Here are four predictions for supply chains in 2022 and beyond

1. By 2026, 75% of companies will have deployed some form of intralogistics robot in their warehouse operations. Due to the increasing labor costs and the residual effects of COVID-19, many companies will be investing in cyber-physical systems to improve their operations. These include smart robots that can be used in warehouses and distribution facilities. The need for more automation in order to supplement the human workforce is addressed by the use of robots. They are more cost effective than traditional methods, such as manually assembling and sorting equipment. 
2. By 2026, more than 71% of commercial supply chain management software vendors will deliver advanced analytics and data science. AI and AA are becoming more prevalent in the supply chain, which is driving the need for more effective decision-making. This is why many companies are responding to this by developing new applications. Due to the increasing number of applications that are embedded with AI and AA capabilities, many companies are now offering these capabilities in their own applications. While the large supply chain suites and vendors have an advantage over their smaller competitors, the smaller players are catching up.
3.  Through 2025, 25% of supply chain decisions will be made across intelligent edge ecosystems. The concept of edge ecosystems refers to physical locations where people, devices, and data connections. These ecosystems allow companies to make informed decisions by taking advantage of the data collected by various sensors and machines.
4. The ability to connect and interact with devices and applications using edge ecosystems enables companies to make informed decisions. These ecosystems can also complement traditional supply chain management solutions. The rise of 5G and Wi-Fi will allow them to support more sophisticated applications. In many supply chains, the emergence and evolution of edge computing are already happening. The next three years will see an increasing number of use cases where autonomous, connected, and automated networks can be used.