CSPs need to be able see what’s happening with an individual subscriber at any point in time. They also need to know how a change made to one part of the network will impact other network segments and subscribers. The only way to gain these capabilities is to install an analytics platform that stitches together data from a number of diverse sources in near-real-time and incorporates a measure of ML to automate some of the decision-making and action-taking.

Analytics let the CSP identify very granular customer experience measures that the operator can then aggregate back up into a network-wide view. It’s possible, for example, to see just where voice calls aren’t working well. They might show a pattern—for example, that customers with a particular model of mobile handset running a particular software version are the ones experiencing a common issue. Armed with that information, the CSP could push out an appropriate notice to those customers that they need a software update. 

Analytics at Scale

The impetus to deploy a carrier-class analytics platform in a CSP organization will likely come from someone who has been tasked to improve service quality and reduce operating costs, even as the infrastructure becomes more complicated—and with no or little budget for additional human resources.  The proverbial “do more with less” mantra speaks directly to the emergence and importance of analytics and automation in the telecom industry.

Different CSP organizations are in different phases of analytics deployment. Some have gotten as far as bringing their data together in a data lake or data warehouse but haven’t yet deployed a platform to generate analytics. A number of CSPs have tried to implement traditional business intelligence (BI) or enterprise-grade analytics but haven’t been rewarded with the returns they were anticipating. The overriding reason is that these systems aren’t geared to the scale, size, complexity and real-time requirements of providing operational intelligence (OI) for today’s carrier networks.

It’s important that the analytics platform scales to meet the large and complex requirements of CSPs. The first step is to identify the relevant sources of data that need to be analyzed and to bring the data together. It’s possible that this function can be accomplished by the analytics platform, depending on the vendor.

The ultimate goal is for analytics to identify issues and automatically fix them. Substantial work in the wireless arena is under way, for example, to build self-organizing networks (SON). One premise behind SON is to leverage the substantial amount of data coming from the network to automatically identify issues impacting customer experience and the changes that can be made to improve that experience. These changes need to balance the effect on the impacted cell sector with the anticipated effect on neighboring sectors and make the appropriate tradeoff that maximizes customer experience.

A fix in one part of the network has a ripple effect elsewhere, and the number and nature of those effects—or tradeoffs—are very complicated in nature. As such, they are nearly impossible for a human to quickly foresee or calculate.  Successful automation such as the SON environment requires AI and ML to build and “understand” the relationships among the various network elements to successfully determine—and execute—the best possible fix.

Start with a Finite Set of Services

To evolve the NOC into one that’s customer-centric, it’s best to begin with a single service, such as voice or real-time streaming, and phase in the analytics on a service-by-service basis. Implementation doesn’t require a rip-and-replace of existing NOC capabilities, but rather the integration of a carrier-scale analytics platform into NOC tools and operations.

Starting with a single service enables telcos to see success quickly and get familiar with the platform. Each service will have some common data sources, measurements, and capabilities, so as CSPs add services and data to the platform, the process will go increasingly faster.

In a digital marketplace obsessed with individual customer experience (CX) levels, CSPs can no longer rely on KPI-based NOC operations alone. By adding smart analytics tools to their NOCs, they gain visibility into each customer’s experiences with their services and are able to begin automating network fixes to help improve those experiences, reduce churn, and slash expenses.