Rev2 Networks

RiskView® service provider case study

One of our customers is a leading telecommunications, media and entertainment company with a portfolio of operations that includes a full suite of advanced digital television, voice and high-speed Internet services, some of the country’s most-watched television networks, and valuable local media and programming properties.  The world-class system connects residential and business customers to communications services, which include digital television, digital voice, high-speed Internet and wifi.

As a customer-service driven Company, the service provider is constantly investing in the technology underlying its network infrastructure to ensure that its services are always available and that its customers’ experience is positive.  In early 2010, the company implemented the RiskView® Risk Concentration Analysis™ tool from Rev2.  The RiskView Service Assurance & Business Continuity module is using next-generation data aggregation and correlation to help the company identify chronically failing equipment, prioritize preventative maintenance, and prevent outages.

Using RiskView, the Company is identifying chronically misbehaving devices within the network (UBRs, backup batteries, etc.) that are causing a high level of customer pain.  RiskView is able to correlate multiple events around a single device – while the events may not appear to be significant individually, when repeated over time they may prove to have a major impact on subscribers.

At the Company, RiskView currently collects data from several sources:  trouble-ticketing, truck roll data, network event data, and call center calls.   This data is consolidated and reported to the Company’s network engineers for analysis on a monthly basis, enabling them to quickly identify chronically misbehaving devices on the network and the associated financial cost.

A chronically misbehaving device is defined as one that generates three or more tickets over the course of the month and, after correlation of all data sources, is determined to have a material service impact cost.  Further, RiskView helps the engineers analyze the resolution codes around each ticket enabling them to determine, for example, when the device was last fixed, what the problem was, how it was resolved, and how many times the device has misbehaved.

This resolution data is disseminated to the relevant regional service organizations, allowing them to proactively address the issues.  Significantly, the engineers can quickly determine which services and which subscribers are potentially impacted by each misbehaving device.

Using the RiskView solution, the Company gained insight that led to a more proactive maintenance program on devices having a material impact on performance, as well as address several key process changes:

• Misbehaving devices that had a ticket opened for repair had an excessively large number of resolutions logged with an “NTF” code – No Trouble Found.  With RiskView, however, it was determined that these devices continued to misbehave and impact subscriber availability. Analysis of this information led the Company to develop a proactive new policy:  if a device issues three NTF tickets in a row, the third ticket should not be accepted and the device should be investigated until the source of problem was found.

• After analyzing RiskView data, the Company further discovered that a significant number of tickets that were coded “non-impact failures” did in fact impact subscribers.  A non-impact failure is defined as a device that goes down for a certain period of time but has no material impact on the subscriber.  As a result, a new process was put in place in order to more accurately capture the true impact of an outage and better prioritize service activity.

• Using RiskView, the engineers were able to isolate a service issue in a geographical region and correlate the problem to a chronic failure of backup battery packs called tmem batteries in peer supply boxes.  The tmem batteries are now performing at an optimal level.

• Using RiskView, the engineers were also able to isolate a geographical region that was below par for the critical ticket measurement of “MTTR” – Mean Time To Repair.  It was quickly determined that the problem was not with the actual repair being provided, but with a miscoding of tickets.  A new policy was quickly enacted to correct the coding issue and to ensure the assignment of tickets to the proper internal repair organization.

With its RiskView implementation, the Company is cementing its standing as a forward-thinking service provider organization – investing in state-of-the-art infrastructure support technologies to sustain the availability of its state-of-the-art services.  In addition, the Company estimates that it realized a return on its RiskView investment within days.

For more information, please contact Rev2 at inforev2net.

Copyright © 2011, Rev2. All rights reserved. The RiskView® application is a registered trademark of Rev2. The Rev2 Managing Risks That Matter™ logo design and the Risk Concentration Analysis™ (RCA) methodology are trademarks of Rev2. All other trademarks in this document are the properties of their respective owners.