The backbone of countless finance organizations is the ERP. Thanks to their abilities to integrate across businesses, locations, and currencies, ERP’s have become the platform for automating tedious and error-prone manual consolidations. They are the alpha dog in the IT stack, with other business and functional systems beholden to support the integrity and efficiency of the ERP.
As these systems grew in size and stature, speed and storage became concerns. Transactional information was further consolidated and merged with similar data for reporting. Later in the reporting cycle, final adjustments and allocations are often 'top-sided', eliminating any alignment that may have existed between the reported numbers and those in the transactional systems.
To remedy these issues and deliver on the promise of big data, transactional details need to be integrated and organized; only then Artificial Intelligence (AI) and Machine Learning (ML) efforts can be launched. Driver based forecasts in complex environments can be evaluated and adjusted, with external forces modeled and strategies aligned.