Isaacson, & Boyle, 2022).

This case provides students the opportunity to develop data analytics skills in a setting that encourages them to think critically about the problem. It is recommended that instructors provide some materials related to the development of an analytics mindset or approach to help students structure their approach to the case. EY (2021) provides a model that focuses on (1) asking meaningful questions; (2) extracting, transferring, and loading relevant data; (3) applying appropriate data techniques; and (4) interpreting and sharing the results.

Upon completion of the case, students should be able to:

1. Identify factors indicating a high risk of material misstatement.

2. Identify fraud risk factors in a financial statement audit.

3. Brainstorm with teammates regarding risks or material misstatement and fraud in an audit and appropriate steps to take to address those risks.

4. Understand the complexities of using client data for analysis.

5. Analyze information from multiple sources for consistency or confirmation.

6. Discuss the implication of audit findings for the remainder of the audit.

This case allows students to work together to evaluate an intentionally high-risk case. It provides an opportunity for students to learn for themselves the difficulties of identifying relevant audit objectives and testing data to address those objectives sufficiently. Finally, the case prompts students to consider the impact of fraud risk on a financial statement audit.

General Background of Deanna's Delights, Inc.

Deanna's Delights, Inc. (DDI) is a fictional non-issuer company headquartered in the Philadelphia area and founded in 2010. The company offers full-service bakery items, baking equipment sales, and baking classes. It has four locations along with a headquarters/warehouse location. It has reached the $10,000,000 net sales mark for the first time. However, the growth has led to problems with cost management and timely budgeting. As a result, cash flows are not up to expectations but client staff have not had time to determine the causes.

Students are assigned to an "audit team" of DDI's audit firm, Braun, Ellis, Garibaldi (BEG). BEG is a regional accounting firm focusing on privately held companies. The case addresses the concerns of the DDI staff regarding the lower-than-expected cash flows. Students are informed that other audit team members are evaluating the possibility of misstatements, fraud, or simple cost inefficiencies in the sales, inventory and payroll areas. The students are expected to focus on the non-inventory procurement cycle to consider control weaknesses and unexpected expense variations. The data set provides a sufficiently large number of transactions for students to focus on overall trends or specific expense areas.

In addition to the data set, the Student Case Materials provide background on the organization of DDI, descriptions of procedures in the procurement cycle, and a partial trial balance with budget and actual balances. Teams should be able to use the case material to develop a preliminary risk assessment that will guide their data analysis.

Case Solutions

The data set includes over 1,200 transactions covering 38 expense accounts. All invoices are for the current year; however, some payments are not made until the following year. While the list below of items embedded in the data is extensive, students may find other concerns or issues as well. To assist instructor review, a spreadsheet with the embedded exceptions is provided.

Preliminary Risk Assessment

The Student Case Materials contain enough background for students to identify several potential risks within the non-inventory procurement cycle. Note DDI has received the invoices for goods and services that the data set focuses on. Therefore, although they may identify risks in the initial ordering process, they will not be able to test those risks with the data set presented. While students may consider any number of risks within the cycle, those risks that can be tested include the following:

1. Fictitious or unapproved vendors - these can be tested by reviewing the Vendor List to ensure that all approvals are by Steve Weimer or Deanna Long. Students can also verify that the Miscellaneous vendor is only used for approved transactions.

2. Unapproved or unauthorized transactions - students can test for incorrect or missing approvals on the Transaction List by noting the authority level of the AP employee that approved the transaction. They can also test that no AP employees are being paid through this system as Payroll should handle employee reimbursements.

3. Inadequate segregation of duties - students can test that transactions are processed and approved by different AP employees on the Transaction List.

4. Missing or duplicate transactions - students can verify that the Transaction List is complete by reviewing the unique Payment IDs. They can also test for duplicate payments or payments recorded out of sequence with the Transaction List.

5. Insufficient cash management - students can test the due dates of payments and any discounts available to ensure the timely payment of vendors by matching payment terms on the Vendor List to payments on the Transaction List. They can also verify that payments are only made on one of the two weekly payment runs.

6. Incorrect classification of expenses - since DDI has two distinct classification policies, students can verify both that the Miscellaneous vendor is only used for approved transaction amounts and that the Repair and Maintenance account is only used for approved invoice amounts. The information is available on the Transaction List.

