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Sales and demand forecasting

Harness the power of automated forecasting with InlinePredict

 

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Forecasting with maximum accuracy and speed! Inlinepredict is a forecasting platform that uses machine learning to deliver highly accurate predictions of your sales and demand. The highly automated platform reduces forecasting time from months to hours - even for big volumes!

 

Platform benefits

  • Reduce forecasting time from days to moments. InlinePredict 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.  
  • Improve forecasting accuracy. InlinePredict tests seven time-series forecasting algorithms before the most accurate one for your data set is automatically selected. This improves the accuracy of your forecasts.
  • Benefit from your own data. 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.

Sales and demand forecasting

 

 

Platform capabilities

Ease of use

Forecasts can be visualized, exported and uploaded to your systems and/or integrated into your applications. 

Automatic Updates

Forecasts are generated automatically and as often and detailed as desired. 

Agile Data

Accurate forecasts are driven in an automated manner simply by using existing history data or adding any other related data sets.

 

Machine Learning

The platform uses 7 different time series forecasting techniques to ensure the best model accuracy for your data.

Data Security

Our secured process, starting from feasibility testing, ensures that your sensitive data is well protected.

Trend Recognition

InlinePredict platform automatically detects and predicts seasonality. 

Want to know more? Book a meeting with us or send an email. 

 

How InlinePredict works

1. Customizable data sources

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.

2. Data insertion preparation

The data input method is selected and support for the input data structure is validated. Additionally, input data anomalies are identified.

3. Training models and supervised learning

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.

4. Forecasts and use

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.

 

 

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