For a VP of Supply Chain, the request from a C-level to implement a new ‘same day’ delivery service is no easy task. There are many constraints to consider. Perhaps they need to offer a 2 hour delivery window. What would the costs be associated with delayed deliveries? Can they offer their end-customer visibility of their delivery from start to finish? So what's the fastest way for them to confidently produce a validated proposal?
There are two highly useful innovative tools that can help; a ‘digital twin’ and a ‘real-time visibility’ platform, and the combination of using both is a game-changer.
A VP of Supply Chain needs access to the right set of data analysis tools, tailored for the complex nature of supply chain execution. These days, a spreadsheet can be fairly limiting when evaluating complex problems. You need the ability to model a supply chain in a very quick and flexible way, which provides you with the full ‘context’ surrounding the decision by leveraging real world supply chain data. Using some very sophisticated software powered by AI and machine learning, it’s now possible to create a virtual ‘digital twin’ of your supply chain and use it to precisely measure the impact of any changes in a simulated environment. You can simply overlay your supply chain on a map interface and move each element (distribution centers, warehouses, retail stores, etc) around and observe the projected impact.
Michigan-based software company Llamasoft offers such a tool. Playing around in this ‘sandbox’ environment allows decision makers to simulate potential solutions to many common supply chain challenges, such as evaluating fleet transportation options or repositioning inventory amongst distribution centers, while taking into account costs, tax & duties, flows, capacities and sustainability. When you have a digital twin, you can carry out this analysis quickly and produce useful data for making decisions.
When the ‘digital twin’ is powered by real-time supply chain data, the life-size simulations you carry out are more accurate. By accessing real-time data, you can see the precise status and location of all supply chain elements and better anticipate and act on problems before they cause knock-on effects further down the line. You can determine things like how many orders are arriving too early compared to those that are running late, which can help you make on-the-fly decisions such as how loading sites could be better utilized, minimizing delays and disruption.