ML Journal

As experienced workers exit the industry, manufacturers must embed product and commercial expertise into scalable, digital processes. 

 

TAKEAWAYS:
● The loss of experienced manufacturing talent creates a hidden commercial risk that impacts sales efficiency, accuracy, and growth.
● Manufacturers can reduce dependency on tribal knowledge by embedding product and pricing expertise into standardized digital processes.
● Guided, system-driven selling approaches help both sellers and buyers navigate complexity as workforce demographics continue to shift.   

 

Manufacturers are undergoing a pivotal workforce shift.

By 2030, 1 in 6 people in the world will be aged 60 years or over, according to the World Health Organization. In the U.S. alone, 10,000 people turn 65 each day. As the workforce ages and industry turnover continues, skilled labor and institutional knowledge are lost across technical roles, especially engineering.

While manufacturers have focused heavily on resilient production and supply chains, there’s an equally critical challenge: commercial and delivery processes still rely on the deep expertise of experienced engineering and product teams. As seasoned technical talent, including engineering and product specialists, retire or transition out of the workforce, manufacturers face knowledge gaps that slow product rollout, increase engineering interruptions, and limit the organization’s ability to scale consistently.

Addressing this challenge means codifying technical and product expertise into scalable, digital processes and rethinking how complex products move from design intent to commercial execution without increasing engineering workload. Manufacturers are navigating a major workforce transition at a time when innovation, customer expectations, and market pressures demand greater productivity to remain competitive.

The Workforce Shift Puts Profitability at Risk

Even as labor markets stabilize, manufacturers continue to struggle with workforce challenges. A survey of over 200 global manufacturers found that 30 percent of companies expect 16 percent or more of their sales and engineering talent to retire in the next five years. Only 32 percent are digitizing internal knowledge—the majority are simply rehiring or mentoring. But failing to capture and easily transfer knowledge across the business is a performance risk.

This can have an impact on both sales and engineering teams. A knowledge gap often results in:

• Slower onboarding and longer time to productivity for new hires
• More errors and costly rework in proposed solutions
• Hours lost waiting for technical validation
• Customers disengaging due to slow and inconsistent quoting processes

Lack of knowledge transfer can cost large businesses millions of dollars per year due to wasted time and missed opportunities.

Competitors that can scale and systematize knowledge are better positioned to capture opportunities with more agility. At the same time, buyer expectations are shifting. Today’s customers want conversations focused less on technical minutiae and more on how solutions support their broader business objectives.

Redefining How Manufacturers Sell Complex Products

For manufacturers with vast product portfolios and highly configurable products, sales has traditionally required deep technical expertise and heavy reliance on engineering for every configuration. This model is nearly impossible to sustain in the speed of today’s market.

New hires take longer to ramp up, engineering teams can get bogged down in creating imperfect solutions, and expecting every salesperson to be a technical expert slows the sales cycle.

By redefining how products are sold, manufacturers can shift from a knowledge-dependent model to one that emphasizes solution building. This shift includes:

• Emphasizing consultative skills over technical memorization
• Moving from feature-based selling to solution-oriented conversations
• Equipping sales teams with structured workflows that guide decision-making
• Driving value-based discussions that connect offerings to business outcomes

To make this shift scalable, manufacturers must embed product and pricing expertise directly into their sales processes, allowing teams to focus less on technical validation and more on customer engagement.

Using a Single Source of Truth in Commercial Processes

With traditional sales models heavily reliant on individual expertise, manufacturers must fundamentally rethink how knowledge flows through the organization.

Manufacturers are shifting from expert-dependent translation of engineering specifications to embedding that knowledge in standardized digital processes, like Configure, Price, Quote (CPQ) technology.

This transformation requires restructuring how product information is organized and accessed. A unified product definition helps bridge technical specifications and commercial logic, enabling teams to understand complex offerings without extensive specialized training—while still supporting millions of valid configurations.

For pricing, the challenge is similar. Highly individualized products make pricing difficult, particularly when new variants are introduced. Embedding pricing rules, margin logic, and cost considerations directly into commercial workflows enables more consistent and confident pricing decisions without requiring constant expert intervention.

Creating Standardized Components for Mass Customization at Scale

Engineer-to-order models have long provided flexibility, but at the cost of scalability. Shifting toward a hybrid configure-to-order approach allows manufacturers to standardize common configurations while still accommodating unique customer requirements.

Engineering teams can break complex products into modular components and pre-validated options, allowing sales teams to assemble solutions without relying on engineering for every request. These standardized components can then be easily translated into rule-based logic for sales teams.

A key enabler of this shift is constraint-based configuration logic. Instead of rigid rules that limit flexibility, a constraint-based approach to CPQ defines how components can be combined based on shared properties, allowing new modules to be introduced without increasing complexity or sales risk. This equates for fewer rules to be maintained and updated as the portfolio grows.

The Move from Expert-Dependent Selling to Design-Governed Solution Guidance

Technical expertise will become harder to scale. Manufacturers are shifting from expert-dependent interactions to design-governed solution guidance. Guided workflows facilitate customer-focused conversations without requiring deep technical expertise in every interaction, while still enforcing engineering intent and product constraints.

Rather than relying on detailed technical knowledge or feature memorization, structured workflows guide conversations around application requirements, operating conditions, and performance outcomes. These inputs are translated into valid, manufacturable solutions based on embedded engineering logic.

• Performance requirements
• Operating environment
• Space or regulatory constraints
• Expected throughput or output

This approach not only protects engineering teams from repeated validation requests, but also improves the customer experience by making complex offerings easier to understand, evaluate, and confidently specify.

Buyers Are Losing Expertise Too

A new generation of buyers is entering decision-making committees with mixed technical backgrounds and higher expectations for transparency and guidance.

As customers lose their own internal experts, they increasingly rely on manufacturers to provide clarity earlier in the buying journey, across both traditional and self-service channels. This level of consistency and confidence depends on a single, digitized source of product knowledge that ensures every channel and interaction reflects the same validated information.

Providing intuitive, guided experiences enables buyers to explore options without waiting for human intervention. This ultimately reduces delays and accelerates buyer decision-making.

Scaling Across Products and Markets

Operational transformation takes time, but it pays off. Manufacturers build resilience by standardizing how technical and product knowledge flows from design through order fulfillment. When engineering rules, constraints, and configuration logic are embedded directly into lifecycle processes, rather than living in people’s heads or disconnected documents, organizations launch new products and variants faster, limit ongoing engineering involvement in commercial requests, and expand into new markets without redesigning core offerings. This approach shortens time to market and creates more consistent and scalable execution across operations.

Managing Your Workforce for Change

Transitioning to scalable commercial models requires thoughtful change management. Veteran experts should be positioned as champions whose knowledge is being amplified rather than replaced. Phased rollouts, cross-functional alignment, and clear communication help ensure adoption while preserving innovation and quality.

Become a Future-Ready Organization

When expertise is embedded into systems rather than tied to individuals, you create operations that can scale, adapt, and perform well beyond today’s workforce constraints.  M

 

About the author:

 

Brian Cuttica is Senior Vice President of Sales in North America at Tacton.