Revitalizing U.S. Manufacturing: The Role of Reshoring and AI

U.S. manufacturing is at yet another inflection point in its growth. The U.S. manufacturing sector grew at an average of 4.9% in the 1990s, but towards the end of the decade, outsourcing and a shift of manufacturing abroad occurred, resulting in less than 1.5% manufacturing growth in the last two decades.

Tides have turned again, as global supply chains are reconfiguring from global to local. Nearly a quarter of global manufacturing trade is estimated to relocate in the current decade, driven by the rise of reshoring, nearshoring, or friendshoring. The best estimates of U.S. manufacturing growth point to a CAGR of 2% to over 3%, which is double to what we have seen recently. A manufacturing renaissance is indeed a paradigm shift. However, U.S. manufacturers must surmount a formidable challenge to unlock this opportunity – which requires labor availability and significant labor productivity improvements.

The Reshoring Opportunity

The manufacturing sector in the U.S. may be on the brink of a major rebound, potentially with significant impacts on the broader economy. Manufacturing contributes $2.3 trillion to the U.S. GDP, employs 13 million people, and sustains numerous local economies. While it only constitutes 11% of GDP and 8% of direct employment, its economic impact is outsized, accounting for 20% of the country’s capital investment, 35% of productivity growth, 60% of exports, and a significant 70% of business research and development spending. (Source: https://fred.stlouisfed.org/)

After two decades of subdued growth, the manufacturing sector finds itself at another inflection point. Supply chain disruptions in the aftermath of the global pandemic and recent geopolitical risks have triggered a shift that could lead to a surge in regionalization within global manufacturing networks as companies look to build shorter, more resilient, and adaptable supply chains that are tailored to the specific needs of different markets. A possible upturn in manufacturing will have a transformative economic impact, adding more than 15% to the GDP and creating more than 1.5 million jobs. (Source: https://www.mckinsey.com/capabilities/operations/our-insights/delivering-the-us-manufacturing-renaissance/) This may all come to fruition, provided manufacturers are able to improve their competitive position by enhancing critical areas such as workforce productivity.

The Workforce Headwinds

Realizing the reshoring opportunity is constrained by several notable challenges: debt, inflation, the cost of energy , and the biggest structural challenge of them all – the manufacturing workforce. Two decades of outsourcing manufacturing operations has created more than a few idiosyncrasies – and gaps - in the U.S. manufacturing talent pool. For the last two decades, U.S. labor productivity has grown at 1.4 percent compared to the historical average of 2.4 percent. At the same time, real wages have slowed, combined with low workforce participation, which has created a genuine talent shortage. (Source: https://fred.stlouisfed.org/)

The illustration above highlights the key manufacturing labor challenges facing the U.S. today:

• The U.S. has a labor shortage
• The most experienced and knowledgeable workforce is retiring this decade
• U.S. productivity is plateauing.

This presents quite a challenge for the U.S. to solve given the 13 million U.S. manufacturing workforce is competing with 200 million Chinese workers alone.

Changing the Anatomy of Work – The Next Productivity Paradigm

Much of the labor productivity gains in the past decades were gained by physical/factory floor automation and computerization and, later, by outsourcing low-value and manual tasks. The plateauing of productivity growth in the last two decades is indicative of the possibility that U.S. manufacturing has reaped productivity dividends by outsourcing every possible low-value job and automating/mechanizing the factory floor and supply chain. It is now time for the next leap in innovation: AI-powered enterprise automation.

AI has the potential to fundamentally alter the anatomy of work, augmenting the capabilities of manufacturing workers by automating many of their individual, repetitive and manual activities. The manufacturing industry embraced Predictive and Perspective AI models within their operations several years ago. With the onset of Generative AI (GenAI), a new class of machine learning has opened new opportunities to accelerate, augment, and automate manufacturing and supply chain operations. According to a recent study by McKinsey, Generative AI alone could enable labor productivity growth of 0.1 to 0.6 percent annually through 2040. Combining Generative AI with all other AI technologies and process automation could add 0.5 to 3.4 percentage points annually to productivity growth. This is precisely the kind of injection the manufacturing sector needs today. (Source: https://www.mckinsey.com/capabilities/operations/our-insights/operations-blog/harnessing-generative-ai-in-manu)facturing-and-supply-chains)

AI in Manufacturing

AI has a breadth of potential use cases in operations, and an application landscape is fast taking shape for what AI-driven manufacturing will look like, with benefits across the plan-make-deliver value stream of any manufacturer.

