The rise of the breathing supply chain – Another great opportunity for the industrial internet of things
- On May 26, 2016
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Information is the bread and butter of supply chain management.
We always plan in order to source, make, ship or return. Nothing moves unless is planned to do so.
Supply chain planning systems have been around forever helping to optimise a supply network with many distribution centers, factories, suppliers, SKU’s, product lanes, and endless production / location combinations.
This is a non – linear mathematical problem. A very complex one.
Intra-company tools based on the all-time favorite excel files or externally purchased software tools have been developed to define all of the underlying assumptions used as inputs for supply planning systems (lead times, days of inventory, production lines run rates, minimum order quantities, supplier lead times, planning fences and much more).
But we still need to reconcile assumptions with reality.
By design, contemporary planning systems have very limited visibility into the real supply chain performance and they rather plan based on our experience or historical or assumed averages.
Supply chains are being planned on assumed not real performance.
This is a problem creating tremendous complexity in day to day operations resulting in employee productivity loss, miscommunications and higher cost and cash to serve your customers.
The industrial internet of things and the application of computation into physical supply chain processes unlocks the opportunity for supply chain planning systems to finally synchronize with reality.
The ability to install various different sensors in different parts of your supply chain and get real time visibility of the status of each supplier’s material shipment location, each finished good’s production status, each customer shipments real time arrival vs planned one will drive the next level of supply chain performance optimization.
Redesigning the interfaces between the assumed performance masterdata with the real time adjustable “smart” masterdata, will be a monstrous task. A task a human can design but cannot do. We even fail to keep our static masterdata 100% accurate.
This is another use case of the tremendous value that Artificial Intelligence & Machine Learning algorithms will provide for supply chains.
Undertanding when and enabling instant translation of real time data feeds from supply chain assets (trucks, production machines etc etc) into smart and dynamic planning system inputs will finally synchronize plans with reality.
The technology to do this is here and getting better and better. Will it be easy? No. Is super complex. But digital transformation is a long journey.
The real question to ask is what are the real supply chain losses in productivity, cost and cash due to the discrepancy between your supply chain’s assumed vs real performance?
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