Inventory Analytics Solution: Making wise, data-driven decisions to increase Inventory Accuracy

Driven by increasing demand for competitive efficiency, today’s inventory management goes beyond ensuring accurate inventory and automating key business processes. Today’s inventory management systems hold the key to powering business insights that help you to make data-driven decisions for increased productivity and profitability.

Inventory accuracy is a critical factor for any business in the food and pharmaceutical industry. Proper inventory accuracy helps businesses maintain adequate stock levels, reduce costs, and improve customer satisfaction. Inaccurate inventory management can lead to lost sales, stockouts, increase inventory carrying costs, inventory expirations, and costly errors. Therefore, it is essential to have effective inventory analytics to improve inventory accuracy in the food and pharma industry. 

With inventory analytics, companies gain insight into their inventory activity that enables it to improve their inventory control, productivity, efficiency, and profitability.

Inventory accuracy is a metric that measures the difference between your records of warehouse stock and your real-life inventory. Inventory accuracy is critical for preventing stockouts, shortages, shrinkage, controlling inventory quality, and maintaining a positive customer experience.

Any inaccuracy can cause a heap of troubles throughout your supply chain. A registered product that doesn’t exist could get sold. Your records could show plenty of stock when you’re down to your last unit.

According to Auburn University’s RFID Lab, average inventory accuracy for companies ranges from 65% to 75%. That includes companies that use SKUs and barcode scanning to manage inventory. The benchmark for most companies that want to improve their inventory management is 97% or higher.

A study published in the International Journal of Industrial Engineering and Management in 2020 showed that the implementation of an analytics-based inventory management system improved inventory accuracy by 20% for a pharmaceutical company. The system used data analytics to optimize inventory levels and reduce the risk of stockouts and overstocking.

In this blog post, we’ll explore some of the ways that inventory analytical solutions can help you improve inventory accuracy.

Inventory analytics refers to the measurements that concentrate on the present stock of goods, assets, or raw materials. The primary aim of these analytics is to keep track of stock levels. Current inventory levels have a significant impact on business processes and can help identify areas that require improvement.

Inventory analytics can also be classified based on the value they provide. Descriptive, diagnostic, predictive, and prescriptive inventory analytics offer value in different ways.

Descriptive Inventory Analytics:

Descriptive inventory analytics provide information on what is happening. These are easily obtained and often come predefined in inventory management solutions. Common examples of these analytics include the number of items on hand and cost per unit.

Diagnostic Inventory Analytics:

Diagnostic inventory analytics help understand why something is happening. For instance, knowing only that a company experienced month-over-month growth is not helpful. Leaders need to understand why there was growth to apply the successes to other departments or product lines. 

Predictive Inventory Analytics: 

Predictive inventory analytics provide insights into what is likely to happen in the future. These analytics can be used to prepare and make adjustments to meet future needs. Machine learning, for example, is all about using technology to learn from the past and predict the future. Experts may perform predictive analysis by studying seasonal demands from the previous year or using prior knowledge of an event.

Predictive analytics is a powerful tool for improving inventory accuracy. Using predictive analytics in inventory management will help a company succeed in a fast-paced market with a high demand for its products. Predicting demand based on weather, holidays, and economic trends, for example, reduces backorders or excess stock levels. 

Inventory analytical solutions can use predictive analytics to forecast demand trends, identify potential stockouts, and optimize inventory levels. This proactive approach can help businesses stay ahead of the curve and avoid costly errors. 

Prescriptive Inventory Analytics: 

Prescriptive inventory analytics is an advanced method of inventory analytics that tell you what you need to do. These analytics provide the quantities of an item necessary to fill 90% of orders in a three-day time frame for areas needing improvement, for example, with the right data. Inventory management analytics solutions can provide prescriptive insights.

The integration of big data and analytical capabilities allows for the prediction of demand and the mitigation of typical inventory-related obstacles. By making use of accurate forecasting, data-driven decisions can prevent shortages, overselling, and shrinkage, all of which lead to increased expenses and have a direct effect on the profitability of a business.

Automate Inventory Tracking:

Automating inventory tracking is one of the most effective ways to improve inventory accuracy. Inventory analytical solutions such as barcode scanning or radio-frequency identification (RFID) can automatically track inventory levels, allowing businesses to easily monitor stock levels and avoid costly errors.

Use Real-Time dashboards:

Using real-time data is crucial for improving inventory accuracy. Inventory analytical solutions can provide businesses with real-time data on inventory levels, sales trends, and demand forecasts. This data can be used to make informed decisions about inventory management, such as when to order new stock or when to reduce inventory levels.

Conduct Regular Audits:

Conducting regular audits is another essential step for improving inventory accuracy. Inventory analytical solutions can provide businesses with a comprehensive view of their inventory levels, allowing them to identify discrepancies and take corrective action quickly.

Implement a FIFO System:

First In, First Out (FIFO) is a method of inventory management that ensures that older stock is used first, reducing the risk of spoilage or expiration. Inventory analytical solutions can help businesses implement a FIFO system by providing real-time data on stock levels and expiration dates.

Integrate Inventory Management with Sales and Procurement:

Integrating inventory management with sales and procurement is essential for improving inventory accuracy. Inventory analytical solutions can provide businesses with a unified view of their inventory levels, sales trends, and procurement needs. This integrated approach can help businesses optimize inventory levels, reduce waste, and improve customer satisfaction.

Continuous Improvement

Inventory accuracy is not a one-time event; it requires continuous improvement. With an inventory analytics solution, you can track performance metrics such as inventory accuracy and identify areas for improvement. By continuously analyzing data and making adjustments, you can improve inventory accuracy over time.

In conclusion, improving inventory accuracy is essential for businesses in the food and pharmaceutical industry. By utilizing inventory analytical solutions, businesses can automate inventory tracking, use real-time data, conduct regular audits, implement a FIFO system, integrate inventory management with sales and procurement, and utilize predictive analytics.
By taking these steps, businesses can optimize inventory levels, reduce waste, and improve customer satisfaction.

Accelerate your success with real-time, customizable inventory analytics from DiLytics. 

Speak to our analytics experts today and discover how we can help you.