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IoT Revenue Opportunities


As artificial intelligence and machine learning become more commonplace, we’ll see predictive maintenance solutions increase in automation capabilities.

What’s needed is a data analytics solution that collects data, processes it instantly, and enacts automated solutions to issues immediately. Operators should be able to tell what problems are occurring, what devices or software may be causing the issue, and how widespread the service disruption is.

The data generated by connected devices can also show operators developing trends in how connected devices are being used, allowing them to create new products and services that support their clients' business operations.

Analytics has three primary applications in business: to improve efficiency, enhance the customer experience, and to advance innovation. CSPs that understand which of these factors is most important to their clients will be able to tailor and package a solution suitable for their needs.

Saving money via predictive maintenance

This real-time data analytics capability can be used to support predictive maintenance, providing CSPs with another service that they can offer their clients in exchange for additional revenue.

At Comarch, we use sensors to gather data from various machines—such as lamps and electrical substations—to monitor performance and predict when clients will need to service their machines and devices. This insight both minimizes downtime and creates business efficiencies as it reduces the number of inspections and service calls.

As artificial intelligence and machine learning become more commonplace, we’ll see predictive maintenance solutions increase in automation capabilities. Offering automated predictive maintenance as a service will set CSPs apart from competitors and give them another way to generate revenue from the Internet of Things.

Creating an upgraded service

Ultimately, we are talking about a holy trinity of opportunities. The combination of greater access to data, the ability to analyze it for actionable insights, and the capability to use that data to power predictive maintenance allows CSPs to focus on the customer experience. For some CSPs, this may mean making their services more efficient or providing greater product capabilities and customer care. Other CSPs may choose to focus on enhancing autonomous systems and self-service.

What’s clear is that it is the access to this data and the flexibility to implement solutions that allow CSPs to offer an upgraded service, improve the customer experience and, as a consequence, reduce customer churn. By focusing on how data can best serve the client, communication service providers create additional revenue opportunities built to last.

Communication service providers are facing stiff competition from OTT providers and, so far, many CSPs have failed to use the data they have to its full advantage. CSPs can no longer rely on their traditional business models to stay in business, let alone thrive in an age where the industry is preparing for 5G and even higher levels of connectivity.

CSPs need to be willing to change the way they operate. They need to be able to analyze and use the vast quantities of data generated by connected devices to develop new solutions and service efficiencies.

This requires a certain level of flexibility and significant insight into what each client needs (and how the data they hold can address these needs). CSPs that get this right will be able to reduce operating costs and create new streams of revenue in an increasingly connected— and competitive—world.



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