March 21, 2025 The Crucial Need for Centralized Sources in Engineering

The creation of unified databases for essential engineering information will help organizations avoid costly project errors and delays.

By Allie Taylor, Principal Product Manager at Accuris

Modern engineers are overwhelmed, facing mounting demands and expectations to innovate faster and more efficiently, while simultaneously reducing costs and ensuring compliance. The engineering sector also faces an unprecedented shortage of skilled professionals, further impeding the timely, methodical delivery of desired outputs. But perhaps the most pervasive challenge for engineers is navigating the troves of data and requirements, especially for complex projects.

Disparate information stored in various forms and locations across company IT libraries stifles processes and wastes valuable engineering resources. This siloed data can cause collaboration challenges and a lack of traceability whereby teams cannot efficiently pinpoint original sources and rationale for product design decisions, or share historical knowledge with new team members.

As engineering standards and regulations are revised and updated frequently, using multiple standards platforms can also create obstacles for effectively updating internal standards and best practices, correlating changes and determining the impact that a new requirement may have on an existing product lifecycle. Organizations purchasing engineering standards from multiple vendors results in standards being spread across numerous platforms. This complicates collaboration, spreads resources thin, and increases the risk of noncompliance if important updates or requirements are missed.

Without a unified framework to connect project requirements, specifications, and critical information, these challenges will continue to proliferate, leading to costly engineering delays and errors.

Connecting the Dots in Engineering with Digital Threading

In an increasingly competitive landscape, a single source of truth for engineering projects is essential for achieving operational success and business agility. A centralized, unified digital library that stores all an organization’s applicable standards, specifications, best practices, lessons learned, and historical data serves as the single source of truth.

Digital threading integrates data and information throughout the product lifecycle to provide real-time, comprehensive insights to engineers. Digital threading and model-based workflows are a transformative change in how engineering data is managed and utilized, especially for companies that still rely on siloed document-based workflows.

Using siloed, document-based processes can have a significant impact on a project’s efficiency, quality and time-to-market. Operating in silos can lead to 40-60% more rework when design requirements conflict. Product quality can also be impacted: engineers who work in a document-based system report 30% more late-stage defects. Late-stage defects are the costliest to correct. Document-based systems are also inefficient and error prone, leading to 25% longer time-to-market. Without traceability, engineers do not have a clear connection to the original source material and are forced to guess why key decisions were made – increasing the risk of errors that could lead to recalls, legal issues or even catastrophic failures.

Model-based systems engineering (MBSE) addresses many of these shortcomings. Engineers have been using the MBSE approach for more than a decade. MBSE uses models instead of traditional paper or PDF documentation to define, design and manage systems. The practice covers the entire project lifecycle: research & requirements, design & development, verification & testing, integration & digital twins, and deployment & optimization. Digital threading provides holistic, reliable traceability back to the original standards or internal specifications that requirements are derived from.

The recent advancements in artificial intelligence, automation, software and digital standards have simplified the adoption and implementation of MBSE and digital threading. Digital threading links various engineering platforms, integrating an organization’s entire catalog of data and information across an engineering lifecycle into one cohesive domain. This thread encompasses everything from requirements definition to design, production, operation and maintenance specifications. This unification of data across the entire engineering lifecycle can streamline processes, improve accuracy, collaboration and traceability, and reduce organizational risk. 

The Journey to Becoming a Model-Based Enterprise

Over the last decade, MBSE has come to the forefront as the new standard for innovation. Becoming a model-based enterprise is a process with several stages: 

• Stage 1: Document-Centric. Organizations struggle with siloed documents, conflicting versions and limited traceability, leading to rework and missed requirements.
• Stage 2: Preliminary MBSE. Organizations are using dual-track processes (documents and models), with inconsistent adoption, leading to confusion and minimal ROI.
• Stage 3: Integrated MBSE. Organizations may be dealing with cultural pushback and tool integration shortfalls, resulting in slowed progress.
• Stage 4: Advanced and Automated MBSE. Organizations are using complex models and governance demands, although there is a risk of quality slips without robust oversight.
• Stage 5: Optimized Enterprise MBSE. Organizations are ensuring digital twins remain accurate and integrating MBSE practices with legacy systems.

Today, most organizations are in stage 1 or 2 of their journey. Many organizations struggle with taking unstructured data and moving it into an integrated, interoperable ecosystem.

Best Practices for Digital Threading

In a model-based enterprise, effective digital threading relies on integrating data across the entire product lifecycle, including as-built, as-processed, and as-tested information. The following best practices can help organizations transition from document-based to model-based:

• Standardizing data formats ensures consistency and compatibility across systems and suppliers.
• Preserving data integrity by minimizing translations—like avoiding conversions from 3D models to 2D drawings—helps maintain the fidelity of critical information.
• Integrating systems through Product Lifecycle Management (PLM) and MBSE tools supports real-time data sharing and process automation, while
• Using secure collaboration platforms enables suppliers to contribute effectively without compromising data security.
• Leveraging digital twins enhances decision-making by enabling real-time performance monitoring and predictive maintenance.
• Following robust cybersecurity protocols to safeguard sensitive data within the digital thread, supported by regular security assessments and compliance with standards.

To maximize the value of digital threading, enterprises should invest in workforce readiness, providing training on tools, data standards, and digital thread concepts. This holistic approach fosters end-to-end traceability, operational efficiency, and continuous innovation across the enterprise.

The Future of Engineering is Digital Threading

To maintain a competitive edge and ensure continuous innovation, organizations should create a centralized, consolidated knowledge base of engineering data and requirements. Digital threading represents the future of engineering and can help companies overcome the unprecedented challenges that arise from data disconnect, manual analysis, and siloed systems.

About the Author:
Allie Taylor is an experienced product management professional with over 9 years of experience in managing and launching B2B, SMB and Enterprise level SaaS Data/Data Visualization, Analytics and Integrations customer-centric products. She has experience working on Generative AI, NLP and ML projects in collaboration with Data Science teams. Allie is also experienced in working in a range of organizations from stealth and small start-up environments to larger, multinational organizations across the ad tech, real estate and cybersecurity industries.

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