Big data has made an indelible impact on many industries and the telecom industry is no different. Telecom growth has remained stagnant for some time now forcing telecom operator to search for new ways to increase their ARPU and overall revenue. Owing to the maturing of the telecom markets many operators are adopting new technologies like Big Data to enhance their service value.
In an increasingly connected world huge sets of structured as well as unstructured data (also called big data in the telecom space) are constantly being generated through digital processes and social media exchanges. The challenge is how to manage data generated with great volume, velocity and variation. To extract value from big data, telecom companies need higher processing capabilities, analytical power and skills to spot new business trends and opportunities. Operators have sought for decades to make the best use of information to improve their business capabilities and their answer lies in big data analytics.
Big Data- an Exceptional Technology
Big data technology focuses on finding hidden threads, trends, or patterns from heaps of data. It provides significant new information for analyzing and tapping new opportunities. Three core reasons behind big data being in the forefront are:
- It provides competitive advantages
- Affects all spheres of business
- Drives innovation and improvement
Dimensions of Big Data in Telecom
The concept of big data gained momentum in the early 2000s and is breaking the threshold of business potential. The dimensions in big data are:
Volume– Telecom operators collect customer data from multiple sources like usage history, VAS subscription details, service transactions, location and lot more. Earlier, data storage used to be a problem but with the advent of new technologies, the burden of large volume of data storage has eased considerably. Moreover, businesses have become smarter when it comes to managing data. New technologies, like Hadoop allow businesses to analyze data at the source with only relevant data stored at the warehouse.
Velocity– Telecommunications being a dynamic sector, data is created at an unparalleled speed, requiring tools that analyze data as soon as it is created. Payments, sensors, RFID tags etc. are driving the requirement to deal with unprecedented amount of data in the near-real time.
Variety- Data is collected in different data formats including structured data formatted in traditional databases to unstructured text documents, financial transactions and emails.
Variability-In addition to the high velocity and variety of data, the flow of data may be inconsistent with periodic peaks. Daily, seasonal or event-triggered data loads may be challenging to manage- even more challenging with unstructured data.
Complexity –Telecom data arrives from multiple sources, which makes it difficult to be inter-link and transform across systems and services. However, it becomes important to connect data relationships, hierarchies and multiple data linkages, or data can go out of control.
Significance of Big Data in Telecom Industry
The advent of smartphones, increased subscriber base and increased consumption of telecom services worldwide, have created a profusion of data. Operators have no dearth of data which is obtained from user transactions, network performance, data sourced from cell-site, service and portfolio offerings spread across geographies and in a real real-time format. This data can reap out trends and patterns on customers’ usage, behavior providing complete end-to-end subscriber insights. Some of the benefits are:
- It saves time by correlating a 360-degree view from fragments of user data, which is complex and time consuming when done manually.
- The quality of collected data has to be polished, trimmed and de-duplicated. This is achieved easily by simple algorithms of big data technologies.
- As the role of telecom is evolving in the economy, technologies like big data give them access to leverage and exploit every bit of customer data to serve the people better quality.
- The rise of many telecom players necessitates each of them to build up key competitive advantages of their operations and services that are extracted from big data monetization.
- Big data is not a replacement of the traditional analytics, but an add-on to the operators to fill the gap between of collecting data and digging valuable business insights.
- The information or insights from big data is asked for and consumed to make better decisions or to create new products and services. This way the whole infrastructure evolves to fulfill the demand in a better way.
- The data collected arrives from different silos of the operator, namely- service provider’s business, network data, IT department, marketing and product departments, etc. Big data co-joins all of it to evolve as a unified business unit.
Additionally, it also helps in reducing data maintenance and storage cost, time in running manual queries on data and helps in lowering down the need for data compression. It further leverages commodity hardware, enhances response in real time and enables easy implementation of any data model from any data source.
Impact of Big Data in Telecom Industry:
Today, the telecommunication sector has found big data as irreplaceably useful. The importance of big data doesn’t rely on the data volume you have but, what is done with it. Data can be collected from any available source and data analysis can be carried out to find results that enable:
- Cost reduction
- Time reduction
- New product/service development
- Service optimization
- Smart decision making
Big data combined with analytics can accomplish many telecom service tasks which promise high sales and increased ARPU, among other things like:
- Determining root case of issues, defects and failures in near-real time
- Creating offers based on customer’s buying habits
- Offering customized services
- Analyzing value proportions
- Calculating risk portfolio within minutes
It is quite important to keep in mind that the core value from big data arrives not only from data in its raw form but from processing those datasets analytically and discovering hidden patterns and generating actionable insights. The solution effectively utilizes structured and unstructured data to improve decision making and alleviating business problems.
By ‘Amit Sanyal, Business Head, Consumer Value Solutions at Mahindra Comviva’.