In addition to supply chain optimization, inventory management is one of the most important logistics tasks for any business. Effective inventory and warehouse management can optimize stock, ensure product availability and shorten delivery times – which reduces capital expenditure and, above all, storage risk. The main objective is to achieve an optimal balance between demand, storage costs and ordering costs.
This can be a daunting and extremely complex challenge. With our innovative Inventory Optimization approach, paretos will help you master it and, in particular, maximize profit margins and minimize losses. Our powerful Artificial Intelligence (AI) model collects and analyzes all appropriate data, creates reliable demand forecasts and so reduces costly and risky manual workloads.
Using AI for accurate optimal inventory forecasts
The golden foundation of the paretos tool is your company’s core and historical data. It accesses your entire data source pool that has been collected over the existence of your business and extracts all relevant information including data on customers, suppliers, products and employees as well as orders, deliveries, sales and inventories and many other relevant factors that influence your strategic goals and KPIs.
AI-based analysis of this data results in accurate and reliable forecasting to help optimize your inventory management. Trends and seasonal fluctuations in demand for certain products in particular are identified and forecasts of future demand are generated which are used to plan stock orders and inventories. This is essential for avoiding overstocks or bottlenecks in the warehouse.
Real-time inventory update
The AI-based software solution also captures and updates data in real time, enabling companies to respond immediately to changes in demand and plan or optimize orders and inventory accordingly. This is done by analyzing data from passive and external inputs such as item prices, sales transactions, orders, weather data and covid reinfections to provide an up-to-date overview of demand and inventory levels. For example, unneeded items or excess stock can be quickly identified and avoided, inventory management improved, out-of-stocks prevented and inventory costs reduced.
The tool’s machine learning-based algorithm is also designed to continuously collect feedback from previous optimization models and adapt to changing conditions and situations. Because of this, new data can be processed more quickly leading to increasingly accurate forecasting. By utilizing the Inventory Optimization Tool from paretos, you will not only ultimately optimize your inventory management and related processes, but also benefit from faster decision-making, higher service quality and more sustainable business strategies – which all leads to greater success for your company.