Operators need to embrace Big Data for more than just marketing

27 May 2014 | Goutham Ekollu

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Goutham Ekollu

Blog Author | Mu Sigma; Cross Industry Delivery Lead


The recent hype around Big Data stems from its positioning as being “revolutionary”. In fact, data insights have been used for centuries. The difference with Big Data is that it gives organisations highly sophisticated capabilities to glean business insights from exponentially growing data volumes and sources, and put them to practical use.

The recent hype around Big Data stems from its positioning as being “revolutionary”. In fact, data insights have been used for centuries. The difference with Big Data is that it gives organisations highly sophisticated capabilities to glean business insights from exponentially growing data volumes and sources, and put them to practical use.

Arguably, telecoms operators should be at the forefront of Big Data, given the vast amount of data they collect, not only about their subscribers but also about their network operations and traffic.

However, they have had to grapple with all this data being spread across disparate systems, which – until recently – could not be mined easily. The drive to integrate these information silos along with new analytics technologies and tools have enabled operators to view their data repositories more holistically.

There are four key areas where Big Data insights can dramatically change the game plan for telecoms companies.

The first, which has arguably been the most prominent to date, is micro-segmentation and individualised customer profiling and targeting, with the aim of optimising customer lifetime value.

Secondly, Big Data is critical to operators’ monetisation strategies. While many industries are trying to monetise their data, the range of information operators capture about their subscribers – social connections, location information, behavioural traits, lifestyle – is unique. In the face of growing competition and declining revenues, selling this data to other industries, from retailers to airlines, will become an important new source of income in the future.

Third, at a time when many operators have delayed infrastructure investments, Big Data analytics is still underused in areas such as network optimisation and management. Here, Big Data analytics can help with forecasting traffic patterns more accurately, reducing the need for overprovisioning. By enabling traffic to be analysed in real time, it can also enable a move to dynamic bandwidth management and real-time resource allocation.

Finally, analytics can help operators identify persistent bottlenecks that may have previously been missed among the myriads of data emanating from the network. It may be possible to resolve some of these through better network management, but others will require upgrading the network infrastructure. However, rather than having to make blanket upgrades, operators can now channel their investments into those specific problem areas.

While the telecoms sector is ideally positioned to exploit Big Data across its entire value chain, there is still much room for improvement when it comes to more complex applications in network optimisation and expansion.