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Case study
Consumer Goods case study

Global healthcare and agricultural company cuts support response time by 53%

AI-powered ticket resolution eliminates error and delay, improving customer experience across 90 applications.

At a glance

Industry
Consumer Goods

Location
North America

Challenge

Legacy support-ticket system underperformed due to human error, lack of 24/7 availability and inconsistency

Products and services
Gen AI Powered Ticket Resolution Solution

Success Highlights

  • 20% reduction in incidents created
  • 53% faster response time
  • 15% cost savings achieved due to reduction in resolution time

The challenge

Global healthcare and agricultural company with a varied set of business units across the globe, including those related to its agricultural division. With its size comes the need to support tickets and incidents raised by users across approximately 90 applications in this division, totaling 5,000 requests annually.

The client’s existing technologies and processes were inefficient and costly, relying heavily on human agents to resolve a high volume of tickets. This manual approach couldn’t guarantee 24/7 support, was prone to errors and provided inconsistent solutions.

Furthermore, the investment required for training and sustaining the large team was significantly impacting the client's budget, with more applications. The high operational costs and lack of scalability inhibited the client’s ability to manage growing demands effectively, resulting in delayed response times and a negative user experience.

With this solution, the client was looking for an optimized and scalable platform to handle tickets from multiple applications, with efficient, reliable and error-free results. This in turn would reduce costs, help maintain a lean support team and minimize the resolution time for any response.

Our approach

Cognizant has been providing data services to the client for over a decade. With this history and our experience in transformative AI solutions, Cognizant made the right partner for this engagement.

Cognizant brought its expertise from past generative AI implementations, addressing the client’s challenge by developing a conversational agent capable of completing end-to-end chat conversations. This solution leverages internal client documentation to provide quick and effective resolutions to user queries, significantly reducing the need for human intervention. The AI agent handles user guidance and instructional queries across multiple applications on the client’s IT platform.

Cognizant conducted the project in three phases:

  • A swift three-month proof of concept for 10 apps powerfully demonstrated our solution's efficacy, forecasting a payback in under two years.
  • A three-to-four-month production phase, in which we developed a solution leveraging advanced LLM models, RAG and prompt engineering, automating processes and ensuring data security and scalability. We completed a model evaluation using industry-standard frameworks before choosing this LLM model and established LLM operations to monitor key metrics.
  • An ongoing support phase, which ensures the production application remains up to date from both data and model perspective and the solution is scalable.
our approach

Cognizant’s solution helped the client instantly meet its needs through several key features:

  • Immediate query resolution: The conversational agent provides instant responses to user queries, addressing issues promptly without waiting for human intervention
  • 24/7 availability: It operates around the clock, offering continuous support and ensuring that users receive assistance at any time, regardless of time zones or business hours
  • Optimized solutions: By leveraging internal client documentation, the AI agent delivers accurate and optimized solutions tailored to the specific needs of the users, reducing the likelihood of errors and improving overall efficiency
  • Reduced human effort: Automating the resolution of redundant queries frees up human agents to focus on more complex issues, enhancing the overall productivity and responsiveness of the support team
  • Scalable support: The solution’s scalability allows it to handle an increasing number of applications and queries without compromising performance, ensuring that the client’s growing needs are met seamlessly

Business outcomes

Cognizant’s automated, scalable AI solution delivered these outcomes, effectively addressing the challenges threatening the client’s ongoing success:

  • 20% reduction in incidents created
  • 53% faster response time
  • 15% cost savings achieved due to reduction in resolution time
Business outcome

The solution allows for the addition of more applications in the future without a proportional increase in the need for human agents, thereby optimizing operational efficiency and reducing costs. Moreover, it enhanced user experience, providing a better response mechanism for customers.

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