A long-held belief that the supply chain starts with buying has been called into question by the problems in the main supply chain over the past four years. Now, manufacturers aren’t sure if it should really start with the product design and production planning steps. The bill of materials (BOM), production schedule, and key performance indicators for product delivery all help with supply chain planning, especially when it comes to transportation logistics.
Industrial freight needs to be delivered quickly and cheaply to distribution centers, but modern supply lines also have to do several other things. Geopolitical and trade penalties, as well as reporting carbon pollution, have all made things more expensive and difficult. So has omnichannel, time-definite, direct-to-consumer e-commerce. Customers in stores expect deliveries to be on time and complete. Businesses need to know where their shipments are and what their statuses are for both incoming materials and produced goods that are leaving the company. For new product launches, supply chain planning becomes crucial to ensure that getting to market on time and sticking to a detailed strategy are met.
“Shift-left” planning is a new way to think about how supply lines will work in the future. The main idea is that logistics are eventually driven by product design and production planning, and if these three aren’t brought together before shipping or even buying, bad things will happen later that weren’t meant to. This aligns with supply chain planning, where integrating production and logistics early in the process can prevent disruptions and inefficiencies.
Decisions about the size, shape, packing, availability, and areas of suppliers, routes, and product lifecycles for parts and assemblies can all affect logistics. However, sharing information is hard because some data systems don’t work with others, creating obstacles for supply chain planning.
Find out how standardizing common data elements can help connect design, production, and logistics, and how modular digital twin “avatars” can use all of an organization’s data and institutional knowledge in seconds to spot trouble, find market opportunities, and answer complicated questions.
