The first to-do on the CFO’s list is to run a customer profitability analysis to get a better view on net profit margins. As the profit and loss statements in the available ERP platform do not include enough details on all the operational and logistic costs on the customer level, they need to build a profitability model.
A profitability model combines a large volume of operational and financial data with a number of business rules. That data, however, is not easily available at our organization, as it uses many separate systems that are not integrated into the ERP backbone. After a first analysis, the project team discovers they need six different data sources to build a relevant model, which are spread across the ERP platform, and three systems that are managed and maintained by the Operations, Sales, and Logistics divisions.
On top of that, the master data at hand are inconsistent. The number of customers and their segmentation, for example, differ between the different systems, as do the product data. Even in the finance team itself, it is hard to get one version of the truth. Different team members, for instance, export data from the ERP system using different filters – which leads to different results.
Thanks to a series of master data mapping exercises and some extra efforts in terms of ETL, the project team manages to build a profitability model that combines all the selected data. To make sure all the hard work pays off and minimizes maintenance efforts in the future, the CFO made sure the model was set up in such a way that it can be leveraged should the organization move towards a data platform in the future.
With a data platform, all the data from the most diverse sources would be centralized, ensuring one version of the truth. The finance team would have access to consistent data that is relevant for any use case.