New Study Reveals $11.28M Annual Opportunity for Industrial Companies to Boost Competitiveness by Modernizing Closed Automation Systems
SuncorSuncor(US:SU) Globenewswire·2025-11-26 07:03

Core Insights - Schneider Electric's new research highlights that closed industrial automation systems are diminishing competitiveness, costing mid-sized organizations an average of $11.28 million annually, which translates to a 7.5% revenue loss [1][2][3] Cost Breakdown - The research identifies four critical cost areas for organizations: - Operational Agility & Resilience: $6.1 million lost annually due to inflexible hardware systems that require physical modifications for updates, with 77.4% of systems needing such changes [10] - Optimization & Efficiency: $2.28 million lost due to maintenance burdens and operational inefficiencies, with companies managing an average of 2 to 10 distinct industrial systems [10] - Preventable Quality Failure and Costly Data Maintenance: $1.2 million lost due to proprietary systems creating data silos, limiting real-time insights, with only 28% of companies accessing real-time data [10] - Sustainability & Compliance Costs: $1.7 million lost due to regulatory changes necessitating costly hardware retrofits [11] Industry Challenges - Traditional hardware-defined automation systems struggle to adapt to dynamic industrial demands, leading to costly technical projects and limited data access, which reduces visibility and responsiveness [4][5] - Hardware complexity results in vendor dependency, with 30% of issues requiring specialized support, exacerbating workforce efficiency challenges amid skills shortages [5] Need for Transformation - The research emphasizes the urgent need for transformation towards open, software-defined automation, which can modernize legacy systems, enhance ROI, and improve industrial competitiveness and resilience [6][9] Benefits of Open Automation - By decoupling software from hardware, manufacturers can integrate multi-vendor systems, adapt to market shifts, and improve productivity through actionable real-time data [7][8]