Again, with the complexity of the data set and case materials, students may consider other controls to test beyond this list. Some of those risks may be testable. For those that are not, students could be encouraged to consider how to test them and include that information in their Summary Risk Assessment memo for Part 3 of the case.

Initial Transaction Testing

Prior to any control testing, the students should determine tolerable exception rates for the various tests. As this case provides the complete population to be evaluated, sampling methods and projections are not required. However, students should still have an idea of what will constitute an acceptable level of exceptions for the controls. Comparing the actual exception rates to the tolerable rates should be part of their concluding risk assessment task. The Transaction List data set is initially sorted by invoice date. However, students should re-sort the data to look for specific processing concerns.

Completeness of Payment Data and Existence of Expenses

Students should perform initial reasonableness checks to ensure that there are no missing payments or duplicate payments. There are no gaps in the payment numbers, and all payments are in chronological order, ranging from PMT 45210 to PMT 46420. As such, there appears to be little risk the data set is incomplete. However, students should verify this for themselves prior to performing other tests. The payment numbers are in a text field, so gap testing will require extracting the number portion (such as with a =RIGHT() function in Excel) in order to easily search for missing numbers.

Five duplicate payments (with the same vendor, invoice number, and amount) were processed by different AP staff members. Students can find these on the Transaction List using filters or pivot tables for vendors (in Excel or Power BI) or use similar processes in other programs. Company policy is to spoil the invoices upon payment and require supporting documentation of delivery to prevent duplicates, which should have prevented this. While the exception rate is only 0.41%, it does raise concerns about the consistent application of controls and the risks of poor cash management.

Some students may note that there are 10 AP employees, counting the manager and two assistant managers, for only 1,211 annual transactions. While it is true the staff processes additional payments for inventory and other items, the department is still overstaffed by most reasonable measures. This may have contributed to these exceptions. Some students may consider the overstaffing to be a control weakness instead of merely a matter of inefficiency.

Classification of Payments

The company has two specific policies regarding the classification of payments in the data set. The first is the requirement that any use of a miscellaneous vendor is for amounts under $1,000 and not for recurring items. None of the payments to the miscellaneous vendors violate the classification requirements. Students should verify this by filtering the data on the Miscellaneous vendor (VND 009999) and reviewing the transactions. Note that most of the transactions for these vendors are classified as Other Miscellaneous Expenses (Account 6609). Students may try to verify this control by looking at the account, not the vendor. However, there are several payments to miscellaneous vendors for other expenses and several entries to Other Miscellaneous Expenses from regular vendors. As the control is that payments to the vendors cannot exceed $1,000, testing the account is insufficient.

The second classification policy is that any items expensed as Repairs and Maintenance Expense be for amounts under $1,000. Here, students should focus on the account more than the vendors as with the previous policy. Testing here will note that two transactions classified as Repairs and Maintenance Expense (Account 630x) are over the capitalization threshold. Both of these transactions were reviewed and approved. Again, the transaction exception rate is less than 0.5%, which students may view as tolerable. The dollar misstatement is $12,637 of the $238,348 total of the Repairs and Maintenance Expense, a greater than 5% overstatement of the account balance.

However, there are an additional 13 pairs of transactions that appear to circumvent this control. In each case, two invoices to the same vendor for work at the same location are dated within 3 days of each other. Each invoice in the pair is below the $1,000 limit. However, taken together, each pair exceeds the limit. Students who sort or filter the data by location/vendor or vendor/date may notice this pattern and recommend additional testing. Counting all of these as exceptions increases the exception rate to 3.7% and the dollar misstatement of the accounts to $30,305 (approximately 13% of the account balance). More seriously, these appear to be intentional violations of the controls as opposed to simple errors. In evaluating the control weaknesses, students should note this difference. It is important to note to students that this anomaly cannot be considered an exception yet. Further testing that examines the actual invoices is required to determine whether these are intentional violations or merely coincidences.

Control Testing

The Student Case Materials describe several specific control activities related to the data set. Students may have selected some or all of the following items to test. Note that students will need to discern whether an item is really a potential control weakness or merely an inefficiency in the AP system.

Proper Vendor Approval

All vendors must be approved by either Steve Weimer or Deanna Long prior to use by DDI. Students can verify that all vendors were appropriately approved by reviewing the Vendor List for the name of the approver. The timeliness of the approval requires students to match the vendor approval date with the earliest invoice from that vendor. This can be completed with a =XLOOKUP() in Excel to bring the approval date into the Transaction List or with a JOIN in Power BI and other relational software. By doing this, students will find that all vendors have been properly and timely approved, with no exceptions.

