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There is no doubt that communications service providers (CSPs) will face continued disruption in their core markets from the web-scale internet companies, including AWS, Google, and Facebook. All are looking at ways to serve their business customers better in the face of relentless competition from these tech giants and from new competitors with disruptive business models that are not centered on connectivity. Many CSPs see analytics, reinvigorated by artificial intelligence (AI), as the tool that will help them in this quest. CSPs around the world are transitioning their analytics capabilities from those established in business intelligence (BI) to those enabled by AI and are readying themselves for better data-driven insights in the future. CSPs need to lower their operational costs and become more efficient in service delivery, and they need to be easier for customers to do business with. They need to invest in the data foundations, skills, and technology now.

Analytics is integral to CSPs' aspirations for efficiency, both at the network level and in business operations, and for additional revenue generation as they move toward more intelligent, personalized, and proactive customer interactions. Those in the process of opening up their networks also need to consider how their customers want to consume the network. It's time to develop appropriate service lines to fulfil those needs. There is also the tricky subject of data monetization. CSPs are well positioned to be legitimate providers of insight based on location data, and, in this area at least, they have time as well as the moral advantage over those tech giants that are increasingly feeling the force of regulators and governments when they fail to protect their customers from abuse of their personal data.

As 5G, AI, and the Internet of Things (IoT) become more pervasive and data volumes increase exponentially, there will be new opportunities for CSPs to explore. Analytics can be used to increase relevance and value by finding patterns and meaning within data. There is growth in the number of opportunities associated with the management and exploitation of information, and it affects all areas of CSPs: marketing, sales, human resources, finance, and operations. In parallel, processing power and advanced analytics tools have evolved. CSPs have new analytical tools, which – supported by cheaper, more powerful, and more flexible compute and scalable storage – allow them to extract more value from data, in a swifter way, and with a shorter time to market.

Foundational work is required in data management to make sense of the complexity that has resulted from large product portfolios that have evolved over time. Concerted efforts are being made in this area, but CSPs still have challenges in achieving a single customer view. CSPs recognize that they must be data-driven businesses or risk getting left behind.

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