From Requirements to Maintenance: Enabling the Digital Thread for Configurable Products

One Digital Thread, From the First Requirement to The Last Service Call

Product complexity rarely starts out looking complex. What begins as a simple product offering can quickly grow into thousands of possible variants, driven by evolving customer requirements, regulatory demands, and business constraints. As products evolve, manufacturers need a better way to understand which decisions drive valid, compliant, and commercially viable product combinations.

In this joint PwC and Configit webinar, we explore how manufacturers can establish a Digital Thread for configurable products by connecting product models, options, dependencies, variants, and lifecycle data into a consistent and traceable framework. At its core is a transparent and controllable solution space, a complete representation of all valid product configurations, that improves visibility, strengthens governance, supports decision-making across engineering, sales, manufacturing, and service, and identifies which lifecycle artifacts apply to a given configuration.

See It in Practice

Using a practical example, we demonstrate how explicit configuration knowledge improves consistency, enables earlier change impact analysis, reduces engineering effort, and accelerates time-to-market. We also show how it enables AI-assisted discovery of decision models, applicability conditions, and lifecycle impacts, while supporting the transition from Engineer-to-Order (ETO) toward scalable Configure-to-Order (CTO) and hybrid CTO+ operating models by making recurring engineering decisions explicit, reusable, and governable.

What you'll learn:

• How to establish a Digital Thread for configurable products.
• How to gain visibility into all valid product configurations.
• How to reduce engineering effort and rework through reusable configuration knowledge.
• How to assess the impact of changes earlier and with confidence.
•How to transition from ETO to scalable CTO while maintaining control of complexity.