History analysis

On a daily basis, the software examines sales transactions and calculates historical data covering several years. It autonomously computes optimal values based on the current or expected circumstances and your company's business strategy.

The system takes into account a crucial element - ABC analysis of the portfolio, guided in the company's key performance indicators (KPIs). Our solution offers multiple methods of ABC analysis, which can be chosen according to company strategy, store locations and categories.

Seasonality and trends

The system can autonomously recognize seasonal patterns & trends, allowing it to appropriately adapt the ordering process throughout the entire year. If historical data is unavailable for a specific item or outlet/warehouse, the system can seek data from an alternative outlet or the relevant category of items.

Eliminating missed opportunities and extreme cases

During the processing of data evaluation for precise forecasting, the system automatically filters out extreme values. For instance, if there is a historical sale with outlier values that represent an isolated occurrence, the system automatically excludes such transactions from the forecast calculation. This step prevents an unwarranted increase of the required stock levels.

Conversely, in cases where historical sales data lacks records due to inventory stock outs, the system calculates the potential transactions that could have occurred had the stock been sufficient. This approach ensures that the sales forecast, used for determining optimal orders, is not underestimated, thus addressing potential gaps in historical data.

Sales forecasting

The resulting demand forecast is automatically generated using a diverse set of over a hundred mathematical, statistical, and self-learning algorithms. The system autonomously selects the method with the highest accuracy among these options. A precise demand forecast is crucial as it enables a high degree of automation in both purchasing and logistics processes.