Novobi Demand Forecasting

Data Science delivers accurate forecasts for thousands of products





Artificial Intelligence for your business

Novobi’s Demand Forecasting Engine streamlines the time consuming tasks of data preprocessing and statistical analysis, delivering continuous improvement and adaptation to changing customer demand.

Leverage the power of data science in your business quickly and easily! Our demand forecasting engine helps you make the best decisions for your inventory in an easy-to-navigate platform.

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Variable Characteristic

Models

Analyze different inventory types with variable characteristics (such as seasonality or irregular demand) using a variety of forecasting methods.

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Demand Type

Classification

Classify products using "demand type" as a unique attribute to help create historical data sets for future analysis. 

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Model

Recommendations

Let the system do the work for you! Using demand type classifications and variable characteristics, the engine will determine the right forecasting model.

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Variable Characteristic Models

Handle different inventory types with variable characteristics (seasonal or irregular demand) using a variety of forecasting methods:

  • Linear approximation

  • Linear regression

  • Triple exponential smoothing

  • ARIMA with seasonality

  • Custom Croston

  • Machine learning

Demand Type Classification

Products in each warehouse are classified based on their demand types and characteristics of their historical demand. 

Demand is classified into one of four unique types:

  • Intermittent

  • Lumpy

  • Smooth

  • Erratic

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Model Recommendation

Given the precomputed demand type of each product, the forecast engine selects the appropriate forecasting models. This is done automatically to ensure you don't need to manually analyze the best forecasting method to optimize your results.