Improve your supply chain in 2023 with 5 key business strategies


As industries have learned, consumer and business needs can change in the blink of an eye, and supply chains must also be ready to activate when demand for goods reaches an imbalance. We are already a month away in 2023 and economic forecasts indicate that a lot of work remains to be done to keep businesses healthy and profitable. To help address the challenges ahead and learn from the lessons of the past, I’ve outlined five critical supply chain strategies that are critically important for businesses to stay agile in the coming year. Read and let me know in the comments how you see things from your perspective.

Nearshoring of manufacturing to alleviate supply shortages

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

Offshoring had been the preferred and cost-effective way for American companies to do their manufacturing since the 1980s. The use of lower-cost Chinese labor to achieve cost-effective production helped keep offshoring in the lead. of international manufacturing list. But when COVID hit and China shut down manufacturing in several regions, the system was badly hit. As I wrote then, “the engine seized up”.

In response, US manufacturers grew nervous, and many began to focus on relocation and proximity strategies. 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 close to your partners makes nearshoring a viable option today. Even our current administration talks about proximity to Mexican companies.

I’m excited about the growth of nearshoring. Increased shipping speed, closer communication with suppliers, and the ability to react quickly to external changes in the supply chain are all benefits of this change. However, it is time to combine advances in AI and manufacturing automation with proximity practices to increase our country’s GDP.

Accelerated adoption of AI and ML to drive people and process improvement

The adoption of artificial intelligence (AI) and machine learning (ML) offers many benefits to manufacturers, including increased efficiency, cost savings and new features. However, the process of adopting these technologies can be complex and multifaceted.

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

This concept applies to various industries, from the aeronautical industry, to paper products, to the automobile. For companies beginning 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 may seek to implement new sensors and data collection systems or work to cleanse existing data for use in training models.

With the data and resources in place, manufacturers can begin training and deploying AI and ML models to effectively improve 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 can be integrated into existing control systems and software or used in the development of new interfaces and workflows to support the use of models.

The success of adopting AI and ML in the manufacturing process may depend in part on adjustments to corporate culture, employee training, and higher levels of risk and change. But it’s worth it to achieve the goals of digital transformation: significant cost savings, new features, improved efficiency, and more insight into inventory structures.

Manufacturer-supplier collaborations to improve

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

With predictive analytics and AI data evaluation, organizations will find new ways to analyze vendor sales, production, and lead-time data to determine the optimal amount of materials and products to keep in stock. We call this ‘hard truth’, which is an organization’s ability to manage inventory so that it ‘always has the right part, in the right place, at the right time’.

With so much data flowing through business systems, it’s critical for businesses to fully understand inventory amounts, vendor lead times, purchase order history, and much more from the data. AI technology is helping manufacturers forecast product demand more accurately. This allows them to better communicate with suppliers for a more efficient supply chain.

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

Technology investments will 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 tech 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 Note Supply Chain Dive.

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

In fact, nearly ⅔ (64%) of companies surveyed in the latest supply chain industry report from MHI, the largest national material handling, logistics and supply chain association, said that they were increasing their technology investments in their supply chain.

Another report from CapGemini Research Institute shows that nearly 40% of companies surveyed plan to increase their technology investments to propel their business transformation and help reduce costs.

As investors look to AI-enabled companies 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 supply network. more resilient.

Organizations should look for ways to reduce their working capital as demand declines

As business pressures and inflation continue to mount in 2023, organizations will likely continue to look for ways to reduce working capital as demand declines. This could be accomplished by reducing the number of employees and also by implementing various cost cutting measures.

Here are some common general ways for businesses to reduce their working capital:

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

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

Organizations can move to find opportunities to remove idle working capital from their balance sheet by implementing strategic materials management. This can help companies cut costs instead of laying off employees. The benefit is that people keep their jobs, the company reduces costs across the organization, and it doesn’t lose good talent. We believe these are areas that many C-suite members would prefer to implement in the long term.



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