How data enablement and creation of a scalable AI/ML environment on Google Cloud Platform enhances field service operations
The advent of digital technologies is driving product and service innovations that are redefining the way companies deliver services.
In order to establish themselves as a market leader, service providers must focus on accelerating service delivery, enhancing customer experiences, and reducing costs. However, legacy systems and distributed data hinder their efforts to transform and achieve their goals.
Field services become vital when it comes to efficient service delivery and top-end customer experience. Service providers need to leverage digital and cloud technologies to deliver proactive field services at scale.
How do service providers transform their legacy systems and embrace latest digital technologies to boost their game?
8% reduction in repair calls
25%faster revenue realization
Our client, a leading telecom operator in North America, was facing a similar challenge. They had to deal with a huge number of service repair calls, repeat and non-productive dispatches. They were unable to get real-time insights from their field data.
In addition, their conventional and rule-based approach failed to validate whether a dispatch was necessary for a customer(s) issue. It resulted in excessive service assurance costs and bad consumer experiences.
Prodapt set the client’s foundation for future growth by reimagining field service operations, harnessing the power of cloud technologies.
Real-time data and insights are a must to deliver superior customer experiences. The client was facing challenges with managing near-real time data from multiple sources. There were limitations due to legacy systems and scattered data. Their existing systems did not have the right toolsets to develop data science and manual intervention was needed in every step. This was impeding their speed to react/respond to their customer needs.
Prodapt, in a consultative approach with the client, built a cloud-native, centralized data, AI/ML platform on Google Cloud. The client’s complexity of a traditional architecture was abstracted into a single self-service platform that could turn event streams into analytics-ready data.
We conducted data-engineering workshops, and co-developed deep learning along with statistical models using closed-loop automation. To scale better across multiple markets, we leveraged the power of MLOps.
Our Google Cloud powered solution helped the client save millions of dollars within the first 2 years of operations. They were also able to achieve 8% reduction in repair calls and 25% faster revenue realization. Our scalable cloud-based approach extended the solution across multiple verticals and increased the customer base.
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