AI/ML can forecast delays before they occur, making the service delivery predictable and fast
The global pandemic has highlighted the fact that high-speed broadband is a necessity, not a luxury. And fiber is one of the ways to faster broadband. This appetite for fiber means that service providers need to roll out fiber-based connectivity services faster. However, with the rising complexities in the order management process, delivering the service within the specified timeline is becoming a nightmare. The main business issue is unpredictability, which may be as important as speed. Its absence means frustration for service providers and their customers.
The main cause of this lack of predictability stems from the structure of the process. In many cases, the enterprise service delivery process has evolved and grown organically. The most common causes of dysfunction are:
- Multiple teams operating in silos prevent a clear view of the process and a single source of truth
- Manual hand-offs leading to errors and delays
- Dependency on external vendors, resulting in vendors operational issues being transferred to the service provider
- Lack of strategies to forecast order delays
- Lack of mechanisms for real-time tracking of service delivery flow
To overcome these challenges and tap into the next wave of opportunities, service delivery operations will require an advanced vision. AI/ML is at the heart of that vision. With AI/ML in service delivery, enterprises can predict and address delays before they impact the business. Enterprise AI can, over time, improve the prediction of potential delays and delivery dates at all points of the order journey. Over time, enterprises can achieve faster processing of orders with improved predictions.
The appetite for high-speed broadband demands a faster rollout of fiber-based connectivity services.