Telcos are unable to leverage big data analytics for business benefit because their organisational setups and data structures have yet to adapt to change, according to an Ovum report.
In new research titled Big Data Analytics and the Telco: How Telcos can Monetize Customer Data, many telcos still lack the necessary data management and analytics skills in-house to make their data work for them.
"Transforming ingrained operating models and business processes is a difficult task for telcos, and many are not entirely sure what they are transforming towards. Therefore, choosing a business intelligence and analytics solution and partner will be one of the most important strategic decisions that they face in the next year," said Clare McCarthy, head of Ovum's Telco Operations practice.
Predicting and reducing churn, promoting loyalty, upselling and cross-selling offers, and personalising services are all key areas where telcos can leverage big data analytics for business benefit, according to the study.
"The proliferation of smart devices and services has led to a considerable increase in the number of customer-telco interactions. This is happening through multiple channels, which is forcing telcos to sharpen their focus," said McCarthy. "As a result, mining a greater volume and variety of data, and doing so in real time, is becoming a powerful competitive advantage for telcos."
As data scientists are in high demand and in short supply, this area is ripe for vendor support, either with pre-integrated solutions or hosted services.
Telcos are generally turning to one of four sources for their big data analytics needs: their existing OSS/BSS providers, trusted IT vendors, telco analytics specialists, or incumbent network equipment providers.
Each carries its own particular competencies and strengths in vying for a share of a big data analytics market that Ovum forecasts will be worth US$7.7billion in 2018.
Ovum reveals that a well-executed big data analytics project requires flexible business structures and logical processes, not siloed structures with artificial constraints, for instance internal politics, that have been defined by the network domains.
In order to succeed, telcos also need to become more data-centric and take lessons from the leaner and more agile data analytics models that are currently being pursued by over-the-top operators.
Only once this issue has been resolved will telcos be able to effectively monetize the increased volume, variety, velocity, and value of the network, subscriber, and business data that they collect as part of their businesses.
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