The Era of Digital Product Development for Consumer Goods

Consumer goods manufacturers have reached a turning point. To remain competitive, makers of discrete goods (furniture and home decor, sporting goods, and fashion and apparel including footwear and luxury watches and other products) work to innovate faster, offer more personalized products, lower environmental impact and improve engineering and manufacturing workflows.

For engineering and manufacturing leaders, the next competitive advantage will not come from more point solutions. Instead, competive advantage comes from implementing a fully digital product lifecycle — from ideation and design through simulation, validation, sourcing and manufacturing planning and alignment.

A neutral signal from the broader manufacturing market supports that shift. Focused on research that ‘accelerate(s) innovation by developers and inventors,’ the National Institute for Standards and Technology (NIST) published research such as, Digital Thread for Smart Manufacturing. The agency focuses helping manufacturers implement a complete digital thread for information that runs through design, manufacturing and product support processes. Plus, Deloitte’s 2026 Consumer Products Industry Global Outlook points to a more complex consumer products market shaped by technology, trade shifts, rising costs, supply chain disruption and changing consumer expectations.

Together, these trends reinforce one conclusion: product development operating as a disconnected front-end process does not support engineering workflows and modernization goals. Engineering and manufacturing teams need shared data, shared context and shared decision-making from the start.

Why AI-Ready Product Development Requires Better Data First

Many consumer product manufacturers want AI to help improve speed, quality and decision-making. Yet AI cannot create much value from disconnected CAD files, manual spreadsheets, unstructured requirements or late-stage manufacturing feedback.
AI-ready product development starts with clean, connected lifecycle data. Engineering teams need a single source of truth for product requirements, design changes, simulation results, materials, supplier inputs and manufacturing constraints. Manufacturing teams need visibility before handoff, not after issues appear on the plant floor.
That foundation matters because the biggest product decisions happen early. Choices around materials, form, performance, manufacturability, sustainability and cost influence downstream outcomes long before production starts. When teams lack shared data, they find problems late. When teams work from a connected digital thread, they can spot risks earlier and make better decisions before rework, scrap or launch delays occur.

From Fragmented Workflows to Concurrent Engineering

With the Dassault Systèmes digital product development approach, companies can address a growing reality: innovation depends on more than moving faster — it depends on connecting people, data and decisions across the lifecycle. For consumer goods manufacturers, the 3DEXPERIENCE platform® helps break down silos by creating a collaborative environment where engineering, simulation, manufacturing and business teams work from shared information. This connected approach supports three core priorities increasingly shaping digital transformation: improving collaboration across disciplines, enabling virtual experiences through virtual twins to evaluate products earlier, and creating a unified digital foundation that helps organizations adapt faster to changing customer and market demands.
Concurrent engineering helps product teams work in parallel rather than waiting for sequential handoffs. Mechanical design, simulation, electrical systems, sourcing, manufacturing engineering and sustainability teams can evaluate decisions together. That shift helps companies move from “design, then validate, then fix” to “design, validate and improve continuously.”
For complex consumer products, that approach supports practical business needs. Sporting goods companies can test comfort, durability and performance earlier. Furniture manufacturers can evaluate materials, assembly and packaging trade-offs sooner. Luxury watch teams can manage precision, variants and supplier requirements with more control. Bathroom fixture manufacturers can connect design choices to manufacturability, compliance and lifecycle impact.

Virtual Twins Help Teams Make Better Decisions Earlier

Virtual twins give engineering and manufacturing teams a shared way to test, refine and validate ideas before committing to physical builds. Instead of relying on static 3D models, teams can use living digital models that connect requirements, behavior, constraints and manufacturing context.
Arena offers a strong consumer products example. Dassault Systèmes announced that Arena used 3DEXPERIENCE Works to improve collaboration, productivity and quality. Cloud-based design and simulation capabilities helped Arena cut the prototyping cycle for swimming goggles by 70% while lowering emissions. For a product category where performance, fit, comfort and style all matter, virtual testing gave teams a faster path to better decisions. (Link to Arena news release)
ASICS shows another dimension of digital product development: personalized products and new manufacturing models. Kenichi Harano, Executive Officer and Senior General Manager at ASICS Institute of Sport Science, described how Virtual Twin as a Service helped the company design its personalization studio. His point cuts directly to the value for engineering leaders: “Designing before physical construction can reduce overall cost.” (Link to ASICS story) That insight matters because it shows how ASICS engineers connected digital product development to measurable business impact through lower costs and better planning before construction began. Virtual twins do not simply help teams visualize a concept. They help teams evaluate scenarios, reduce risk and prepare physical operations with greater confidence.

The Benefits of AI-enabled Product Development

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With digital product development on the 3DEXPERIENCE platform, digital continuity replaces fragmented data with shared intelligence. Virtual twins add the power of science-based simulation and prediction to model real-world behavior. Finally, AI capabilities, advanced computational logic and automated traceability ensure consumer products meet global safety standards and performance requirements.

Digital Product Development Aligns Engineering With Manufacturing

Product complexity now spans more than product features. Manufacturers also manage sustainability targets, shorter development cycles, regional market requirements, personalization, sourcing volatility and margin pressure.
A digital product lifecycle for consumer products helps teams align product intent with manufacturing reality. Design data connects to simulation data. Simulation insights connect to manufacturing planning. Manufacturing feedback informs engineering decisions earlier. Teams gain a consistent view of requirements, design maturity, risks and trade-offs.
For manufacturing leaders, that alignment helps reduce late-stage disruptions. For engineering leaders, it gives teams more confidence that product decisions can survive real-world production constraints.

The Value of the 3DEXPERIENCE Platform for Consumer Products Manufacturers

Consumer goods manufacturers can connect people, information and workflows across the product lifecycle with the 3DEXPERIENCE platform. Key benefits for engineering and manufacturing teams include:

• Unified visibility across design, simulation and manufacturing planning
• Virtual twins that help teams test performance and manufacturability earlier
• Concurrent engineering workflows that reduce sequential handoffs
• Connected lifecycle information that can better support future AI initiatives
• Cloud collaboration that helps teams and partners work from shared context

The Time to Prepare for AI Has Arrived

For consumer goods manufacturers exploring AI, preparation starts with improving visibility across product development and manufacturing processes.
So, should engineering and manufacturing leaders treat AI-ready product development as a near-term priority?

Many are beginning to evaluate it more closely. As the Arena and ASICS examples suggest, companies are looking for ways to improve collaboration, reduce delays and make better decisions earlier in development. AI may eventually help accelerate those efforts, but it depends on accessible, structured lifecycle information and fewer disconnects between engineering and manufacturing. Organizations that improve coordination, visibility and workflow efficiency today may be better positioned to take advantage of AI capabilities as they mature through AI-enabled product development for consumer goods.

Manufacturers that move first will not simply layer AI onto disconnected processes. They will build a traceable, platform-based digital thread that connects development, manufacturing alignment and product innovation. That connected foundation gives AI-ready product development the structure needed to deliver meaningful long-term value.

Additional links and Frequently Asked Questions

Faster Consumer Product Innovation with Unified Engineering

The Importance of Virtual Twins in Manufacturing Operations

Frequently Asked Questions