AI-based demand forecasting and inventory optimization system
Based on trends, past sales and seasonality, the system suggests which products to order in advance. This helps to avoid shortages or, on the contrary, warehouse overload. We use AutoML, Time Series AI, and Prophet to create multi-factor forecasting models with an accuracy of up to 95%. The system analyses historical data and market trends and generates recommendations for optimal procurement volumes.
Inventory management is one of the most challenging tasks for retail and wholesale businesses. According to research, ineffective inventory management leads to a loss of 3.2% of annual revenue due to out-of-stocks and 7.5% due to overstocks. Traditional forecasting methods based on simple extrapolation of past sales can be up to 40% inaccurate, especially in the face of seasonal fluctuations, changing trends and volatile market conditions.
Our Demand Forecast service implements an intelligent system that uses machine learning algorithms to accurately predict future demand for goods. The system analyses historical sales data, market trends, seasonality, marketing activities, competitor data and macroeconomic indicators to create a multi-factor forecasting model for each product category.
The solution is based on advanced tools:
- AutoML - automated machine learning technology that selects the best algorithms for each type of product
- Time Series AI - specialised algorithms for analysing time series and identifying patterns in sales
- Prophet - a development by Facebook for high-precision forecasting with regard to seasonality and trends
How the system works:
- Collecting and integrating data from your ERP, CRM and other systems
- Cleaning and preparation of data for analysis
- Creating customised predictive models for different product categories
- Continuous training of models on new data to improve accuracy
- Generate recommendations for optimal purchase volumes, taking into account delivery times, minimum quantities and logistical constraints
The system provides forecasts in a user-friendly format through an intuitive dashboard and can integrate with your procurement and planning systems.
The service is ideal for:
- Retailers with a wide range of products
- Online stores and marketplaces
- Manufacturing companies that purchase raw materials and components
- Distributors and wholesale companies
- Seasonal businesses facing high demand volatility
Key benefits of AI demand forecasting for businesses
Implementing an intelligent demand forecasting system provides your business with a number of strategic advantages:
Improved forecasting accuracy. Our system ensures forecast accuracy of 85-95%, even for goods with high seasonality and unstable demand. This is 30-40% higher than the accuracy of traditional forecasting methods.
Optimisation of stock levels. The system determines the optimal inventory level for each SKU, taking into account delivery times, minimum batches and storage costs. According to our customers, this allows them to reduce inventory levels by 20-30% without the risk of shortages.
Reduction of lost sales. Accurate forecasting minimises out-of-stock situations. Our clients reduce lost sales due to out-of-stock by 70-85%, which directly affects revenue.
Optimisation of working capital. Reducing excess inventory frees up working capital. According to our statistics, customers free up 15% to 25% of funds frozen in excess inventory, which can be invested in business development.
Automation of the procurement process. The system not only forecasts demand, but also generates recommendations on the optimal volume and timing of purchases, which greatly simplifies the work of the procurement department and reduces the risk of human error.
Dynamic adaptation to market changes. Machine learning algorithms constantly analyse new data and adapt forecasting models to take into account changes in consumer behaviour, new trends and market conditions.
Product lifecycle management. The system recognises the different stages of the product life cycle (launch, growth, maturity, decline) and generates appropriate inventory management strategies for each stage.
Forecasting for new products. Unlike traditional methods, our system is able to forecast demand even for new products without a sales history, using data on similar products and their dynamics.
Why choose digiants.agency to implement a demand forecasting system
The digiants.agency team combines deep expertise in machine learning and data analytics with practical experience in optimising business processes in retail and distribution. Our approach to demand forecasting has the following advantages:
Individual customisation for your business. We do not use one-size-fits-all solutions. The system is customised to suit your industry, business model, product range, and demand patterns. We create separate forecasting models for different product categories, regions and sales channels.
Integration with your systems. Our solution seamlessly integrates with your ERP, WMS, CRM, and other systems via APIs, enabling automatic data exchange and implementation of recommendations into workflows.
Combination of AI and expertise. We combine the power of machine learning algorithms with the expertise of our inventory management and logistics specialists. This provides not only accurate forecasts but also practical recommendations that take into account real-world constraints and business context.
Adaptation to the Ukrainian market. Our models take into account the specifics of the Ukrainian market, including local holidays, economic cycles, seasonal features and consumer trends, which ensures higher forecast accuracy compared to international solutions.
Gradual implementation and measurable results. We offer a phased implementation of the system, starting with pilot product categories, which allows you to quickly see results and ROI. Each stage is accompanied by detailed performance analytics and comparison with previous forecasting methods.
Proven effectiveness. Our clients record an increase in inventory turnover by 30-45%, a reduction in excess inventory by 25-35%, and an increase in service level (availability of goods) by 10-15% within the first 3-6 months after the system implementation. The average project payback period is 4-8 months.
Are you ready to optimise your inventory management and increase the efficiency of your business? Contact us for a free demo analysis based on your real data. We will prepare a customised presentation with examples of forecasts for your product range and a calculation of the potential economic impact.
