Case Study: Reducing cost and increasing transformation velocity of a Tier 1 Telecom network
The Challenge
A Tier 1 U.S.-based telecommunications provider with over 100 million subscribers and infrastructure spanning hundreds of metro regions struggled to modernize their complex, multi-vendor and multi-generational environment, including over 220K legacy SONET and DACS elements across 150+ LATAs. For over a decade, the provider attempted to migrate away from their legacy TDM-based systems to a next-generation packet-based infrastructure with little progress. Previous internal efforts had stalled, with the first targeted migration site taking over a year to complete. Unable to effectively move forward, they continued to invest in inefficient and unnecessary operational costs, including spare equipment purchases and maintenance, despite having vast unused inventory scattered throughout their network. Traditional strategies were simply not working, risking their ability to deliver industry-leading services at
LightRiver’s nIO™ Tailored Solution
Utilizing the Tier 1 provider’s offline inventory data, enhanced with real-time network data provided by LightRiver’s netFLEX™ platform, the Network Inventory Optimization (nIO™) solution was able to address their consolidation, migration, and modernization needs.
Solution Fit
nIO uniquely combines real-time network data with static inventory to provide a comprehensive view of all network elements and interconnections. This was essential to mapping their multi-vendor, multi-generation network and to the success of their overall strategic goals. nIO is the leading industry-wide solution capable of connecting cross-vendor, end-to-end circuit paths.
Deployment Approach
LightRiver began with an initial engagement focused on identifying unused and harvestable equipment. This expanded into networkwide migration prioritization and metro-area modernization planning. A data science-led methodology first segmented the network into migration quadrants (easy to hard), allowing the provider to prioritize lower-complexity areas first. This systematic approach was able to identify and achieve the highest savings and returns achievable at every stage of the migration, delivering significant and measurable quarterly ROIs for stakeholders.