Proper Authorizations

All invoices must be approved for payment prior to being paid. This approval varies by the dollar amounts involved. The approval limits are included in the employee data set. There are no exceptions where an invoice was approved by someone not authorized to approve it. Students should verify this by filtering the data on transaction amount. As the authority to approve the transaction is based on the invoice amount, it is the amount not the approver that determines whether the control has been followed. Students that filter, or otherwise test, based on approver will find that each manager approved invoices ranging from under $100 to their respective limits, providing indirect evidence the control worked effectively.

By filtering on amount, students will gather direct evidence of the control effectiveness. All 29 transactions over $10,000 were approved for payment by Ben Farmer. (There were no transactions over $100,000.) All 45 transactions between $5,000 and $10,000 were approved by either Ben Farmer or Charlotte Rodriquez, the Assistant AP Manager. The remaining transactions were approved by Livia Garcia or one of the others as per policy.

Appropriate Segregation of Duties

As a general personnel control, authorizing vendors is separated from authorizing transactions. Payments are made on approval of Steven Weimer, who has no transaction processing authority in AP. Reconciliations are performed by Mr. Weimer, based on payments made by AP staff. Prior tests of vendor and transaction approvals are described above.

One area not yet tested is the segregation of transaction approval from transaction processing. The AP policies explicitly prohibit one employee from approving and processing the same transaction. This requires students to compare the Processor and the Approver on the Transaction List to ensure that these are different employees.

While the policy does not specify, those with the authority to approve transactions should not be processing any transactions, even those approved by another manager. The level of staffing (or overstaffing) of the AP department makes it unlikely that there would ever be a lack of processing staff available. This means there are two controls that could be tested in this area: (1) that no staff member processes transactions that he or she has approved and (2) that those with approval authority do not process any transactions.

To test the first (explicit) control, students should compare the employee numbers in the Processor and Approval columns. A logical test in Excel (FIF(/Processor]=/Approver]) ) or any other software should identify four instances where the same AP employee both approved and processed transactions totaling $6,991, for a 0.3% exception rate. This employee is the second Assistant AP Manager, Livia Garcia. All four of the transactions were under her approval limit. However, processing the transactions at all constitutes a control exception.

For the second, implicit control, students can simply filter the Processor column for any managers from the Employee List to detect that the same Assistant AP Manager also processed a fifth transaction that had been approved by the first Assistant AP Manager, Charlotte Rodriquez. The total of the exceptions for this test total $10,991, a 0.4% exception rate, covering 0.5% of the total dollars processed during the year.

Controlled Payment Runs

The AP payments process includes both controls for financial reporting and operating effectiveness. This is most clearly noted in the controls of payment runs. Operating effectiveness and cash management policies mandate that discounts be taken whenever available and possible. Additional cash management and financial controls require AP payments to be made in one of two payment runs per week on Tuesdays and Fridays. While any testing in this area can only indicate a potential control violation, many students will likely test these controls, as they are suggestive of inefficiencies or the overall function of the AP department.

Testing for discounts requires students to match the discount terms from the Vendor List to the individual records in the Transaction List. Next, students will need to identify those with discounts available using a filter on the Payment Terms (222 of the transactions have discount terms). For these transactions, students will need to extract the discount percentage and period from the Payment Terms field using text functions such as =LEFT() or =MID() in Excel or similar functions in other software. Once they have extracted the discount percentage, students should calculate the net amount owed to compare to the actual payment amount. Students will note that DDI failed to take the discounts on eight transactions, resulting in $138 in missed discounts. This translates to a 3.6% exception rate, but only 0.06% of total dollars eligible for discount.

However, to determine the actual control issue, students will need to take the testing one step further. Failure to take the discount could be caused by paying the invoice after the discount period and therefore missing the discount period. It could also be caused by paying the invoice timely but simply failing to deduct the discount. The first scenario could be a situation where Steve Weimer intentionally did not have the invoice paid in time to take the discount for cash management purposes. As noted in the Student Case Materials, "It is DDI policy to make every effort to pay invoices within any discount period offered." Intentionally missing the discount as part of a larger cash management policy would actually demonstrate the effectiveness of the control.

