Business Overview
Our client is one of the leading mobile network operators (MNO) in the United States.
Business Problem
Enterprise Customer Web Portal is intended to present customers with up-to-date services configuration, network performance parameters (e.g. bandwidth utilization, delay, up/down time, etc.) and SLA (Service Level Agreement) deviations. However, the portal is plagued with inaccurate, incomplete and inconsistent representation of customers’ services requiring significant offline data manipulation and correlation, and resulting in customers’ dissatisfaction. Some of the root causes are:
- Missing and/or inconsistent data (e.g. customer name, service type, device ID, Circuit ID, etc.) between key data sources of Order Management, Network Inventory and Network Performance Monitoring systems
- Inaccurate device configuration information in Network Inventory System
- Misconfiguration of CPE (Customer Premise Equipment) and network PE (Provider Edge)devices Legacy non-standard customer service data
- Manual processes and long lag time in customer order data propagation
Our Solution
- Solution design required continuous and near-real time of extracting and comparing customer service configuration data, and providing corrected data for consumption by Enterprise Customer Web Portal.
- Using 1Data platform, data from key source systems and are ingested, normalized and corrected to solve the business problem:
- Ingestion Data Sources:
- Customer Orders Management System [SFDC]
- Network Inventory System [Granite]
- Network Performance Monitoring System [CA Spectrum]
- Intelligent Rules Engine: using input microservices and Python scripts, multiple custom-defined rules were created to analyze the data from source systems, make appropriate corrections and prepare output data for consumption by the enterprise portal. Some examples are:
- Identifying completed and activated customer service orders by Service Type and correcting corresponding Inventory System data
- Identifying correct device information, including equipment type and configuration parameters, for customer services and correcting the corresponding Inventory System data
- Identifying misconfigured network devices, and using 1Data Workflow, track correction by network operators
- Preparation of clean and correct Service Configuration data for use by Enterprise Customer Web Portal on hourly basis
Key Benefits
- Customer Service data accuracy in the enterprise web portal was increased to nearly 90% from 60% prior to the solution deployment
- The enterprise web portal was enabled to show changes in customer services within an hour of network events (activation, deactivation, faults, etc.) vs. days/weeks prior to 1Data deployment
- Newly provisioned circuit configurations were analyzed in real time and corrected to ensure downstream systems could correctly ingest data