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Enhancing operational efficiency and minimizing opex: the potential of asset integration for tower companies



In today’s data-driven era, tower companies (TowerCos) handle an abundance of data points generated by their vast infrastructure. However, companies only analyze a small proportion of the data they have, leaving an ocean of untapped opportunities for valuable insight.

By integrating unconnected physical assets – towers, equipment, systems – with the digital world, TowerCos can tap into unprecedented operational efficiency and drive down OPEX. AI and IoT adoption can reduce energy costs in wireless networks, enhancing performance, cutting costs, and promoting the longevity of equipment.

Moreover, this integration contributes positively to sustainability goals. With the telecom industry contributing around 1% of global CO2 emissions, connecting unconnected assets and using data analytics provides a real-time way to monitor and manage resource usage.




The scale and complexity of telecom networks pose significant challenges. Although many companies use IoT to monitor their assets in real-time, the full potential for insight remains unrealized. 

Data gaps due to connectivity issues and lack of reliable data still persist. TowerCos that use remote monitoring systems (RMS) are typically configured to capture only a subset of data and unable to standardize it, leading to a fragmented and incomplete view of the network.

Current processes often require staff to manually export data into a database, and then into Excel to identify trends and patterns – a method far from efficient in the age of data. It is also extremely expensive.

However, the key issue is that there is such a large amount of data across the network that it is almost impossible to find the efficiencies hidden within it. Even budget allowing, the sheer volume of data means it is impossible for humans to process it and find the efficiencies hidden within that can transform their operations.




Data analytics is a proven tool to deal with business issues and a reliable methodology to make informed decisions. The rapid advancements in Big Data, data science, artificial intelligence, machine learning and automation has allowed intelligent systems to bring game changing benefits to almost all industries.

Technological innovations are powering a major digital transformation in the wider telecommunications industry. By attaining data transparency throughout their supply chain and accounts payable processes, telecom organizations are benefitting from a comprehensive overview of internal operations. This not only provides a thorough understanding of existing inefficiencies but also enables the implementation of AI and ML tools to generate recommendations for process improvement and automation. This has the potential to reduce human capital costs and enhance the quality of available data in the future.

By acquiring and applying knowledge about customers’ profiles and usage patterns, telecom companies are also enhancing customer satisfaction and reducing expenses. Providers can identify customers who are more likely to encounter payment difficulties, allowing for preemptive measures. This helps to increase recurring revenue streams and aids in better managing a stable customer base. Customers who are on the verge of contributing to churn can be offered early renewal proposals or tailored product placements.

In the network, telco providers are leveraging data-driven insights to anticipate network issues and deliver predictive maintenance. Everything along the network – from customers’ home boxes all the way to data centre servers – is now monitored and analysed to deliver short term benefits to network performance as well as longer term strategic ambitions concerning new customer experiences and growth.

In the retail sector, Amazon gathers data from each of its consumers via its website, virtual assistants such as Alexa, recommendations, one-click ordering and anticipatory shipping model. With over 1 million requests landing on Amazon Web store alone every second, the incredible scale of data collection is clear. Big data analytics is then deployed to optimize supply chain and prices, identify signs of fraud, encourage customer behavior and change and adapt physical stores.

A data-driven approach to farming is also enhancing the productivity and sustainability of the industry. The industry increasingly relies on data science and the emergence of digital technologies to enhance operations and outcomes. Bayer has developed an application that employs ML and AI to identify weeds. Farmers capture weed images, which are then matched against a comprehensive Bayer database of around 100,000 photos to detect the weed species. The app then intervenes at the right time to protect crops and improve yields. This increases output, reduces costs and minimizes the environmental impact of agriculture.




TowerCos are 5-10 years behind other industries when it comes to harnessing the power of data. Yet mobile connectivity is crucial to the development and deployment of next-generation technologies that underpin such examples of Industry 4.0. Just as farmers use large data sets to identify and manage weeds before they impact their crops, TowerCos must spot efficiencies throughout their network to improve operational efficiency and minimize OPEX.

Real-time closed loop AI has the capacity to streamline complex tower infrastructure at scale by employing advanced data science models to pinpoint inefficiencies. By processing billions of data points, these smart systems can autonomously monitor and adjust thousands of parameters in real time.

This means that previously unnoticed infrastructure issues – such as a broken solar panel or leaking fuel tank – are detected and modified automatically. These adjustments optimize power usage, promote preventive maintenance, diminish downtime, and improve the lifespan and performance of existing assets. Issues needing manual intervention are flagged to operations teams, significantly reducing the average detection and repair time from months to weeks or days.

Connecting unconnected assets represents a vast potential for business to leverage data analytics to increase operational efficiency, reduce costs, and support sustainability targets. has enabled TowerCos to save up to 30% in diesel consumption and has reduced CO2 emissions by approximately 15%. The intelligence platform that uses highly targeted data science tools in a closed loop manner to optimise power management, automate issue detection and fast-track resolution.

By deploying platforms such as this, TowerCos can make a paradigm shift in how they view and use data. Efficient operations, cost savings, and real-time power use reduction will drive the industry, its customers and communities towards a more efficient and sustainable future.


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By enabling cellular infrastructure to be built and managed more efficiently, targeted data science tools can help accelerate the expansion of cellular infrastructure across the continent while promoting sustainable practices for a greener, more cost-effective future in African mobile connectivity.

A shift is happening in the industry and leading cellular infrastructure companies have already integrated AI-driven solutions like into the way they manage and operate their systems. As more organisations recognise the potential of AI-driven solutions, the rollout of advanced cellular infrastructure in Africa can gain momentum, ultimately connecting millions of people, empowering communities and helping to bridge the digital divide sustainably.

With AI-driven infrastructure, TowerCo’s can maximise efficiencies whenever and wherever possible, drive down CO2 emissions to support net zero, reduce site management costs and expand responsibly and sustainably to mitigate environmental impact, while delivering for customers and investors. 


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