The second scenario would not be consistent with company policy or effective cash management controls. To test for discounts not taken when available, students will need to calculate the end of the discount period based on the Invoice Date and their extraction of the discount terms from above. By comparing the end of the discount period with the actual Payment Date, students would see that only one invoice was paid timely but without a discount, resulting in a loss of $13. This equates to a 0.5% exception rate and a minuscule dollar loss.

To test to the controlled payment runs, students will need to calculate the day of the week the payments were made on using =WEEKDA Y () in Excel or a similar function in other software. All payments should be on Tuesdays (weekday 3) or on Fridays (weekday 6). Filtering on these days will show that there are no exceptions to this policy.

Budget-to-actual and Related Analytical Procedures

A monthly budget is provided for the current year for the expenses included in the data set. Students may want to compare actual amounts with the budgeted amounts to look for unusual variances. It is important to note that the staff of DDI acknowledges the budgeting is not managed well. Students can see this for themselves as they examine the budget file. Many of the expenses, with the noted exceptions of utilities and accounting services, are budgeted for constant amounts every month. Many of the accounts are at least slightly over budget. The rent on Store 3 is budgeted for $100 less than actual every month, implying that a rent increase was not updated in the budget. That is not to say the budget provides no assistance in evaluating the expense accounts. Rent Expense for Store 2 and Store 4 each have a payment one order of magnitude too large.

For students to use the budget most effectively, they need to create a Pivot Table or similar construct to total expenses by account and month. The use of Excel's Data Model or other relational software techniques would allow budget and actual numbers to be combined in the same analysis. Students may even want to analyze the amounts by location, using the Sub Account column to identify any trends by store.

Potential Fraudulent Activity

While the focus of this case is risk assessment and control testing, fraud assessment is a necessary component of this. The data set does not provide any explicit examples of fraud such as fictitious vendors or employees. As noted above, it does provide evidence of the potential circumvention of controls over transaction authorization and classification.

Additionally, the Transaction List has been seeded with six suspicious transactions. One of the weaker controls in the AP system is the use of the "Miscellaneous" vendor to process small transactions. While these transactions were shown to be small in dollar terms, they do account for 105 of the 1,211 transactions (8.7%) and $54,452 of the $2,011,407 in amounts paid (2.7%). More importantly, they do not require the standard vendor approval procedures regular vendors require. As such, a Miscellaneous vendor can be added by any AP staff member.

This provides an area for potential fraud as an AP staff member can add his or her own information to the Miscellaneous vendor file and submit payments to it. The Student Case Materials note that any payments to employees for reimbursements should be processed through the Payroll Department. As such, there should be no overlap between AP employee addresses and Miscellaneous vendor addresses. Yet, one employee's (Chloe Miller) address appears in six Miscellaneous vendor transactions, totaling $3,453, two of which she processed herself.

To find this anomaly, students will first need to match the Misc. Payment List with the Employee List. This may be done with a =XLOOKUP() in Excel, or more easily, in a relational table that filters only those Misc. Payments with an address on the Employee List. This will identify the six transactions to Chloe Miller's address. To determine the dollar amount involved and the employees involved in processing the transactions, students will need to join in the Transaction List data and match the Payment ID to the analysis. Note that merely finding this anomaly is not proof of fraud, it should raise questions in the students and they should note the need to additional testing to conclude on the situation.

Appendix A - Student Case Materials

Deanna's Delights, Inc.: Data Analytics in Audit of the Procurement Cycle

In the spring of 2010, Deanna Long graduated from culinary school and considered her future. After talking with friends and family, Deanna decided to start her own business, called Deanna's Delights, Inc. (DDI), teaching baking classes to small groups, grade schools and private customers at their own locations. Her business was a success right away and soon Deanna had expanded to her own store location with fresh-baked goods for sale, a regular schedule of baking classes, and sales of baking equipment.

Over the years, DDI has grown larger. It has four full-service locations, online sales and class scheduling, and baking class contracts with several retirement communities and other organizations. It owns the original store and the building next to it, which serves as both the headquarters of DDI and the main warehouse. To achieve this growth, Deanna brought in three additional investors and borrowed from her local bank. Even though DDI is privately held, the bank and investors require an audit to ensure the financial reporting is reliable.

Braun, Ellis, Garibaldi (BEG) is a regional accounting firm with eight offices. It performs audit and tax services for local businesses and consulting on a variety of business solutions. Most of BEG's clients are privately held, often with multiple locations. The industries served by BEG range from service to light manufacturing to hospitality. As a result of BEG's commitment to providing high-quality service, all BEG staff are well-trained and focus on one industry or service line after their second year at the firm.

