Modernizing Warranty Return Rate Prediction with Google Cloud

A global leader in data storage solutions relies on accurate Warranty Return Rate (WRR) predictions to guide financial planning, product lifecycle decisions, and overall business performance.

Over time, however, the system supporting these predictions became increasingly difficult to scale and maintain.

The Challenge: When Critical Insights Are Hard to Access

The organization’s warranty prediction system had been built and refined over 15–20 years using SAS.

It wasn’t a question of trust—the system had been used for years and was well understood by those who built it.
The real challenge was sustainability.

As the system evolved, maintaining it became increasingly difficult:

• The original developers were no longer available
• Very few SAS experts remained to support or enhance the system
• Even small updates required significant time and effort

For analysts, accessing insights was also not straightforward.

They often had to navigate multiple reports, interpret outputs, and spend time validating results before making decisions. What should have been a quick process became time-intensive.

At the same time, growing data volumes added pressure on performance and scalability.

The challenge wasn’t about whether the system worked—it was about whether it could continue to work efficiently at scale.

The Turning Point: From Static Reports to Intelligent Interactions

To address this, the organization partnered with Pluto7 to rethink how warranty insights should be delivered in a modern data environment.

Using Google Cloud and Planning in a Box – Pi Agent, the focus shifted from simply rebuilding the system to transforming how users interact with data.

This is where the Warranty Pi Agent became central to the solution.

The Solution: Warranty Pi Agent + Modern Data Platform

The transformation combined a scalable data foundation with AI-driven interaction.

• Modern Data Backbone
  Warranty return rate  and Annualized return rate logic were migrated from SAS into BigQuery, creating a more scalable and maintainable foundation.
• Unified and Reliable Data Pipelines
  Data from Oracle EDW was streamlined into a single environment, ensuring consistency and availability.
• Warranty Pi Agent: Making Data Conversational
  Instead of navigating multiple reports, analysts can now simply ask questions in natural language.
  Whether it’s understanding return trends, comparing product performance, or validating assumptions—the Warranty Pi Agent retrieves answers instantly.
  What previously required navigating reports and cross-checking data is now reduced to a simple interaction.
  
• User-Friendly Access Layer
  A web interface complements the agent, providing structured access to reports and insights when needed.

A Phased Approach to Transformation

The journey was designed to minimize disruption while delivering value early.

An initial 12-week validation phase ensured the new system aligned with business expectations across a select set of products.

This was followed by a broader rollout, gradually expanding coverage while maintaining stability.

The program began as Pilot on December 2, 2024, and was rolled out on Production for Business use on March 27 2026.

The Impact: From Time-Consuming Analysis to Instant Insights

The biggest shift wasn’t just in technology—it was in how teams worked.

• Reduced Time to Generate Insights
  The time required to generate and validate warranty return insights has been significantly reduced—enabling faster decision-making.
• Simplified Access to Data
  Analysts no longer need to navigate multiple reports or rely heavily on specialized expertise.
• Improved Operational Efficiency
  Teams spend less time gathering data and more time acting on insights.
• Future-Ready Architecture
  The modern platform is easier to maintain and scale as business needs evolve.

Just as importantly, the dependency on a small group of SAS experts has been reduced—making the system more sustainable long-term.

Closing Thought

This transformation reflects a broader shift—from systems that deliver reports to platforms that enable conversations with data.

By introducing the Warranty Pi Agent on top of a modern data foundation, the organization has made warranty insights faster, more accessible, and easier to act on—turning data into decisions, in real time.