Predictive Network Analytics Essential for Next-Gen Networks

In today’s highly competitive communications marketplace, communications service providers (CSPs) need to know their subscribers and understand how they use their services. They need to deploy innovative business models that maximize revenue, and efficiently manage their network resources. Predictive network analytics is critical to their success going forward because it is the only type of network planning, which can enable them to do this.

A recent Heavy Reading White Paper discusses how network analytics is becoming an essential part of understanding and anticipating the requirements of today’s next-generation networks. The paper covers the traditional network analytics systems that are still in prevalent use today:

• Pure-Play analytics, business intelligence or data warehouse solutions
• In-house network planning tools
• Traditional service fulfillment systems
• Discovery and Reconciliation (D&R)

In contrast to these reactive approaches requiring real-time network data, predictive network analytics enables network-wide management without additional network-measurement hardware or signaling overheads that typically limit reactive implementations. In addition, the proactive approach detects and handles changes over time caused by subscriber and network modifications. Carriers can no longer afford to run at the low utilization rates of the past, but instead need a better understanding of traffic patterns and their impact on the network’s performance.

A next-generation analytics based system can take carriers out of traditional planning mode and transform them into much more efficient just-in-time type operations. The whitepaper goes into detail on the analytics-driven planning systems which are required by today’s networks.

It highlights the difference between traditional and next-generation network planning solutions. We agree that next-generation network analytics are indispensible to solving today’s key business problems. This approach can assist with LTE migrations, virtualization analytics, and other common network challenges as well as applications and use cases for these solutions. This can only be accomplished with the type of accurate network planning afforded by predictive network analytics tools such as those provided by VPIsystems.

In order to survive in today’s increasingly bandwidth hungry and rapidly changing environment, operators need to leverage these new tools for network optimization, monetization and increased efficiencies.

We have seen examples of this in our own client base. For example, a Tier 1 mobile operator was able to predict RAN congestion with greater than 90 percent accuracy using our predictive network analytics tools and the number of predicted congestion events was within 2 percent of those observed in their production environment. To read this entire case study, click here. We have seen similar results in the Cable MSO space as well. Where we have seen CapEx and OpEx savings in the range of 30 percent and the reduction of planning cycle time from months to days. To read this case study click here.

Russ Green is SVP, Product Management & Marketing, VPIsystems . He has 15 years of enterprise software experience in large-scale, high availability systems, working with globally-distributed development groups and customers. Before joining VPIsystems, Russ was the vice president of Development for 724 Solutions, based in Switzerland. Contact him at russ.green@vpisystems.com.