How operators can leverage geospatial data to improve network planning and service delivery

One tool that could prove invaluable for the sector is geospatial data. As the name suggests, geospatial data refers to information that has a geographic component, combining location data with other types of non-spatial information. It is most typically associated with geographic information systems (GIS), a term used to describe the the practice of finding patterns, trends and relationships between spatial and non-spatial geographic data^[1].

Collecting and analysing geospatial data is a long-established practice that has been used to provide clear visualisations and insights in numerous sectors, including urban planning, environmental management and disaster response, among others^[2]. For a telecoms sector where network management is one of, if not the biggest priority, geospatial data can be an invaluable asset, giving operators the ability to monitor network conditions in real time or even anticipate changes to the operating environment.

One area where geospatial data can prove useful is in finding and fixing faults in the network. By feeding data into detailed maps of infrastructure assets across localities and regions, operators can anticipate faults in the network and tweak maintenance schedules to ensure the weakest points in the network are prioritised, saving precious time and resources. Canadian operator TELUS has leveraged spatial data for this very purpose, creating internal coverage maps used by network support agents to troubleshoot network incidents^[3]. This information is also used to assist technicians in identifying the most appropriate locations for the installation of equipment, based on areas where the signal is strongest.

Even when a network is running smoothly, spikes in demand and the need for continuous low-latency throughput can place added pressure on performance. In some cases, this can mean reconfiguring existing cell sites into smaller sites capable of delivering high-speed data transmission and signal flow in more targeted locations^[4]. More granular and accurate geodata can therefore be collected to facilitate higher throughput, reduced latency and fewer bottlenecks, taking into account variables such as demographics and weather patterns.

But it’s not just fault-finding and network monitoring where geospatial data can prove useful. Access to rich spatial datasets can also help operators with future network planning, assisting with identification of new markets and regions for deployments, optimising site selection for existing rollout plans, and determining how best to connect network components. T-Mobile, for example, has used spatial indexing and geospatial data visualisation to assist with visualisation of its 5G deployment programme. Dense maps were created to help its data team visualise the number of households that might be served when placing cells in specific locations^[5].

These same maps can be broadened out further for the purposes of market analysis and customer service. This does not only help with network coverage decisions, but identification of underserved areas, customer behaviour trends and detailed competitor analysis. Taken in its entirety, this cluster of information can be used to modify and fine-tune marketing strategies, tailoring them to specific regions. In an industry where churn rates are high and operators are often focused on acquisition rather than retention, such capabilities can prove pivotal to an operator’s long-term growth.

In the case of UK operator Vodafone, for example, it used geospatial data technology to develop a more detailed understanding of key demographic insights in built-up areas, such as visitor and tourist numbers and movements. The company then used these insights to tailor a more customer-centric service offering, honing in on key catchment areas where demand was greatest^[6]. A digital twin of its UK mobile mast network provided an even more detailed picture, with over 500,000 network features and over 40m environmental features, such as buildings, hills and trees giving the company a comprehensive view of the physical barriers to network delivery^[7].