In planning, AI can consolidate cross-functional insights and qualitative customer analysis to enhance demand forecasts. It can suggest the following best production plans to mitigate supply chain disruptions. It can also provide insights into inventory health or recommendations for optimizing inventory. Improving customer is another frontier where AI can have a transformative impact.

Fig- AI uses cases in Planning and Strategy

On the operations and manufacturing side, AI can unlock untapped productivity during production by utilizing root cause analysis to predict failures, reduce defects, and generate dynamic, easy-to-follow work instructions. It can also enhance operator stations with AI-supported troubleshooting and real-time operating guidance.

Fig- AI uses cases in Manufacturing Operations

In delivery, AI can ensure timely and complete product deliveries by automating document generation, verifying tasks/orders before shipment, and facilitating customer communication through chatbots. Coupled with digital twins, AI can also accelerate the analysis of facility designs and production scenarios.

Fig- AI uses cases in Delivery and supply Chain

Supercharge your AI adoption with Generative AI

Conventional and Generative AI have their values, and operational benefits can multiply when the two are deployed in tandem. The obvious application of Generative AI is to demystify the black-box recommendations of conventional predictive or prescriptive processes, explaining recommendations in easy-to-understand language, thus increasing confidence in AI and thus facilitating change management. GenAI is creating its own application landscape that transcends from shop floor to top floor and plan-make-deliver that can even.
 
Fig- Gen-AI and RPA Use Cases

Emerging areas include project management, from generating executive summaries to conceptualizing and simulating entire projects. GenAI’s inherent capabilities to clarify the emphasis and focus on the salient points of any document have wide-ranging applications, from contract reviews to business process emails. An emerging area of applications includes enhancement of product development - GenAI can transform the traditionally manual and resource-intensive task of product attribute creation into an automated, accurate, and creative process for product advisor co-bots. GenAI can streamline the benchmarking of facilities to orchestrate workforce deployment by creating a highly effective Start of Shift Script. We have barely begun to scratch the surface yet, but the possibilities are endless.

Where to Start with AI: Build vs Buy

Manufacturers keen on seizing this opportunity must have a definitive roadmap for AI implementation. This starts with several questions about the business use case, the availability of data, availability of AI talent in the organization, time to implement and business priorities. These questions usually culminate into a key decision – should manufacturers build  buy a managed service for their AI.

A key factor guiding the build vs buy decision is cost. There are obvious costs, such as AI Platform SaaS Licenses, Strategy & Consulting Fees, MLOps and Model Management but these only represent 25% of the cost of an AI project. Manufacturers must realize that there is an even larger hidden component of building AI projects such as - costs to hire data scientists, data architects, AI engineers, solution managers, etc., ongoing maintenance fees, time spent creating processes and developing the models, and more importantly the requirement to be prepared for a 30-40% employee attrition after the second year.

At Infor we have been partnering with manufacturers with our unique managed service to make AI easily accessible regardless of the manufacturers AI competence. Our comprehensive offering, AIS, is focused on empowering organizations with Predictive, Prescriptive, and Generative AI to drive greater personalization, productivity, and innovation for every user in the manufacturing industry. Our platform-centric approach with our Industry AI, powered by Infor OS platform is the industry cloud platform that sits as the foundation of your enterprise ecosystem below your ERP and Business Applications has a suite of capabilities such as industry AI, data, integration, app development, security and more. We combine these modern technologies thatare pre-configured to our CloudSuite/apps to deliver a suite of solutions to provide a managed service of Augmented Intelligence Solution and Enterprise Automation that is purpose-built to accelerate innovation and intelligence rather than requiring our customers to manage a stack of disjointed technologies and worry about integration.

Reshoring is a golden opportunity for the U.S., stimulated by several exceptional events and factors. However, this opportunity comes with a significant resourcing and productivity challenge. The U.S. has a first-mover advantage in several areas of AI that can be translated into workforce productivity, making American manufacturing globally more competitive and ushering in a new era of growth and prosperity. Don't miss out on this opportunity - click here to unlock the future of manufacturing with AI.