In this SMU ACCT433 assignment, students act as business analysts proposing a Robotic Process Automation pilot. Using a process discovery interview about how an AR clerk and Account Managers chase overdue customer balances with Xero, Excel and Gmail, they must document the current process, show where time and errors are lost, and justify the pilot to executives with TCO, ROI and payback figures.

Case Background: AR Past-Due Customer Reminder Process

The process discovery interview describes how overdue balances are followed up today:

• An Account Manager emails the AR clerk (on average about twice a month, with no fixed schedule) asking for the latest outstanding balances of their customers.
• The AR clerk logs in to Xero, runs the Aged Receivables (AR Summary) report at the relevant month-end date and exports it to Excel.
• Customers are matched to Account Managers using a manually maintained Excel Customer Master List (customer name, Account Manager, email address), matched by customer name rather than a unique ID.
• Only customers with a past-due balance greater than zero are included; an Excel file with customer name, email, overdue balance and Account Manager is attached to a reply email (about 10 minutes per request).
• The Account Manager then writes one reminder email per customer in Gmail from a standard wording, copying the name and overdue amount and checking each email (about 5 to 8 minutes per customer).
• Scale: around 200 Account Managers, around 50 customers each and more than 10,000 tenants in total; many Account Managers request more than twice a month.
• Pain points include repetitive extraction and matching, similar customer names, filtering errors, copying the wrong amount or email address, and an out-of-date master list.
• Exceptions (customers not found in the master list, missing email addresses, name mismatches, duplicate records) must be flagged for human review, and Account Managers may still decide not to send a reminder for relationship reasons.

Business Case Document Components

1. Executive Summary

A one to two paragraph standalone overview that summarises the process and organisational context and includes the vision statement, so that a senior decision-maker can understand the business case without reading the rest of the document.

2. Current State Analysis

• How the process currently operates
• The key activities and stakeholders involved
• Relevant process volumes, processing times, labour requirements and error rates
• The key pain points and inefficiencies
• An “As-Is” process map showing the current workflow and where the pain points lie

3. Proposed Solution

• Which parts of the process will be automated
• Which activities, if any, will remain with human employees
• How the automation addresses the pain points identified
• The expected improvements to the process (no detailed technical design needed)

4. Cost-Benefit Analysis

Evaluate the expected costs and benefits of the RPA pilot using quantitative data and clearly stated assumptions.

• Costs: the relevant Total Cost of Ownership (TCO), such as software licensing, infrastructure or cloud, implementation and development, testing and deployment, training and change management, and ongoing maintenance and support
• Benefits: employee hours saved, FTE capacity released, reductions in processing time, error rates and rework, faster fulfilment of requests and increased capacity
• Non-financial benefits: employee experience, process consistency, control and auditability, and stakeholder experience

5. Key Financial Metrics

At a minimum, calculate the estimated Return on Investment (ROI) and the estimated payback period, showing the formula, the values used, the time period covered and the underlying assumptions, all traceable to the evidence in the earlier sections.

6. Summary and Recommendation

Bring together the problem, how the RPA solution addresses it, the expected operational and financial benefits and the key metrics, and conclude with a clear recommendation on whether to proceed with the pilot.

Submission Requirements

• Submit individually on eLearn as a Microsoft Word document named <Full Student Name>_BusinessCase.doc before the stated deadline.
• Complete the AI-use declaration and follow the SMU Code of Academic Integrity.
• Grading follows the Business Case Document Grading Rubric.