Organizations often find themselves wading through pools of disconnected order and customer information. This severely limits their ability to optimize billing and collection activities.
Goals and Objectives
Recently, companies have turned to structured machine learning to speed up/streamline order-to-cash processes, including advanced order management, AR automation, invoice remittance, reconciliation, recognition, and credit details. In addition, early adopters of machine learning have been able to eliminate a large amount of time spent on manual tasking while also decreasing the error rate.
Enterprise hardware, personal devices, cloud, Big Data and analytics, mobile, applications, business consulting, cognitive technologies, and IoT
Use Case Summary
Technology is used to develop, implement, and measure the order-to-cash processes.