Assignment

You have been assigned to an audit team. With your team, you need to review the memos Casey Peters, your audit senior, has prepared to identify potential risks in the procurement cycle. Other audit team members have been assigned risk assessment in the sales, inventory, and payroll cycles. Some information regarding these areas is provided to help you understand the overall processes, controls, and risks at DDI. You will not need to test these areas. You will need to:

1. Begin with a general risk assessment, and then focus on risks in your audit area of noninventory procurement.

a. Brainstorm potential misstatements and fraud risks and evaluate the design of the controls for effectiveness.

b. Determine specific tests to conduct on the data set you will be provided and the goals of those tests.

2. Using the data set provided by your instructor to test for identified risks.

a. Ensure the data set is complete with respect to transactions for the year for noninventory procurement.

b. Identify anomalies in the data that may explain the client's concerns or indicate potential misstatements or fraud.

3. Prepare a written risk assessment memo for the non-inventory procurement cycle:

a. What specific aspects of the cycle did you choose for testing?

b. What made those aspects most relevant or in need of testing?

c. What specific tests did you perform on the data and what was the goal of the tests?

d. What are your findings and what conclusions have you drawn regarding additional substantive testing needed in this area?

DDI Background

Ownership

DDI is a privately held Pennsylvania corporation. There are four shareholders: Deanna Long (51%), Ron Hartman, (23%), Kim Lee (17%) and Pat Allen (9%). Long is the only one of the owners involved with day-to-day activities. The Board of Directors consists of Long, Hartman, Lee, and a local lawyer. An annual audit is required by the terms of DDI's financing.

Organization

DDI has centralized accounting and warehouse processes located at the corporate headquarters. Additionally, there are five revenue centers: four full-service stores and one online store. Annual net sales have recently exceeded $10,000,000 for the first time. However, the growth has led to problems with cost management and timely budgeting. As a result, cash flows are not up to expectations but client staff have not had time to determine the causes. The organization chart is shown below.

Policy and Procedure Documentation Review

Ms. Long insisted on producing written job descriptions and responsibilities for all employees on the organization chart (Figure 1), regardless of the location of their work. She provided a copy of these to BEG staff. Relevant information gleaned from this documentation is summarized below.

Sales

Ms. Warren manages the sales both online and at all the stores. For the bakery and equipment sales, she receives sales summaries from the managers and compares them to target sales numbers. Any large discrepancies (positive or negative) result in follow-up calls. Ms. Warren combines the sales summaries from all the stores to prepare reports on trends in sales units and to recommend inventory or pricing changes. All such changes are approved by Ms. Long. For the classes, Ms. Warren sets target class revenue numbers and compares the stores performance to target every month. If a store 1s falling behind, she will meet with the store manager to determine the best options for improvement. Finally, a bonus 1s paid quarterly to Ms. Warren, the online

manager and the store managers if sales have reached a pre-determined target. The bonuses amount to 1.25% of the employee's annual salary.

Accounts Receivable (AR)

Ms. Lasher receives a daily summary report from each store and the online manager of all sales by type. Her staff reconciles the totals with the store cash receipts and records the revenue in the accounting records. She then provides a summary for Mr. Weimer to match to the bank reconciliation. Each month, one of the AR staff prepares a schedule of outstanding AR accounts. Ms. Lasher reviews it for accuracy and forwards it to Mr. Weimer for review. On the rare occasion when an outstanding account is deemed uncollectible, Mr. Weimer makes a note on the schedule and Ms. Lasher performs the actual write-off of the account.

Inventory

DDI has inventory in five different physical locations: all four full-service stores and the warehouse at headquarters. There are two distinct types of inventory, with a separate manager for each type: baking goods and equipment. Mr. Madison is responsible for making sure that all locations have inventory as needed with minimal waste and minimum necessary storage. Both the bakeries and the baking classes require grocery items on hand, tracked by the Bakery Inventory Manager. All these are purchased, based upon store inventory levels, from either a local grocery chain that DDI has contracted with or a specialty baking company that ships goods out for overnight delivery. The grocery chain offers DDI a reduced price because of the quantities ordered.

The specialty baking goods are purchased in larger quantities and stored at the warehouse until delivered to the stores by an inventory staff person. These are typically items with longer shelf life. The Bakery Inventory Manager orders these items based upon current stock in the warehouse. He receives an electronic copy of all orders and matches those to receiving documents supplied by the stores or in the warehouse. He then forwards the information to Mr. Madison.

