Level Up Your Supply Chain In 2023 With 5 Key Business Strategies

As industries have learned, both consumer and business needs can change in the blink of an eye, and supply chains must also be ready to turn on a dime when demand for goods hits an imbalance. We are already a month into 2023, and economic forecasts indicate a lot of work ahead for enterprises to stay healthy and profitable. To help with the challenges ahead and build on learnings from the past, I’ve outlined five critical strategies for supply chains that are deeply significant for businesses to stay nimble in the year ahead. Have a read, and let me know in the comments how you see things from your perspective.

Nearshoring of Manufacturing to Mitigate Supply Shortages

Last year in this column, I wrote about how the pandemic severely impacted American companies’ offshoring practices over the past few decades.

Offshoring was the preferred, cost-friendly way that American firms performed their manufacturing since the 1980s. Using lower-cost Chinese labor to achieve profitable production helped keep offshoring at the top of the international manufacturing list. But when COVID hit and China shut down manufacturing across multiple regions, the system was severely impacted. As I wrote then, “the engine seized.”

In response, American manufacturers became nervous, and many began to focus on strategies to employ reshoring and near-shoring. Unfortunately, this trend has snowballed and is expected to grow in 2023.

Nearshoring works because it’s about getting closer to your suppliers, manufacturers, and customers. Being strategically located in countries near your partners makes nearshoring a viable option today. Even our current administration is talking about nearshoring with Mexico firms.

I am enthusiastic about the growth of nearshoring. Increased speed in shipping, closer communication with suppliers, and the ability to react swiftly to external supply chain changes are all benefits of this shift. However, it’s time to bring the advances in AI and manufacturing automation together with nearshoring practices to increase our country’s GDP.

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Accelerated Adoption of AI and ML to Fuel Improvement for People and Processes

Adopting artificial intelligence (AI) and machine learning (ML) brings multiple benefits to manufacturers, including improved efficiency, cost savings, and new capabilities. However, the process of adopting these technologies can be complex and multifaceted.

As challenging economic headwinds continue for most businesses, global manufacturers must learn to prioritize digitalization and manage risk better. They can do this by optimizing MRO spend analysis or, as part of their procurement processes, launching a supplier intelligence solution.

This notion applies to various industries, from the aviation industry, to paper products, to automotive. For companies starting to adopt AI and ML, an essential step is to identify specific areas of the manufacturing process that can be improved with these technologies. This may involve analyzing data from existing systems to identify patterns and trends. Companies can seek to implement new sensors and data collection systems or work to clean up existing data for use in training models.

Once the data and resources are in place, manufacturers can begin to train and deploy AI and ML models to effectively improve the targeted areas of the manufacturing process. Once tested and verified, AI/ML models can be integrated.

These new AI/cloud-based technologies can help harmonize data and optimize supply chain network architecture. To facilitate the process, they may be integrated with existing control systems and software or used in developing new interfaces and workflows to support the use of the models.

The success of AI and ML adoption in the manufacturing process may depend partly on adjustments in company culture, employee training, and higher levels of risk and change. But it’s worth it to meet the goals of the digital transformation – significant savings, new capabilities, improved efficiency, and more insights into inventory structures.

Manufacturer-Supplier Collaborations to Improve

An important aspect of this year’s moves into AI and ML is that manufacturers will collaborate easier and better with suppliers than before. Using AI systems can help manufacturers collaborate more effectively with suppliers.

Using AI’s predictive analytics and data evaluation, organizations will find new ways to analyze data on sales, production, and supplier lead times to determine the optimal quantity of materials and products to hold in stock. We call this the ‘Material Truth,’ which is an organization’s ability to manage inventory in order to ‘always have the right part, in the right place, at the right time.’

With so much data moving through enterprise systems, it’s critical for businesses to fully understand inventory amounts, supplier lead times, purchase order history and more from the data. AI technology helps manufacturers to predict demand for products more accurately. This allows them to communicate better with suppliers for a more effective supply chain.

AI communication tools are already in use in many organizations, like AI-enabled chatbots, virtual assistants, and other such tools. These can also help suppliers and manufacturers to communicate effectively, providing real-time information on order status, delivery dates, and other vital data points.

Technology investments to Continue Despite Inflationary Pressures

Despite high-interest rates, inflationary pressures, and an uncertain economy, major manufacturers continue to invest in their AI and technology supply chain practices.

Investments are flowing into technology companies that can help supply chain leaders with AI technologies, predictive analytics, automation equipment, software systems for warehousing, distribution and logistics, and information systems and controls notes Supply Chain Dive.

A prime example in early 2023 is MacroFab’s recent $42 million in new capital for its cloud manufacturing platform for electronics manufacturers.

In fact, almost ⅔ (64%) of the companies surveyed in the most recent Supply Chain Industry report by MHI, the nation's largest material handling, logistics and supply chain association, reported that they were increasing technology investments into their supply chain.

Another report from CapGemini Research Institute shows that nearly 40% of the businesses surveyed plan to boost technology investment to propel their business transformation and to help reduce costs.

As investors look to AI-enabled businesses to lead the charge, we see a bright future for companies to transform their approach to managing their operational risk with working capital by building a more resilient supply network.

Organizations to Seek Ways to Reduce Working Capital as Demand Wanes

As business pressures and inflation continue to escalate in 2023, organizations will likely continue to seek ways to reduce working capital as demand wanes. This could be accomplished by lowering employee headcount and also by implementing a variety of cost-cutting measures.

Some general common ways for companies to decrease working capital may be to:

• Negotiate better payment terms with suppliers
• Manage accounts payable / accounts receivable more tightly.
• Streamline production processes to reduce lead times
• Increase efficiency in inventory management, such as implementing new AI-enabled materials management systems to help get more insights into inventory levels;
• Reduce overall operating costs by cutting expenses and laying off employees

Reducing working capital carries risks in production and delivery schedules, so these decisions should be made carefully.

Organizations can move to find opportunities for removing unused working capital from their balance sheet by implementing strategic materials management. Doing so can help companies reduce costs instead of making employee layoffs. The benefit is that people keep their jobs, the company lowers costs across the organization, and it doesn’t lose good talent. We feel that these are areas that many in the C-suite would prefer to implement in the long term.

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