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Machine Learning for Inventory Optimization
Since Machine Learning is Data-Driven, it can be trained to create valuable predictive models that can guide proper decisions and smart actions.
“Back of Store Inventory Optimization”
A Clear Intelligence Case Study
A supplier wants to ensure they have up to the minute inventory data for the back of store to ensure customer always has the optimal amount of inventory.
The Problem: back of store inventory is the buffer to ensure no out of stock on the retailers floor. The supplier wants to ensure that enough inventory is in and react to surges in demand in a real time manner. This will allow the supplier to optimize inventory and ensure customer service is maintained.
The Solution: Implement camera in back of store in combination with leveraging IBM Watson visual recognition assessment to enable them to identify by product current real time inventory levels in back of store and react accordingly by changing the next delivery to optimize inventory. This removes the need for inventorying the product manually and also allows real time reaction so optimizes working capital and reduces losses for products that have limited shelf life. Solution can also be extended to loss prevention / delivery verification.
Implementation of the solution is just the beginning. We remain engaged with your team in a collaborative effort to drive adoption and scale to extract the full value of the solution. With continuous improvement frameworks in place, we will ensure the solution continually evolves and drives increased value as the business changes. This is where the full ROI and competitive disruption is realized and, more importantly, maintained.