Ease of use
Forecasts can be visualized, exported and uploaded to your systems and/or integrated into your applications.
The solution automates data collection and check-up as well as identifies the key factors needed for forecasting. The automated process means that you can save days of manual work every time a forecast update is needed.
The solution tests 10 time-series forecasting algorithms before the most accurate one for your data set is automatically selected. This improves the accuracy of your forecasts.
Analyze your historical sales data with time-series modeling and take your forecasts to the next level. Use cases can vary from planning the product demand to financial and resource planning.
InlinePredict harnesses data from selected internal sources, such as CRM and ERP systems and sales, inventory, and consumption. Also, data from external sources, like industry indicators, weather details, and calendar data can be included in the analysis.
Forecasting levels e.g. product group hierarchies are selected. This enables getting accurate predictions on channel, store, product group, or even on a product level.
The data input method is selected and support for the input data structure is validated. Additionally, input data anomalies are identified.
InlinePredict automatically feeds the input data to different forecasting methods, compares the accuracy between methods, and selects the best performing method. Algorithms automatically detect trends and seasonality.
The platform generates the forecasts and confidence intervals on desired levels and selected time period. The forecasts can be utilized for demand forecasting, sales predictions, and optimizing product availability.