In order to properly respond to rapidly evolving service demands, such as online video content and gaming, cloud computing, virtualization and mobile data, it is critical that service providers effectively can manage more complex networks, thus increasing their top-line revenue growth while maintaining or even improving operational efficiency.
Such architecture must have the flexibility and capacity to satisfy customer demands rapidly and reduce the time from service request to revenue collection. This is only possible if network resources can be reconfigured dynamically to fulfill new service orders with minimal human intervention. To underscore this point, a recent study from McKinsey Group stated that “a software-enabled network architecture can reduce test and service delivery time by 20 percent for initial service deployments and up to 70 percent for line upgrades (i.e. bandwidth, service type, QoS, etc.)”
To capitalize on such an approach, service providers need a comprehensive toolkit to aid in the service lifecycle, including (but not limited to):
- Proactive capacity planning and design tools
- Auto discovery of network elements, topology, capabilities and capacity during network deployment
- Rapid service provisioning from a unified GUI — with a view of services and the transport network — aided by service templates and control plane technology
- Reconfigurable and programmable components, such as network element line cards, which can be remotely changed on the fly
- Monitoring tools to ensure the network is running at peak performance.
Traditional Service Deployment Model
With traditional, static networks, service providers have to invest significant CAPEX to overbuild their network to ensure they have ample equipment and capacity to keep up with lumpy user demand.
In this model, the network planning team relies on an out-of-date inventory view of deployed equipment and available capacity in their network. Often, the only view of this critical data is an obsolete Excel spreadsheet or inventory tools that are maintained through manual data entry. Frequently, there are no active checks and balances between these back-office inventory systems and the live, customer-facing network. Human intervention is prone to errors, and outdated systems do not provide the advance validation of network asset availability to ensure proper processing of service orders.
This imprecise view of the network is a main cause of ill-placed network investment, inaccurate inventory control, stranded bandwidth, service turn-up delays and order cancellations, resulting in lost revenue opportunities.
A manual approach often takes up to six months for a service provider to fulfill a service order. Lack of visibility of network capacity, costly truck rolls, and cumbersome provisioning and service delivery tasks can lead to unnecessary delays. Today, customers demand virtually immediate service creation that is measured in hours, or at most, days, thus rendering legacy service delivery mechanisms obsolete.
