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"The Secret Behind Warehouse Operations: Businesses Are Losing Money Because They Haven't Managed Their Inventory Digitally!"

December 15, 2025 by
"The Secret Behind Warehouse Operations: Businesses Are Losing Money Because They Haven't Managed Their Inventory Digitally!"
Nguyễn Văn Minh
1. The Concept of Digital Inventory Management
​Digital inventory management (Digital Warehouse Management) is understood as the process of applying digital technologies such as Enterprise Resource Planning (ERP), the Internet of Things (IoT), barcodes, QR codes, automated sensors, and artificial intelligence algorithms to standardize and automate inventory management operations.
​This model includes a comprehensive set of digitized processes, from receiving incoming goods, allocating and organizing storage locations in the warehouse, monitoring inventory in real time, coordinating manufacturer activities, to tracing origin by batch, serial number, or expiration date. In addition, the system integrates an automatic alert mechanism against unexpected situations, such as exceeding inventory limits, missing synchronization units, or low goods transfer rates.

​From an operational perspective, digital inventory management creates a highly accurate and transparent data environment, significantly reducing reliance on manual processes that are prone to errors. As a result, businesses can enhance the reliability of existing data, improve forecasting capabilities, and optimize decisions related to supply, production, and distribution.

2. Why should businesses switch to digital inventory management?

​Transitioning to digital warehouse management is no longer an option but a strategic requirement for any business wishing to maintain competitiveness and sustainability in the Industry 4.0 era. The rationale for this transition is built on the principle of supply chain optimization, specifically waste elimination (Muda), enhanced transparency, and improved data quality. 

  •  Increased data accuracy and reduced operational errors: 

​The main benefit of a digital warehouse management system is its ability to enhance data integrity. In traditional management models, errors arising from manual identification, document errors, and discrepancies between book data and actual inventory (inventory discrepancies) are unavoidable. The shift to automated identification and data collection (AIDC) technologies such as 2D barcodes/QR codes and Radio Frequency Identification (RFID) completely replaces this process. Quantitatively, industry studies indicate that the application of AIDC in conjunction with Warehouse Management Systems (WMS) can reduce inventory errors by 50% to 80%, including inventory losses and picking errors. For example, a report from GS1 Global showed that companies implementing standardized product data encoding achieved inventory accuracy of up to 99.8%, a figure unattainable with manual methods. This accuracy eliminates hidden costs arising from handling returned orders, unwanted periodic inventory checks due to data discrepancies, and losses from lost goods. 

  • Optimized operational performance and processing time savings: 

​Time efficiency is a direct consequence of process digitization. By utilizing smart mobile devices capable of scanning, inventory management, receiving/delivering goods, and sorting are performed instantly without complex paperwork or manual data entry. Following the principles of Lean Management, eliminating unnecessary waiting times and paper-based processes minimizes waste. Empirical data shows that inventory management and receiving operations can be 3 to 5 times faster, equivalent to saving 30% to 60% of time compared to traditional methods. This not only enhances labor productivity but also significantly shortens order fulfillment cycle times, a crucial factor in maintaining competitiveness in terms of speed to market. 

  • Data-driven decision-making platform: 

​Digital systems provide the ability to manage goods based on detailed parameters such as lot numbers, serial numbers, and especially expiration dates. This allows businesses to adopt advanced inventory management strategies such as FEFO (First-In, First-Out) instead of relying solely on the FIFO (First-In, First-Out) principle. Data is updated in real time on available inventory levels, precise warehouse location, and quality status. This creates a comprehensive view of the warehouse, helping relevant departments – especially supply and production – shift from reactive to proactive management. For example, tracking expiration dates allows the system to automatically alert to implement timely liquidation strategies, thus minimizing the risk of having to liquidate or destroy goods (obsolescence costs). This detailed traceability also meets stringent legal and quality requirements in many industries. 

  • Enhanced Customer Responsiveness and Service Quality: 

​The transparency of digitized inventory data is key to improving customer service levels (CSL). Today's customers demand accurate information about supply availability and delivery times. When businesses know exactly "how much inventory they have," "where the goods are located," and "when they can be restocked," they can reliably commit to Availability-to-Promise (ATP). This directly speeds up service and reduces customer wait times. In a study on the correlation between customer service and inventory management, companies using WMS systems improved their average Order Fulfillment Rate by 98%, thereby strengthening customer loyalty and increasing customer lifetime value. 

