Enterprises, particularly manufacturers, are facing difficulties in overseeing inventory effectively since, with globalization, the inventory supply chain has turned out to be substantially more unpredictable. Materials are imported from all over the globe to make the supply meet demand across the enterprises. Due to this, making use of inventory analytics to enhance production networks is becoming more critical in the present worldwide market. Stock enhancement is in need of great importance, to supply with the uncertainty of how to circulate the right stock, in the right quantity, to the right place, and at the perfect time.
Predictive analytics for inventory management can avoid pitfalls and can succeed in demanding marketplaces. Previously, excel spreadsheet was used, to identify the needs of customers and merchants and when the time there could be an increase in the demands. But these assumptions did not meet the needs and expectations as demands fluctuated. Using advanced predictive analytics in the operations can give the accurate results of customer needs, thereby minimizing unnecessary inventory and reducing working capital requirements. Predictive analytics in inventory management can readily determine optimal purchase levels to support the production facilities, and help in undertaking preventive measures for reducing supply disruption. This can generate route optimization and efficient transportation using GPS-enabled big data telematics.
The best method to follow for Inventory management is the ABC method. Group A includes bestselling products that need highest inventory control as this brings high profits. Group B consists of the products that are not sold rapidly. Finally, group C occupies less percentage of inventories, and they account for least benefits. Manufacturers and retailers are always prone to shrinkage when all the stock is not sold out as expected due to breakage during shipment and customers who steal products in the stores. The reasons behind shrinkage are not always similar to every manufacturer or retailer.
Successful management of inventory is a crucial factor in the financial success of every manufacturer. It’s important to customize the outcomes of tools as much as possible by using predictive data analytics for inventory management purposes. Retail analytics is growing its importance and is evident than before due to the rapid expansion of the database, statistical, analytical, and decision modeling solutions. Advanced analytical tools are guarded by complex algorithms that offer improved insights on optimizing inventory.