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The Digital Thread in Manufacturing: Connecting Data Earlier Across the Lifecycle

By connecting customer intent and configuration data early to the product lifecycle, manufacturers extend the digital thread across sales, engineering, and production.

The Digital Thread in Manufacturing: Connecting Data Earlier Across the Lifecycle

A digital thread is a chain of connected data from engineering design through production and the serviceable life of a product. In a traditional view, the digital thread provides end-to-end traceability starting in engineering systems like CAD and PLM and continuing through delivery and aftermarket systems to provide the most up-to-date and accurate information to all functions. However, most conversations don’t include configuration, quoting, and customer intent, which happens earlier in the commercial lifecycle.  

Creating a digital thread in manufacturing requires a full view of the product lifecycle to capture and carry customer requirements, configuration logic, and engineering data forward as a single, continuous source of truth for the rest of the lifecycle.  

What is a digital thread in manufacturing?  

A digital thread provides continuity across each manufacturing function by connecting product lifecycle data and presenting it in the right context for each team. It’s achieved by properly integrating key design, manufacturing, and service systems, so that data is made available across these systems in the appropriate and most relevant format.  

Take the example of a manufacturer of customized industrial machinery that uses configure, price, quote (CPQ) to validate thousands of configuration combinations. Once the product is configured, a connected data framework allows systems to automatically generate engineering and manufacturing BOMs and documentation, which translates that CPQ quote data specifically for these departmental needs. This ensures the entire build process traces back to the original customer configuration and their needs. 

While a digital thread sounds similar to a digital twin, there are key differences.  

Digital thread vs digital twin: what’s the difference?  

A digital twin is a virtual representation of a specific product or process across its lifecycle. At its core, it’s a simulation used to understand how a physical product will perform, helping inform decisions in engineering, manufacturing, and service.

A digital thread, by contrast, is not a simulation. It’s a connected data framework that ensures consistent, accurate product information flows across all functions and systems involved in designing, selling, building, and servicing products. The digital thread provides the foundation that enables digital twin technology by making trusted lifecycle data accessible in the right context.

Critically, a complete digital thread needs to start earlier than engineering. By capturing customer requirements, configuration decisions, and commercial intent through CPQ, manufacturers create what can be thought of as an engagement twin—a digital representation of the configured solution that was actually sold. This engagement twin becomes the foundation of the digital thread, ensuring engineering, manufacturing, and service teams work from the same validated product definition throughout the lifecycle.

The benefits of the digital thread  

By creating a way for all teams—from customer-facing sales to services—to access crucial product lifecycle information, you can create efficiencies and optimize processes more effectively.  

The benefits of the digital thread include: 

  • Engineering time savings and faster quote-to-production: With validated, up-to-date product logic available to sales teams through CPQ, engineering spends far less time reviewing configurations. This frees engineers to focus on higher-value design and reduces quote-to-production cycle time.
  • Margin protection: Misalignment between what was quoted, what engineering interprets, and what manufacturing ultimately builds can hurt your profitability. A connected digital thread provides consistent, accurate data across every stage, catching discrepancies earlier in the manufacturing lifecycle. 
  • Error elimination: Traceability and connected data provides all teams with the most up-to-date information, so everyone works from the same data source even as changes are made. 
  • True traceability: By linking downstream performance, service or maintenance data, and lifecycle information back to the original sales configuration and requirements, the digital thread enables variant-specific insights and equips sales and aftermarket teams to identify upgrade and service opportunities.
  • Faster change order management: A connected digital thread synchronizes updates to product logic, engineering data, BOM structures, and manufacturing instructions across every system and team. When changes are made in engineering—such as redesigns, compliance updates, or new options—those updates flow to CPQ, ERP, and MES automatically. This reduces the risk of selling outdated configurations.
  • Scalability across partners: Your entire distribution network works from the same accurate, governed product logic for better consistency across regions and channels.  

Steps for establishing a digital thread across commercial, engineering, and production processes

In most digital threads, manufacturers begin by defining a product within CAD, PLM, and CAE systems to create engineering BOMs, drawings, and models. The thread is then built through integrations and structured product data. Via the PLM, product data is pushed to systems like the ERP and MES for costing, work instructions, and routing. From there, production can build the product and provide data to services teams through MES and quality systems.  

Commercial decisions aren’t traditionally part of the digital thread, creating information siloes that lead to incompatible product configurations in the sales process. So, how can you build a true digital thread that encompasses the full lifecycle?  

