NEWS
Manufacturers know how to build for consistency, scale, and efficiency. The problem is that customization does not behave like standard production, according to Daniel Joseph Barry, Vice President of Product Marketing at Configit.
During a recent fireside chat, Barry explained that both B2B and B2C customers now expect products to match specific technical and commercial requirements. However, many manufacturers are still trying to meet that demand with systems built for a narrower range of choices.
In many companies, engineering, sales, operations, service, and supply chains do not work from the same product definition. Each team may have a workable view of the product inside its own system, but customization cuts across all of them. What looks manageable inside one function becomes hard to control across the lifecycle.
Two responses are common. One is engineer-to-order. For complex, high-value work, it can be the right model. But it uses engineering time, slows commercial response, and can erode margins when assumptions change after the quote.
The other is to keep adding product variants. That can look more scalable at first, but it often pushes complexity into the portfolio instead of reducing it. Over time, small differences accumulate. Teams end up supporting large numbers of similar options, along with the inventory, documentation, and maintenance burden that follows.
A configuration includes features, rules, dependencies, commercial conditions, production constraints, and service implications.
That is why fragmented configuration data causes so much trouble. Each function sees a symptom.
Sales sees quoting friction. Engineering sees governance problems. Operations sees build misalignment. Service sees the downstream consequences when it is unclear what was actually delivered, which parts are compatible, or how the asset changed over time.
That gap shows up in quoting mistakes, delays, rework, extra engineering effort, inventory risk, and service inefficiency. In many businesses, experienced employees keep those problems from becoming visible. They know where the systems disagree and how to patch the gaps manually.
That effort keeps orders moving, but it also hides how fragile the process has become.
A Configuration Lifecycle Management approach builds a shared product model that connects product data, business rules, and configuration logic across engineering, sales, manufacturing, and service. With that structure in place, the business has a clearer view of what can be sold, what can be built, what can be delivered, and what can be supported.
That changes the economics of customization. Sales can guide customers toward valid choices without relying on manual escalation. Engineering has more control over what enters the market. Manufacturing has a cleaner link between the order and the build. Service has a more reliable record of the as-delivered configuration instead of having to reconstruct it later.
Better software helps, but it does not solve broken configuration logic on its own. In an Industry 4.0 environment, digital threads, connected systems, and AI tools depend on reliable underlying data. Without that foundation, automation spreads confusion faster. With it, automation becomes useful.
The market is not moving toward simplicity. Product portfolios are shifting, supply chains are volatile, and customers still expect personalization without higher prices or longer lead times.
Manufacturers do not need to eliminate complexity. In many cases, complexity is part of the value they sell. They do need more control over it.
The companies that build that control will be in a stronger position than the ones still relying on disconnected fixes and manual workarounds.
Ready to learn more? Watch the full webinar, Mastering the Complexity of Customization and Personalization.
NEWS
