Sales Forecasts
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.
