Michael Krahn CPA, CMA, CHFP, MS Business Analytics and Project Management

September 8, 2024

If your organization is planning to move your Enterprise Resource Planning (ERP) System to the cloud, consider using the Python programming language to not only save money and time during your project, but also to greatly increase the post-implementation value of your project deliverables.

Through my experience leading the design, build, and implementation of ERP Finance systems, I have found that using Python to do most of the heavy lifting in a major systems implementation can dramatically reduce the time and cost of implementation. Here are seven great reasons for using Python in your next major systems implementation / upgrade and making it a part of your post-implementation digitization journey:

1) Use Python to reduce customizations to your cloud ERP. Excessively customizing a cloud-based ERP is one of the most common mistakes made by implementing organizations. These customizations make it much more difficult to test and maintain the functionality of your cloud ERP as the vendor regularly introduces updates to their software. With Python, you can easily access ‘as delivered’ data elements from your database, data warehouse, data lake, or other repository, transforming the data ‘post ERP’ and integrating seamlessly with Microsoft Excel for end-to-end reporting and analysis solutions, keeping your cloud ERP customizations to a minimum. Use Python to easily fill functionality gaps in your new cloud ERP while drastically shortening the time your ERP vendor needs to develop your new functionality requests in the core ERP product.

2) Use Python to simplify and reduce the cost and time of data migration (extraction, transformation, load) from legacy systems to your new system. Efficient, effective, and accurate data migration is one of the most critical success factors for your project. Python and its related data wrangling modules are powerful, flexible, and transparent, making it a smart choice for this application. Python is as good or better, for this use case than any of the expensive proprietary data migration tools on the market today.

3) Use Python to automate your data validation process. Data validation often is the most time consuming and difficult part of any finance system implementation. Python easily manages the largest of files, and Python code is clear, concise, repeatable, and easily readable for this purpose. Confidently deliver consistent, user-friendly data validation artifacts to your project and operations teams, and other stakeholders using Python.

4) Use Python to develop / enhance integration with your other finance systems. Python excels at tying disparate information systems together, serving as the programming glue that allows these systems to effectively talk to each other. Python has a robust, web-ready API development ecosystem that makes it a programming language of choice for tying together cloud based applications.

5) Use Python to take advantage of your ERP’s application programming interfaces (API’s). Most cloud-based ERP’s and other financial applications have well documented APIs that Python (or other coding language) developers can access to create custom web-based applications for your new ERP or other financial system. Obtaining data from APIs (rather than the application itself) allows you to have automated, ‘real-time’ access to your data for analysis and problem solving.

6) Python continues to add post-implementation value to your organization. Python becomes your ‘go to’ coding tool for solving business problems of all kinds via automation, work-flow simplification, and advanced data analysis. Python is not necessarily a ‘throw away’ implementation tool. Instead, it can continue to serve as a core component of your company’s digitization journey. Python modules are constantly being updated for the latest in data analytics, AI, and machine learning functionality. Continue to add value to your organization while saving money and using industry leading technologies, all tied together with the Python programming language.

7) Python integrates nicely with Microsoft Excel. Microsoft has delivered a beta version of ‘Python in Excel’ which is currently being evaluated by Microsoft insiders for improvements in anticipation of a production release. Integrating Python now with Excel in your implementation will help to prepare your teams for the future of Excel where Python powers the data wrangling and analysis features in MS Excel.

Please contact me personally at (203)500-0343 If you’d like to get more information about how our transformation experts at Remarc Consulting and Data Solutions can help you apply Python-based solutions to add value to your ERP implementation or other financial system project.