The equipment inventory is handled slightly differently. The equipment can be requisitioned by a bakery for use in the store, requisitioned by the baking instructors for use in the classes, or sold to customers in the stores and online. As a result, each store is required to prepare a physical inventory count each week, tracking all changes to receiving reports, requisitions or sales slips. These are forwarded to the Equipment Inventory Manager to compare to his records and ensure there are no discrepancies. He then prepares a report each Monday tracking all changes in inventory at the warehouse, including inventory received, shipped to the stores, or shipped to online customers. This report and the supporting documents are forwarded to Mr. Madison.

Payroll

Mr. Scott and his staff are responsible for all payroll at DDI. All headquarters managers are on salary, as are the inventory and store managers. The rest of the headquarters staff consists of 20 full-time hourly employees. At each store, the staffing is similar, with a mix of full-time and part-time hourly employees to support the manager. The warehouse has two managers, each responsible for part-time staff. Finally, the online staff includes the manager and two hourly staff members. Salaries employees are paid on the 1st and 15" of each month. The payroll staff uses a standard entry process as the amounts are the same each time.

For the bonuses, Mr. Weimer provides a list during the first week of a quarter for any bonuses to be paid for the prior quarter. Additionally, any reimbursement of employees is processed through the payroll system. Both the bonuses and reimbursements are processed as a special payroll on the 15™ of the month.

For the hourly employees, both full-time and part-time, the payroll staff receive the hours from the appropriate manager each Monday. Mr. Scott reviews the payroll reports for accuracy before the actual payroll is prepared. Payroll is prepared on Wednesday and employees receive their pay each Friday. Since all funds are paid via direct deposit, there are no checks to sign. Instead, Mr. Scott prepares a payroll summary register for Mr. Weimer of all employees and their pay. Mr. Weimer then uses this during his bank reconciliation process. Finally, all payroll taxes and other withholdings are summarized in a schedule and forwarded to Ben Farmer for payment.

Accounts Payable (AP)

Mr. Farmer and his staff are responsible for processing and recording all AP transactions. Invoices for all inventory items are submitted by Mr. Madison, along with receiving reports confirming the proper delivery. Invoices for other purchases are submitted by the store manager or headquarters staff. All vendors have been approved in advance by Ms. Long or Mr. Weimer. It is DDI policy to make every effort to pay invoices within any discount period offered.

There are a number of recurring payments related to DDI financing. Payments are due monthly for the rent on three of the stores, the mortgage on the remaining store and headquarters building, and other loans outstanding. Also, payroll remittances and taxes are paid each month for the prior month balances. Mr. Farmer keeps a schedule of all payments due to ensure that none is paid late.

Each week, Mr. Farmer reviews the list of payments due to all vendors for the next four weeks. He identifies those that need to be paid in the current week and forwards the list to Mr. Weimer for approval of payments. Two payment runs are prepared each week, on Tuesdays and Fridays. On Mondays and Thursdays, Mr. Farmer prepares the payments to go out, primarily by electronic bill-pay, and the payments are made the next morning. He forwards the payment register to Mr. Weimer for use in the bank reconciliations.

Cash Management

Ms. Morgan manages all cash accounts, investment accounts and loan contracts. She is responsible for ensuring that DDI can pay its bills on time and that excess cash is used to reduce outstanding debt or earn investment income. Each Tuesday, she meets with Mr. Weimer to determine the expected cash needs for the week. Each day, the stores deposit their cash receipts in a local branch of the company's bank. Any other deposits, such as AR receipts, are made toward the end of the week. All payments for payroll and AP are on scheduled days. Mr. Weimer uses reports from Ms. Warren in Sales to anticipate the store cash receipts and any variations in payroll. He uses the reports from Mr. Farmer to anticipate cash payments for the current and next week.

At this point, Ms. Morgan has an understanding of the cash needs for the coming weeks. If there is likely to be a shortfall at any point, she arranges the cash to come in from investments or a line of credit DDI has with its bank. If there is likely to be an excess of cash, she determines whether to pay down the line or invest the funds in DDI's stock and bond investment portfolio. At the end of the week, once all her cash management transactions have been completed, she provides

Mr. Weimer with a report of the current outstanding balance on the line of credit and other loans, as well as the current balance of the investment portfolio. She reconciles the investment portfolio accounts and the line of credit account to the statements each month.

