The reasoning behind becoming a data-driven telco

Truly data-driven organisations excel at understanding their customers, driving new revenues, and evolving their business models. In order to achieve these benefits, telcos will need to create more useable data sets, accessible to all across the organisation – and to external partners in the future. What practical steps should they take to get there?

Becoming a data-driven telco

There have been many case studies over the last five years demonstrating the disruption caused by “data-driven businesses”, i.e. those using insights to understand customers, automate processes, change their business models and drive new revenues. In the future, this concept will become an integral part of what it takes to compete successfully, allowing organisations to understand and run all parts of their operations, work with their customers and partners and take part in external activities in new ecosystems. This applies to telecoms operators as much as any other industry.

This research builds on a range of reports STL Partners has previously published on strategic topics related to telcos’ use of data, including:

AI and automation for telcos: Mapping the financial value (assessing the financial value of using A3 (analytics, AI and automation) internally)
Telco data monetisation: What’s it worth? (assessing the financial value of creating data products for a telco’s enterprise customers)
A3 for enterprise: Where should telcos focus?
The future of work: How AI can help telcos keep up (exploring the long-term strategic impact of A3)

This research turns to the practical topics of delivering on these strategic goals. The diagram below offers an overview of the drivers and barriers affecting delivery areas such as telco data management and machine learning (ML) in the short and longer-termart.

What capabilities should telcos develop?

Telcos are reasonably sophisticated users of data, but their particularly complex web of legacy systems requires a good deal of work around data management and governance to enable the extraction of data sets to give a 360-degree view of the customer – and increasingly to provide training data for algorithms.

In the mid-term, telcos that are successful in selling IoT and becoming ecosystem players will require new A3 to deal with the increasing number of services, devices, price points and parties involved in providing service to a customer. Our research suggests that there is a range of new A3 technologies that can provide the automation and intelligence for this, as well as for the underlying data management processes.

In the longer term, A3 will speed up decision-making, impacting company strategy, new product and service creation, and customer experience. Humans will increasingly be supported by AI-, ML- and automation-powered tools in their decision-making. A similar progression will occur among competitors in telecoms, and in adjacent markets, increasing the complexity and speed of doing business. Besides integrating A3 into human workflows, working at increasing speed will depend on getting richer insights out of the available data with techniques such as small data and creation of synthetic data.