HomeRepair Modernising data for future-ready insights

HomeRepair is a national repairer of homes for customers of Australia’s leading general insurers. They sought to improve reporting, enhance decision-making, and prepare for future innovations like AI through a more efficient and reliable data system.

HomeRepair, as a national repairer for Australia’s leading insurers, recognised an urgent need for a more efficient and reliable data system. This was not merely about improving current reporting and enhancing decision making, but also about strategically preparing for future innovations, including the integration of AI.

The company faced a confluence of significant challenges that impeded its progress.
A fundamental issue was a pervasive lack of data trust and governance, rooted in outdated legacy platform data models, unsupported features, and fragmented reporting. This directly resulted in inconsistent analytics and limited adoption of essential reporting tools. Furthermore, reporting itself was complex and inefficient; the absence of critical CRM source data attributes in Redshift necessitated cumbersome workarounds and custom SQL queries, severely complicating Business Intelligence reporting.

Unwieldy data integration and orchestration tools, whose processes were difficult to support and incapable of managing upstream source system schema changes were also a topic for HomeRepair’s internal processes. Ultimately, these limitations in scalability and future readiness stifled HomeRepair’s’ aspirations for digital transformation and data-driven decisions, preventing it from fully leveraging its valuable data assets.

To address its need for a scalable and future-proof data solution, HomeRepair collaborated with Fujitsu, adopting its AWS Databricks Lakehouse Accelerator, a best-practice approach to modern data architecture. This solution was rapidly deployed in just eight weeks. The initial phase focused on building a more intelligent data system, utilizing a medallion platform architecture, which now automates data ingestion, transformation, and modeling, establishing a single, reliable source of truth for finance and operations reporting, which in turn reduces business intelligence reporting errors and complexity.

The project also significantly enhanced data integration and governance. Salesforce (CRM) data was seamlessly integrated using Amazon AppFlow, streamlining data flow and improving overall data governance and accessibility, thereby increasing trust in analytics. Recognizing the platform’s potential, HomeRepair extended Fujitsu’s engagement via T&M consulting services to further expand its data capabilities. This extension successfully integrated Amazon Connect for deeper customer interaction insights and Definitiv Payroll for improved workforce analytics. A vital part of this expanded effort was the upskilling of the HomeRepair team, enabling them to independently manage and enhance the platform.

With the introduction of its new AWS Databricks Lakehouse, HomeRepair has achieved a new level of operational excellence. Automated data ingestion and reporting now streamline workflows, leading to a significant reduction in manual effort and a marked improvement in productivity. This unified and accurate data source is pivotal for enhanced decision-making, providing leaders with the confidence needed to act decisively. Beyond immediate gains, the modernized Databricks data intelligence platform ensures scalability for future innovation, acting as the bedrock for AI-driven insights and enabling HomeRepair to continuously optimize its processes.

The robust governance and seamless integration have instilled a new level of trust in the data by eliminating inconsistencies, guaranteeing secure and reliable analytics. This comprehensive approach, guided by Fujitsu’s data modernization expertise, has transformed HomeRepair’s’ data landscape, making it a powerful asset for ongoing digital innovation.