Phantom inventory represents products that are deemed in-stock by a management system, but are actually absent from the shelf because they’ve been misplaced or forgotten in a back room, according to the report.
These inaccurate inventory reports can create issues with demand forecasts, raise operating costs and complicate automatic replenishment processes in the supply chain. Phantom inventory also hurts time management, as employees often waste time tracking down lost items, according to the report.
To limit the effect of phantom inventory, organizations can implement a special analytics solution that taps machine learning technology for use alongside existing inventory management methods. An analytics system that relies on machine learning technology can recreate demand patterns for specific products and keep demand inventory uncertainty in mind when creating forecasts and plans, according to the report.
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