When it comes to inventory optimisation, Artificial Intelligence (AI), also know as Machine Learning (ML) have the potential to create systems which are self-balancing; optimising parameters, as requirements change with the passing of time, to create a system which really does know best.
Many companies, large and small, struggle with the challenges of inventory optimisation and the selection, appropriate setup, configuration and running of Enterprise Resource Planning (ERP) or Sales & Operations Planning (S&OP) systems often has a significant part to play in this. AI may enable the creation of an holistic optimisation, possibly of more than just inventory, based on new big-data approaches. But AI also creates the possibility that such systems may become a more complex and impenetrable ‘black-box'. In with case users may be left at the mercy of the mysterious operations within and unable to challenge outcomes - as the system knows best.
For now, AI is yet to be well-regarded as a stable approach; Gartner’s Hype Cycle report* places it on the ‘peak of inflated expectations’. With that said, Machine Learning is a hot topic and it is being applied to nearly every business problem - no doubt we will see more of what it can offer inventory optimisation in the near future.
For more on the challenges of getting inventory optimisation right, take a look at our recent paper:
If you are interested in learning more about Machine Learning and AI, then check out our introductory guide:
*Gartner Hype Cycle for Supply Chain Planning Technologies, 18th December 2017