White Paper. Big Data for Telecom: Monetizing Insights into Dollars

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1 White Paper Big Data for Telecom: Monetizing Insights into Dollars

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3 Monetizing Insights into Dollars Background Big Data is one of the hottest buzzwords around at the moment, and is believed to have a significant impact on businesses by changing the world. Some experts say that it can be bigger than the Internet, while some expect it to be the next oil. Big Data can be used as a tool to support several different initiatives within a business. However, it is important to understand that its ultimate aim is not to just implement a technology but fulfill a specific business objective, e.g. enhancing the consumer experience, developing new products, and reducing churn. Data mining and data warehousing is not a new phenomenon, these tools have been the foundation for efficient operations of Communication Service Providers (CSPs) and have been used for internal intelligence and external marketing. But now, with the advent of Big Data, the vast amount of consumer data which CSPs have accumulated over the years and remained underutilized for long, has suddenly become an accelerating factor to move business objectives into overdrive. In their relentless quest to monetize and optimize their operations, Big Data analytics will play a bigger role for CSPs. What is Big Data? Big Data basically refers to the ability to collect and analyze the vast amount of structured and unstructured data sets that cannot be processed with traditional data processing tools. It is this exponential volume and complexity of the data which makes it difficult and unprecedented. These data sets are characterized by high-volume, high-variety and high-velocity information that require innovative information processing. Ability to analyze the exponential amount of data can change the way we look at the world and everything within it. Some advanced Big Data analyses include getting traffic updates through population movements, predicting consumer behavior, concentrating marketing efforts to a specific target segment or locality, and preventing epidemic like Ebola and Swine flu. Why so much fuss about Big Data? Big Data is not a new concept; companies have been sitting on the vast amount of data for a long time. What has changed now is the variety and the complexity of the data that is coming through different data sources and in different formats. Broadly, there are two important facts about Big Data in the current scenario. Data deluge Today there are large numbers of data sources, thanks to the wireless boom, smartphones, 3G & 4G services. Digitization of everyday activities like book reading, listening to music and social media updates (Facebook, Twitter and YouTube) is creating humungous amount of data. Let us have a look at some of the live cases of datafication and digitization of our day-to-day activities. Earlier no one knew about one s book reading habits and pattern, but today through Kindle one can be tracked regarding the What, When and How of his/her reading pattern and habits. Similarly, live music and movies are creating digital footprints that can be tracked by companies. Smartphone usage gives information of people s location, favorite places and friends through social media. Devices are also connected to each other through the Internet of Things. Plenitude and Affordability of Big Data Technologies Cloud computing has made Big Data technologies such as MapReduce, Hadoop, and Hive affordable to everyone, irrespective of their size. These technologies come handy in dealing with the large amount of unstructured and complex data, which was not possible with the earlier available traditional techniques. Using these technologies, companies can now bring together different and previously inaccessible data sources to generate impressive results. Some real examples of Big Data analytics making a difference to people s lives: Various law enforcement agencies are using Big Data to take action in real time, e.g. FBI has a Law Enforcement National Data Exchange (N-DEx), which is a tool to encourage and enforce collaboration of data to track, predict and prevent crimes. Social media companies are using Big Data for various purposes; Facebook uses face recognition tools for automatic photo-tagging and suggesting friends. 3

4 Sutherland Global Services Today, political parties use data science to contest elections, e.g. the US President Obama s re-election campaign in 2012 took political data science to new heights. The campaign had a large and well-funded analytics team, which worked nearly two years to collect data and segmented and categorized the entire American electorate in ways that had never been attempted before. UPS (one of the largest logistics operators in the world) collects data from hundreds of sensors in each of its vehicles, which is then analyzed to predict things like when a part is likely to break down, allowing UPS to save millions in maintenance cost. Big Data Requirements and Challenges for CSPs Data is growing and so is the challenge for CSPs to collect, manage and analyze this data in pursuit of extracting as much value as possible. This data deluge has happened because of higher mobile penetration and demand for realtime services that are more video-intensive, integrated and interactive. Big Data has the following requirements and challenges ahead: data storage capabilities. But before enhancing storage capability, it needs to be understood that the data, spread across the organization, is collected in silos by various departments, which makes data collection all the more difficult. Variety Social media, mobile devices, and sensors monitor everything from an individual s reading and eating habits, utility use to medical compliance. These different sources are flooding CSPs infrastructures with data in myriad formats, which makes it difficult to clean and synthesize the data to be leveraged effectively. Velocity It s not the volume alone which has become a challenge to handle with, the velocity of data (the speed at which this data is generated) is creating the need to analyze it on the real-time basis. The penetration of smart phones and internet have increased the volume and velocity of the data, just think of 1 billion smart phones across the globe and a few seconds a social media message takes to go viral. Earlier the data was analyzed in batch mode, which does not permit the realtime analysis that companies today need to instantly analyze large amounts of information produced at high velocity. There was 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days, and the pace is accelerating. Eric Schmidt Big Data Application Areas for CSPs A lot of hype is surrounding Big Data; but it is not the hype that is leading to the exponential increase in the amount and complexity of data in the world. CSPs control communications infrastructure, which gives them a unique advantage of having available more data and insights about their subscribers, as compared to other players in the Big Data market. Volume Volume of data, which was in gigabytes at the start, rose to petabytes more recently. But today the amount of data generated every day climbs into exabytes, and soon will be into zettabytes. This overflow of data has been the result of LTE/4G mobile networks, IPv6, location sensors and machine-to-machine devices. Such humungous amount of data will demand efficient Once a Big Data analytic solution is in place, CSPs can more easily introduce new capabilities that will increase revenue and customer satisfaction, and reduce costs with the following uses: Optimizing Network Poor quality of service leads to customer dissatisfaction and is the primary reason for 4

