After reading this guide you will be able to create a build vs buy analysis for revenue recognition software.

Want a Google Sheets version of the Build vs Buy calculator? Click here to access it.
When evaluating the decision of building or buying a revenue recognition (rev rec) automation solution, there are numerous factors to weigh. With dozens of companies in the market providing out-of-the-box solutions and the alternative of having your CTO and engineering team build something in-house, the decision isn't always straightforward. This guide will help you conduct a clear and actionable build vs. buy analysis so that your organization can make the best choice.
At the end, we’ll also provide a template to streamline this analysis for your particular case.
If you do an internal build - here are a few common technical issues that will add unexpected complexity:
The decision to build or buy a revenue recognition automation solution depends on your organization’s size, growth stage, and available resources. While building gives you flexibility, the hidden costs, including opportunity costs, compliance risks, and technical pitfalls, can quickly add up. Buying, on the other hand, offers quicker implementation, lower compliance risks, and ongoing support from vendors.
HubiFi was designed by a CFO and CTO who dealt with these common issues when doing their own internal build at past companies. As such it is built to provide a robust and cost-effective solution for revenue recognition automation. With:
HubiFi provides a fast to implement (<1 month) way to streamline your revenue recognition process, ensuring you meet compliance standards without breaking the bank.
Feel free to use this guide and the included template to create a build vs. buy analysis and determine which solution is the best fit for your organization.

Accounting Automation | Product | Technical Accounting | Accounting Systems Nerd
Cody Leach, CPA is a technology and automation focused CPA helping finance leaders bring their processes into the 21st century. He's advised finance teams around technical accounting and automation - such as Cursor, Meta, Strava, and many others and has helped SaaS and AI finance teams turn messy and usage data into clean, automated revenue reporting that actually matches how the business runs. Former KPMG auditor, Cody holds in Masters in Accounting from North Carolina State University. He is a CPA.