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. 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 […]
