The telecommunications industry is one of the largest and oldest industries in the world. With the increase in the number of hand-held devices, the number of subscribers and the volume of data generated by them has increased tremendously. Data collected through customers such as voice, video, SMS, and social media activities are enabling telecom companies to innovate and offer customized services as well as products.
AT&T is one of the top 10 Fortune-500 companies of 2020 and is the largest telecommunication company in the world. As per AT&T’s blog, the amount of data at AT&T has increased 470,000% since 2007. Along with huge data comes massive business challenges related to optimizing networks and product churn. The company has hence set up its own teams at its Data Office, Research Lab, and Technology Development, dedicated to research and development (R&D) of intelligent systems for better customer interactions and next-gen technologies.
Areas of data science implementation
The Chief Data Office and AT&T Labs research are standalone entities of the company that focuses on using data as a tool to enhance their workforce efficiency and capability. The teams have created automation tools in a way that it is easily accessible by everyone from the company who wants to work on it or get their data-related questions answered. It provides a ready-to-use format of reusable architectures to generate advanced analytical insights from the data. Let us look at some of the areas that the company practices the use of Data Science in order to regulate day-to-day operations and business.
In order to successfully implement 5G technology, continuous planning, and site-visit for the deployment of thousands of cell sites are required. Data science and AI tools are helping the planning team at AT&T to simulate a virtual environment to test and determine the ideal position for such installments. Moreover, the sites are automatically analyzed and monitored periodically to identify faults at the remote towers. Data-driven decision making is also done based on climate data and helps in the implementation of various infrastructural decisions.
The ability to predict the failures even before they occur allows the company to significantly reduce customer care calls by 15-20%. For example, a majority of customer service calls for network problems could be fixed by simply rebooting the network. Having an automated predictive process through “Network outage detection and notification” allowed the company to detect such problems beforehand and fix them without having to spend time answering customer calls or deploying technicians at different locations. This process largely helped the company have uninterrupted service and top-notch experience for the customer.
AT&T also uses automation and predictive algorithms to match customer’s demands and dispatch technicians to serve the customers faster. This ensures the availability of a technician as soon as the demand occurs and also allows customers to view the real-time location of the technician who is on the way.
Frauds and cyber attacks have been increasing at an alarming rate these days. Modern methods to deal with them include Data Science tools and techniques to automate the process of anomaly detection wherein the data and its sources are continuously evaluated for anomalies to keep the network safe from cyber-attacks and abnormalities. These tools have been largely helping the team at AT&T in detecting problems before the network is compromised and hence provide better service to its customers.
Along with the above-mentioned areas, the company has been continually working towards democratizing the power of data. Acumos is one of the open-source contributions of AT&T that provides a platform to easily setup and deploy data-powered applications.
As quoted by AT&T, “Being data-powered means being informed. Making a data-powered decision means making an informed decision.” The growing digitization demands new methods to be able to optimize and use data efficiently. Data science plays a critical role in utilizing the massive amount of data from consumers and industries to generate impactful information. It transforms the way of doing things and helps in improving business processes.
We also recommend you to have a look at ‘How can businesses use data science‘.
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