Digital Thread Insights with Ettore Soldi
Companies Must Focus on the Digital Thread and Flexible Manufacturing — Only Then Can They Reap the Benefits of AI and Digital Twins
By Piero Macrì
April 29, 2025
To address the growing complexity in manufacturing, Engineering is focusing on integrating data from PDM, PLM, MES, ERP and CRM systems. The goal: to build a digital thread that enables flexible manufacturing, facilitates product customization, breaks down silos and creates a single source of truth. The potential of AI, Digital Twins and predictive simulation in manufacturing is immense. The leading digital transformation companies in manufacturing seem to agree: to achieve greater efficiency, resilience and productivity, investments must target “flexible manufacturing” — an approach that dynamically adapts enterprise processes to demand and production changes. In IT terms, this translates into the concept of a digital thread, which involves integrating data repositories across PDM, PLM, MES, ERP and CRM systems.
“This is not just a technological exercise for its own sake. The number of factors — engineering, regulatory, technical, compliance, sustainability — that must now be considered during product development is so broad that we need a fundamental shift in speed and approach. That shift can only happen through true data and information integration,” says Ettore Soldi, Executive Vice President of Engineering Industries eXcellence, the global division of the Engineering Group specialized in the development, integration and implementation of holistic digital transformation solutions covering the end-to-end lifecycle and supply chain of all industrial products and processes.
There is another compelling reason companies must adopt a digital thread approach: unifying data sources from various departments is a prerequisite for unlocking the potential of artificial intelligence and Digital Twins — technologies that many experts consider the true engines of flexible manufacturing.
“Integrating engineering, production and supply chain data is essential for decision-making, analyzing real-time data, identifying inefficiencies and optimizing production, sales and marketing processes,” says Soldi.
In short, by overcoming internal silos and creating an integrated information flow fed by multidisciplinary data — a single source of truth — key stakeholders can collaborate leveraging their shared expertise to meet today’s manufacturing challenges. This is the digital thread for flexible manufacturing according to Engineering Industries eXcellence.
Q&A with Ettore Soldi
Q: How do you approach integrating core manufacturing systems like PDM, PLM, MES, ERP and CRM?
A: It’s essential to plan the digital journey by identifying projects with the highest return on investment. This requires a thorough analysis of business needs and available technologies. Before integration, it is important to assess the maturity of existing technologies and processes to identify improvement areas and define a starting point for digital transformation. Setting clear and measurable objectives — such as improving operational efficiency, reducing cycle times or increasing product quality — is key. Integration should be done gradually, starting with pilot projects that can be scaled later. This allows companies to test and optimize processes before full-scale implementation. Finally, it is vital to continuously monitor results using performance indicators and make adjustments to ensure goals are met.
Q: The market is trending towards highly configurable products. What’s the value of integration in that context?
A: Everyone is facing increased supply chain complexity and product configurability, which creates demand for systems that can quickly adapt to changing requirements. This is especially critical in engineering-to-order environments like aerospace, packaging or any sector where complex machinery is designed. Thanks to the digital thread, all engineering changes can be tracked and communicated in real time to production systems. Every phase of the process uses the most up-to-date information, improving final product quality and reducing downtime.
Q: What’s your message to factory workers, entrepreneurs, managers, plant directors and operations directors?
A: When we talk about the digital thread, we are talking about creating the best conditions for a more efficient and responsive manufacturing value chain. The digital thread facilitates the integration of processes, systems, and unstructured data — creating a seamless flow of information from design to production, distribution, and end use. It supports product customization and supply chain complexity management. Implementing a digital thread is how companies stay competitive and adapt quickly to market needs.
Q: Can you give an example of the benefits from deeper integration between design and production?
A: Integration ensures continuous alignment between design and production phases. For example, if an engineer modifies a Bill of Materials or process, the MES can automatically receive the update, ensuring production uses the latest data. This reduces errors and improves efficiency. Additionally, any deviation in the production process can be traced, creating a digital history of the product that can be compared with the initial design expectations.
Q: What does “single source of truth” mean in practice?
A: It means having a consistent, unified data source for designers, line operators, plant managers and distributors. An integrated system where all product- or process-related data is centralized and accessible through an enterprise data lake. This concept is key to ensuring data consistency, accuracy and traceability across the product lifecycle — from design through production and beyond.
Q: Another major challenge is breaking down silos — arguably the mission of companies like Engineering.
A: Exactly. Engineering, manufacturing and supply chain. Integrating a multivendor and multidisciplinary environment with data tied to diverse software platforms enables flexible manufacturing. To achieve this, companies need expertise in both technology and process. Aerospace, automotive, pharma, food & beverage, packaging, consumer goods — every client is different. What matters is knowing what change to introduce in the process and identifying ROI starting with the low-hanging fruit.
Q: What do you mean by “low-hanging fruit”?
A: Projects that are easy to implement and deliver a high return-on-investment with relatively low effort. This helps prioritize investments and ensures resources are allocated strategically. In the context of digital transformation and process optimization, identifying the low-hanging fruit is essential — it enables quick, tangible results and helps accelerate adoption of new technologies. We focus on projects that require fewer resources and time but bring significant improvements in efficiency, quality and customer satisfaction.
Q: Is extensive digitization and data integration necessary to fully leverage AI?
A: Absolutely. Without a digital foundation, companies won’t get far. They won’t be able to use new technologies to their full potential. We talk a lot about AI and innovation, but without a digital backbone — an integrated enterprise where PLM communicates with MES and ERP — real change is impossible. Without an adequate digital thread, AI and predictive analytics, which are essential to optimizing production processes and supporting informed decision-making, remain highly limited.
Q: What’s AI’s role in production processes?
A: AI multiplies the value of data. Machine learning algorithms can analyze large datasets from PLM, MES and ERP systems to identify bottlenecks and inefficiencies. This allows informed adjustments to production line layouts, improving operational efficiency and reducing downtime. AI also supports decision-making at all organizational levels through simulation and predictive analysis. For example, if quality issues arise, AI can analyze engineering data to detect anomalies in design or materials and suggest changes before defects become widespread—improving final product quality.
