Thinking big

MEA telcos can increasingly look at big data and analytics to reinvent themselves.
Wejdi Harzallah is Principal at Booz Allen Hamilton, MENA
Wejdi Harzallah is Principal at Booz Allen Hamilton, MENA


By Wejdi Harzallah

The telecom market in the MEA region is maturing after several years of healthy growth. Competition and price pressure are intensifying, Mobile Virtual Network Operators (MVNOs) with leaner organisations and niche offerings are gradually emerging to claim a share of the market, and new digital entrants and established players from adjacent sectors are increasingly threatening telecom revenues.

Meanwhile, significant infrastructure investments are required from the telecom sector to continue to stay ahead of the curve and roll-out next generation networks. In this context, big data and analytics hold the key to some of telco’s most pressing questions: How can they attract new customers without compromising revenues? How can they turn their low revenue users into new growth avenues? How can they prevent customers from churning to competition? How can they make the best out of every dollar invested in network deployments and maintenance? And, how can they develop new revenue streams using their data assets and their analytics capabilities?

In that context, given the wealth of data that is generated and captured by operators, MEA telcos are increasingly looking at big data and analytics to improve their efficiency, differentiate their services, develop new revenue streams, and even reinvent themselves.

Making it count

Telecom operators process a massive amount of data that, when properly captured and analysed, can reveal powerful insights about users, groups and populations. Traditionally, they have used structured customer data such as customer profile and billing data to develop customer segments, determine optimal pricing, monitor business performance and optimise operations. Big data and advanced analytics, on the other hand, provide them with the tools and techniques required to harness and integrate new sources and types of data in larger volumes and in real-time. By integrating additional information such as call records, geolocation, browsing data, and by applying advanced data science techniques such as machine learning, semantic processing, simulation and modeling, and enhanced visualisations they can reach new levels of customer intelligence and business efficiency.

Some of the ways in which telcos can directly benefit from big data include:

• Business efficiency and optimisation - Leveraging big data and analytics tools, telcos can develop enriched 360-degree customer profiles, micro-segmentations and next best offer recommendations. They can improve call centre productivity, develop more targeted offers and pricing, predict and reduce churn, and propose up-sell/cross-sell offers more effectively.

• Data monetisation - Beyond the efficiency and optimisation of their core businesses, telcos are increasingly leveraging their data assets to generate new revenue streams. By analysing anonymised and aggregated customer data, they can extract insights on crowd movement, behavior and interests that are valuable to marketers, retailers, and government agencies.

• Big data and analytics-as-a-service - Telcos can ultimately leverage their capabilities to provide big data-related cloud, connectivity, infrastructure and professional services to enterprise customers at reasonable price points given the potential economies of scale at hand.

Overcoming obstacles

With the many opportunities, there are also a few challenges. For instance, there are important data privacy and security considerations that must be addressed when handling telecom data. Other challenges include:

• Business governance - Lack of overall business-driven vision, mission and goals to pursue big data opportunities can impact business governance. Lack of planning, focus, commitment and monitoring of business results are other impediments.

• Data governance - Data is owned by multiple stakeholders who are reluctant to share it not knowing what will happen to it.

• Culture - Lack of buy-in from management and stakeholders who fail to appreciate insights that can be derived from data analytics or take definitive action based on the findings.

• Skills - Shortage of analytics expertise and data science talent. This is becoming truly a global challenge with the industry working closely with leading academic institutions to establish leading data science programs. Case in point is Booz Allen Hamilton’s partnership with MIT Sloan School around the prestigious Institute for Data, Systems, and Society (IDSS) to establish a specialised data science graduate program.

Although technology can be a key challenge in the path of real-time data analytics, it is also one that offers the most systematic solutions. The future is calling and telcos in the MEA can be better positioned to reap the many benefits of big data as they update their respective business strategies after assessing factors such as mission and goals, roadmap, existing infrastructure, capabilities and end-users.

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