To cope with the growing service assurance issues in massive mobile data networks, operators are increasingly turning to analytics solutions. Tradtional, network-element-centric assurance systems were never really designed to look at the quality experienced by individual users. Even today, customer calls to the contact center remain one of the best sources operators rely on to pinpoint network issues.
But by combining big data platforms with DPI feeds that tie every mobile network event to a handset, analytics solutions are beginning to close the network intelligence gap and provide more customer-centric and business-focused functionality.
Rather than relying on thousands of alarm triggers to infer root cause, analytics compiles statistics to show how things are trending. Or it uncovers a root cause by triangulating multiple data streams such as handset type, RAN performance, and cell towers.
If root cause is the reactive side of service assurance, then capacity planning delivers the proactive side. And here we can compare the role of analytics to the architectural stress tests performed on city buildings to find which structures and construction materials will best withstand major earthquakes.
The network equivalent of an earthquake is a major sports event, live concert, or city parade that stretches the limits of mobile infrastructure. To plan for those events properly requires the kind of meticulous simulation and testing for which analytics is well-suited.
Still another analytics focus is user behavior. If an operator understands how its customers are using mobile broadband, they can identify congestion points and determine who they affect. Armed with this type of insight, an operator can improve its network investment metholodogies to enhance customer experience and even to ensure that premium customers are treated as such.
So, as operators examine strategies for investing in and evolving analytics capabilities to solve service assurance problems, they may consider the following perspectives as useful inputs:
The human mind best grasps multi-dimensional complexity when data is presented visually. Operators should pay close attention to a solution’s visual capabilities as they are the keys to making sense of the data being analyzed and guiding and effective course of action.
Photo by NEC Corporation of America with Creative Commons license
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