The sales forecasting module offers a full range of advanced features to help you accurately anticipate demand.
A key point in your supply chain, the sales forecast will irrigate all your logistics nodes and serve as the basis for calculating projections and order proposals.
Sales forecasting allows you to anticipate your turnover thanks to the analysis of previous commercial data.
Our OptimiX XFR Supply Chain solution therefore relies on corrected sales histories. Our algorithm selects the best forecast model as well as the best parameters associated with your products and sites.
We automatically calculate various forecast components, such as the non-promotional forecast and the promotional forecast. We take every detail of your products into account. Seasonality, trends… are automatically detected.
Automatic selection of the best statistical model
Our module analyzes historical data to automatically select the optimal statistical models for sales forecasting, taking into account seasonality, trend and other factors.
An adequate amount of data is needed to obtain reliable predictions. In addition, the model is regularly retrained for accurate forecasts adapted to current changes.
Our solution consists of more than 50 models, some of which are widely proven statistical models, while others are neural network models that achieve the best results.
To guarantee the best results, we select the models best suited to the dynamics of our customers’ needs.
Application of the optimal model to the product-site
Our sales forecasting module applies the optimal statistical models to each specific product and site.
In addition, it takes into account the unique characteristics of each product-site combination to provide personalized forecasts adapted to the reality of each point of sale.
Forecasts based on different types of events
Our module takes into account promotional, seasonal and special events (such as school vacations and public holidays) to adjust forecasts accordingly.
Capture demand fluctuations linked to these events and obtain more accurate forecasts.
Managing your sales forecasts
For maximum accuracy, our module adjusts forecasts for every relevant component, such as trends, seasonality, special events, etc.
Take into account all the factors influencing demand and refine forecasts accordingly.
Management of new products, store openings, and replacements
Our module supports forecast management for new products, new store openings and replacements for existing products.
It integrates these elements into global forecasts for better supply chain planning.
Our module offers reliability measures such as RMSE (Root Mean Square Error), MAPE (Mean Absolute Percentage Error) and BIAIS to assess forecast accuracy.
It allows real-time recalculation of forecasts and the possibility of recalculating forecasts in the past for retrospective analysis.
Model and parameter visualization
Our module provides a clear visualization of the statistical models used and their associated parameters.
This therefore allows users to understand and interpret forecast results.
Management by exception
Finally, to facilitate forecast management, our module highlights significant gaps between forecasts and actual results, thus allowing proactive management by exception.
Concentrate efforts on aspects requiring particular attention.
*6 months after deployment in 45 stores.
They trust us
FAQ 1 : Why is it important to correct sales histories in supply chain management?
Correcting sales histories is essential for accurate supply chain planning. Unadjusted historical data may be distorted by events such as promotions, stock-outs or exceptional sales.
These biases can lead to errors in demand forecasts, affecting inventory management, supply orders and customer satisfaction. By correcting this data, we obtain a more realistic view of normal demand, allowing for better decision-making.
FAQ 2 : How can sales history correction improve the accuracy of demand forecasts?
By eliminating bias caused by exceptional events, corrected sales histories reflect more accurate standard demand. This is crucial to improve the reliability of forecasts. For example, if a promotion led to a temporary increase in sales, adjusting it avoids overestimating future demand. Thus, correcting historical records makes it possible to obtain forecasts more aligned with market reality, reducing the risks of inventory surpluses or shortages.
FAQ 3 : Is it necessary to correct out-of-stock sales histories together?
It is essential to correct sales histories in the event of stock shortages. A shortage can distort the perception of real demand, because sales decrease not because of a drop in demand, but because of unavailability of the product.
However, not all categories require systematic correction, and breakpoints may vary. XFR’s historical correction module identifies these periods and adjusts the data to reflect standard demand, providing more accurate future analytics.
FAQ 4 : How does Optimix XFR's Supply Chain solution correct for exceptional sales?
The Optimix XFR Supply Chain solution has a specific module to identify and correct exceptional sales. These sales, which deviate from normal, can distort the interpretation of historical data. By identifying and adjusting them, XFR ensures that historical data reflects actual demand, without being influenced by exceptional events. This allows companies to obtain more stable and representative data for effective analysis and planning of their supply chain.
FAQ 5 : How does the module distinguish between a stock shortage and a drop in demand?
Correctly identifying a stock shortage is crucial to avoid forecasting errors. The module uses advanced algorithms to analyze trends in historical sales data. In the event of a significant variation for no apparent reason (such as a promotion or a particular event), the system recognizes this period as a potential out of stock. Additionally, by integrating other data, such as inventory information or supplier reports, the module can confirm or refute these suspicions to make precise adjustments.
FAQ 6 : How does XFR integrate with other supply chain management systems or existing ERPs?
The XFR solution is designed to be compatible with many supply chain management and ERP systems. Its modular architecture allows for seamless integration with other platforms, ensuring a smooth transition and optimal use of data. This flexibility ensures retailers rapid implementation and efficient collaboration between the different tools used in their ecosystem.
FAQ 7: How is the confidentiality and security of historical data ensured when using the XFR solution?
Data security and privacy are paramount to XFR. The solution employs advanced security protocols to ensure information remains secure. Measures such as data encryption, strict access controls and regular audits are put in place to prevent any data breaches. Retailers can therefore have confidence in the protection of their valuable information while benefiting from the advantages of the solution.