Big data is a gold mine for telecom operators if they can put the pieces in place to take advantage of the opportunity.
Without a doubt the rise of big data within the telecommunications industry has allowed companies to redefine strategies and adapt business models to meet current trends.
While change in any industry takes time, there has been some early success that can be categorized into three levels:
Level 1 – process optimization
Thanks Apache Hadoop, it is possible to store and compute massive amounts of disparate structured, unstructured or semistructured data sources at a low cost. Telecommunications companies have identified this advantage and offloaded expensive enterprise data warehouse into Hadoop.
Once data is combined it gives telecom operators the opportunity to see connections and correlations that were not previously exposed. With access to more historical data, businesses can base more efficient operations based on precise models.
Level 2 – data discovery
Once existing internal processes are optimized, telcos have the opportunity to explore other use cases. Using analytics to supplement customer analytics, network operations and fraud detection allow telcos to understand business from a new perspective.
The addition of new data sources such as social media and other unstructured data allows them to answer questions that couldn’t be answered before. Questions such as:
• What leads my customers to churn and how can I reduce it?
• How can I increase the customer acquisition rate?
• How can I improve my customer service and overall experience?
• How can I optimize the network utilization?
• How can I enhance operations using predictive maintenance?
An important point to note at this level is that the data quality is incredibly important, as it will dictate how new use cases are formulated and the value that is achieved.
Level 3 – new revenue streams
While this is the most coveted level, most telecommunications companies that have implemented big data initiatives have not yet achieved new revenue streams. The reason? Formulating new revenue streams from big data analysis not only requires going through level 1 and 2, but it also involves, in some cases, coping with country regulations around data protection. These regulations vary from country to country and in some cases customer consent is required. For that reason, attaining new revenue streams requires that new models abide by data governance regulations.
For example, telecom operators have found ways to offer new services, like high-quality and value-added services that were created after the analysis of their customers’ needs, like high-definition video service.
This level requires working in conjunction with other industries outside of the telecom market, such as – but not limited to – financial institutions, retail, automotive and health care to bring new products and services to the market. According to GSMA’s recent report “The Mobile Economy 2014”, the mobile ecosystem is expected to grow to over $2 trillion by 2020. So, there is definitely room to play.
Industry giants like AT&T, Verizon Communications and Microsoft are implementing projects that will turn the concept of smart cities and intelligent resource management into a reality. This is not just a U.S. phenomenon. In Asia, Huawei, SK telecom and Telkom Indonesia are driving discussions and projects that we will likely come to fruition within the next few years.
In regards to the “internet of things,” Telefónica offers a product called “Thinking Things,” which is a modular end-to-end and plug-and-play solution designed to help build intelligent and connected products, allowing companies to expand their offerings. Already, it is being used to adjust climate and lighting in buildings, and it is expected to eventually control more home and office equipment to make buildings smarter and more efficient.
While there are a number of companies adopting successful big data analytics strategies, the industry as a whole will need to step up to the challenge of actively using all of the data that is being generated while ensuring privacy. After all, if telecommunications companies are planning to stay competitive, they will need to strive for the coveted third level. Data monetization is a “must” in order to succeed in the long term.
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