  • Build a centralized product configuration model. Define options, rules, constraints, BOM logic, and dependencies into a single, authoritative model.
  • Map the configuration model to lifecycle systems. Connect commercial tools like CPQ, PLM, ERP, and MES so they interpret the same configuration definitions without duplicate rule sets or manual translation.
  • Orchestrate data flow across systems. Establish structured integrations so configuration data flows automatically into engineering and manufacturing systems and returns lifecycle data back upstream when needed.
  • Connect configuration decisions to engineering data.Connect commercial configuration decisions directly to engineering systems, so selected options and constraints automatically drive CAD models, variant-specific EBOMs, and engineering workflows. This ensures engineering works from the same validated product definition that was sold, without manual reinterpretation.
  • Maintain synchronized BOM structures. Ensure eBOMs, mBOMs, and commercial BOMs remain coordinated as constraints or engineering definitions change.
  • Automate lifecycle transitions. Enable transitions from one part of the lifecycle to the next to follow defined rules and workflows instead of manual handoffs.
  • Implement change management. Propagate engineering changes, new rules, and product updates through all systems, so outdated configurations are never sold or built. 
  • Establish a standard configuration service for all channels. Expose validated configuration logic to all sales channels so every buyer interaction uses the same governed model.
  • Capture lifecycle data for traceability and feedback loops. Tie as-built, quality, and service data back to the original configuration and lifecycle definitions to improve future designs and customer engagement.
  • Govern variants across their full lifecycle. Manage how configurations are introduced, updated, retired, or replaced. 

Real-world examples: strengthening the digital thread with configuration

Manufacturers like Piab vacuum automation and lifting solutions and Vantage Elevator Solutions show how establishing a digital thread between commercial and design functions creates immediate, measurable results.

By establishing configuration as a governed source of product truth, Piab unified pricing, visualization, and ERP synchronization with engineering data. This enabled more than 40,000 self-service configurations per month and direct linkage of 58,000 configured items to product and engineering structures. The result was faster, more consistent quoting and a reliable handoff into downstream manufacturing systems.

Vantage Elevator Solutions achieved similar gains by connecting constraint-based configuration with ERP-integrated quoting. This eliminated unworkable designs, reduced turnaround times, and ensured that what was sold aligned with what manufacturing could build, removing costly manual interpretation between sales and engineering.

In both cases, extending the digital thread to configuration improved accuracy, scalability, and traceability at the front end of the lifecycle. Just as importantly, it creates a stronger foundation for future lifecycle connections, making it possible to feed fulfillment and service insights back into the thread over time and further strengthen decisions across the product lifecycle.

Connect data across your manufacturing lifecycle 

The digital thread needs to start earlier to truly eliminate quoting, engineering, and production issues. Manufacturers that connect CPQ, lifecycle management, and core operations get faster, more accurate and profitable outcomes. 

Tacton, the most complete end-to-end lifecycle platform for manufacturers, helps your teams create the continuity, accuracy, and configurability needed to deliver the right product every time. Explore how a smarter approach to configuration and data flow can strengthen your entire value chain. 

Learn More About Tacton  

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6 Manufacturing Trends in 2025 to Watch

Tacton's 2025 State of Manufacturing survey reveals six industry trends in strategic initiatives, digital transformation, AI and more.

6 Manufacturing Trends in 2025 to Watch

Our annual State of Manufacturing survey reveals manufacturers are charging ahead with transformation in 2025, but not always in the same direction. The survey of over 200 global industrial leaders uncovered rising tensions shaping the year’s biggest shifts: manual vs. digital, efficiency vs. experience, resilience vs. innovation.

While some companies are making bold moves with AI and automation, others are still held back by manual sales processes, fragmented data, and knowledge loss. These 2025 manufacturing trends show the urgency, uneven progress, and growing pressure to connect operations and customer engagement into a single, scalable strategy.

1. Manual Sales Processes Are Becoming a Competitive Risk

In favor of transformation on the production floor, manufacturers remain stagnant on digital sale transformation in 2025.  

Despite widespread digital transformation efforts, 43% of manufacturers still configure, price, and quote customer solutions using manual, Excel-based processes.  Furthermore, 62% of survey respondents still rely on manual consultation to guide solutions, and nearly half of manufacturers report still using static product catalogs to guide conversations.  

CPQ adoption 2025 state of manufacturing report

This signals more than just an inefficiency issue. Manual processes limit the ability to tailor conversations to customer needs in real time. When sales teams rely on static tools, inconsistent logic, or engineering back-and-forth to deliver a proposed solution, they lose the ability to confidently guide buyers, explore tradeoffs, or pivot to value. 

According to research by Forrester, 86% of B2B purchases stall during the buying process and 81% of buyers express dissatisfaction with the vendors they choose. Buyers indicate that while digital, self-service experiences are desirable, when speaking with a sales representative, they want someone who understands and is responsive to their needs and goals.  

As product portfolios become more complex and buying expectations shift toward speed and autonomy, the gap between manual processes and modern sales models will continue to widen. Manufacturers that fail to digitize their sales processes risk losing ground in both efficiency and buyer trust. 

2. Supply Chain Visibility Continues to Be a Top Internal Priority

Manufacturers have learned the hard way that volatility, shortages, and delays can undo even the most sophisticated engineering or sales strategies. That’s why supply chain remains the heartbeat of transformation efforts in 2025:

  • 66% of manufacturers rank it as their top investment priority during economic uncertainty

  • 44% list supply chain visibility among their most critical digital transformation goals alongside workflow automation and production line efficiency

Digital transformation gains 2025 state of manufacturing report

But while internal supply chain visibility is improving, there’s little indication this data is flowing into customer-facing processes like quoting, lead-time accuracy, or the customer experience. 

