Key Takeaways:

• AI-Driven Modernization: RubinBrown led a comprehensive AI Data Readiness Assessment to evaluate the client’s systems, processes, and data maturity.
• Data Strategy Alignment: Developed a strategic roadmap linking AI, ERP modernization, and data governance to enable intelligent operations.
• Operational Impact: Improved efficiency, costing visibility, and cross-functional collaboration across manufacturing and engineering.
• Strategic Confidence: Leadership gained clarity to confidently advance their AI and digital transformation initiatives with measurable business value.

Client:

A building materials manufacturer with approximately half a billion in revenue partnered with RubinBrown to develop a data-enabled business transformation roadmap focused on modernizing systems, improving operational efficiency, and preparing for AI-driven growth.

The client, an industry leader in their field, recognized that its legacy, homegrown technology platforms were constraining scalability, cross-functional integration, and business insight. Leadership sought RubinBrown’s expertise to assess readiness, define a data strategy, and identify opportunities where AI applications could deliver measurable operational and financial impact.

Challenge:

Despite strong market performance, the manufacturer faced increasing pressure to modernize its systems and establish a data foundation for AI enablement. Its existing technology ecosystem relied heavily on manual, non-integrated processes, creating inefficiencies, compliance risks, and limited visibility into cost, variance, and performance metrics.

Key transformation challenges included:

• Homegrown systems that lacked scalability and cross-functional integration
• Manual workarounds leading to duplicate data and limited control over compliance requirements (SOX / J-SOX)
• Inefficient costing and variance visibility impacting profitability and decision-making
• Disconnection between engineering and sales, reducing cross-selling and customer insight
• High maintenance and repair costs ($22M annually) with minimal use of predictive or preventive maintenance capabilities

The company needed a clear roadmap to align data, process, and technology modernization with AI-driven opportunities ensuring operational readiness and long-term growth enablement.