The data story behind sustainability
Together, digital maturity and connected data empower organizations to embed sustainability into engineering, manufacturing and supply chains
Industrial companies today face unprecedented pressure to measure, manage, and communicate sustainability performance. The European Union's Digital Product Passport mandate, effective 2027, exemplifies how sustainability information management has become central to regulatory compliance and market access. Yet beyond compliance, effective management of Life Cycle Assessment (LCA) data, technical data sheets, product specifications, and comprehensive data capture systems represents a transformative opportunity to drive innovation, optimize operations, and establish competitive differentiation.
"Digitalization transforms sustainability information from isolated documents into actionable intelligence that drives design, procurement, and strategic decision‑making."
Life Cycle Assessment provides the methodology for quantifying environmental impacts across a product's entire lifecycle—from raw material extraction through manufacturing, distribution, use, and end-of-life disposal. Governed by ISO 14040 and ISO 14044 standards, LCA encompasses four interconnected phases: goal and scope definition, inventory analysis, impact assessment, and interpretation. This rigorous framework evaluates multiple environmental impact categories, providing comprehensive visibility beyond simple carbon footprinting.
However, traditional LCA approaches struggle with data-intensive requirements, creating substantial management burdens. Studies indicate that up to 75% of companies lack adequate sustainability data infrastructure. Digital transformation fundamentally reshapes LCA capabilities by enabling automated data collection, real-time monitoring, and integration across enterprise systems. IoT sensors embedded throughout manufacturing facilities continuously capture energy consumption and emissions data, feeding directly into LCA calculations. Digital Twins enable designers to simulate environmental impacts across design scenarios, facilitating optimization before physical production while maintaining comprehensive traceability.
Understanding the difference between digitization and digitalization holds profound implications for sustainability information management strategies. Digitization converts analog information into digital formats—scanning paper-based technical data sheets, converting inspection logs to electronic records, creating searchable databases of certifications. While digitization delivers efficiency gains and improves accessibility, it maintains existing processes in digital form without fundamentally transforming value creation.
Digitalization, by contrast, leverages digital technologies to transform business processes and decision-making frameworks. Digitalization integrates sustainability data across PLM (Product Lifecycle Management), ERP (Enterprise Resource Planning), and supply chain systems, creating unified Digital common Threads connecting design decisions with environmental outcomes. This integration enables fundamentally new capabilities: automated LCA calculations triggered by design changes, real-time supplier sustainability scorecards informing procurement decisions, and predictive analytics identifying optimization opportunities.
The progression typically unfolds in three stages. Initial digitization establishes digital infrastructure by converting existing information assets. Subsequent digitalization implements technologies enhancing processes and enabling data-driven decision-making through automation, IoT integration, and advanced analytics. The final stage—business model digitalization—fundamentally reimagines operations by embedding digital solutions into strategic frameworks. For industrial manufacturers, this final stage manifests powerfully through servitization strategies.
Servitization—the strategic shift from selling products to delivering integrated solutions and outcomes—has emerged as the most transformative business model innovation available to industrial manufacturers. This evolution transcends after-sales service additions; it represents fundamental reconceptualization of how manufacturers create and capture value while addressing sustainability imperatives. Leading examples include Rolls-Royce's pioneering "power-by-the-hour" pricing model and comprehensive remote monitoring services.
The strategic rationale aligns powerfully with sustainability objectives. When manufacturers retain product ownership and provide functionality as services, they internalize lifecycle costs and environmental impacts—creating direct economic incentives for durability, repairability, and resource efficiency. This contrasts sharply with transactional models where manufacturers profit from volume sales while customers bear operational costs and disposal burdens.
For industrial companies managing product complexity, servitization enables systematic knowledge capture and reuse. Manufacturing expertise accumulated over decades can be systematically documented, organized, and disseminated through digital platforms. Knowledge management systems integrated with PLM and ERP infrastructures create living repositories of best practices, ensuring critical insights survive workforce transitions. Servitization also fundamentally enhances collaboration across organizational boundaries. When manufacturers transition from product suppliers to service partners, they develop deeper customer relationships built on shared performance objectives.
Technical data sheets and product specifications represent critical sustainability information assets, yet their potential often remains underutilized due to fragmented systems. Modern Product Data Management systems provide centralized, version-controlled management of these information assets, integrating with PLM and ERP platforms to create comprehensive digital threads.
Document capture technologies—combining scanning hardware with optical character recognition and automated workflow routing—systematically liberate sustainability information trapped in analog formats. The environmental case proves compelling: transitioning to digital document management reduces paper consumption by up to 90%, eliminates physical storage requirements, and minimizes waste generation. AI-powered systems automatically classify documents and extract key fields, automatically populating database records with material compositions, emission factors, and compliance certifications.
Effective circular economy practices require unprecedented collaboration across organizational boundaries. Collaborative digital platforms enable geographically distributed teams—including external partners—to access relevant product information while maintaining security controls. Component reuse, material recycling, and knowledge dissemination require coordinated action across multiple stakeholders with aligned incentives.
"Sustainability data, when systematically captured, intelligently managed, and strategically leveraged, becomes the most valuable asset for navigating industrial transition."
Organizations should begin with Digital Maturity assessments establishing baseline capabilities, then systematically progress through digitization (establishing data infrastructure), digitalization (implementing integration technologies), and business model transformation (enabling servitization and circular practices). The integration of PLM, ERP, and sustainability platforms—supported by advanced document capture technologies, digital twins, and collaborative platforms—creates comprehensive information environments where sustainability considerations inform every strategic decision.
As regulatory pressures intensify and market expectations evolve, industrial companies that systematically manage sustainability information will establish durable competitive advantages. Organizations recognizing that sustainability data, when systematically captured, intelligently managed, and strategically leveraged, becomes their most valuable asset for navigating industrial transitions will lead their sectors into the sustainable future propelling the data-first approach for the whole company.
The survey provided insights into the pressures organizations face to supply sustainability data. The results indicate that more than 75% either feel this pressure or anticipate experiencing it in the future. Comparing this with the level of preparation and support from digital business applications, the data suggests that many companies are not yet prepared or do not collect data in a structured manner using such tools. Given these findings, organizations may need to begin focusing on developing data capturing, collection, and reporting practices related to sustainability.