General Ledger

Mr. Weimer manages the general ledger and reconciliations. Each week, he deposits any AR receipts to the bank and tracks cash inflows based upon Ms. Lasher's documentation. He keeps the deposit information until month-end when he reconciles the bank accounts. At that time, he meets with Ms. Lasher regarding outstanding AR. He takes the report she prepares and discusses the status of the AR accounts. If he feels it is necessary to write-off a customer, he notes in on the report, signs the report, and gives it back to Ms. Lasher for processing.

He also oversees the weekly cash payments for payroll and AP. Mr. Scott provides the payroll summary registers and Mr. Weimer uses this to match to the bank reconciliation. For AP, he reviews the outstanding payables list from Mr. Farmer, compares the amounts to the cash projections and approves select accounts for payment. Once Mr. Farmer makes the payments, Mr. Weimer takes the payment register, stores it with the payroll register and sales deposit information until he reconciles the bank accounts.

Every Tuesday morning, Mr. Weimer takes the deposit and payment information and prepares a cash flow report. He then meets with Ms. Morgan Tuesday afternoon to discuss cash needs, leaving her to manage the actual cash balances.

The Procurement Cycle

The non-inventory procurement cycle covers all amounts paid for current assets or expenses that are not related to inventory or payroll. These fall into two categories based on the origination of the purchase and the documentation available. Each category is described below.

Non-Inventory Purchases

Non-inventory purchases of goods and services may consist of office expenses, selling expenses, other general expenses or prepaid items. They may originate at the individual stores or at the headquarters. All purchase requests must be made in writing using a two-part non-inventory Purchase Request Form, which includes the item, quantity needed and date needed. The first copy is forwarded to Steve Weimer, the controller, while the originator keeps the second. Mr. Weimer determines the necessity and availability of the item, considering usage and alternatives. For example, requests for office products by a store may simply require a pickup at the headquarters.

For items that are not on hand, Mr. Weimer will have Ben Farmer determine which vendor can meet the request for the best price. Mr. Farmer works off an established vendor list and price lists/catalogs for those vendors. Any item not available through a currently established vendor will require approval from Ms. Long. Once he has found the item, the AP staff completes a four-part Purchase Order (PO). All requests over $100,000 require approval from Ms. Long. The first copy of the approved PO is sent to the vendor. The second is forwarded in the controller's office. The third is sent to the originator of the request. The fourth is maintained by AP staff to await payment.

When the shipments arrive, the originating store/department opens each package and inspects the contents for damage. A three-part receiving report is prepared noting the item, quantity and condition of the goods. The first copy is sent to Mr. Weimer to match with the PO. The second copy is sent to the Ben Farmer to await payment. The final copy is kept by the originator.

Recurring Bills

Certain bills, such as utilities, rent and insurance do not go through the standard acquisition process. The AP staff maintains a schedule of recurring payments, complete with payment terms, due dates, general ledger account codes and location sub-account codes. For items with invoices (e.g., utility bills), the date the invoice arrived is logged in the schedule along with the due date and amount due. For items without invoices (e.g., rent), a "To Be Processed" date is pre-listed in the schedule along with the due dates and amount due. When the invoice is received or upon the "To Be Processed" date, Mr. Farmer prepares a two-part authorization form. The first copy is attached to the invoice, if available, and given to the AP staff for processing with other invoices. The second copy is sent to the controller's office for filing.

Payments

When a vendor invoice arrives, an AP staff member stamps it so that numbers and approvals can be written directly on the invoice. A second staff member then matches the invoice with the purchase order and receiving report, comparing item number, description, and quantity and notes the account codes directly on the stamp, showing the general ledger account and location sub-account. If there are no discrepancies, the three forms are stapled into an AP package and entered into the accounting software on the processing date. For invoices without receiving information, support documentation should be attached from Mr. Weimer's office. This is verified before processing into the accounting system. All completed AP Packages are then forwarded to one of the Assistant AP Managers who reviews them for completeness, recalculates the amounts, and approves them. Each of them has a different approval limit. Payments over $5,000 must be approved by the first Assistant or Mr. Farmer. Payments over $10,000 must be approved by Mr. Farmer. Payments over $100,000 require the approval of Ms. Long. Also, the processing and approval must be performed by different AP employees.

