Since the topic of artificial intelligence (AI) came to be, humanity has debated the ethics and morals of creating artificial beings that dwarf human intelligence. Despite the debate, researchers continue to plug away, further expanding and applying it to a wide range of industries. In recent years and as the market continues to trend toward information dominance, AI is more and more being applied to Supply Chain Management (SCM).
In our first post on optimizing supply and demand through demand shaping, we expanded upon the traditional definition of demand shaping to mean a process where the optimal demand and supply decisions are made by using all available supply and demand information.
An organization’s ability to align supply and demand is one of the most important measures on profitability. In a perfect world, demand would always meet the supply and supply would always meet the demand. Unfortunately, there are constant fluctuations in the demand and supply dynamics.
Technology has come a very long way in the last 150 years. From the seeds of industrialization in the late 1800s to the assembly-lines of the early 1900s, to robotic technology and computational technology and now to the international computer conferencing and communication via the Internet. Each of these steps have had an end goal of increasing profits by optimizing the manufacturing process (or parts of the process, at least). Today, manufacturing is no different — optimization across the enterprise is arguably the most important goal.