Digital service providers (DSPs) have started leveraging robotic process automation (RPA) to automate various telecom processes, especially in the service provisioning. However, standard bots are not able to automate the complete process as it involves multiple levels of manual assistance in processing unstructured data and decision making. According to Gartner, more than 80% of enterprise data is unstructured in nature. Processing unstructured data and performing end-to-end automation with standard RPA is a major challenge for DSPs.
Natural Language Processing (NLP) is the art of extracting information from unstructured text. NLP-based decision engine can play a critical role in processing these unstructured data, derive insights and provide the next best action. This insight talks about how DSPs can build a robust NLP/NLU-based decision engine to achieve complete automation in service provisioning.
- Madhusudhanan S
- Velmurugan M
- Gurunath L V
- Mogan A.B.