As traditional business models and boundaries collapsed, communications service providers lost their dominant positions in the service delivery value chain. The new services landscape is replete with competition from inside and outside the industry, forcing an infrastructure evolution that can provide connectivity and services for everything, including machine-to-machine (M2M) and Internet of Things (IoT) applications as well as virtual network services. This evolution into what is known as a digital service provider (DSP) represents a significant shift in the way service providers must run their day-to-day operations.
Transforming into a DSP is much more than just creating a new business unit. A DSP must be able to:
- Behave like a nimble retailer that can quickly and efficiently adjust to evolving market conditions and customer demands.
- Sell and distribute products that are assembled from a constantly changing menu of devices and applications provided by a growing number of partners and suppliers.
- Manage a complex supply chain rather than a network and distribution channels instead of direct sales.
- Ensure a consistent and high-quality experience to every customer at every level through positive network performance, successful application/service delivery and proactive customer care.
The transformation from traditional network operator to digital services provider is now more prevalent than ever across the globe, but it is a step-by-step process that requires innovation in key business and technology areas. As customers begin to dictate when, where and what products are delivered, DSPs must recognize that transformations in the network must extend to nearly every aspect of the business. Let’s take a look at five areas in which data management-centric innovation gives the service provider a strong baseline for their transformation into a DSP.
1. Network Visibility and Adaptability for Service Assurance
The best way to ensure that network-based services are delivered effectively is by having a comprehensive view of network elements and activity as well as an understanding of current-state performance values. However, the ability to make real-time decisions based on existing network configurations and proactive, future-state changes is where the true value resides. By using data management processes that capture and examine activities across different network elements at different times, service providers can detect network anomalies that may cause congestion or outages and use analytics to make better proactive decisions. This also allows traffic to be rerouted to avoid poor service performance and ensures that any and all service assurance KPIs or requirements are met. A true digital service provider will adopt this type of network analytics strategy to provide visibility into the network and enable the reconfiguration of traffic patterns in intelligent, self-configuring and self-optimizing environments.
2. Centralized, Dynamic Product Catalog for Faster Time-to-Market
Service creation is critical to DSP revenue growth, but oftentimes is hindered by the tangle of legacy BSS/OSS infrastructure and operational approaches. While a full-scale overhaul may be out of reach, DSPs can improve service operations by deploying a centralized and dynamic product/service catalog. The catalog can act as a hub for digital service lifecycle management, providing a single data source that becomes the master reference point for products and service definitions throughout the OSS architecture. It can eliminate disparate legacy databases that hinder service creation and fulfillment. This reduces time-to-market through the creation of pre-validated service building blocks that come from service providers and partner-based service elements. As a result, new products and services rarely have to be started from scratch and different “flavors” of existing service types can be defined and made live in just hours.
3. Greater Service Lifecycle Data Intelligence for Improved Customer Experience
Since digital experiences revolve around customers, effective use of customer data is paramount to delivering the contextual experiences customers want. While every customer journey is different, the typical service lifecycle of a customer will usually fit the patterns mapped to specific metrics, including customer demographics, service usages, billing characteristics, etc. Many service providers today lack the ability to provide continuous and consistent customer journeys across channels based on these characteristics and aren’t helped by marketing-, sales- and care-based operations that are siloed and inconsistent. Data intelligence tools that provide customer journey management capabilities leverage relevant data sources to better manage customer lifecycles, address issues, make recommendations and take intelligent actions across a variety of channels. This insight means better guided journeys, more personalized customer experiences and, ultimately, happier customers.
4. Zero-Touch Provisioning for Faster Network ROI
Zero-touch provisioning is just what it sounds like: the automated configuration and installation of modern network devices and infrastructure with minimal human input. It reduces the need for human activity or intervention and uses data intelligence to ensure networks are located and provisioned correctly with all relevant networks settings made automatically. This reduces the long-term costs of network management, eliminates potential error-prone human intervention and facilitates the faster delivery of new services. At a time when customers are more fickle than ever and willing to churn at a moment’s notice due to service quality, eliminating any service issues through automation will be of significant benefit.
5. Extended Data Management and Analysis for Added Enterprise Customer Value
As mobility becomes increasingly central to enterprise day-to-day operations, usage data intelligence is of great value, particularly if it can be boiled down into actionable insights for specific customers. From basic information like usage and cost data to metrics derived from changes in location or corporate policy enforcement around app usage, key information about how, when, where and why enterprises are using mobile services and devices has substantial value. Service providers today often do not provide much beyond billing, usage and device inventory information. As such, extending engagement with enterprises to provide insight into data management and analysis and subsequently finding ways to cater to those needs with value-added services represents a market opportunity and an important customer experience factor.
Paul Hughes is director of strategy at Netcracker Technology and has more than 20 years of telecom industry experience. Paul is responsible for all aspects of Netcracker’s strategic initiatives across BSS/OSS, customer experience and cable specific business lines. Before joining Netcracker, Paul was program director for IDC’s Storage and Data Management Services practice, where he provided research, consulting and marketing support to communications, media and cloud service providers in the areas of digital transformation, customer experience, business requirements for new revenue models, and new product strategy and development.
