Inventory is one priciest asset for any business, usually costing between 7%–16%, including the weighted average cost of capital. This means you have the room to optimize inventory to avoid unnecessary expenses and improve profitability. But how can you do that effectively?

The answer lies in data analytics. 

It includes transforming raw data into insights that help businesses make better decisions. Applying data analytics to inventory management can enhance your demand forecasting, help identify trends and patterns, and optimize inventory levels across the supply chain.
How? In this blog, we will explore how data analytics can help businesses achieve inventory optimization, one of the key objectives of MRO procurement.

Potential of Data Analytics in Inventory Optimization

As per McKinsey¹, applying data analytics to inventory management can reduce lost sales by 65%, due to improved data forecasting abilities. 

Some other benefits are as follows: 

• Optimizing inventory levels can reduce the amount of capital tied up in inventory, as well as the costs of storage, handling insurance, and obsolescence, thereby reducing inventory costs by 30–50%². 

• Businesses can also prevent stock outs by using real-time data and analytics to monitor inventory availability, demand fluctuations, and supply chain disruptions.

Data visualization and optimization techniques can help you reduce waste, increase productivity, enhance quality, and foster innovation. This can give you a competitive edge, increase customer satisfaction, and achieve higher profitability.

Optimizing Supply Chain using Data

Supply chain solutions providers use data analytics by offering end-to-end services including data collection, integration, analysis, visualization, and optimization. Here’s how these techniques can help your business: 

• Demand Forecasting: Businesses can use advanced analytics and machine learning to generate more accurate and granular forecasts for the short-term demand of products. 

• Identify Trends: By leveraging data visualization and predictive analytics, you can identify trends in inventory performance, such as variability, seasonality, excess, and obsolescence. This can help you improve inventory planning, allocation, and replenishment strategies while reducing waste and inefficiencies. 

• Optimize Inventory: You can also use data science and optimization techniques to determine the optimal levels for each product, location, and channel. This can help you minimize inventory holding costs, maximize inventory turnover, and enhance customer satisfaction.

Conclusion

Over 80% supply chain professionals believe analytics will play an important role in reducing supply chain costs. That’s why many businesses rely on supply chain solutions providers such as Moglix that can help you achieve significant savings and efficiencies through digital transformation of their indirect procurement.
For instance, Moglix enabled an FMCG conglomerate to unlock 4% savings on total cost of ownership by introducing catalog-based buying and streamlining their procurement process. If you want to learn more about how Moglix can help you leverage data analytics for inventory optimization, schedule a demo with us today.