  • Optimizing Cash Flow and Working Capital 

​Financially, digital inventory management directly impacts the Cash Conversion Cycle (CCC). Inventory is a key component of cash flow. Working capital is crucial, and inefficient management can "trap" this valuable resource. Digitalization helps minimize dead stock and slow-moving inventory through forecasting algorithms and quantitative control. By ensuring that orders are placed only at the right time (Just-in-Time principles), businesses reduce holding costs (H$) and insurance costs. Simultaneously, inventory turnover is improved, freeing up capital for reinvestment. This inventory optimization not only cuts costs but also strengthens the balance sheet, facilitating future investment and expansion.

3. Implementation Roadmap: Five Steps to Digital Transformation in Inventory Management
​The digital transformation process in inventory management does not occur randomly but follows a structured roadmap. The five steps below are considered a common implementation model in research and practical literature on digital supply chain management.
Step 1: Standardizing Original Data
​Standardizing the foundational data is considered a prerequisite for any digital inventory management system. This data includes product codes, units of measurement, product classifications, supplier lists, and business rules related to import, export, and storage.
​Standardization not only ensures consistency and synchronization between subsystems but also acts as a "common dictionary" for the entire operational chain. Many studies emphasize that the quality of original data directly impacts inventory accuracy, forecasting efficiency, and future system scalability.
​Therefore, standardized data is considered the fundamental foundation for the formation of a smart warehouse.
Step 2: Digitizing Warehouse Processes
​Digitizing processes is the stage of transferring traditional warehouse management activities from paper-based operations and paperwork to a digital management system. Core processes include: receiving goods (Inbound), shipping goods (Outbound), internal warehouse transfers, periodic inventory checks, and updating warehouse layout diagrams.
​Each task is recorded in real time, helping to minimize losses, reduce discrepancies, and create a seamless data chain. Digitizing processes is also a prerequisite for advanced technologies such as IoT, AI, and data analytics to operate effectively.
Step 3: Applying Recognition and IoT Technology
​In this stage, businesses integrate recognition devices and technologies to increase automation and reduce reliance on manual operations. Examples: Barcodes and QR codes for products; RFID for bulk goods or those requiring continuous tracking; Electronic scales directly connected to the system; AI-powered cameras for error detection; Environmental sensors (temperature, humidity) for cold storage
​Applications depend on the specific industry and organizational scale. However, the general trend shows that the higher the level of automation, the better the warehouse efficiency and data quality.
Step 4: Building a dashboard and intelligent alert system
​The dashboard acts as the central data analysis system, allowing for real-time monitoring of inventory indicators, turnover rate, expiration dates, and inventory value. The value of the dashboard lies not only in its visual aggregation capabilities but also in its support for data-driven decision-making.
​Along with the dashboard, the intelligent alert system based on established rules helps detect risks early, such as overstocking, sudden shortages, or goods nearing their expiration date. This contributes to improved coordination efficiency and minimizes financial losses.
Step 5: Training and Maintaining Digital Operations
​Although technology is crucial, the sustainability of the system largely depends on human factors and operational discipline. Businesses need to implement user training, establish mandatory procedures, build a system for evaluating warehouse KPIs, and conduct periodic inspections.

​From a research perspective, many digital transformation models fail due to a lack of organizational consensus and a lack of technological competence among personnel. Therefore, this stage plays a vital role in ensuring the connection between technology and people, aiming for stable and continuous operation.

4. Popular Digital Inventory Management Models in Businesses
​In the context of digital transformation of the supply chain, many inventory management models have been developed to meet the specific requirements of each industry. Below are four typical models, widely recognized in research and practical implementation in manufacturing and trading businesses.
4.1. Location-Based Management Model
​This model is based on the principle of assigning a unique identifier to each storage location in the warehouse (shelf, compartment, area). The management process is usually carried out through two operations: scanning the location code and scanning the product code. Once the data is recorded, the management system automatically identifies the location of each item in real time.
​This approach significantly reduces the time spent searching for goods, while improving the ability to control the flow of goods in the warehouse. In particular, this model is suitable for warehouses with a high degree of location fragmentation or a diverse product catalog.
4.2. Batch/Serial Management Model
​Batch or serial management is considered an essential model for industries with strict traceability requirements, including manufacturing, pharmaceuticals, chemicals, and electronics.
A batch management system allows businesses to track the entire product lifecycle – from raw material input, production process, warehousing, distribution to final consumption. Serial tracing increases transparency and effectively supports quality control and product recalls when errors occur.
4.3. Expiration Date Management Model (FIFO/FEFO)
​For products with a finite lifespan, especially in the food, beverage, pharmaceutical, and cosmetic industries, expiration date management is a crucial model.
The system is established according to two principles:
  • FIFO (First In – First Out): prioritizing the shipment of incoming batches.
  • FEFO (First Expired – First Out): prioritizing the shipment of batches with the earliest expiration dates.
​By automatically suggesting suitable batches during the shipping process, this model helps limit the risk of expiration, reduce losses, and optimize warehousing costs.

