Manufacturers generate more data than ever, while also facing a pressing need to simplify access to that data. However, data accessibility and contextualization continue to remain a major challenge. As factories become more connected, the need for next-generation data architecture is critical. Many plants are still grappling with fragmented systems that limit visibility and stall decision-making.
GE Vernova’s Proficy Data Hub looks to address this ongoing problem. Proficy Data Hub software breaks down data silos and connects Operational Technology (OT) data across Industry 4.0 ecosystems. With industrial data volumes expected to reach 4.4 Zettabytes (ZB) by 2030, manufacturers that invest in scalable data fabric architecture today will hold a competitive edge tomorrow.
Risks of Not Unifying Manufacturing Data
Well-designed and well-managed data architecture is a key pillar of digital transformation. Without data fabric, manufacturers will struggle to convert OT data into actionable insights. Significant blind spots are formed when dealing with fragmented systems and isolated data across plants and business units. Below are the key risks manufacturers face without a robust data unification framework:
- Limited Value from AI Tools: Digital technologies, notably Artificial Intelligence (AI) and Generative Artificial Intelligence (Gen AI), are only as good as the data they are fed. If these tools cannot collect and contextualize data across disparate systems and/or facilities, manufacturers are not getting the most value out of their technology investments.
- Persistent Data Silos: Data silos remain one of the biggest challenges facing manufacturers with digital transformation aspirations. Operations leaders require a unified view across various systems and factories to make enterprise-wide adjustments as they scale.
- IT/OT Misalignment: When Information Technology (IT) and OT teams lack strong convergence, manufacturers struggle with data integration, system interoperability, and data quality.
- Delayed Deployment Timelines: Disconnected systems and poor data integration can delay Industry 4.0 technology deployments, costing time and competitiveness, alongside reducing buy-in for future technology adoption.
- Increased Cybersecurity Vulnerabilities: Cybersecurity is a leading concern among manufacturers surveyed by ABI Research. Strong data management practices enhance data visibility and data hygiene, aligning with current Chief Information Officer (CIO) priorities.
Data Maturity Developed Through Proficy Data Hub Framework
The Proficy Data Hub solution drives data maturity by orienting around four key frameworks: Data Model, Data Fabric, UNS, and Directory Service. It leverages a Unified Namespace (UNS) approach to form a centralized point of data integration and management. Crucially, this framework enables manufacturers to connect both Proficy Suite tools and third-party software, creating a bidirectional data fabric. The data unification platform simplifies data capture, data access, and data quality—all prerequisites to fast deployment, scalability, and value creation of a technology integration.
A primary advantage of Proficy Data Hub is its ability to provide a single source of truth, building synergy between IT and OT departments. For data contextualization, Proficy Data Hub utilizes a directory service that unifies and democratizes connections across the broader Proficy suite. It retains the origin and meaning of OT data, which ensures that all other aspects of Proficy Data Hub can optimally leverage it. This helps manufacturers maximize value from their Industry 4.0 investments.
Mapping Out the Data Maturity Journey
As manufacturers look to implement more mature and effective data architecture, they should look to take the following short-term, medium-term, and long-term actions.
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Timeline |
Strategic Actions |
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Short-Term (0–12 months) |
· Assess current data maturity across tools, people, processes, and governance. · Identify long-term-focused vendors and integration partners. · Ensure IT and OT buy-in and representation, alongside promoting data literacy among stakeholders. · Build a data roadmap and assign accountability; define governance and security early. · Launch UNS architecture pilots to test and refine deployment processes. |
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Medium-Term (6–18 months) |
· Scale UNS architecture enterprise-wide with plant-level collaboration. · Evaluate and enforce governance and security frameworks for consistent data quality. · Continue training to embed processes and support adoption. |
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Long-Term (18–36 months) |
· Use unified data for AI, Overall Equipment Effectiveness (OEE), digital twins, and optimization. · Stay aligned with vendor roadmaps to drive ongoing innovation. |
Leading manufacturers are constantly driving technology adoption and development within their operations. By not building a unified data fabric, manufacturers risk suboptimal deployments of Industry 4.0 solutions and being left behind by more data-mature competitors. Proficy Data Hub provides manufacturers a path to take for their data maturity journey. For a deeper analysis, download the Executive Brief, Enterprise-Wide Industrial Production Optimization: The Benefits Of Building A Core Data Fabric
