The most fundamental requirement is that the decision makers have a good understanding of supply chain management itself. The key reason that if you are vague about the basic drivers, elements and operating principles you cannot use techniques as precise as AI for improving supply chain management.
So what are the principle components, driver and elements of supply chains and how can you learn to be precise in their definition and usage?
The base minimum knowledge base that is required includes - the five flows of supply chains, the two key requirements of supply chains and four underlying pillars of supply chain management should be intuitively understood. The best way to get basic understanding of these elements is to read the FAQs and Quick Notes in our website.
At the most basic level people should not confuse supply chain and logistics, or supply chain and procurement.
Once optimisation and integration - the two key requirements of supply chains become paramount goals - people will automatically get out of satisficer mindset and look for AI as the solution for optimisation.
With this understanding comes a willingness to take calculated bets on new technologies and make these bets pay off. And with that comes an ability to expand the winning technology bets and contract those that do not pay off adequately.
Finally, availability of data set, and willingness to collaborate and invest is needed to incorporate the use of AI into supply chain.
The requirements of an organisation to implement AI includes High computing capacity, high data storage capacity, efficient networking infrastructure and security over network and data.