A new perspective on manufacturing workforce challenges

Headcount versus knowledge

Many workforce conversations still focus on headcount. While that remains important, knowledge is increasingly the larger risk to consider.

Experienced employees are retiring, taking decades of operational expertise with them. At the same time, many organizations struggle to build sufficient pipelines of skilled workers to replace that expertise.

“Manufacturers are facing a combination of an aging population, a less-skilled population, a lack of apprenticeships and other structural labor challenges,” said Grant Thornton Transformation Advisory Director Sanjiv Raman. The combination creates risks that extend beyond recruitment. Every departure can slow onboarding, increase training costs and create inconsistencies in production performance. Institutional knowledge that once existed in the minds of experienced operators can be difficult to replace.

That’s part of why workforce issues have expanded beyond staffing concerns to threaten business continuity. The best approach to this expanded issue might not be to replace labor, but to extend knowledge with technology.

Tech-driven strategies can expand

Many manufacturers have spent years pursuing automation strategies in robotics, and today’s technologies can expand the capabilities driving these strategies.

“On the plant floor, you might be able to move beyond old chiefdom knowledge if a digital coworker can dynamically tell workers how to do something, when to do it or what's wrong,” said Grant Thornton Manufacturing Industry Head Kelly Schindler.

Schindler explained that the goal is to reduce dependence on knowledge that is locked inside a handful of individuals. “Some companies are using cameras and computer vision technologies to observe how experienced employees perform critical tasks on the shop floor,” she said.

These systems can capture and document workflows step by step, helping organizations document processes more accurately and consistently while reducing the risk of knowledge loss when employees retire or change roles. The documented processes create centralized knowledge repositories that are searchable for reference, process improvement and training. “It creates a digital record of activities that have traditionally relied on tribal knowledge,” Schindler said.

The result is a workforce that captures institutional knowledge in a way that it can retain, share and scale. That has implications beyond the shop floor, as new technologies can support both production workers and back-office employees.

The larger operating model

Many manufacturers need to refresh workforce strategies with a reevaluation of how work is organized throughout the business.

“Leaders are looking at the spans and layers of roles, with the impact of AI, and redesigning the organization,” Raman said. “How are you thinking about the jobs to be done with AI tools, and how does that shape the organization and its governing structure?”

As AI evolves from being a software application to playing a more of an interactive role in business processes, it can have implications for organizational design, as well as for skill architectures and the balance of employees and technology.

Ranzau described this shift as AI taking “a functional place within the operating model,” helping accelerate or automate activities. Many leading companies are thinking about where AI can amplify human capabilities to increase output and value rather than just to streamline existing tasks.

AI-powered digital co-workers can observe operations, monitor equipment, answer questions and execute routine tasks, helping companies extend the reach of their workforce and generate new capacity without being constrained by physical staffing levels. These digital employees can be supervised remotely, enabling experienced personnel to oversee activities across multiple facilities, amplify their expertise and focus more of their time on higher-value decisions, innovation and continuous improvement.

In the back office, companies can use finance technologies with AI and automation to offer earned wage access or daily pay options that were traditionally too difficult for payroll teams to support. Automated payroll calculations, compliance checks and payment processing let employees access earned wages more readily. This can be an important tool for competitive worker recruitment and retention, while helping workers better manage their financial needs.

When organizations apply AI capabilities effectively, they can improve productivity, onboarding, retention, institutional knowledge and scalability, proactively moving ahead of ongoing workforce limitations.

Solve shortages with growth

Many leaders traditionally approach workforce investments with the lens of ROI. They want clear payback periods and measurable cost savings.

Those measures still matter. However, workforce technologies increasingly create value through resilience, knowledge retention, risk reduction, quality improvement and operational consistency. These solutions can deliver their greatest value in periods of disruption, providing a level of stability that enables delivery that competitors cannot match.

However, they can also help deliver growth. That is why workforce strategies need a new perspective beyond a cost-savings initiative or technology purchase. Manufacturers need to consider the ongoing problem they are trying to solve. The industry's workforce challenges continue, and companies still need to find a way to balance staffing, skills, production quality and operational efficiency.

However, the tools have changed. Leaders can rethink how knowledge is captured, how work is performed and how people and technology collaborate to meet the organization’s goals. To overcome ongoing workforce challenges, a new strategic perspective could be the most valuable tool of all.