(c)iStock.com/sorbetto
When organisations attempt to build strategic big data analytics programmes, the obstacles they face often vary by industry. Banks and insurers commonly wrestle with legacy systems, retailers struggle with excessive data volume, and telecom operators (telcos) approach big data from widely different starting points. Unlike other sectors, telcos do not share a single set of use cases; they pursue diverse initiatives as they seek to monetise data. Despite these differences in use cases, telcos tend to encounter similar underlying challenges when trying to capitalise on big data. Below are the three most frequent obstacles telcos face and how some are addressing them.
The silo stumbling block
Many telcos still operate in traditional silos, which prevents the adoption of an integrated big data strategy spanning the entire organisation. When data, decision-making and processes remain isolated by business unit—such as mobile, fixed, broadband or enterprise data—companies can’t consistently determine the best recommended action for a customer. Escaping these silos is essential to scale big data effectively: shared data across the business enables more accurate predictions and coordinated responses, whether for customer experience and churn management or for network-focused tasks like predictive maintenance.
Only by breaking down these barriers can a telco align customer service, field operations, order fulfilment and network management to create cohesive, proactive workflows. Without integration, insights produced in one area remain unused by others, and opportunities to improve outcomes are missed.
Lost optimisation opportunities
Siloed processes and poor data flow lead directly to missed optimisation and a frustrating customer experience. Consider a common scenario: a new customer signs up for an unlimited broadband plan but is instead provisioned with a capped 40 GB package. Months pass before the customer contacts the provider to correct the issue, and after assurances of upgrade, the service delivered may even be downgraded to a slower ADSL connection. Multiple calls and engineer visits later, confusion persists and customer trust erodes.
The problem is not merely poor service; it highlights broken handoffs and missed chances to act on available information. Why were two different orders placed? Who had oversight of the order and provisioning data? In these situations, the telco is so preoccupied resolving basic fulfilment errors that it never reaches the stage of optimising the customer experience or personalising services. This inability to coordinate order management, field activities, device provisioning and customer support is a direct consequence of functioning in silos.
Surmounting scale
Addressing silos and the missed optimisation opportunities requires a comprehensive big data analytics strategy and the organisational capacity to execute it. Many firms attempt incremental change—adopting one or two technologies to chip away at silos—but for large telcos this is often insufficient. Transforming a complex operator is more like an industrial-scale project than a simple technology swap.
Telcos are structured around multiple substantial business lines—mobile, fixed, broadband and enterprise data—each with its own internal divisions such as field service, device management and fault recovery. The scale challenge is therefore twofold: telcos must manage very large volumes of data and they must coordinate numerous functional units that operate independently.
As telcos deepen partnerships with social platforms and IoT providers, incoming data volumes will surge, increasing the potential for monetisation but only if operators adopt smarter frameworks and platforms to process and act on that data. The prize is significant, but realising it requires modern, scalable architectures and disciplined operational change.
One company, one big data vision
To overcome these obstacles, telcos must stop treating big data as merely a technology purchase and instead embrace it as an enterprise-wide strategic capability. Choosing a single big data product will not deliver sustainable results; success depends on aligning architectural choices, engineering practices and data science efforts across the business.
Without a joint perspective, organisations risk fragmented infrastructure, inconsistent processes and a lack of strategic direction—outcomes that can erode competitive advantage and market share. Telcos should identify successful use cases that emerged inside individual silos and then work to replicate and scale those successes across the organisation by removing barriers between data stores and enabling straightforward data sharing.
When telcos get integration and governance right, they can shift customer interactions from reactive problem-solving to proactive optimisation. A solid foundation enables the development of a future-proof architectural vision: pilot promising capabilities across departments, identify and close gaps, then roll out proven solutions enterprise-wide. With these steps in place, telcos can responsibly adopt new big data tools and technologies to deliver superior customer experiences and a more reliable, efficient network.