Our client is one of the largest vehicle ancillary product warranty providers in the United States, serving OEMs (Original Equipment Manufacturers) including Hyundai, Toyota, Volkswagen, Nissan, Subaru, Honda, Bentley, Porsche, and Mazda. Each relationship carries its own operational complexity across sales, accounting, bonus reporting, and reconciliation for each OEM under stringent SLAs.
With millions of warranty records and financial transactions flowing through their systems every year, the pressure to stay accurate, scalable, and reliable isn’t optional. It is foundational to their success.
As their business grew and the cracks in their legacy infrastructure became harder to ignore, they needed help to modernize from the ground up and build something that could actually keep pace with where they were headed.
The Challenges That Were Ahead Of Us
By the time we came on board, the client’s data ecosystem had been built and patched over more than a decade. Their fragmented web of legacy systems was struggling under the weight of the business. The problems were interconnected:
- Data lived in disparate sources with no unified integration layer, making consistent reporting across OEMs unnecessarily complex.
- Legacy infrastructure couldn’t keep pace with growing data volumes, causing performance slowdowns that put SLA adherence at risk.
- Reporting cycles depended heavily on manual workflows, which were time-consuming, error-prone, and impossible to scale.
- Visibility was a persistent gap. Without unified dashboards, stakeholders had no real-time view of OEM-level KPIs, which meant decisions were routinely made on delayed or incomplete information.
- And underneath all of this was a more fundamental problem: the existing architecture simply wasn’t built for the cloud, and the business had long outgrown it.
The client needed more than incremental fixes. They needed a structured modernization strategy — one capable of handling complex, high-volume data across a dozen-plus OEMs, maintaining SLA compliance without exception, and laying the groundwork for the growth they were planning.
How We Helped
What began as a targeted reporting engagement in 2012 evolved, over the course of a decade, into one of the most comprehensive data modernization programs we’ve undertaken.
2012–2015: Building the Foundation
We started with SQL-based reporting solutions for a handful of OEM programs, delivering SSRS reports with consistent quality and SLA discipline. This early phase was as much about establishing trust as it was about technology — building the communication cadences and QA standards that would anchor everything that followed.
2016–2018: Scaling the Scope and Teams
As reporting demands expanded across new OEM programs, so did our team. We standardized delivery processes, introduced Jira for project tracking, and embedded Agile practices into the workflow. The groundwork for data consolidation and automation was laid during this period.
2019–2020: Modernizing the Architecture
With legacy limitations becoming increasingly apparent, we began redesigning the data infrastructure. Critical components migrated to Microsoft Azure, DevOps pipelines were put in place, and Selenium-powered automated testing brought new reliability to deployments.
2021–2022: Moving to the Cloud and Automation
Core data workloads moved to Snowflake, delivering the elastic scalability needed to handle massive OEM data volumes without performance trade-offs. GitLab-driven CI/CD pipelines cut release times and significantly reduced manual intervention.
2023–Present: Unified Intelligence
We built a secure BI Portal that brought all OEM reporting under one roof. Power BI and Tableau dashboards gave executives real-time visibility across operations, finance, and performance — supported by a dedicated team of 70+ professionals managing data delivery, QA, and support across 12+ OEMs.
The Results
What this partnership delivered goes beyond technical milestones. The client today operates with a data infrastructure that’s genuinely built for the business it has become. Reporting that once moved through slow, manual cycles, it now runs on automated pipelines with real-time visibility.
Decision-making has fundamentally shifted. Executives now work from live Power BI and Tableau dashboards rather than waiting on delayed reports. Teams collaborate with greater clarity through Agile workflows and transparent project tracking.
Perhaps most telling is the scale of the partnership itself. What started with a team of five has grown to over 70 professionals — a reflection not just of expanded scope, but also of a decade-long relationship built on delivery, trust, and continuous improvement.
