Troubleshooting telecoms: A smarter way
One of my first projects in the telecom industry in the 1980s was to assess Ericsson’s network management system against that of the competition. and it’s fair to say that packets, traffic, and data have changed dramatically since then!
Today’s challenge is to make sense of the mounting complexity of underlying technology and simplify the services being offered to telcos, partners, and customers alike. At the same time the demand being placed on the network from the ‘outside’ continues to expand from individuals, households, businesses, and societies, let alone from machines and sensors across the globe. Never have so many aspects of our personal and business lives been predicated on the connectivity services that the telecom industry delivers. The explosion of multiple forms of traffic underpinning business-to-business-to-everything (B2B2X) models is leading to unmanageable volumes of data requiring constant analysis.
Given the emerging tools and the power of cloud-based computer platforms, there’s a temptation to gather every single piece of data, store it in an unwieldy data lake, and try to analyze it all. But a more sophisticated solution now exists. The new advanced troubleshooting capability in Ericsson Expert Analytics adopts fresh thinking by linking analysis of events back to the underlying raw packets and identifying issues (in line with subscriber activity) to help shape the overall service experience. And, given the advent of machine learning (ML) and increasing activity around artificial intelligence (AI), Ericsson can build more and more layers of embedded intelligence into the overall system. This blend of raw technology analysis, coupled with Ericsson’s industry pedigree, stands out as a key approach to helping the world’s communications service providers (CSPs) cope with the deluge of data it’s facing whilst maintaining and improving network delivery.
Using the right data to fuel the most effective troubleshooting strategy
Ericsson Expert Analytics' new capabilities for advanced troubleshooting get to the heart of the matter. This new offering is a focused approach, using data selected intelligently by the system to focus on the information needed as a first step, rather than the attempt to ‘boil the ocean’ approach provided by other offerings. Combining event and raw data analysis in line with subscribers’ issues improves troubleshooting making it more effective and precise and over time, it will continuously improve the network and operational environment.
The secret sauce in the recipe is in fact a secret source of real time event data rather than the retrospective extrapolated data provided by many players. And, importantly, Ericsson’s domain expertise in telecommunications, particularly driving the 5G world, is key when compared to other point solutions and more general testing offerings from outside the industry. Ericsson has developed a broad range of related products and solutions over the years that can be knitted together coherently, and its extensive experience helps identify CSP pain points and develop thoughtful tech solutions to resolve them.
This targeted approach leads to an estimated more than 50 percent reduction in the total cost of ownership in terms of activities, bandwidth, compute, cloud, and energy.
A smarter approach to network complexity for CSPs
Today, CSPs are increasingly not in control of all elements shaping the service experience, nor indeed the ways networks will have to behave to react to the demands of ecosystem partners. Yes, it is more complex, but the job of companies like Ericsson and CSPs is to shield that complexity from the customers wherever they sit in the B2B2X model.
The future will require much more collaboration with other vendors, app providers, and developers as well as different ecosystem partners playing the primary role with customers, so this ever-improving, continuously updated operational engine is crucial. An application programming interface-based economy will delve down into the network and draw out the necessary services/functions, including slicing. Underpinning this foundational role for CSPs must start with the raw packet analysis resulting in significantly less data being analyzed and it will be easier to recognize how the network's service links to the final result.
We often talk about smarter approaches to problems. Continuous improvement through ML and AI with industry experience is evidently a smarter approach to the increasing volume and complexity of the telecommunications environment. The role of the CSP will increasingly be to provide its services seamlessly to its partners and customers as the focus shifts to outcomes defined by applications, content, and commercial executions. The service experience is built on the broadband of the future being delivered invisibly and at the highest quality levels.
Instead of continuing to analyze all data, focusing the effort on key triggers in the network and building automated knowledge of operational environments will ultimately be more efficient in underpinning the service experience which, in turn, will keep customers happy. Today’s complexity is overstretching resources, hence the focus on automation at many levels. We can only imagine how additionally intricate the picture will become with increased activities around AI and the moves into virtual worlds including the Metaverse. The industry must be prepared for this exponential shift and know how to keep it hidden from the outside world.
Data management and business models—a symbiotic relationship
And finally, this unified approach to troubleshooting can help bridge formerly isolated data silos and operational and line of business (LOB) activities within the world’s CSPs. Every member of the boardroom will benefit from this approach as it ties service delivery right back to the core of the telco offering, building confidence in developing new services.
In short, the Ericsson Expert Analytics advanced troubleshooting capability offers continuous improvement of the operational environment. Its core element of building layers of embedded intelligence in the system’s workflows leads in turn to more automated intelligence in the system, freeing up the human factor to focus on business efficiency with all LOBs and partners in the ecosystem.
Through its ability to quickly analyze intelligently selected data, this approach showcases the future of telecommunications analytics in complex next-generation networks.
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