5 Monetizing Insights into Dollars churn. CSPs can use network, service and device data along with usage to manage their network and service delivery. Big Data and network analytics can have dual benefits of enhancing the customer experience and optimizing capital investments, which further results in reduced churn and more revenue. Sales and Marketing Customer data of different types like billing and payments records, consumer complaints through customer care, usage pattern for calls, SMS data and other multimedia products can be used for marketing campaigns and understanding consumer behavior, which can further help in churn management. Monetizing Big Data The most important and soughtafter area of Big Data analytics monetization of big data surrounds new business models. CSPs have the opportunity to cash in on the monetization trend by examining their different types of data subscriber, device, usage, demographic and location-based and then selling the anonymized data to third parties such as retailers or outdoor billboard operators. Several CSPs have formed business units, such as Verizon s Precision Market Insights and Telefonica Dynamic Insights, to implement Big Data analytics, addressing this Big Data market; and many others are expected to follow suit. to population location and movement to get insights for decision making. This anonymized and aggregated mobile network data can assist companies and government organizations to measure, compare, and understand what factors influence the number of people visiting a location at any time. To monetize the data on population movement, CSPs either have to invest in and develop sophisticated platforms or should tie up with partners who have expertise and platforms for such analytics. Big Data Analytics Market Opportunity Telecom Big Data Analytics Market by Type Monetizing Big Data is the most Sought-after Opportunity by CSPs Telecom Big Data Analytics Market USD Bn Strategies for Monetizing Big Data CSPs have long been collecting customer data and had access to key information like subscribers location, mobile devices being used etc., but this information has rarely been used other than for some internal planning and marketing. Today, the most promising opportunity for CSPs arises from new business models. These revenue-generating models can be the key to CSPs pursuit of increased top-line. However, to harness this opportunity, CSPs need to understand the data & analytics value chain before venturing into any new business model. It is important for them to first identify vertical opportunities in various industries, for example, advertising and market research companies seem to be the most ready and developed market interested in purchasing anonymized consumer data on demographics. To monetize the data on population movement, CSPs either have to invest in and develop sophisticated platforms or should tie up with partners who have expertise and platforms for such analytics. Similarly governments, transport authorities, city planners and retailers would also be interested in data related 5

6 Sutherland Global Services What CSPs are doing to tap Big Data Opportunities? Y-O-Y Total Revenue Growth CSPs across the globe have many goals, such as increasing top-line, checking expenses, reducing churn and increasing subscriber base to remain competitive. Hence, companies have started to think how they can utilize vast amount of data and insights they have to achieve these goals. However, the main question for CSPs still remains unanswered: What are the tangible benefits of Big Data in terms of revenue and how to convert insights into dollars? Large CSPs like AT&T, Verizon and Telefonica have already started looking for new revenue streams and seeking ways to generate cash from their vast volumes of network and subscriber data. Y-o-Y Growth for Wireline Revenue AT&T, through its program called Service Quality Management, has invented breakthrough technologies that use sophisticated analytics to make sense of its massive volume of network data and detect what customers are experiencing. The company has made Big Data analytics a core component of its business decision-making process to drive growth and maximize customer satisfaction. AT&T is not alone to go down that road; Verizon Wireless formed its Precision Market Insights team in Through Precision Market Insights, Verizon provides addressable advertising solutions for agencies, brands and channel partners. Y-o-Y Growth for Wireless Revenue Similarly, Telefonica announced the establishment of Telefonica Dynamic Insights, a new global business unit, dedicated to identifying and unlocking the potential opportunities for creating value from Big Data. It plans to develop a range of products and services using different data sets, including machine-to-machine data, and anonymized and aggregated mobile network data. How to Convert Insights into Dollars? CSPs today face various challenges including stiff competitive environment, declining wireline and voice revenue. It is imperative for CSPs to review customer preferences, launch new products and offers targeted towards growing segments. Big Data can certainly help to identify and strategize new focus areas and large CSPs like AT&T and Verizon already seem to be learning and using the big data tools to maintain the revenue growth. customer needs and preferences are changing, these CSPs have utilized big data tools very well in order to shift focus towards more lucrative and growing segments. As evident, AT&T and Verizon have maintained their topline growth in spite of the fact that their wireline business has gone down. The focus is on wireless business where 6

7 Conclusion Internet giants like Google, Apple and Facebook have leapfrogged in terms of Big Data conversion into cash. CSPs definitely have an edge over other players with their richer information of consumers; they just need to find ways to generate new revenues from this advantage. Competition in the Big Data space is brewing up with new and emerging players entering in a large scale. Hence, it is important for CSPs to start strategizing Big Data initiatives by developing platforms, identifying partners and looking for attractive verticals to target upon as they surely cannot afford to procrastinate for too long. Copyright Sutherland Global Services Sutherland Global Services 1160 Pittsford-Victor Road Pittsford, NY Produced in the United States of America July 2015 This document is current as of the initial date of publication and may be changed by SGS at any time. Not all offerings are available in every country in which SGS operates About Sutherland Global Services Established in 1986, Sutherland Global Services is a global BPO and technology-enabled services company offering an integrated set of backoffice and customer facing front-office services that support the entire customer lifecycle. It is one of the largest, independent BPO companies in the world serving marquee clients in major industry verticals. Headquartered in Rochester, New York, United States, Sutherland employs over 36,000 professionals and has nearly 60 global delivery centers in the United States, Australia, Brazil, Bulgaria, Canada, China, Colombia, Egypt, Estonia, India, Jamaica, Malaysia, Mexico, Morocco, the Philippines, Slovakia, Sweden, the United Arab Emirates, and the United Kingdom. For more information, visit Please recycle. 7