Global telecommunications and media industries are seeing tremendous disruptions and opportunities. In the most recent decade, nearly 70% of the companies in the Fortune 1000 list were new (as shown in the book “Built to Change: How to Achieve Sustained Organizational Effectiveness”, by Christopher Wiley), which is a 2-fold increase from previous decades. No one is safe! Players from many sectors are converging and modularizing an industry that was formerly vertically integrated. But even as traditional revenue streams such as voice have dried up, there are vast new market opportunities in data, media content and services opening via higher bandwidth and penetration of mobile devices in developed and developing nations.
Today companies have to decide on their strategy to become reliable network and services providers, own the customer experience through targeted applications and content, business enablers to open their networks to a portfolio of own and partner services, or true global multi-marketers that combine all of the above. The primary business imperatives for these strategies is agility - agility in data, agility in business processes, agility in partnerships together providing agility in responding to customer and market needs. Thus the investment in an agile information infrastructure is on par with or greater than physical network infrastructures. Learn how you can take advantage from the benefits of data virtualization for telecommunications and media.
Telecommunications players from regional service providers to global networks have leveraged data virtualization in sophisticated and diverse ways to deliver operational business intelligence, improve customer service experience and self-service, enable rapid rollout of new products and services by virtually integrating rigid OSS/BSS systems, transfer customer and network big data analytics into operational data services, and enable data sharing among partners to capitalize on joint opportunities. Data virtualization for telecommunications and media benefits includes faster access to disparate data, integrated canonical views aligned to business needs, and data services that accelerates new application and product development. Some example use cases are below:
This is not the same Customer 360 promised by CRM vendors a decade ago based on partially or wholly replicating customer data into one central place. Today we have innovative challengers and global giants using data virtualization to enrich core customer information with other data that continues to live elsewhere - transactional, network, social, location, feedback, competitive, partner, and more - to provide a truly superior customer experience. And this experience is delivered seamlessly through multiple channels of engagement including self-service portals, retail, call-centers and devices such as contextual TV menus, DVRs and set-top-boxes by the use of flexible data services delivery modes.
Companies are generating immense data from their networks, customer usage, social networks and web / media. While some of this has traditionally been used for marketing and advertising campaigns online or offline, customers are getting savvier in ignoring or bypassing those. What has proven to work much better is driving deeper customer understanding through customer analytics and combining that with operational scenarios to deliver contextual marketing. Our customers are using data virtualization to deliver numerous examples such as cable package upsells recommended through DVRs, co-marketing of partner services in travel, entertainment, insurance based on network and social analytics, intervention to prevent customer churn based on usage data, etc. Data virtualization is also used to aggregate data for other types of analytics such as security, fraud, and revenue loss.
A giant Telco operating in Europe and South America, uses data virtualization to knit together network monitoring and analytics applications from many vendors, call logs, communication services usage patterns, guaranteed service levels to premium customers, and other factors to provide situational awareness and operational business intelligence on their networks and prioritize critical response actions when something goes wrong. The virtual data services are reused for accurate view of network assets and inventory and their useful service life to recommend ongoing optimizations to the network reducing network maintenance and upgrade costs.
Data retention is mandatory in many countries to comply with regulatory norms and must be produced for legal or security investigations to competent authorities. It is also commonplace in online e-commerce and telco services to retain extensive data on customer transactions and usage for better customer profiling and market intelligence. Data virtualization offers a cost-effective solution to collect and aggregate this information and expose data services for final use. DV allows parts of this data to be in big data systems as cold storage while only the most recent or useful data kept in expensive analytical data warehouses. Data virtualization creates a logical data warehouse layer across both saving cost and easing access.
Relevant information available to operational workers in the context of the customer interaction not only improves customer satisfaction, it also cuts operational costs. Data virtualization has been used by many companies to derive direct ROI from reduced call center agents, reduced training time for agents, lower wait times in high-rent retail storefronts translating to smaller stores, and reduced errors and resolutions in back-office operational costs.