Commercialisation of data in the telecommunications sector

By Laolu Akindele

Background Globally, telecommunication industry revenues are declining in their core business services such as SMS and voice calls due to the availability of alternatives and pressure from over-the-top (OTT) services such as WhatsApp, Skype, Zoom, Google chat, etc. These circumstances have necessitated telcos to find new sources of revenues.

At the same time, mobile phones have become invaluable to us due to their sophistication and advanced data connectivity. They have become a ubiquitous tool for communication, transportation, shopping, entertainment, news, banking, insurance and money transfer services, and this has provided telcos with an avenue to tap into data monetisation opportunities through insights into customer behaviours and usage patterns.

Leading telecom operators are making significant investments in data analytics and technologies and seeking new ways of using data to grow their businesses by deriving meaningful insights and creating value to gain a competitive advantage. Some of the key types of data collected by telcos are customer information data, device data, usage data and location data. In the industry, the various ways that telcos are trying to use that data to derive value are collectively referred to as Telecom Data as a Service (TDaaS).

Teleco Data as a Service (TDaaS) The value of TDaaS can be considered from an internal and external perspective.

From an internal perspective, telcos are digitising their businesses across key process cycles such as sales, operations and customer lifecycle management. With high quality and structured data, they can provide value adding services such as:

Relevant tailor made services for their customers,
Differentiated products and services,
Targeted cross-selling of products to customers,
Streamlined operations by identifying and remediating areas of inefficiency,
Improved quality of network service through analysis,
Enhanced revenue assurance and fraud management and
Insightful identification of customer behaviour trends and responses in real time.

A telco can use predictive analytics to identify behaviours by analysing data to answer questions such as: Are customers using mobile wallet services only? When do they make calls? What is the frequency of calls? What is their mobile usage trend over a period? amongst others.

From an external perspective, data provides a new potential source of revenue for telcos. They can create new business opportunities by providing anonymised and aggregated data to third parties.

“Machine learning and Artificial intelligence will play a key role in extracting value from data”

The value and benefits of data We can see the value derived from data in our world today in various applications such as Google Maps, which uses location-based analytics to inform us of traffic patterns in a particular location. Credit scoring in mobile loan applications, shopping applications which offer discounts based on shopping trends or advertise relevant products to us and other data-driven applications have changed our lives in innumerable ways.

The potential benefits of the use of telco data are immense. These benefits include but are not limited to:

Easier navigation and reduced commute times,
Targeted and tailored marketing,
Effective billboard placements,
More accurate credit-related information and credit scoring,
Specific demographic insights,
Individualised health-related information notifications,
Real-time location tracking and population movements during emergencies,
Predictive regional and urban planning (route planning),
Competitive location planning for businesses and
Innovative digital products and solutions through partnerships.

These and other benefits can be transformative, but telcos need to navigate the use of data carefully. Some of the key challenges that need to be addressed are:

Governance models - Having the right structures and operating model is important to foster data-driven decision making. Telcos are implementing different models depending on their big data strategy or their organisation’s capabilities. There are two common models for data management: centralised and distributed. In the centralised model, the organisation has a department responsible for data analytics and provides data services to the entire organisation while in the distributed model, data analytics activities are housed within various departments in the organisation. The centralised model enables data monetisation, but it should still get inputs from various departments to develop appropriate use cases.
Legal - Personal data stored by telcos is very sensitive and must be securely protected. Privacy of data is at the top of every telco’s agenda since it forms the foundation of customer trust. The GDPR and Kenya’s Data Protection Act, 2019 gives customers greater control over their data and therefore the legal aspect of privacy and data protection is one that should be carefully considered by telcos. Consent collection is critical and the level of data anonymisation and aggregation needs to be taken into consideration before data is used for commercial purposes.
Technology - Identifying data sources and the data that is held, understanding data architecture, gathering data, consolidating data and data cleansing are some of the challenges that need to be navigated before data can be used. Investing in the right technology infrastructure is also critical because it must be able to store and efficiently process the data. Telcos will have to decide whether to invest in on-premise or cloud-based infrastructure as well as open source products versus licensed products for big data analytics. It is also important to ensure that appropriate data security controls are embedded in the technology infrastructure to mitigate the risk of unauthorised access to the data.
Developing relevant use cases - Building use cases for relevant customers is a critical component of data monetisation. Telcos should strive to identify relevant use cases that create the most value. Telcos can navigate this by partnering with third parties and involving user departments to develop relevant use cases.

In summary, data monetisation creates possibilities of additional revenue streams for telcos whilst also providing value to customers as well as social benefits. However, telcos need to navigate the legal and technology implications carefully and develop use cases that are attractive and relevant to their clients.

Digitisation in the public sector

Digitisation is crucial for creating a more innovation-driven, competition-based and value-adding economy. In this article, PwC's Laolu Akindele compares local and gloabl trends in digitisation and highlights the key areas that Kenya’s government should prioritise on its digitisation journey.

Read on

Transforming Africa through ICT: Managing crises through technology

The COVID-19 pandemic provides an opportunity for Africa to transform its economies through innovation and ICT, as well as to prepare more effectively for future crises. PwC Rwanda Senior Manager, Victor Omurunga, however notes that countries will have to invest in ICT infrastructure, foster innovations and effectively regulate emerging technologies to achieve a balance between collective safety and individual privacy, if they are to realise these benefits.

Read on

Cybersecurity priorities for the public sector

Organisations must dig deeper to uncover cybersecurity risks. In this article, PwC's Benjamin Mkwizu explains why achieving greater cyber resilience as a society and within organisations will require a more concerted effort to uncover and manage new risks inherent in emerging technologies.

Read on