Big Data

Five Ways A Modern Data Architecture Can Reduce Costs in Telco


During the COVID-19 pandemic, telcos made unprecedented use of data and data-driven automation to optimize their network operations, improve customer support, and identify opportunities to expand into new markets. This is no less crucial today, as telcos balance the needs to cut costs and improve efficiencies while delivering innovative products and services.

The way to achieve this balance is by moving to a modern data architecture (MDA) that makes it easier to manage, integrate, and govern large volumes of distributed data. Adopting an MDA is more efficient and cost effective than legacy data architectures which are siloed, poorly governed, with vast redundant data sets and data processes that are expensive and expose the company to risk. 

An MDA allows you to identify silos and disparate processes, providing visibility across data functions and assets allowing rapid consolidation and harmonization. When you deploy a platform that supports MDA you can consolidate other systems, like legacy data mediation and disparate data storage solutions. There are savings to be made in modernizing the data stack itself, in addition to applying data across the enterprise.

A modern data architecture can provide the foundation for real-time visibility into the health of telecom networks, enabling telcos to rapidly diagnose and resolve service issues and boost operational efficiency. And by facilitating transparent access to applications, services and real-time data sources, telcos can develop personalized products and services that transform the customer experience.

Reducing cost with modern data architecture

A recent report from McKinsey says that “Telcos’ success hinges on leveraging data and deploying advanced analytics, AI, and automation at scale to drive new growth and change the broader economics of the business.”

To realize this end, Telcos should take the following steps to adopt a modern data architecture—minimizing disruption, controlling for risk, and positioning themselves for growth.

Modernize data flows. Most telcos rely on legacy applications that create data silos and limit interoperability. By adopting a modern, distributed data architecture (see chart below), they can eliminate silos, reduce capital and operational expenditures, and improve worker productivity. A modern, distributed data architecture supports a hybrid data platform for managing, integrating, and governing data across on-premises and multi-cloud environments, enabling a panoramic view of data and making it easier for telcos to pursue new business opportunities and respond to changing conditions.

Offload data from legacy, on-premises analytic platforms and appliances. On-premises analytic systems can often cost more than cloud-based alternatives. Appliance-based models are usually significantly more expensive than disaggregated solutions. By adopting a modern data architecture, telcos can offload excess data to inexpensive virtualized storageon-prem or in the public cloudensuring its seamless availability to existing users and applications. In this hybrid model, on-premises systems remain the primary interface for data access, enabling telcos to avoid costly and time-consuming application rewrites. 

Reduce customer complaints. Customer complaints are costly! Telcos can correlate data generated by connected devices with existing sources of customer data to identify and predict service outages and disruptions. By using predictive models and machine learning (ML), telcos can reach out to affected customers, suggesting workarounds or offering credits, refunds, and incentives. By using ML to analyze data from call centers, chat logs, and social media, they can create personalized interactive voice response (IVR) messages, de-escalating high-intensity interactions and providing a tailored customer experience.

Simplify, and where possible, automate governance. Data governance is crucial for ensuring data accuracy, quality, integrity, and privacy, as well as for promoting trust in data. However, the activity of millions of connected 5G devices, for instance, will present an unprecedented challenge to data governance. Telcos will need to use device data to enhance their networks, transform their operations, and improve the customer experience. To achieve this, they must integrate this data with sensitive information from customer accounts. Navigating this challenge requires robust data governance controls that permit a holistic view of data, track how data is used and by whom, allow for role-based access, and enable authorized users to access data easily and securely. Privacy and other compliance constraints are increasing, and making sure that data flows are equipped with the appropriate toolssuch as tagging, masking and tokenizationcan offset significant future costs.

Reduce the frequency, severity, and duration of network outages. By correlating network performance with behavioral and hygiene data (e.g. weather, maintenance logs), telcos can predict and prevent outages, optimize coverage, detect threats, and enhance the user experience. To cite one use case: telcos can use predictive modeling to define thresholds for events like network element failure, triggering alerts so managers are automatically notified.

How Cloudera supports telcos and the move to modern data architectures

Cloudera makes moving to modern data architectures possible, giving telcos a comprehensive solution for data management, analytics, and machine learning. Telco operators can extract valuable insights and take immediate action from any type of data, regardless of its source or location to identify cost-saving opportunities, improve decision-making processes, and proactively address network issues, ultimately leading to significant cost reductions. 

Learn how Cloudera is accelerating data-driven transformation in Telco.