Partnering with telecommunications teams on network optimization, personalization, and workforce management
to solve key telco challenges
Challenge: Network Maintenance and Optimization
Network operations and performance are one of the key value propositions of large telco operators. The near real-time nature of the challenges coupled with the size of the data (for example, telemetry data, network logs, hardware maintenance, software updates, weather information) prevent users from deriving the types of insights that provide a truly transformative end user experience.
Solution: Network Knowledge Graphs
A network knowledge graph combines information contained from a variety of structured and unstructured data sources into a single ontology layer that can be used for troubleshooting, querying, and optimization.
This network knowledge graph allows for an understanding of what actions are best suited to resolve faults based on historical data and embedded expert telco knowledge, resulting in better network quality and maintenance.
4% reduction in network costs, driven by lowering network faults, and an increase in network quality translating into higher NPSs from customers.
Challenge: Commercial Excellence
Customers want a unified, personalized experience across channels. However the customer journey today is fragmented across multiple departments and the associated data reflects these silos. This makes acquisition, cross-selling, upselling, winback, and personalization difficult.
Solution: Personalized Targeting and Offering
Personalization helps to provide the right message, at the right time, to the right user providing an overall better customer experience. Building on top of a relational knowledge graph allows more data types to be connected and domain knowledge to be embedded. The result is increased revenue and customer satisfaction.
10-20% revenue uplift, 5-10% increase in testing speed and 20-30% customer engagement and satisfaction.
Challenge: Workforce Management
Large telco organizations need to make decisions on how to optimize their workforce operations, with an eye for both local and global constraints. Making those timely decisions involve reasoning across complex siloed data sources (timesheet, working manuals, past history of faults, geo-spatial information, etc.) which are hard to ingest and connect.
Solution: Automated Reasoning and Optimization
A relational knowledge graph allows structured and unstructured data sources to be connected and augmented with domain knowledge. Automated reasoning allows carriers to enhance data with new knowledge that is often inaccessible to existing systems (for example, linked faults, regional preferences, criticality of events, and more …)
This complex knowledge structure allows for better forecasting, inventory management, and workforce optimization, reducing cost and increasing customer satisfaction.
25% reduction in human capital cost while obtaining a 5% increase in performance.