How a Digital Twin Leads to Better Supply Chain Decisions
Supply chain organizations are still in the early stages of making the most of advances in digital supply chain technology, including the use of a digital twin. In many ways, you could argue that businesses are mostly using the astonishing capabilities of computing and internet connectivity to do what they did before – just faster and cheaper. With a more connected world, there is an increased amount of supply chain data available. This increase in data is incredible but can be daunting. That’s why smart companies focus not just on gathering data, and figuring out how to filter and analyze it, but how to use it to make better, faster, more informed decisions with a digital twin. Since data management is not usually the core business of companies engaged in manufacturing and/or selling goods, most need to rely on a trusted technology partner to help them make the most of this brave new world.
Artificial intelligence and machine learning can handle more parameters than most are aware. Typically, there’s more than one “right” answer, and the software helps get the best answer for the current strategy. With this artificial intelligence, companies can then employ a digital twin that will assist in analyzing different scenarios. With these scenarios available, companies can explore the impact of changes with little effort and no cost.
Accurate, up-to-date data is vital to achieving these advanced insights. This affects how long it takes to identify something that happened in the supply chain that needs to be addressed – or something that is likely to happen. With readily available insights companies can then use AI, machine learning and advanced analytics to solve problems.
With this increase of information and artificial intelligence, a refined plan is no longer a nice-to-have, but a necessity. Companies are no longer limited to monthly, weekly or daily reports, they can refine their strategy through the entire process, up until the product is headed to the customer.