Automating the Order-to-Cash Process with RPA (Class 4/4)

Why is this important?

Effective automation does not end with the execution of tasks; rather, mature automation projects include robust reporting mechanisms that communicate outcomes, performance metrics, and exceptions to stakeholders. In business environments, dashboards serve as a critical interface between automated processes and decision-makers, transforming raw data into actionable insights. Moreover, in the context of governance and compliance, dashboards play a key role in providing transparency into bot activity, including execution logs, error rates, and process bottlenecks. This class motivates the development of automated reporting tools as both a technical skill and a governance imperative, emphasizing that the strategic value of automation increases substantially when paired with well-designed reporting and monitoring systems.

What will we do?

In this class, we will explore how to automate reporting and dashboarding processes using structured data generated by our RPA bots. We will build simple dashboards that summarize key process outputs (e.g., number of orders processed, errors encountered) and begin to consider what metrics are most useful for operational oversight. Additionally, we will design basic governance dashboards that log bot activity, track process performance, and provide audit-relevant details such as time stamps and status codes. These reporting structures will serve as a foundation for more advanced analytics and process mining tools in future applications.

Review and Extension:

Thus far, we have built RPA bots capable of moving data between systems and have introduced governance functions through metadata tagging for process transparency. This class extends that foundation by introducing the reporting layer of automation — a critical component for communicating results, monitoring process health, and ensuring compliance with organizational policies.

In future classes and projects, we will consider how automated reporting can evolve beyond simple dashboards to include real-time monitoring, exception handling workflows, and integration with business intelligence platforms such as Power BI or Tableau. We will also explore how process mining tools can leverage the governance data generated by our bots to visualize end-to-end process flows, identify inefficiencies, and support continuous improvement initiatives.

Materials and Suggested Seating:

Case: Pure Reformed Oils (Swindler and Simpson: The path to redemption) Case, Continued.
No slides are available for this class.
Data: A data update may be required for this class. To ensure your files are the most up-to-date, navigate to ACCTG528_Labs folder and run the command git pull.
Automation Tools: UIPath: students should be comfortable with many activities and be able to complete their workflow in this class using UIPath.
Automated Tasks: Excel related activities
Automated Tasks: Starting the audit trail/metadata logging for controls and/or process mining

Note on Pre-Class Preparation:

There is no suggested preparation for this class.

Class Plan:

1. We will continue working on the Redemption of Skylar and Victoria Case, working in the labs from the beginning of class.
2. Use git pull to obtain a new folder with a bot and data.
3. As this final class in the four part Skylar and Victoria's Redemption Case, we will establish the base solution, and students should be working on their extension to the automation, considering candidate tasks such as an automatic output for a dashboard, audit logging and metadata tagging, and any other extension to the automation they wish to build.