Rise of the machines? Self-learning boosts analytics capabilities
Alan Turing’s famous test in 1950 put a person in conversation with a hidden machine – if the person was convinced the responses were from a human, the machine was deemed to be truly intelligent. Although artificial intelligence (AI) has yet to pass this test, machine learning is a reality today and we are applying it for the benefit of service providers and their customers.
The approach recognizes that the more machines learn, the more they can use that knowledge to handle more intelligent tasks. Based on the pioneering research and development work at Nokia Bell Labs, we are going beyond the standard algorithms used for data analytics to apply AI for service providers. This includes technologies that map the internet, providing integrated cloud, application and IP network insight in real time so service providers can quickly improve network performance, efficiency and security.
The standard today is basic decision making using network data, such as detecting congestion in one area and alleviating the problem by moving traffic to a neighboring area.
Nokia is now transforming its approach to intelligence with Cognitive Analytics, which is based on adaptive self-learning. This is a process whereby machines continuously learn and update themselves depending on previous tasks and the data they encounter, becoming more efficient and accurate over time. The result is more capable, smarter and more automated solutions.
200+ practical uses…and growing
Nokia Cognitive Analytics solutions are already making a difference, delivering better customer experiences, improved efficiency and new revenue streams for service providers. We have a rapidly growing library of use cases, more than 200 at last count, built on many aspects important to end users and networks at all stages of the lifecycle.
A good example is Autonomous Customer Care, which can predict and solve issues that affect services even before users notice them. Stats show that while 96% of customers don’t complain after a poor customer experience, 91% of them will switch providers, so the ability to fix issues before they impact subscribers is invaluable to service providers.
Autonomous Customer Care can predict and resolve up to 70% of residential issues like poor DSL or WiFi performance. It also interfaces with consumer intelligent assistants like Amazon Alexa, letting subscribers use natural language to troubleshoot issues and request new services. This translates into a better customer experience.
Another example is Cognitive Analytics for Crowd Insight, which taps machine learning to track, analyze and understand crowd behavior using real-time network data. It aims to help service providers monetize their data by, for example, enabling retailers to identify potential customers and high-traffic areas for new stores, or to benchmark against competing stores. It can also help transportation agencies optimize bus routes, while advertisers can zoom in to determine the right content for digital billboards at the most appropriate times of the day. One organization achieved a 40% increase in shopping mall traffic from nearby neighborhoods as a result of tailored campaigns using Crowd Insight data.
Meanwhile, the new Nokia Analytics Office Services suite enables service providers to make the most of our Cognitive Analytics capabilities. It provides access to Nokia experts to help operators transform their processes and organization to improve customer experience, monetize services, and move to a service operations center (SOC) approach.
The potential of Cognitive Analytics is vast. Machine learning can be extended to Augmented Intelligence, where machines assess the need for human intervention, and ultimately approach human levels of awareness, intelligence and goal setting. The door is opening to a new era of data analysis and performance optimization.
As Turing worked at Bell Labs for a time, I think he would be pleased with Nokia’s direction.
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