tive SLM. Some products are based primarily on the collection of fault data and are built on top of existing fault management solutions. However, as discussed above, in many cases there is only a restricted capability to measure service quality when using fault management data alone. This type of approach also tends toward reactive rather than proactive management. The SLM architecture shown in Figure 7.6 indicates that a number of different data sources are required to support effective SLM. As discussed above, these data sources are not just network focused but also need to extract data from other busi- ness systems. A solution based on aggregating data from multiple sources raises questions regarding how the complexity of such a solution can be implemented and managed. There are two keys to achieving this kind of implementation. First, a hierarchical definition of services is used in such a way that allows the inheritance of generic key quality indicators. Figure 7.7 uses the definition of a OSS for Telecom Networks Time to provision Generic Provisioning success Commercial Service Customer fault reports BSS/xGSN availability GPRS Service Attach PDP context Round trip delay GPRS Interactive Service Data loss Application hits Specific Application access time GPRS Corporate access Server availability Average response time Figure 7.7 KPIs with a range of granularities. GPRS service to show the inheritance approach for defining SLA parameters. A number of measurables that are common to all services are defined. In addition to these, other parameters may be identified that are applicable to all GPRS services. The approach then extends to defining additional parameters that are required for managing an SLA against a specific GPRS service. This hierarchical approach reduces the time and effort to implement SLAs for new services that are based on existing services. Second, the solution must be capable of supporting the use of hierarchical meas- urements. There are a few solutions that successfully support this granular