Service providers are grappling with the operational challenges of managing the massive amounts of data, both unstructured and structured being generated by the increasing expectations of their always-connected customer base. Such data takes on many different formats including image, voice, message and web traffic. Moreover, machine to machine generated data, multiples the network traffic that Telcos must handle. This complicates management of network bandwidth as well as overall data management.

To add to the problem, the increasing use of content and media rich services is combining with a challenging business environment in which service providers need to make use of the vast amounts of data being produced by, and passing through, its network. Increasingly customer data is being analysed with the objective of getting business intelligence to improve customer experience and control costs, and thus generate revenue.

Data Growth and Challenges

A recent report by Ericsson states that there will be 50 billion internet connected devices by 2020, with the fastest growing telecommunications industry being in the Asia Pacific and Africa regions. According to TM Forum Report, data has grown at a compound annual growth Rate (CAGR) of 29 per cent over the past five years, and is likely to grow at double-digit rates in the future. Today there are nearly 6 billion phones in operation, and over 2.5 billion of them are in Asia.

The data growth is increasing due to the transition for 2G networks to 3G and beyond, combined with the continued reduction in price points for smart phones and tablets. By the end of 2013, many smart phones will be sold for less than $100 USD, which alone will accelerate the transition to 3G and also bump network traffic. This trend of democratization will lead to increased adoption of mobile devices and significantly higher data usage. The number of 2G connections will peak in 2013, according to Analysys Mason, at 2.3 billion subsricbers, then will decline, as 3G subscriptions grow, rising to 1.5 billion by 2016, or 41 per cent of SIMS – up from just 1 per cent in 2008. All of those new 3G users have bought the proposition of instant, real time access anywhere to their data and content, from any device. And as services grow, and as network traffic rises; three things will become mandatory to handle all this big data:

Network analytics to address the degraded application performance due to increased network traffic in limited bandwidths

Better tiered storage data management and automated data migration strategies, to lower the cost of handling all the data

Better metadata lifecycle management, to handle the machine-to-machine, application generated, and human input metadata due to the increased applications and data files.

This data growth presents multiple operational challenges to the service providers. To successfully exploit this data, service providers need to put cohesive strategies in place to be able to capture, control and understand the data. This data must be archived (to meet privacy regulations, for example) in expensive storage mediums, which create economics that simply do not make business sense. While it is true the per gigabyte storage cost is declining, the increase in data is rising more than the decrease per unit storage cost, meaning service providers must spend increasing amounts of money to store, backup, and manage the data.  As a result, many service providers are starting to focus on providing storage infrastructures and solutions that facilitate efficient management and use of big data, in order to better address the operational challenges presented by this deluge of network and user generated data

In addition to creating and implementing a strategy which manages the operational challenges of big data in the telecommunications environment, service providers are under increasing competitive pressure to leverage their vast big data assets to add value to their customers, as well as to use the data to drive revenue opportunities.

Opportunities for service providers

Effective use and montetisation of big data is about creating a holistic, end to end approach which includes storing, capturing, searching and analysing data.  While service providers currently collect (albeit in multiple silos) and store the data, the end to end organization of this data, and the required analytics across the entire data set is not up to the same level, at least in many service providers. In other words, they have yet to evolve from a storage provider to a solution provider.

For the service provider, the combination of Big Data Analytics and Business/Operations Support Systems (BSS/OSS) is evolving toward Customer Experience Management (CEM) and Subscriber Data Management (SDM). CEM and SDM provide the analytics applications which take the massive amounts of data generated by the network and subscriber and provide business focused solutions.  CEM uses big data, such as service subscription records and customer complaints, and analytics to monitor, track, and improve customer satisfaction at every touch point, and within the network.

The market dynamics recognize these facts. The Analysys Mason report notes that:

CEM has risen to near the top of the priority lists of communications service providers

CEM has become a central focus as competition increases and things like churn, retention and loyalty take center stage

Service Providers need to provide differentiated value based on something other than offering a commoditized service or product at a more attractive price.

Service providers are taking positive steps to improve their CEM and move to big data aware architectures, including:

Transforming CRM and BSS/OSS systems and processes in order to take advantage of big data and advanced analytics

Utilising data mining and advanced techniques to analyze the increasingly large amounts of unstructured data from social networks and other user generated content

Leveraging the underlying data to gain valuable insights into customer behaviour, allowing for the creation of differentiated service plans to improve revenue and increase customer retention (i.e. reduce churn).

Monitor the entire customer experience from network edge or device through the network and including call center and all its interactions, in order to increase retention, and provide upsell and cross sell opportunities at all customer touch points.

Creating a Big Data capable Infrastructure

To overcome various operational challenges, and unlock the business value, service providers will need to improve their IT infrastructure, storage management knowhow, and business models. With the right selection of IT infrastuture solutons, they can be assured that they will meet the operational challenges of big data in their networks.

The right IT infrastructure solutions can help a service provider:

Monetise content with management and analysis tools

Deliver more services faster with common management for all data and platforms, contributing to a simple, more reliable operating environment.

Improve the economics of big data infrastructures by reducing the costs, and improving efficiency of data archiving, backup, and consolidation

With these exponential growth of telecommunications market worldwide, the challenge of big data can only be more prominent.  However, by leveraging big data aware architecture capability of advanced analytics, service providers are better positioned to achieve improved revenue from the boom in content-rich communications.