The first Assistant AP Manager maintains the AP subsidiary ledger. This is shared with Mr. Farmer for his outstanding payables list that he reviews with Mr. Weimer to decide on which payments to make. Once approved for payment, the second Assistant AP manager removes the package, prepares an electronic check for the amount less any discounts available, and writes "PAID" across the package with the confirmation code to ensure invoices are not paid twice.

DDI Expense Policies

DDI maintains a Miscellaneous Expense account for infrequent or unusual items that do not belong in any other expense account. These may be for travel and entertainment (T&E) purposes, meals or any other business item. They should not include recurring payments such as telephone bills. DDI policy is that no expense greater than $1,000 may be classified as miscellaneous.

It also has a policy for fixed assets. GAAP rules allow a company to set a threshold for capitalizing fixed assets, regardless of their useful life. DDI has established a policy that any item under $1,000 may be expensed to Repair and Maintenance Expense. Any item greater than that should be capitalized to the appropriate fixed asset account.

Transaction Data

DDI has provided your audit team with the full transaction data for the non-inventory procurement cycle. It has also provided information about the vendors, the general ledger accounts, and the AP employees that process the transactions. Finally, you will be provided with a monthly budget for the expense accounts included in the transaction data.

You will need to evaluate this data and test for specific risks regarding the internal controls, account balances and potential for fraud. Your instructor will provide you with information on accessing the data and the data analysis tools you should use.

About the Authors

Discussion Questions

1. Inthe Deanna's Delights Inc. case illustrates the importance of data analytics in the risk assessment phase of an audit. What are some specific risks identified in the non-inventory procurement cycle, and how can data analytics test these risks effectively?

2. The case discusses the various internal controls related to the procurement cycle at Deanna's Delights Inc. How would you test the effectiveness of these controls using the provided data set? Provide examples of tests you would perform and the potential outcomes you might expect.

3. What steps would you take to identify and investigate anomalies in the data that may indicate fraud?

To Cite this Article

Paz, V., Souza, J. L., & Weinberger, A. (2024, Spring). Deanna's Delights, Inc.: Data analytics in the audit of the procurement cycle. Journal of Multidisciplinary Research, 16(1), 97-117.

Sidebar

Dr. Veronica Paz ([email protected]) is a Professor of Accounting and Information Technology at the Indiana University of Pennsylvania, where she teaches upper-level undergraduate accounting courses and graduate courses at the master's level and Ph.D. levels. Dr. Paz teaches auditing, Accounting Information Systems, Forensic Accounting, Data Analytics, and Business Analytics. Dr. Paz is a Certified Public Accountant (CPA) in Florida and Pennsylvania. She is a Certified Information Technology Professional (CITP), Certified in Financial Forensics (CFF), and a Certified Global Management Accountant (CGMA). She has published 3 books and more than 27 other publications. ORCID 0000-0002-2089-0499.

Dr. J. L. Souza ([email protected]) is an Assistant Professor of Accounting at Saint Joseph's University (SJU). Dr. Souza has taught various accounting- and audit-related courses over the past 18 years, including the required introductory accounting and basic audit courses, intermediate accounting, advanced auditing topics, fraud auditing, internal auditing, and IT auditing. She currently teaches at SJU after teaching at the University of Memphis and Penn State University. In her role at SJU, Dr. Souza teaches accounting students the skills required to succeed in the profession, bringing new and critical competencies to SJU graduates. She has worked on teaching projects for introductory courses. She has written cases regarding auditor judgment and reporting, data analytics, and technological preparation for students entering the auditing profession. She also has researched audit reporting and the efficacy of audit reporting standards. Dr. Souza holds an active CPA (Certified Public Accountant) license in Pennsylvania and has years of experience in the audit profession. She audited public and private companies with one of the largest international audit firms. She has provided training services for auditors at firms such as FedEx. ORCID 00000002-3903-0325.

Andrew Weinberger ([email protected]) is an Associate Professor of Accounting at Central Connecticut State University, focusing on managerial accounting and accounting analytics. Prior to joining academia, Andrew had 10 years of industry experience in the public and private accounting sectors. As an Audit Consultant at NSRE, he was responsible for utilizing analytics to evaluate and improve the effectiveness of risk management, control, and governance processes. Prior to joining NSRE, he held various positions including internal auditor and IT SOX Manager at The Hartford Insurance. He holds a D.B.A. from Creighton University. ORCID 0000-0002-6766-5803.

References

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