Creating New Customer Insights with Well-Connected Data Analytics and “Remote Everything”

Digital collaboration has never been more commonplace—or more critical. In the new world of “remote everything,” the wholesale transformation communications service providers (CSPs) have been talking about for years is finally here. We’ve gone from “nice to have” 4K streaming for sports and gaming enthusiasts, to “must have” bandwidth and reliable connectivity for everyone, on all their devices, all the time, everywhere they go. Demand for new services in compressed delivery cycles is upending the old approach of managing an optical network with careful, diligent CAPEX planning and controls. And while all the fast-paced change is disruptive, the good news is that, even though network complexity appears to be growing, it’s never been easier to apply network data analytics to pinpoint the levers to pull and the right moment to pull them, in order to create new revenue opportunities and boost profitability.  

It’s all about the data. Data is everywhere. Network endpoints are GUSHING data, with streaming telemetry and new network performance management tools making data collection and storage cheap and easy. As optical networks take on more of the characteristics of service-oriented architectures, CSPs can finally break through simple connectivity and monetize the kinds of dynamic services previously reserved for the upper network layers. Now, we can use tools like pluggable OTDR with physical infrastructure and open interfaces to create direct linkages between fiber cuts, how that impacts network performance, and the customer behaviors related to that usage, and associated billing. CSPs can use these network data-gathering and network data analytics innovations to develop new revenue streams using flexible business models and hyper-adaptive pricing for direct AND indirect customers.

From Dumb Pipe to the Biggest Link in the Value Chain

When remote everything is combined with the speeds and performance of 5G services, both capacity and quality of service will become primary competitive advantages for CSPs. This has major implications for network expansion plans, and amounts to turning the “dumb pipe” into the biggest value-creating link in the value chain. Now, thanks to the new generation of network data analytics tools, the usage associated with content, development, devices, and endpoints can be directly linked to dynamic business and pricing models on demand.

To align revenue with network value, CSPs have a wide array of pricing and usage levers at their disposal. The trick is unique combinations of lever-pulls that meet consumer needs, promote desired behaviors, and align revenue with cost. 

Dynamic, on-demand business models and pricing can apply network data analytics to multiple factors, such as:

• Partitioning and prioritizing traffic
• Throughput and transmission speeds
• Managing high-traffic users that impact service quality for other customers
• Handoff capabilities between networks
• Managing low- and high-density geographies differently
• Pricing structures based on different types of traffic

Analyzing data between layers creates additional efficiencies beyond what legacy methods, like routing protocols and optical pipes working independently, can achieve. This form of network data analytics provides much greater sophistication in pricing and consumer segmentation as it relates to network usage.

To start, CSPs should consider a data initiative with these table stakes:

1. A strategy for collecting and storing all the data all the time
2. Organizational and technical access to all customer and network data
3. A commitment to remove organizational barriers that keep data siloed
4. A way to connect data to business results

The first three are organizational and can be accomplished with organizational goals and resources. The fourth requires tool sets and automation capabilities that are constantly informed and shaped by network data analytics and AI. Together, these network data analytics tools and automation capabilities are what make it possible to monetize the data by aligning revenue directly to network value.

Maximizing network value and monetization

The fastest and most efficient way to connect network usage to business results is to use cloud native microservices that glue the hybrid environment together, linking infrastructure and network analytics and AI microapplications to the OSS/BSS. Then, throughout the product lifecycle, network intelligence and analytics continuously inform connected services with finely tuned customer outcomes, turning anonymous transactions into personal digital experiences.

Automate the converged network with microapplications powered by analytics and AI

Virtuora AX is a collection of cloud-native microservices, data transformation tools, and network models that apply network data analytics to extend traditional network monitoring into actionable and automated network intelligence. Using distributed data sources, global topologies, and physical and virtual network element dependencies, network operations and DevOps can use microapplications to automate the network and make the digital infrastructure work harder, aligning revenue with network value.