Capstone Projects

Automation of Cincom to Gross Margin Matching

Program: Data Science Master's
Host Company: Trane Technologies
Location: La Crosse, Wisconsin (onsite)
Student: Laurie Nekola

The client project entails learning the details of a manual accounting process and automating it to save time and ensure accuracy and consistency. The client is a publicly-traded company, so in addition to meeting GAAP (Generally Accepted Accounting Practices), they must comply with SOX (Sarbanes-Oxley) controls. The systems involved included a manufacturing application that was deployed in the 1990s and an accounting application that was last upgraded in 2009. The complexity with this is that data from the manufacturing system does not flow to the accounting system, so matching data between these two sources have been manual for several years. Because these systems do not connect, the accounting application enters estimated costs for a project. Monthly, during month-end financial close, the actual costs are provided and adjustments are made to correct estimates. Practices employed in this project were documenting existing processes and decision points while handling the data, cleansing extraneous data and creating key identifiers when needed, and providing an output for a journal entry. The final requirements for this was to save time on the first workday of month-end close to allow accountants to use their time for more value-added work, to ensure accurate calculation of compensation for sales persons, and correct reporting of revenue each quarter. Once fully automated, the process was reduced from ten hours of work by three accountants to one hour of work by one accountant. This allows them to do further analysis of the data rather than spending time handling the data for review.