Top Tips to Optimize Data and Inventory Management

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Inventory management is a key component of supply chain management that ensures an appropriate quantity of stock is available to meet...

Inventory management is a key component of supply chain management that ensures an appropriate quantity of stock is available to meet customers’ demands. A streamlined inventory management process facilitates business owners to fulfill orders, meet sales goals, and satisfy customer expectations. Failing to manage inventory can affect their bottom line and disrupt their businesses. However, inventory management has become a mammoth task with increasingly complex business operations and fluctuating global market trends. 

Identifying and fixing a small error in inventory management through the traditional approach can be time-consuming and costly. Therefore, organizations are replacing conventional inventory management with the new generation, real-time technology like Inventory software solutions. Managing your supplies and inventories is scalable, transparent, and traceable with such systems. 

This article sheds light on a few top-most tips to optimize data and inventory management. 

The role of IoT (Internet of Things) in inventory management is to convert data collected by RFID readers into meaningful insights. The inventory management system that uses RFID and IoT technology tracks inventory items through RFID tags. Each RFID tag consists of a unique identification number (UID) that holds encoded digital information about the inventory item, such as batch number, quantity, models, size, etc. Once an RFID reader scans the tag, the data on the tag is read and transferred to a cloudinventory managementsolution. It helps to track the exact location of the item, know the delivery status, time of arrival, transit status, etc. All this information is populated in real-time and optimizes the inventory management process. As the cost of IoT is decreasing continuously, it is turning out as a cost-effective solution for companies to manage inventory.

Big data is referred to as extremely large datasets that are processed and analyzed rapidly. It is turning out to be a game-changing technology for managing inventory. It is a priority for every business owner to meet customer demand without overstocking. Big data analytics gives real-time insights into the inventory movement and enables business owners to order products as per the requirements. Besides that, it also helps to predict the product demand in advance. Earlier it was not possible to predict the future demand for inventory, but with the help of big data analytics and artificial intelligence, it is possible to stock inventory by predicting market demand. Data analytics and artificial intelligence provide information about customer behavior, product sale, and performance of the product on various channels. 

AI intelligently segregates customers’ data such as purchase history, demographics, browsing patterns, etc. All these insights are valuable for demand forecasting and stock inventory accordingly. In addition to real-time information about orders, shipments, delays, etc., big data analytics give details about vendor performance and profitability. It enables business owners to strengthen their relationships with vendors. Big data, along with IoT, unlocks the true potential of data analytics and optimizes inventory management.

 Inventory management software helps to store and process all types of data. The centralized storage system ensures data consistency and eliminates errors in managing inventory. Business owners that operate in multiple locations usually deal with fragmented data and find it challenging to manage them manually. With fragmented data, business owners cannot derive meaningful insights necessary to make business-critical decisions. Inventory management software offers a single platform to standardize the data throughout all the locations. The best inventory management software allows business owners to have a 360-degree view of the inventory. Some of the inventories sit on the shelves for ages and result in dead stock. 

Inventory management software keeps track of such inventories and reduces the stock of unsold inventories. Inventory management software facilitates the free flow of inventory and reduces the costs around it. Maintaining accurate master data ensures that all stakeholders have real-time information about the quantities, costing, and location of goods. Besides that, it also supports easy transfers of data to other departments, such as accounting for billing and invoicing.

There are various data science models used for inventory analytics, such as statistical models, non-neural machine learning models, and ML-based models with a deep neural network.  It is essential that business owners select the inventory optimization model that meets business objectives.  Based on this model, business owners collect information necessary for managing inventory efficiently like demand forecasting, inventory cost analysis, inventory lead time, etc.

A key to efficient inventory management is to constantly improve the inventory management process.  As the organization expands its operations, business owners need to ensure that there is minimum complexity in the inventory process.  It is possible when business enterprises strive for continuous improvement of the inventory management process.  Business owners need to identify the gaps in the existing inventory process and take measures to improve the performance.  By continuously monitoring and collecting data on KPIs that business owners can detect errors in the inventory management process. By using business intelligence and data visualization tools, business owners can analyze data on a much granular level.  It enables them to discover the fault line in the inventory management process and fix them promptly so that it improves over time.

For an efficient inventory process, there are many resources that work together – people, equipment, and other assets. If any of these resources are facing issues, it can affect the inventory management process. In order to avoid any unexpected incidents, it is recommended that business owners should have a contingency plan ready. Business owners can use data to identify risks associated with the inventory process and prepare a backup plan accordingly.   

Businesses implementing best inventory management practices are destined to succeed.  It is among one of the core processes of business organizations and an important link in supply chain management. However, business organizations are experiencing a shift in customers, business operations, and technologies due to globalization. It demands the inventory management process to become more agile, responsive, and faster. Implementing an inventory management process that is resilient and efficient while addressing a complex market is a difficult task. It requires detailed insights into consumer behavior, market trends, and risks associated with it. However, by accessing critical data, tools, and following a few tips for inventory optimization, it is possible to make the inventory management process efficient.

This article on inventory management is a guest contribution by Jason Adams.