4.4. IoT-enabled Smart Warehouse Model
​Smart warehouses are based on the integration of IoT technology, including sensors, RFID systems, AI cameras, and automated transport robots (AGVs). This model aims for comprehensive automation of warehouse operations, from data recording, environmental monitoring, anomaly detection to internal transportation.

​Studies show that the IoT model can significantly increase labor efficiency, improve data accuracy, and reduce manual error rates. However, the level of investment depends on the size of the organization and the long-term development strategy of the business.

5. Long-Term Benefits of Adopting Digital Inventory Management
​Implementing a digital inventory management system offers benefits that extend beyond short-term operational optimization; numerous studies and empirical surveys show its impact is sustainable and directly affects the competitiveness of businesses.
5.1. Increased Warehouse Operational Productivity
​Digitalized systems, especially when combined with identification and automation technologies, increase warehouse processing productivity by 2 to 3 times compared to traditional manual models. This stems from the ability to shorten product search time, reduce redundant operations, and eliminate most human errors.
5.2. Reduced Operating Costs
​Thanks to optimized processes, reduced losses, and improved labor efficiency, businesses typically see a 15–20% reduction in warehouse operating costs annually. Cost savings include personnel costs, warehousing costs, error handling costs, and administrative management costs.
5.3. Enhancing Inventory Data Accuracy
​One of the outstanding advantages of a digital system is its ability to ensure high inventory accuracy, potentially reaching 99% in standardized operating models. Accurate inventory data helps businesses reduce "phantom inventory," limit unexpected shortages, and ensure a stable supply chain.
5.4. Minimizing Losses and Fraud
​Automated real-time recording mechanisms create transparency throughout the entire product lifecycle. When all input, output, and warehouse transfer operations are tracked, the risk of losses due to manual errors or fraudulent behavior is significantly reduced.
5.5. Enhancing Supply Chain Transparency
​Digital inventory management systems provide traceability by batch, serial number, or expiration date, helping businesses track the flow of materials throughout the supply chain. This transparency is particularly important in industries requiring compliance with quality standards or risk management.
5.6. Improving Data-Driven Decision-Making Capabilities
​With real-time reporting, dashboards, and data analytics, decisions related to procurement, production, safe inventory, or distribution are no longer based on guesswork but are supported by quantitative data. This contributes to improved forecasting quality and increased proactive management.
5.7. Enhancing Overall Business Management Capabilities

​When inventory data becomes transparent and consistent, businesses achieve a higher level of control over their operational processes. This helps to establish standardized working methods according to international standards, creating a foundation for long-term scaling and strategic transformation.

6. Conclusion: Digital Transformation in Inventory Management – ​​From a Strategic Choice to a Survival Condition
​In the context of increasingly fierce competition and unpredictable supply chains, digital inventory management is no longer just an innovative option, but has become a vital element for every business. Businesses possessing accurate data, the ability to track inventory flow in real time, and standardized operational processes have a significant advantage in optimizing costs, increasing productivity, and making decisions based on evidence rather than emotion.
​Research shows that the success of digital warehouse transformation depends directly on the accuracy of the underlying data, the degree of process digitization, and the ability to integrate appropriate technologies into the operating model. Therefore, to achieve sustainable effectiveness, businesses need to start on the right track—from standardizing source data, choosing a suitable management model, to implementing technology according to a feasible roadmap and focusing on user training.

​Ultimately, digital inventory management not only improves warehouse efficiency but also creates a transparent, seamless, and scalable operational ecosystem. This is the foundation that enables businesses to adapt quickly, upgrade operational standards, and maintain a long-term competitive advantage in the digital economy.

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DIGITAL TRANSFORMATION HANDBOOK FOR BUSINESSES: UNDERSTAND CORRECTLY – DO CORRECTLY – OPTIMIZE