CASE STUDY

How Telco Analytics and MLOps Helped Telecom Giant Revamp the Analytical Landscape?

Sep 28, 2022

Highlights of the Case Study 

Particulars Description 
Client A San-Francisco-based telecommunications company seeking to leverage MLOps for improved analytics and business growth. 
Business Challenge The client was losing business opportunities due to a lack of visibility and prioritization of user needs. In addition, poor analytical and cloud infrastructure was leading to a slow-down in operations. 
Impact Quantzig’s telco analytics team and MLOps techniques enabled the client to improve deployment speed, increase revenue, and drive toward long-term business growth.  

Game-Changing Solutions for the Telecom Industry 

Let’s first understand the role of telco analytics in the telecom industry. Rapid remodeling of telecommunication services and technologies by different sectors and parallel evolution of advanced technologies at software and hardware levels are vital influencers in the success of the telecom industry, which has progressed from the first-generation cellular networking technology to the present day’s fifth-generation (5G) cellular networking technology.  

This fast adaptation of telco networking is backed up by ML (machine learning)-based models. Over time, these models get redundant and need to be replaced or revamped by new ones to incorporate the changes in the data to maintain the accuracy of the outcomes.  

Quantzig helps Telecoms design, develop, and implement a smooth transformation from its current analytical landscape to the latest technologies. This helps the companies reposition themselves as nimble market leaders by bringing onboard MLOps (machine learning operations), AI, and cloud infrastructure.  

The Challenges of the Telecom Client 

Our client is a San-Francisco-based telecommunications company struggling with declining profits from intense competition and analytical developments that redefined the industrial landscape. The client’s retail demand and stock control systems are automated and responsible for managing demand and supply for over 1,200 retail stores worldwide. This system calculates the devices that must be procured and distributed to each store. This is referred to as a traditional Waterfall approach wherein the requirements (based on the user data) are bundled together and sent to the offshore partner for action. However, by this stage, the IT team has already lost visibility over the changes in requirements and has zero control over the prioritization of these actions. To compound the issue, poor analytical and cloud infrastructure was slowing operations, holding up the development and delaying industrial partnerships and the passing of new features to the users.  

The client approached Quantzig to leverage MLOps to develop models that can make more accurate predictions. It wanted to apply DevOps principles to its AI-infused application and revamp its existing analytical landscape. The client wished Quantzig to make its ML-based model capable enough to learn and respond to the changes in the data industry and make accurate predictions.  

With Quantzig’s telco analytics solutions, the client wanted to improve their retail revenue.

Quantzig’s Telco Analytics Solutions 

We began by analyzing the client’s application development lifecycle, from identifying the users’ requirements to testing and deploying the application. The outcomes of this analysis revealed that the requirements prediction and the design process were the major bottlenecks.  

Quantzig’s MLOps techniques, which apply DevOps principles to AI-driven applications, enabled the client to develop a revamped DevOps continual delivery pipeline to speed up the development lifecycle by letting the requirements pass through the applications in small batches, disconnected from the other conditions. Quantzig also worked with all parties to ensure that the client had full visibility and check over each internal or external requirement.  Several of Quantzig’s valuable automation tools were brought in to capture and predict the exact requirement and accelerate the deployment process further.  

Impact Analysis of Telco Analytics  

Quantzig’s telco analytics team and the implementation of MLOps techniques helped the client achieve improvement in deployment speed, increase revenue, and drive long-term business growth:  

  • Deployment speed – Before this partnership, the client invested 9 to 10 months to release an offering or a product bundle based on customer requirement data. With Quantzig’s advanced analytical tools, the client could successfully reduce this release cycle from 10 months to one month.  
  • Revenue – Retail revenue jumped from less than 10 percent to 40 percent annually.  
  • Business growth – The success of the customers’ requirements reached 100 percent, hovering around 62 percent earlier.  
  • Long-term goals – Enabled cost reduction by 20 percent over three years.  
telco analytics

Key Outcomes 

Quantzig’s intervention enabled a smooth transition to adopt MLOps, which helped optimize the client’s processes. The client had a better understanding of the needs of its customers and could deliver better services. It also led to a drastic improvement in deployment speed by reducing it from ten months earlier to a month now. All these factors positively affected the bottom line of the clients, leading to cost savings and increased revenue. 

Broad Perspective on the Role of Analytics and MLOps in the Telecom Industry 

The wireless communication industry has seen remarkable success resulting from synergistic innovations in wireless technology. Access to a network, enabled by mobile/wireless communication, is transforming society, enhancing personal lives, and making businesses more competitive. Technological advancements in the communication industry have redefined how human beings, machines, and devices interact with each other. At the same time, they have challenged network operators to think about deploying newer technologies that will provide better speed, low latency, and high mobility.   

Quantzig can help companies transition from an older to a newer technology model with its data analytics solutions. The upgradation to new technologies has become essential for telecom companies to remain relevant, deliver optimum services to their customers, and drive consistent business growth. 

Key Takeaways 

Quantzig’s analytics solutions helped the client achieve the following: 

  • Improve deployment speed by reducing release cycle time from 10 months to 1 month  
  • Increase retail revenue from less than 10% to 40% annually  
  • Have a better understanding of customers’ requirements 
  • Enable cost reduction by 20% over three years 
  • Have better visibility and control over users’ changing needs 

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