fusion_global=”1097″]span style=”font-weight: 400;”>Although several factors, such as the pandemic, labor shortages in trucking and other industries, and raw material availability, have contributed to supply chain disruptions, the little-known secret is that supply chain and logistics systems have simply not been up to the task of dealing with these anomalies.
Despite the fact that there are some variables over which you have no control as a corporation (labor shortages, worldwide pandemics, and raw material and part availability), you must develop products that people want to buy. More than fixing external situations that you can’t control, this is about knowledge and intelligence. If you look at the firms that will still be able to deliver on time in 2021 and today, you’ll find that they all use the same set of principles, such as the ability to work around obstacles with highly intelligent automation. They’re using actual intelligence, not just data, to solve problems in the supply chain. While they won’t be able to solve all of them, they’ll be able to remove many of the roadblocks we have today in transporting products.
In many cases, for example, some parts are not accessible to finish the manufacture of a product. However, there is enough past data to estimate where the part may be found by other vendors and the possibility of availability and on-time delivery in real time. Some businesses store components ahead of expected shortages predicted by AI systems before they are noticed by other businesses, or they can even automate reengineering portions of the completed product so that alternative parts may be swapped without causing a quality problem. In certain circumstances, these systems end up obtaining superior parts that may cost a little more but result in the availability of millions of dollars in products. What’s noteworthy about this technique is that it doesn’t require C-suite executives to do all-nighters in order to come up with these novel ideas. It’s completely automated, based on massive quantities of data and machine learning, and it’s embedded directly into business operations, so the correction happens seconds after the supply chain issue is discovered. These features of intelligent supply chain automation aren’t brand new. For years, there has been much discussion about how to more efficiently automate supply chains. Those of you who work in supply chains are all too aware of this.
How many businesses are ready to put their money into the creativity — and even the danger — of implementing these new systems? The majority aren’t, and they’re witnessing the drawbacks of the markets throwing curveballs at them, which they try to deal with using old methods. By distinguishing themselves with these sophisticated cloud-based tools, organizations who were before in 10th position in a market are now in second or third place. Some of this may be altered by the growth of industrial clouds. These sorts of services will be adopted and provided by public cloud providers in no time. Those who want to take advantage of this benefit will simply use the services provided by public cloud providers rather than building their own.