Inventory control means that a manufacturer accumulates inventory in a facility such as a warehouse until the point of sale. Inventory control aims to place the right products at the right time in the right place.

Effective inventory management plays an important role in meeting customer demand and minimizing inventory loss. On the other hand, improper inventory management can lead to increased storage costs and waste of labor resources, which often leads to a decrease in sales and customer dissatisfaction.

Therefore, companies need to maximize operational efficiency through an inventory management system. In this article, we will explain why an inventory management system is important and what is needed to build an efficient inventory management system.

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Importance of Inventory Management

Operational Efficiency

Proper inventory management reduces unnecessary costs and allows capital to be used efficiently. Excess inventory increases storage and labor costs, which can have a negative impact on a company's financial position if accumulated.

Accurate inventory management increases the accuracy of financial reporting and helps management make decisions. The accuracy of inventory data reflects the financial position of the company and can be reliable data for investors and stakeholders.

Therefore, companies should collect and analyze real-time data through an inventory management system to make better decisions. Optimizing inventory levels can help companies reduce costs and achieve capital efficiency at the same time.

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Customer satisfaction

An inventory management system ensures that products are available when customers want them and minimizes delivery delays. When companies use an efficient inventory management system, they can track inventory levels while also forecasting demand. This allows them to respond quickly to sudden changes in purchasing patterns.

This type of system creates a reliable flow that prevents stock-outs and backorders as products move smoothly from suppliers to warehouses and finally to customers.

When they find out that a product is out of stock or that delivery is delayed, most customers decide to cancel their order. They often then move on to a competitor. An effective inventory management system can analyze trends and adjust inventory levels accordingly to predict demand and reduce the likelihood of out-of-stocks.

It can also help you fulfill orders faster and more accurately by knowing the exact location of each product in the supply chain. The ability to ensure that customers receive the right items on time has the greatest impact on trust, which is the foundation of customer satisfaction.

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Responding to changes in demand

Inventory management is the foundation of a company's ability to effectively respond to changes in demand. Modern inventory management systems must also predict requirements and ensure that the company has the right amount of products to meet customer expectations.

Changes in demand can be caused by a variety of factors, including seasonal changes, market trends, and external factors such as changes in consumer preferences. An effective inventory management system enables companies to operate flexibly and respond quickly.

In fact, solutions such as IMPACTIVE AI's 'Deepflow' can help prevent situations where products are unexpectedly sold out or costly overstocking.

Using deep flow can help you accurately forecast demand, optimize inventory, reduce losses, meet delivery deadlines, and improve customer satisfaction.

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Why inventory management operations fail

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Many companies are experiencing various problems in the inventory management area. Not only are they suffering from the continuous accumulation of losses due to excess inventory, but they are also experiencing more frequent emergencies due to insufficient inventory.

In addition, they experience delays in delivery and a decline in customer trust due to failure to predict demand. Some studies have shown that the work stress of those in charge is increasing due to multi-item ordering and inventory management.

About 43% of small and medium-sized businesses experience losses due to inaccurate inventory tracking, and the average annual inventory management error results in a cumulative loss of 10-25% of sales.

There is a survey of industry professionals on the causes of inventory management failures. The technical factors include inaccurate inventory tracking systems, outdated inventory management software, and insufficient real-time inventory updates.

In addition, human factors such as insufficient employee training, human error, and reliance on manual processes have also been pointed out as causes of failure.

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Guide to Efficient Inventory Management

ABC analysis technique

ABC analysis is a key technique in inventory management, also known as the Pareto principle. It is a method of classifying inventory items into three groups, A, B, and C, according to their importance.

By analyzing the value of material consumption over a certain period of time based on the amount spent, the priority of each item can be determined. This method maximizes the efficiency of inventory management by taking advantage of the fact that a small number of items account for most of the total sales.

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Group A is the group with the highest sales contribution, and it includes a small number of products that account for 80% of total sales. Since it is the product group with the highest consumption every year, it requires intensive management. The higher the inventory turnover rate and the more thorough the management, the more cost and risk reduction effects can be expected.

Group B is a product with an intermediate level of sales contribution, which is between groups A and C. The inventory management strategy for products in this group may vary depending on sales fluctuations. Since products in group B have the potential to be promoted to group A, it is important to manage and analyze them.

Item C is the item with the lowest sales contribution. Items in this group have a large quantitative share but relatively low sales, so they require minimal management. As this is a product group with low cost-effectiveness for inventory management, a strategy is needed to operate efficiently by minimizing management resources.

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The ABC analysis technique has the advantage of enabling efficient inventory management by focusing on items with high value. However, there is a tendency to simplify the inventory management system by focusing too much on monetary value and profit generation.

