There's a seismic shift taking place in the telecom market and it is creating a fiercely competitive landscape. Deregulation, new technologies, changing subscriber expectations and new, nontraditional competitors are driving this transformation and challenging operators to rethink not only their networks but also their fundamental business models. To compete in this demanding environment, operators need new tools that enable them to make informed business and network decisions.
Actionable intelligence based on real-time network data is fundamental to ensuring network optimization, profitability and business innovation. A critical step in business and network evolution is the ability to identify the right key performance indicators (KPIs). KPIs provide operators with the quantifiable metrics that are important for long-germ profitability. Identifying, measuring and managing the right KPIs can be the difference between growth and prosperity, and decline and failure.
Modern networks are multi-technology hybrids populated with equipment from a variety of vendors. Each element has its own method of collecting and computing data. Correlating data from multiple sources poses significant challenges, including the synchronization of collection intervals, management of diverse data types and formats, and uniform data aggregation.
And even when all of the network equipment is supplied by the same vendor, data production and delivery procedures may not be consistent across all of the products. The result is an incoherent mix of data from multiple, measurement sources that provides little value for operators looking to manage and optimize network-wide quality of service (QoS) and SLAs.
Operators today offer a portfolio of services -- voice, video and data -- across networks with a variety of technologies, protocols and access types. Blending these services requires the interplay of a number of network elements. As operators add more equipment types, they find it increasingly difficult to manage network-wide QoS for a specific service since each element provides only a local snapshot of the network. With limited network visibility, operators cannot gather the data required to trace sessions across the entire network that will help them determine end-to-end QoS or understand their subscribers' experience.
Adding to the challenge is the fact that many services traverse partner networks through inter-operator agreements. Meeting service performance and customer satisfaction metrics in such a multi-technology environment is extremely challenging - especially since operators don't necessarily own and operate the end-to-end transport network and access networks.
Measure, manage, monetize
Data-collection quality issues reverberate throughout the operator's entire business organization. Poor or deficient data can negatively impact short- and long-term business objectives, customer relationships, and network planning and optimization.
The KPI management model - measure, manage, monetize - exploits the benefit from collected data by offering a systematic approach to continuously improve the process of collecting, analyzing and utilizing selected KPI data. The model consists of three key steps. First is to identify the most important KPIs for improving efficiency and profitability. Second, validate the quality of the network data being used to develop the KPI metrics. Third, leverage the KPI data across the right organizations to make decisions to improve the business.
For example, an operator that wants to focus on network optimization may look at the following network performance metrics. Within a network, performance indicators for service quality include answer seizure ratio (ASR), network efficiency ratio (NER), average length of call, and average set-up time. Other in-network metrics are service usage and trends based on application performance such as prepaid service success and failures.