Inventory management is a key focal area for enterprises of industries like manufacturing, retail, food & beverage, pharmaceutical and electronics. Effective inventory optimization practices lead to improved customer experience, greater profits and reduced productivity losses. Thanks to the emerging analytics technologies, that offer us assistance in managing inventory in ways that were not possible in previous eras.
Predictive analytics helps organizations make predictions about future events through techniques like data mining, modeling, statistics, artificial intelligence and machine learning. If organizations leverage predictive analytics for inventory management, they can avoid pitfalls and attain a competitive edge in this demanding marketplaces.
Let’s discuss how predictive analytics is helping businesses in inventory management in its entire lifecycle – starting from procuring raw material from suppliers, manufacturing products at the manufacturing facilities, moving the products via distributors and retailers to ultimately delivering the product to the end customers.
Forecasting appropriate stock levels
Gone are the days when companies were using tools like Excel sheets to figure out what their suppliers and customers will require in the future and when demand might surge or fall. Today, predictive analytics helps organizations predict customer needs, thereby enabling them to maintain the appropriate stock levels, reducing unnecessary inventory and operating more efficiently during high demand periods.
Keeping the right products at hand
Manufacturers and suppliers need to keep their products handy to meet urgent requirements. Companies those who offer after-sales service/support must determine which products are most necessary for handling customers’ requests. Predictive analytics does this all for you cutting down the probability of storing access products or not enough.
If you are in the manufacturing or retail industry, then it is obvious that you would deal with inventory shrinkage, which happens when all expected inventory doesn’t exist due to issues like theft, breakage during transportation or miscounting . Predictive analytics makes shrinkage less problematic by detecting risk factors you may not notice at all before they happen.
Highlighting bestselling products
In your inventory, there are products that are more popular than others and bring you more profits. Predictive analytics aids in highlighting the best-selling products and those that need the tightest inventory control. You don’t always have the knowledge about your best-selling and poorest-selling products; such powerful insights help you take effective business decisions.
Predictive analytics drives the practice of upselling. Nowadays, companies like Amazon are offering suggestions to customers encouraging them to buy products they will probably like to buy. Such suggestions attract customers to buy products related to their previous purchases. Apart from boosting sales and providing customers a better purchasing experience, such use of predictive analytics enables manufacturers and retailers to manage their inventory in well-informed ways without guesswork.
Predictive analytics enables Inventory optimization driven by powerful insights. The better you explore your data, the better you can manage your inventory.