Even items with low value may be essential for customer satisfaction, but they are given low priority in the ABC analysis technique.

For items with fluctuating demand, the ABC category may need to be adjusted on a regular basis, which may ultimately increase the workload of the manager.

If the demand for items classified as C increases rapidly, ABC analysis alone cannot effectively respond to the situation, so a more agile approach is needed.

In addition, ABC analysis categorizes items based on historical data, so it may not explain seasonal or sudden market changes. This static approach makes it difficult to respond flexibly to customer preferences and market changes unless it is updated regularly.

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The Need for AI-Based Solutions

AI-based inventory management systems monitor inventory levels in real time and help maintain appropriate inventory levels through demand forecasting.

For example, machine learning algorithms can be used to analyze historical sales data and predict future demand, thereby reducing unnecessary inventory and saving costs.

These AI-based solutions are particularly popular with large-scale retailers.

Data analysis is becoming a key element of inventory management. Big data can be used to analyze customers' purchasing patterns, which makes demand forecasting more accurate.

Cloud-based inventory management systems provide companies with the flexibility to manage inventory anytime, anywhere.

Cloud technology allows for real-time updates of inventory data and centralized management of inventory status across multiple branches. The cloud system also improves operational efficiency by enhancing data security and accessibility.

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AI-based demand forecasting and inventory management system, Deepflow

AI demand forecasting

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One of the core functions of Deepflow is to predict future demand. Unlike the traditional method of relying on historical data analysis, Deepflow can predict the future shipment and order volume for each item for the next six to 12 months using a machine learning-based AI prediction model.

This allows companies to identify future demand trends at a glance and to establish production and inventory plans based on them.

In addition, it provides a variety of information not only for forecasting shipment/order volume, but also for forecasting-based inventory and production management optimization. For example, it can predict future inventory levels based on changes in shipment volume or gain insight into future performance.

It also provides data analysis related to corporate financial indicators such as future shipment rankings, growth contribution rates, profitability, and cost reduction.

The data collected in this way is provided to users in the form of a dashboard. Deepflow users can make more strategic decisions based on future forecasting information, rather than being confined to the framework of past data analysis.

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AI Inventory Management

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Deepflow automatically calculates the production/order quantity of numerous items, taking into account the optimal inventory level and lead time. This minimizes overstocking and shortages and maintains an appropriate inventory level.

First, it automatically calculates the production/order quantity of numerous items, taking into account the optimal inventory level and lead time. It also predicts future inventory levels, allowing you to prevent shortages and overstocking in advance.

This not only allows you to maintain an appropriate inventory level, but also reduces the frequency of emergencies and enables you to establish stable production and sales plans.

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Forecasting new product performance

In addition, we predict sales volume in the first quarter after the launch of a new product to evaluate the success of the new product in advance. We derive a profile of new products with high potential for success to increase the likelihood of success from the product planning stage.

Through Deepflow, we can establish an efficient new product development strategy while minimizing the loss caused by the failure to launch a new product.

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Raw material requirements and price forecast

It analyzes the trends in changes in raw material prices to predict the optimal time to purchase raw materials. In particular, it can optimize the management of raw material inventories based on the prediction of raw material requirements.

This allows companies to reduce the cost of purchasing raw materials and minimize the risk of price fluctuations. It also helps reduce the cost of holding unnecessary inventories and ensures that the necessary raw materials are available at the right time.

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Dynamic Price Optimization

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Deepflow uses a machine learning-based demand forecasting model to predict the optimal price for each product. Dynamic price optimization can be expected to increase sales.

Setting the lowest price can increase customers' willingness to buy, which can lead to increased sales, and it can also establish a flexible pricing strategy that takes into account market conditions and the competitive environment.

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Data automation and SaaS provision

Deepflow automatically collects data in conjunction with the customer's ERP system. Users can use Deepflow without having to input data.

It is also provided in the form of SaaS, so it can be used through a web browser without having to build a separate system. This reduces initial implementation costs and reduces the burden of system management.

Deepflow is periodically updating its predictive model automatically. We will continue to focus on research and development to ensure that the latest predictive information is always available.

After introducing Deepflow, IMPACTIVE AI's inventory management and demand forecasting solution, many companies have been relieved of the difficulties of inventory management that have accumulated over time.

After introducing Deepflow, Company O saw a 49.1% reduction in inventory shortages and a 70.9% reduction in inventory overstock. As a result, it achieved a monthly cost reduction of more than 1.1 billion won.

Accurate and efficient inventory management is essential for the successful operation of a company. With the AI-based solution Deepflow, you can solve inventory management problems and improve business performance.

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