Supply and Demand Evolution – Logistics -> Chain -> Network
There is a rapid evolution occurring in the management of supply and demand. It started with Logistics with the use of the stubby pencil and lookup tables. Then it evolved to Supply Chain Management with logistics automation and data communications. Now there is an emerging trend toward Supply Network Management. This is a synchronous, agent approach with the use of heuristics, simulations, and analytics to synchronize tactical and strategic real-time decision-making across all stakeholders in the supply network.
Logistics Systems. I started off in the military and I remember that logisticians relied on thick manuals with numerous lookup tables to calculate things like days of supply, consumption rates, and so on. The first Mainframe logistics software applications focused on order management (management-by-exception and order status) and managing warehouse stocking levels.
Supply Chain Systems. With the advent of data communications / Electronic Data Interchange (EDI), servers, and desktop computers, supply chain applications focused on automating all aspects of logistics (warehouse, order management, transportation, and so on), and linking these applications across the supply chain. Additionally, planning tools such as network planning / optimization and inventory optimization became a must-have tool to use on a periodic basis.
Supply Network Systems. Now there is an emerging realization that the supply chain is not just an asynchronous linear system, but also a synchronous system with many stakeholders and factors that are affecting it to varying degrees at different times. To best support a real-time supply network, software applications need to move beyond linear algorithms. A heuristics approach is needed to assist managers at all levels with discovering issues, offering solutions, managing risk, and simulating “what if” scenarios. Example tools include network simulation, expert systems, analytics / business intelligence (BI), data mining, and real-time optimization.
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Supply Chain Optimization versus Simulation - Dan Gilmore - SCDigest
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Tags: AI, BI, Simulation, supply chain