Industry Trends and Market Drivers
Operators worldwide are facing a myriad of challenges – deregulation, changing service requirements, new technologies, industry consolidation and competition from non-traditional telecom providers. The telecom operator business model has drastically changed, requiring new tools to manage not just the network, but the business as well. Operators require solutions to meet the needs of planning and engineering departments, in addition to providing mission-critical statistics for finance, sales and marketing. Deriving “actionable” business intelligence - based on network traffic – is critical for ensuring network optimization, evolution, profitability and business innovation.
A critical step in managing and evolving the network and business is to identify and measure the right Key Performance Indicators (KPIs). The purpose of KPIs is to give an operator quantifiable metrics deemed important for long-term profitability from operations. Identifying the most important KPIs is the first step towards realizing increased efficiency and profitability.
Multiple sources of measurements - A typical network consists of multi-vendor equipment, each with its own method of producing performance data. Even when the equipment is from the same vendor, the performance data production and delivery procedures are often different. The result is an incoherent mix of data that provides very little value for operators looking to manage and optimize end-to-end network Quality of Service (QoS) and Service Level Agreements (SLAs) across multi-vendor, multi-technology networks.
Management of end-to-end QoS - Creating a framework of network-based KPIs is critical for ensuring end-to-end QoS and optimizing the network. Today's operator offers a portfolio of services - voice, video and data - across a hybrid network with various technologies, protocols and access types. As operators add more equipment types, they find it more difficult to manage end-to-end QoS for a specific service. Each network component produces performance data locally and has no indication of end-to-end quality or the impact on subscriber experience.
Quality of data - Reliable and error-free data availability is critical to managing network-wide QoS. Correlating data from multiple components offers many challenges:
Synchronization of collection intervals across components
Uniform aggregation and rollup of data
Ability to audit data
The lack of credible solutions generates low confidence in the accuracy of the collected data, thus impacting performance analysis, troubleshooting and ultimately, profitability.
Ability of multiple business entities to leverage data internally – Integrating and leveraging the same network data across multiple organizations is essential for operators to achieve short- and long-term business goals. If data collected by the operator has quality issues, along with multiple formats, then integration into day-to-day business procedures is difficult, if not impossible.
Model for Collecting Data Value
The Measure-Manage-Monetize model of “KPI management” allows operators to maximize their benefit from collected data, by offering a systematic approach for continuously improving the process of collecting, analyzing and utilizing KPI data. Measure the KPIs that matter for each entity within a business. Manage or create a process to gather information from the KPIs and feed the information into multiple organizations within the business. And, Monetize or develop plans to understand and leverage financial metrics – like service growth rates, Capital Expenditure (CapEx), and Operating Expenditure (OpEx) investment needs.
For example, when an operator wants to focus on network optimization using KPIs, they may want to look at the following network performance metrics:
Performance indicators for service quality like Answer Seizure Ratio (ASR), Network Efficiency Ratio (NER), Average Length of Call (ALOC), and average setup time
Service usage and trends based on application performance, e.g. prepaid service success and failures
SLA management with partner operators
Interconnection performance indicators for service quality like ASR, NER, average setup time, and abnormal call release
Service usage and trends based on application performance, e.g. Number Portability (NP) - number of times a call was handed to an operator without doing an NP dip
KPIs need to be organized by organizational relevance in order to be integrated into business operations, such as:
Operations and Planning
Providing quality of the network resources and their usage
Providing quality of service and the service usage
Providing a view into customer habits, service take rates and trending
Business and Executives
Providing early visibility into CapEx and OpEx needs
Signaling Based Solution
Operators can leverage network wide monitoring systems to collect signaling information for the purpose of generating “x DRs” - Call/Transaction/Session Detail Records. These xDRs can be used to calculate KPIs that can be leveraged to alleviate many of the problems confronting operators. Signaling-based KPIs are ideal for the following reasons:
Information is generated by an independent source
System is synchronized by a single clock source and hence, all data across a network is naturally synchronized
Measurements are based on network signaling, thereby being uniform irrespective of network element vendor
Possible to generate a network wide multiprotocol trace for troubleshooting and diagnostics
System is not in the critical path and measurements do not place a load on the network elements
Changes in measurements are easily implemented
The benefits of utilizing KPIs generated from a central performance/service system are:
Ability to analyze QoS and usage patterns, thus determining profitability based on income versus usage costs
Developing marketing plans that enhance profitability based on the capacity to analyze usage patterns by region and end-points
Capability to manage services in developing network, planning and growth initiatives
Identification of early fraud potential by analyzing origination data
Identification of potential revenue leakage
Generation of day-to-day usage reports for traffic analysis
Generation of week-to-week reports for identifying trending in take rates
Case Study Example – Resolving a High Rate of Prepaid Call Failures
A wireless service provider received complaints from prepaid subscribers concerning originated calls that would not complete.
On examining the call completion report from an integrated monitoring system (in this case, Tekelec's Integrated Applications Solution [IAS]), the service provider was able to quickly identify the cause as a prepaid Service Control Point (SCP) issue. A deeper analysis of the KPI information indicated that the prepaid transactions were timing out due to SCP overload. Examining the same call completion report over a three week period, the operator saw a pattern that showed the SCP had abnormal activity several times between 5PM and 8PM on weekdays and was dangerously close to engineered transaction capacity.
Based on this information, the operator added capacity to the SCP to alleviate the problem. The diverse reporting capability of the Tekelec IAS system enabled the service provider to quickly gain visibility into the problem and take corrective action, which resulted in improved service quality and fewer customer complaints.
Since the operator had a process in place to leverage the data into multiple organizations within the business, the following proactive actions were taken to avoid similar occurrences.
Setup a counter on the Tekelec IAS system to count the number of transactions on each SCP, irrespective of service
Setup an alarm on the IAS system to notify when the counter crossed a certain threshold in a given interval
Setup a corrective action process to alleviate the problem, if it occurred again
Setup automatic notifications to Network Planning & Engineering if an alarm occurs multiple times/days
Network Planning & Engineering
Setup an early warning metric to re-engineer routes and capacity to SCPs
Setup an early warning metric to grow capacity on SCPs
Established tighter alignment with Marketing and Business Development to understand service take-rate trending
Used the already established process of continuous improvement and setup an early warning metric for budget needs to sustain network operations and avoid future subscriber experiences of this nature.
By using the Tekelec IAS platform, along with the measure-manage-monetize methodology, the operator was able to quickly and efficiently solve the problem.
With a plethora of systems in the network, it is increasingly difficult for operators to manage performance data from individual systems to get an end-to-end view of QoS and subscriber experience. The preferred approach requires a network-wide monitoring system to collect signaling information and generate accurate performance indicators. By adopting the measure-manage-monetize model, these indicators can be leveraged across the business to achieve short-term and long-term business goals.
Tekelec's IAS platform processes and archives call detail records (CDRs) from the network that can be used to optimize a variety of services – prepaid, voice over IP (VoIP), short message service (SMS), etc. The Tekelec IAS system supports all requirements for monitoring hybrid networks: KPIs; multi-protocol and multi-technology; real-time and historical data gathering; drill-down capabilities; end-to-end network visibility and call/session tracing. IAS is being used today by more than “175” Tier 1 and 2 operators to monitor their networks – TDM, IP, 2G/3G, VoIP and IMS.
For additional information on Tekelec's portfolio of products, or to download Tekelec's “Monitoring Hybrid Networks” whitepaper, please visit http://www.tekelec.com