As Manufacturing Returns Home – Here Is How AI Can Help Ensure Better Collaboration Between Suppliers

As Chinese manufacturing slows and the war in Ukraine continues, more U.S. companies are shifting their offshore operations back to reshoring or near-shoring activities. Closer, faster, and more streamlined are the big themes for the U.S. manufacturing industry as reshoring and foreign direct investment (FDI) accelerate domestically. According to the Reshoring Initiative, producing in or near the home market benefits companies with higher product quality and consistency, a skilled workforce, better lead times, more manageable inventory levels, and improved responses to ever-changing customer preferences.

CNBC notes that mentions of “reshoring” and “AI” in S&P 500 earnings call transcripts rose exponentially during the past year. The connection becomes clearer in other ways as well. A USB analyst points out that more U.S. companies are making capital expenditures to build new facilities, buy new equipment, and create a more substantial infrastructure that utilizes AI in its operational focus.

With the rise in technological innovations, the industry is seeing a complete rethink in how manufacturers function and collaborate internally and with external suppliers.

Traditionally, manufacturers have relied on Enterprise Resource Planning (ERP) systems for maintenance, repair, and operations (MRO) inventory management. However, they need more advanced analytical capabilities to drive the strategic procurement and operations management required to optimize spare parts and MRO materials.

With a revised agenda, management commitments, new goals, and burgeoning technology capabilities in MRO/inventory management, manufacturers need to step up their game and improve their communications and technology, and AI can certainly help.

AI’s Impact on Collaboration

Managing collaboration issues internally and with suppliers, especially as companies bring production back to the U.S., is not as daunting a task as it may initially seem. Occasional challenges and misunderstandings may arise between suppliers and procurement specialists, but using today’s streamlined AI systems to handle communications flow can help minimize these issues.

In particular, a significant time gap exists between when a product user identifies their needs and when they communicate that information to a supplier before placing an order. Addressing this issue involves having the capability to share real-time updates on changes in demand. This facilitates improved management and awareness of product availability, reduces lead times, and expands networks beyond individual environments.

AI can analyze large amounts of data across the supply chain to identify inefficiencies, delays, or other issues. It can then recommend ways to streamline communication and coordination between teams, departments, and partner companies and significantly impact MRO (Maintenance, Repair, and Operations) strategies.

Manufacturers and suppliers can strategically align themselves through MRO to optimize their supply chains for service, cost-to-serve, capital, and waste reduction. Manufacturers and suppliers can streamline their MRO processes and gain a mutual competitive advantage by building a collaborative relationship based on trust, open communication, and shared goals.

AI to Maximize Supply Chain Optimization

The past year has seen a sudden uptick in the use of AI to maximize better communications between buyers and suppliers for supply chain optimization. The precise reasons for this growth come down to significant benefits manufacturers are starting to realize:

• Cost Savings: Collaborating with indirect material suppliers is helping manufacturers save costs by optimizing the procurement processes. This helps to identify the optimal materials suppliers need to stock. Additionally, procurement costs may decrease through volume discounts, special pricing, or other cost-saving programs.
• Reduced Risk/Downtime: Supplier collaboration can help reduce downtime caused by equipment breakdowns or maintenance issues. With a reliable MRO supplier that can quickly provide spare parts, manufacturers can minimize the time equipment is out of service, helping improve productivity, reduce costs, and meet production deadlines.
• Predictive analytics: Buyers and suppliers can coordinate by using AI tools to analyze past supply chain disruptions and use machine learning to predict where new issues may arise. Companies can strengthen collaborations with predictive analytics before problems or bottlenecks can occur proactively.
• Improved Efficiency / Automated workflows: Using AI with partners can help streamline procurement processes and reduce the time and effort required to order and receive materials. Miscommunications and mistakes that can happen with manual work can be reduced. Smart contracts enabled by AI can also improve supplier relationships.
• Human Collaboration/Knowledge Transfer: AI technology is central to enhancing overall supply chain efficiency through improved information utilization. However, achieving widespread improvements relies heavily on structured knowledge transfer among individuals, particularly the experts operating within the system. As we anticipate a generational shift in the next five to 10 years, with veteran workers retiring, we risk losing the critical understanding of the “why” behind decision-making. Human collaboration and knowledge transfer are essential to preserving and passing on valuable insights.
• Quality Assurance: When buyer-supplier collaboration is high, quality assurance levels are often equally high. The result is high-quality products that meet requirements. Good collaboration means improving overall business performance while avoiding quality issues and reducing the risk of downtime or equipment failures.
• Inventory optimization: AI algorithms and MRO inventory tools can fulfill inventory needs and placements across supply chains. These will ensure that production resources, materials, and products are located where needed.
• Innovation: Using AI with MRO suppliers boosts company innovation. Access to new materials, components, or equipment can improve performance or reduce maintenance requirements. This collaboration means staying updated with the latest industry technologies and innovations.

Through data-driven insights stemming from real-world transactions, AI boosts the performance of buyer-supplier collaboration, as it helps companies simulate different supply chain scenarios and stress-test their networks. Redundancies and flexibility can be built into systems, allowing for better cooperation during disruptions and a massively important benefit as U.S. manufacturing and production move back onshore.

Enable real-time MRO inventory visibility

Most businesses today still rely on disparate and outdated systems, restricting the ability to establish real-time visibility of MRO inventory data. Siloed data and slow, manual systems are not flexible enough to respond to operational and procurement needs, making the system rife with inefficiencies.

To better meet the challenges associated with reshoring, an AI-powered MRO platform can provide a holistic view of the entire supply network, helping ensure optimal collaboration between partners and the fast, accurate, and efficient support domestic manufacturing will require.