Managing the Challenge: How Ready Are You? (Cont'd)

This power to tailor offerings to each subscriber is possible not only on a monthly basis, but dynamically from moment to moment—a customer-empowering alternative to accepting the one-size-fits-all offerings determined by the provider. Theoretically, the number of services afforded by this on-demand model could match the number of subscribers.

Further, providers can deliver Web portals to customers for subscriber self-selection and self-management of services. In addition to spurring customer loyalty through enhanced choice, service self-management also reduces the provider’s own operational costs by effectively recruiting the customer to provision services.

One View of Subscriber, Service, and Network
Exploiting all these possible revenue-enhancing opportunities cannot be achieved without a central mechanism to manage the complex interactions inherent to greater choice.

Fortunately, IP service convergence enables providers to offer the subscriber a single point of entry into all IP services. This affords the operator the opportunity to develop a central authentication, authorization, and accounting system for all services and all subscribers. To fully exploit this opportunity, the provider can consolidate its disparate data repositories containing subscriber profiles (identity, privileges, etc.) and repositories containing applications profiles and their delivery requirements.

Once a service provider has consolidated subscriber and application profiles, subscriber access to applications can be automated based on subscriber-centric policy management. Such a policy management system correlates subscriber privileges with application profiles to apply and enforce policies on a per-subscriber, per-application basis. A primary benefit of this approach is the enhanced ability to offer choice without losing control of limited network resources.

Subscriber-centric policy management, in fact, transforms network engineering into expanded dynamic control. In traditional network resource planning, telephone networks were long engineered for peak calls on holidays. For example, in many countries Mother’s Day is by far the most popular day to make telephone calls. During the other 364 days of the year, the capacity might lay idle. Similarly, streaming servers might be manually chained together for well publicized Internet broadcasts (like the Victoria’s Secret fashion show in North America), and then manually reapportioned afterward. However, these resource allocation policies are fixed and network-centric: they are determined by aggregate network capacity for predictable events and effectively engineered into the network as a one-time-only task.

By contrast, peak traffic on a converged IP voice, data, and video network cannot reliably be known beforehand, either in aggregate or per subscriber. The personalized IP service paradigm therefore requires subscriber-centric, as well as network-centric, resource planning and allocation. Given the limits on last-mile capacity even in broadband access networks, sharing of resources among thousands of unpredictable subscribers must be managed not just once, but dynamically and continually.

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