Telecommunications companies (telcos) have an abundance of valuable data but have struggled to capitalise on it. Data monetisation for telcos means getting value from the huge amounts of data they already have. Easier said than done? It’s challenging because of the complexity and varying revenue opportunities across different industries.

Telcos play a crucial role in today’s digital world and could play an even great role by using their data to offer new services and insights, benefiting various industries like banking and startups. According to a Deloitte study, 36% of ICT executives make money from selling data. By the end of this decade, this market could grow to $15.5 billion. High-performing companies are more likely to see significant revenue from data monetisation.

How can telcos gain a competitive edge? By analysing data from their services and networks, including data from internet usage, mobile apps, social media, geolocation, and IoT sensors.

THE MISSING PIECE

To fully benefit from data monetisation, telcos need a data-driven culture. Everyone in the company could use data in their daily tasks and decision-making.

Creating a data-driven culture requires a shift in mindset. Data access shouldn’t be limited to the IT department. Decision-makers need to understand and use data directly to avoid conflicting information. Emphasising data use across all business areas fosters innovation and embeds a data-driven culture. Only with a data-driven culture can telcos fully leverage their data assets for monetisation.

THE DATA-DRIVEN CULTURE

A data culture values and uses data consistently for decision-making. It involves continuous learning and a mindset that prioritises data. Data literacy is crucial and should be developed over time. Basic analytics skills should be taught early, with advanced concepts introduced as needed.

Tech companies like Facebook, Amazon, Apple, Netflix, and Google (techcos) excel in data-driven cultures. They use data to understand and serve users, creating a diverse ecosystem of digital players that further monetise their data.

HOW TELCOS CAN LEARN FROM TECHOS

Many telcos are still transitioning to modern technology companies. Legacy systems can hinder their ability to use big data analytics and AI. Techcos, on the other hand, have advanced data analytics capabilities and set high standards for data monetisation.

Techcos invest in research and development to stay ahead in data utilisation. They experiment with new ways to use data for business insights and revenue. Telcos need to adopt a similar focus on data-driven innovation, investing in the right skills and capabilities.

Techcos also sell the same product to different users for various purposes. Telcos should adopt this approach to maximise monetisation. For example, Google uses data from its products (Search, YouTube, Maps) for various monetisation strategies, such as targeted advertising and selling insights for logistics and urban planning.

THE CRITICAL ROLE OF TRUST

Telcos face challenges in using customer data due to privacy concerns and regulations. Maintaining customer trust is essential. Misusing data can lead to loss of trust and legal issues. Telcos need strong data security and management to navigate these challenges and maximise monetisation opportunities.

Organisations must use strong encryption, access controls, and continuous monitoring to secure their data. These measures should be integrated into every new system, service, or product.

Efficient data organisation, cleaning, and storage are crucial. This requires a dedicated team of data engineers and scientists to build and automate systems.

UNLOCKING BUSINESS VALUE FROM DATA

Monetising data is an ongoing process that needs continuous investment and improvement. Companies need a data-driven culture, quality data, and strong data management practices. BSG offers structured frameworks and approaches to help telcos build these foundations and accelerate business value. Key areas include:

• Strategy and roadmap development, prioritisation and business value definition, and adoption and change management;
• Data strategy maturity assessments, value-driven data roadmaps;
• Accelerating results through data management centres of excellence;
• Data security and data management capability development, including data science and data engineering;
• Data analytics proof of concept identification and definition, agile engagement execution and feature enhancements, skilling and training.