Sales Histories Corrections

The history correction module offers advanced features to improve the accuracy of historical sales data. XFR relies on advanced sales history correction to obtain an accurate sales forecast.

illustration-xfr

The module can be used to assess the impact of out-of-stock situations, promotions, exceptional sales and special events, in order to forecast normal demand.

By eliminating the biases caused by promotions, out-of-stocks and exceptional sales, obtain corrected and more reliable data for better decision-making in supply chain planning, inventory management and demand forecasting.

Impact of sales promotion

Storage and correction of promotional impacts

This module takes into account the effects of promotions on sales. It records information linked to different promotions and applies adjustments to historical sales data to reflect the real impact of promotions on sales.

This automatically generates corrected sales data, a key factor in improving accuracy.

Stockout-related corrections

The sales history correction module identifies these break periods and makes adjustments to reflect standard demand.

Eliminate out-of-stock bias and provide more accurate data for future analysis.

stock-break corrections
Supply chain planning

Correction of exceptional sales

The module identifies exceptional sales and corrects them to prevent them from distorting historical data.

Get more stable, representative data for better demand analysis and supply chain planning.

improvement in your forecasts
+ 0 %
stockouts*
- 0 %
level of inventory
0 %
breakages
- 0 %

*6 months after deployment in 45 stores.

FAQ

Sales Histories Corrections

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.

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.

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.

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.

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.

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.

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.

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