In the digital world, where competition is growing by the day, what can enterprises do to stay in the race? The answer lies in asking how well an enterprise takes advantage of something that lies at the core of the organization – data. Yes, data is the new oil; the new currency. And data science, the practice of mining insights from data can help enterprises grow.
Can telecom companies use data science to improve their processes and enhance customer satisfaction? My recent experience prompts me to say “yes.” A few weeks ago, I started facing trouble with the mobile network reception at my home. I had been contemplating lodging a complaint, but even before I could do so, the issue was resolved.
I later got to know — from a notification sent by the service provider — that they had embarked on a network optimization exercise based on an analysis of data from nearby cell phone towers. Due to a large number of people visiting a recently opened mall in the locality, there was an increase in the number of people using the network in our area, leading to high bandwidth usage. The operator therefore ran capacity expansion programs to ensure uninterrupted services.
In what other ways can data science benefit telecom companies? Telecom organizations can use it to gain insights on customer priorities, discover faults in their systems, optimize their processes, unlock new revenue streams, predict customer churn, and launch targeted advertising.
While data science is a useful tool for telecom companies, they can face certain challenges while adopting the technology. These include non-integration of different formats of data from various sources; limited number of skilled data scientists; perishable nature of insights derived from the data; and high costs associated with advanced analytics.
The advancements in technology can help enterprises address these challenges. Firms can use the services of data exchanges or marketplaces, which assist in aggregating data from various sources. For instance, Pinsight Media, a division of Sprint, ingests data from multiple sources and uses data science to create sets of target audiences, which, it then offers directly to brands.
While human intelligence has no match, sophisticated artificial intelligence algorithms and statistical modelling techniques can be used by enterprises until they find skilled data scientists. Evolving approaches like stream analytics help enterprises derive insights in real time or near real time. In reality, the benefits of data science outweigh the challenges. Let’s take a look at a few telecom companies working in the data analytics space.
A leading US-based multiservice provider improved its channel experience through advanced video network analytics. The organization analyzed data to understand customers’ interaction with cloud TV platforms to offer better services. Another large telecom company in the Middle East was able to successfully predict potential churners based on social network and CDR data analysis.
Telefonica has created Telefonica Dynamic Insights (TDI), which is focused on the development of products and services that leverage Telefonica’s global Big Data assets. Smart Steps, the company’s Big Data solution, uses aggregated data from millions of mobile phones to deliver insights into the movement of people and traffic. This data helps town planners and administrators to keep the city moving by planning traffic and facilities better.
As more companies start adopting IoT across the globe, there will be an exponential increase in the amount of data generated. In order to ensure competitiveness, it will become crucial for enterprises to gain insights into this data. So how does your organization plan to leverage it?