Why AI and Analytics are Key to Monetizing IoT

The telecom industry currently faces a critical challenge in monetizing IoT to remain competitive. Advanced technologies are key to finding new revenue streams.

Nadine Manjaro

April 7, 2020

4 Min Read
Why AI and Analytics are Key to Monetizing IoT
(Source: Pixabay)

As the telecom industry faces diluted revenues due in part to service commoditization and competition from over-the-top (OTT) providers, companies feel added pressure to adopt new and emerging revenue streams. According to a recent McKinsey & Company article about the state of the industry today, “The OTT industries and companies like Google and Facebook have generated enormous value and opportunities, not because they improved existing industries, but because they created brand new ones, using telecom infrastructure to do so. So much of the value of these new companies comes from the data they collect, analyze, and monetize.”

One of the largest and most promising markets for telcos to monetize their data is the Internet of Things (IoT), which Gartner predicts will grow to 22 billion endpoints by 2025. Even with an abundance of opportunities, there are a number of challenges Telcos must overcome before reaching profitability. Simply having access to multiple streams of data is insufficient. Since most telcos currently don’t have the right tools to deliver the high-value, cost-efficient, scalable, and data-driven service necessary to effectively drive a successful IoT strategy, how can telcos navigate a path toward IoT profitability?

AI and Advanced Analytics are Key to Monetization

To profit from IoT, telcos must be able to provide an exceptional customer experience with outstanding service quality, reliability, and dynamic capacity allocation. This is especially important for mission-critical applications in utilities, transportation and autonomous vehicles, and remote health monitoring devices. But in order to deliver on these promises, utilizing advanced technologies to deploy AI-based network analytics is critical. This capability will enable telcos to remain competitive via the following:

  • Automated data ingestion from multiple IoT-enabled sources

  • Ability to make data-driven decisions in real time

  • Enhanced network optimization and traffic routing

  • Improved customer experience, reduced customer churn

  • Ability to develop and deliver new revenue streams

Bringing the Data to Life

Telcos remain rich in data due to their decades-long market leadership in internet and connectivity. Paired with the next wave of global 5G network deployments—a key factor in supporting mass adoption of IoT—telcos will have significantly more information to process. It’s worth considering that 5G enables a whopping 1 million IoT devices per square mile—ten times the amount enabled by 4G.

Unfortunately, being data-rich presents little value for telcos if their infrastructure isn’t capable of managing or seeing the data in context. AI and advanced analytics are two emerging technologies that have the capability to take the data telcos are already sitting on, manage its scale, and generate actionable insights. As the world operates faster and churns more data, the capacity of these automated technologies is now essential to creating and distributing the new services and revenue streams necessary to remain competitive in the evolving hyper-connected market.

More specifically, critical AI-powered analytics will allow telcos to unify disparate data from varied IoT sensors and network sources into a single platform, and then query that data as needed. Among the variety of insights they can derive from data are network fault prediction, or customer consumption patterns. With data insights into traffic patterns, capacity fluctuations and demand, and even problem areas in the network, telcos can make data-driven decisions about how to better allocate and optimize network resources. This will ultimately drive stronger network performance (e.g., fewer service outages and lower latency), cost savings, and more satisfied customers. Additionally, with deeper insights into customer activity, providers can personalize existing offerings for customers or develop new bundles of offerings based on verticals. Altogether, advanced technologies provide much more than fresh approaches to existing business operations; they present telcos new revenue streams.

Unplanned downtime due to equipment failure is currently one of the biggest costs impacting manufacturers, as it is difficult to predict or adequately set aside funds for issue management. As a result, one of the most promising areas in IoT is predictive maintenance, which enables telco service providers to predict future incidents such as machine failure or network malfunctions and prevent downtime. Thus, telcos will be able to offer predictive maintenance as-a-service to their customers to monitor the life cycle of key equipment and proactively address issues. This as-a-service solution is software-enabled and customized to address customers' unique requirements. Additionally, virtualization enables network slicing, which will allow operators to deploy portions of their networks for specific customer use cases. Predictive maintenance can also apply to emerging technologies like autonomous vehicles by leveraging real-time vehicle health data to anticipate machine failures and minimize downtime among fleets.

The Path to Profitability

As the telco industry enters a new era and individual service providers look to drive new sources of revenue, advanced technologies, including AI and data analytics will be the key differentiators for telecom companies to achieve IoT profitability.

About the Author(s)

Nadine Manjaro

Nadine Manjaro is the Principal Telecom/IoT Industry Consultant at Teradata.

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