It’s a missed opportunity. For many, the quoting process still operates in isolation, without immediate visibility into inventory constraints, production timelines, or part availability, and vice versa. Manufacturers have the opportunity to use configure, price, quote (CPQ) data, for example, to forecast demand and make supply chain data accessible, relevant, and actionable in the sales process to improve the customer experience at all points in the buying journey.

3. Mid-Market Manufacturers Are Gaining Momentum in Advanced Technology and AI 

Manufacturers in the $500M–$999M revenue range are showing strong momentum in AI adoption—22% report already investing heavily in AI, more than double the rate of their enterprise peers with over $5B in revenue (just 10%). They’re also exploring AI uses cases at the same rate as larger companies. While larger companies ($1B–$5B) lead in overall AI investment levels, it’s these mid-sized firms that are showing increasing focus in digital maturity. They’re prioritizing AI-driven automation (51% vs 10% of large enterprises), cloud solutions (49%), and data analytics (46%) at higher rates than their enterprise counterparts, suggesting a strategic focus on agility and practical outcomes over complexity.

The future of manufacturing innovation won’t be shaped solely by size, but by speed and adaptability. As firms from $100M to $1B scale their AI capabilities, they’re becoming the real-world test beds for what smart manufacturing can deliver.

4. Current Solutions to Workforce Transitions Are Threatening Scalability

While many manufacturers continue to invest in automating production and managing supply chain risk, a growing challenge is emerging within their commercial and engineering teams: knowledge loss and workforce transition. 

According to our survey, 30% of manufacturers expect at least 16% of their sales and engineering workforce to retire within the next five years. Yet fewer than half feel fully prepared to manage that transition. Most are responding through mentorship programs (52%), structured training (46%), or proactive recruiting (39%), while only 32% are digitizing internal product or sales knowledge. 

At the same time, onboarding is at risk of slowing down as companies try to expand their product portfolios or enter new markets.  

Manufacturers are still relying on human-to-human transfer of knowledge to sell and quote complex products. That model isn’t scalable, and it’s especially risky in a tight labor market or during generational turnover. 

If institutional knowledge continues to live only in the heads of a few experienced sellers and engineers, organizations will face slower time to revenue, inconsistent buyer experiences, and increased quoting risk. The manufacturers that succeed will be those who embed expertise into systems, not just people. 

5. Operational Gains Are Outpacing Customer Engagement Improvements. 

Digital transformation is delivering results in production and fulfillment. According to the survey, 52% of manufacturers are focused on warehouse management, 41% on inventory visibility, and 44% on workflow automation. Many report real improvements: 59% cite increased productivity, 41% improved inventory management, and 39% reduced manual processes as direct outcomes of their transformation efforts.  

Digital transformation priorities 2025 state of manufacturing report

These backend gains are beginning to improve fulfillment timelines, order accuracy, and supply chain coordination. But the front of the customer journey tells a different story, with sales gains trailing behind. 

Sales transformation efforts are losing momentum, falling from 68% in 2022 to just 52% in 2025. Self-service configuration, guided selling, and personalized buying experiences remain underdeveloped, even as quote volumes and complexity rise. 

Manufacturers are starting to deliver value faster at the end of the process, but to compete, they’ll need to do the same at the beginning. As B2B buyers expect more from their first interaction, it’s not enough to fulfill quickly. Manufacturers that extend transformation to the front of the sales cycle will be better positioned to connect operational efficiency with commercial impact and build loyalty from the first touchpoint.

6. Digital Strategy Is Accelerated by Competition 

Manufacturers aren’t just planning transformation, they’re actively searching for it. 

Across every channel—whether it’s reading trade publications, attending events, calling vendors, or benchmarking competitors—engagement with new digital technology solutions is up from 2023 to 2025, according to the survey. Compared to 2023, more manufacturers are looking for tech solutions by: 

  • Attending industry events and conferences (up 8% in 2025) 
  • Reviewing trade publications and industry reports (up 17% in 2025) 
  • Hiring technology advisors (up 14% in 2025) 
  • Engaging with peers and partners for recommendations 

At the same time, competitive pressure was named as the second greatest transformation driver, surpassing economic uncertainty, energy costs, or even customer expectations. 

Transformation is no longer a back-office planning exercise but a visible, competitive race. The urgency is higher, the market signals are louder, and digital solution evaluation is happening in more places than before. 

Understanding the Bigger Picture of Manufacturing in 2025  

These trends reflect deeper shifts in how manufacturers are approaching complexity, competitiveness, and transformation in 2025. From the persistence of manual processes to the rise of AI in mid-market innovation, each trend points to the growing need for more connected, scalable, and customer-aligned ways of working.  

For a deeper look at the data behind these insights, download our full 2025 State of Manufacturing report. The survey, conducted by Tacton and Researchscape, reveals how over 200 global manufacturers are navigating digital transformation and AI, economic uncertainty, go-to-market agility, and workforce shifts.  

And if your business is looking to bring these strategies to life, whether it’s digitizing your sales cycle, embedding product intelligence into quoting, or scaling expertise across teams, Tacton is here to help. Our CPQ buyer engagement platform is built to simplify complexity and accelerate your go-to-market strategy. 

Download the Full State of Manufacturing Report