Communications service providers (CSPs) are under constant pressure to compete in an increasingly crowded marketplace, writes Lakshmi Randall, the director of product marketing at Denodo.

Customers are increasingly difficult to retain, and they are experiencing tremendous disruptions and opportunities, as players from many sectors converge and modularize an industry that was formerly vertically integrated. But even as traditional revenue streams such as voice have evaporated, there are a plethora of new market opportunities in data, media content and services opening thanks to higher bandwidth and vast penetration of mobile devices in developed and developing nations.

Adding fuel to the fire, subscribers are always in search of the latest and greatest services and will quickly gravitate to the provider with the best offer, best customer service, and the widest, most available network coverage. Most CSPs have heard the rallying cry and are seeking the best technologies to overcome:

1. Fragmented customer service: Customers expect to be treated like royalty, but representatives often do not have enough data at their disposal to help every customer right away, because data is often stored across disparate, separate systems. Customer frustration is one of the primary causes of churn.
2. Rigid business structures: Business support systems are traditionally very rigid. But companies are called upon to change their business models, pricing structures, or many other facets, in an agile manner. CSPs need a way to limber up their businesses.
3. Stagnating Networks: To remain competitive, CSPs need to continually optimise network operations. However, like business support systems, operational support systems can also be unyielding. CSPs need to find ways of introducing continual optimisation into their existing network infrastructure.

In order to address the challenges above, CSPs, from regional service providers to global networks, need to use the right technology that will enable them to: deliver operational business intelligence; improve customer service experience and self-service; rapidly 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 share data among partners to capitalise on joint opportunities.

While there are a wide range of approaches and technologies to leverage, such as cloud, business intelligence (BI), data virtualisation (DV) is becoming one to examine. Regardless of the technology an organisation ultimately selects, it’s clear that investing in an agile information infrastructure is as important – or perhaps even more so – than physical network infrastructures.

Because DV accommodates existing infrastructure in its existing state, it is relatively easy to implement, compared with other solutions. And because it provides a view of the data in real-time from a variety of systems that are normally very time consuming to integrate, such as transactional processing systems and cloud-based storage systems, it can support a wide variety of uses including:

• Empower customer service reps with real-time data: Every representative can access all available data to resolve more cases on the customer’s schedule.
• Gain business agility: With an agile architecture in place, employees are not affected if companies need to upgrade systems, or perform complete modernisations, in the background.
• More effectively optimise network operations: With real-time data, equipment can be proactively replaced or serviced, resulting in faster resolution of network-related customer calls.

Ultra Mobile has transformed the way information is disseminated and consumed throughout the organisation, and the company has successfully shifted from reactive business decision making to proactive business management. This is particularly important where EA pros are finding that traditional data architectures are failing to meet new business requirements, especially around data integration for streaming real-time analytics.

Ultra Mobile is a US-based, national mobile virtual network operator that provides talk, text, and data services within the US and between the US and abroad. Rapid growth required a swift evolution of the supporting IT systems, and the company’s BI team implemented a Hadoop based data warehousing platform to accommodate the new application data. However, even this modern, flexible platform couldn’t produce consumable data structures at the pace that business users required. It still required skilled subject matter experts to manually assemble and cultivate key pieces of information, which was not sustainable.

More critically, the company lacked a holistic view of the organisation’s data, so Ultra Mobile’s business users could not readily answer basic questions such as “Where will the next phase of growth come from?” or “How do we best retain our customers?” Ultra Mobile needed to improve the quality and speed with which information was delivered, and upper management gave the BI team five months to start transforming the company into an organisation based on data-driven decision making.

The company decided to implement a data virtualisation platform, which enables seamless, real-time access across the company’s disparate sources while providing a unified layer of governance across the entire infrastructure. Ultra Mobile deployed Looker as the exploration layer, and Tableau/Power BI, as the analyst tools. Since implementation, Ultra Mobile has become profitable, and its quality of service delivery has improved as much as 22% in some international destinations. The time-to-market for BI releases was reduced from weeks to hours, and it is now possible to pass billions of rows of business and consumer data through online dashboards that operate at close to the speed of thought. Quality-of-service issues are now proactively detected and corrected, averting mass customer churn, and Ultra Mobile can now quickly identify process inefficiencies and make changes that drive profitability.

Another Spanish CSP also applied data virtualisation and increased the quality of customer service having achieved a satisfaction index of over 94%. The CSP also decreased back-office workloads by more than 50%; increased first-call-resolution rate to over 90% and doubled its customer retention level.

While there are a number of options such as ESB and ETL for CSPs, many technologies consume too many resources and require too much time and cost to be viable. Data virtualisation can be a solid option because it integrates data without replication, it always provides useful context and in real-time. At the end of the day, organisations can avoid downtime for its customers, reduce the number of hours spent by its customer service reps in talking to customers, prevent the wrong router to be shipped to a given customer, and create some much-needed economic value for both itself and its customers.