As the industry knows, both consumer and business demands can change in the blink of an eye, and supply chains must be prepared to kick in when there is an imbalance in demand for commodities. We’re a month into 2023, and economic forecasts suggest businesses have a lot of work to do to stay healthy and profitable. To help meet future challenges and draw on the lessons of the past, I outline five key strategies for supply chains that have profound implications for businesses to remain agile in the year ahead. Give it a read and let me know in the comments how you see things from your perspective.
Manufacturing nearshoring to ease supply shortages
In this column last year, I wrote about how pandemics have severely affected the offshore operations of US companies over the past few decades.
Since the 1980s, offshoring has been the preferred and cost-friendly way for US companies to conduct manufacturing. The use of lower-cost Chinese labor for profitable production has helped keep offshoring at the top of the international manufacturing list. However, when COVID hit and China shut down manufacturing in several regions, the system was severely impacted. As I wrote at the time, “the engine stuck.”
In response, U.S. manufacturers have grown nervous, with many focusing on strategies such as reshoring and nearshoring. Unfortunately, this trend has snowballed and is expected to grow in 2023.
Nearshoring works because it brings you 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 is talking about nearshoring with Mexican companies.
I am passionate about the development of nearshoring. Increased shipping speeds, closer communication with suppliers and the ability to react quickly to external supply chain changes are all benefits of this shift. However, it is time to combine advances in artificial intelligence and manufacturing automation with nearshoring practices to increase our nation’s GDP.
Accelerate adoption of AI and ML to drive improvements in people and processes
Adoption of artificial intelligence (AI) and machine learning (ML) can provide manufacturers with multiple benefits, including increased efficiency, cost savings, and new capabilities. However, the process of adopting these technologies can be complex and multifaceted.
As economic headwinds that are challenging for most businesses persist, global manufacturers must learn to prioritize digitalization and better manage risk. They can do this by optimizing MRO spend analysis or enabling supplier intelligence solutions in the procurement process.
The concept is applicable across industries, from aviation to paper products to automotive. An important step for companies beginning to adopt AI and ML is to identify specific areas in the manufacturing process that could be improved by 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 clean existing data for use in training models.
Once the data and resources are in place, manufacturers can begin training and deploying AI and ML models to effectively improve targeted areas of the manufacturing process. Once tested and validated, AI/ML models can be integrated.
These new AI/cloud-based technologies can help harmonize data and optimize supply chain network architectures. To facilitate this process, they can be integrated with existing control systems and software, or used to develop new interfaces and workflows to support the use of the model.
The success of adopting AI and ML in manufacturing may depend in part on adjustments to company culture, employee training, and higher levels of risk and change. But it’s worth it for the goals of digital transformation—significant savings, new features, improved efficiency, and more insight into inventory structure.
Manufacturers collaborate with suppliers to improve
An important aspect of this year’s shift to AI and ML is that manufacturers will be able to work with suppliers easier and better than ever before. Using artificial intelligence systems can help manufacturers collaborate more effectively with suppliers.
Using AI for predictive analytics and data evaluation, organizations will find new ways to analyze data about sales, production, and supplier lead times to determine the optimal quantities of materials and products to stock. We call this “material truth,” which is the ability of an organization to manage its inventory so that it “always has the right part in the right place at the right time.”
With so much data flowing through enterprise systems, it’s critical for businesses to fully understand inventory levels, supplier lead times, purchase order histories, and more from the data. Artificial intelligence technology helps manufacturers more accurately predict product demand. This enables 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 such tools. These can also help suppliers and manufacturers communicate effectively, providing real-time information on order status, delivery dates and other important data points.
Tech investment 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.
Investment is flowing into technology companies that can help supply chain leaders with artificial intelligence technology, predictive analytics, automation equipment, warehousing, distribution and logistics software systems, and information systems and control instructions Supply Chain Dive.
A prime example of early 2023 is MacroFab’s recent $42 million in new funding 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 materials handling, logistics and supply chain association in the US, said they were increasing technology investments in their supply chains.
Another report from the CapGemini Research Institute shows that nearly 40 percent of companies surveyed plan to increase technology investments to drive business transformation and help reduce costs.
As investors look to AI-enabled businesses to lead the way, we see bright prospects for companies to transform the way they use working capital to manage operational risk by building more resilient supply networks.
Organizations seek ways to reduce working capital as demand weakens
As business pressures and inflation continue to escalate in 2023, organizations will likely continue to seek ways to reduce working capital as demand weakens. This can be achieved by reducing headcount as well as implementing various cost-cutting measures.
Some general common ways companies can reduce their working capital may be:
- Negotiate better payment terms with suppliers
- Tighter management of accounts payable/receivable.
- Simplify production processes to shorten lead times
- Improving inventory management efficiencies, such as implementing a new AI-enabled materials management system to help provide greater insight into inventory levels;
- Reduce overall operating costs through spending cuts and layoffs
Reducing working capital poses risks to production and delivery schedules, so these decisions should be made carefully.
Organizations can identify opportunities to move unused working capital off the balance sheet by implementing strategic materials management. Doing so can help the company reduce costs, rather than lay off workers. The benefit is that people keep their jobs, the company reduces costs across the organization, and it doesn’t lose great talent. We believe that these are areas that many top management would like to implement in the long run.