How Artificial Intelligence is improving your inventory optimization

Summary

This retail company offers a highly precise sales forecasting platform that optimizes inventory management. By using machine learning algorithms, the platform evaluates historical data and compares forecasts with actual market sales. It ensures accurate demand predictions, lowers stock levels by up to 65%, and prevents out-of-stock situations. With an integrated cargo optimization module and seamless ERP integration, the solution enhances order accuracy. The company emphasizes training and change management, helping users fully leverage AI technology to optimize their business operations, reduce warehouse congestion, and improve customer satisfaction.

Takeaways

• 😀 The team in the retail company manages ordering goods for 50 suppliers daily, relying on reports from the IT department.
• 😀 The current process involves manual work, which often results in challenges, especially in optimizing truck fillings with factors like package sizes and lead times.
• 😀 The solution uses machine learning algorithms to forecast sales, with two main components: one for algorithm selection and the other for comparing forecasts with actual sales.
• 😀 The platform can forecast inventory with up to 97% precision, allowing for timely, fully-controlled orders that avoid warehouse congestion and stock-outs.
• 😀 High forecast accuracy can reduce stock levels by up to 65% in certain categories, optimizing inventory while preventing out-of-stock situations.
• 😀 The solution integrates historical data, external non-transactional data, and vendor-specific constraints without needing on-site installation.
• 😀 The platform’s secret is selecting the best machine learning algorithm for each stock keeping unit (SKU) and creating a demand forecast accordingly.
• 😀 The forecast is refined by applying vendor-specific constraints, including a cargo optimization module, to create an optimal order proposal.
• 😀 Fully optimized order proposals are seamlessly integrated into ERP systems through modern APIs.
• 😀 Many companies talk about AI, but few successfully leverage it. Success often depends on investing in last-mile activities like end-user development, training, and change management.

Q & A

What is the main challenge faced by the retail team in this script?

The main challenge is the manual process of ordering goods for 50 suppliers, which often leads to issues such as inefficiencies in truck fillings and inventory management.

How does the solution optimize truck fillings?

The solution optimizes truck fillings by using data such as package sizes, lead times, and other relevant information to streamline the ordering process.

What two components make the sales forecasting highly precise?

The first component involves using a machine learning algorithm that best fits each item. The second component compares the recommendations made by the system with actual sales data to continually improve its accuracy.

How accurate is the sales forecasting model in predicting inventory needs?

The model can accurately forecast up to 97% of the inventory requirements.

What is the impact of precise forecasting on stock levels?

Precise forecasting allows for reducing stock levels by up to 65% in some categories, while avoiding out-of-stock situations.

How does the platform handle external data?

The platform integrates historical data, external non-transactional data, and other relevant constraints without requiring any installation on the premises.

What is the role of the cargo optimization module?

The cargo optimization module ensures that the proposed orders are fully optimized, considering all relevant vendor-specific constraints and providing an optimal solution for the upcoming orders.

How does the platform integrate with existing ERP systems?

The platform seamlessly integrates with your ERP solution using modern APIs, enabling a smooth and automated workflow for order proposals.

Why do some companies fail to leverage AI effectively?

Many companies fail to leverage AI effectively because they focus solely on technology, neglecting crucial last-mile activities such as end-user development, training, and change management.

What is the approach taken by this platform to ensure successful AI implementation?

This platform invests significant time in working with end users, providing them with training, development, and support, and using their feedback to continually improve the solution.