Fabric & Domestic Cleaning Products Company

SOLUTIONS DESIGNED TO SYSTEMATICALLY ESTIMATE MARKET DEMAND 

Be it New Product Development, Planning, or Promotions, implementing collaborative Demand Forecasting provides you with statistical / ML / AI data to support the course of action in the medium term. 

the puzzle

Demand Planning comprises key step of arriving at a baseline number. This is done by using Statistical and ML/AI methods. The Module applies various methods of forecasting on the historical Sales data to arrive at the forecast in the coming months. The forecasting can be done at various levels such as SKU-Depot / Brand-Region / SKU Region 

the result

Multiple Heirarchy

Forecasting at multiple Hierarchies e.g. SKU-Location, SKU-Sales Office, Brand-Channel etc.

Supersession

Supersession that allows linking of old to new items to provide meaningful continuity in history for effective forecasting new product

Statistical Methods

Variety of Forecasting Techniques using efficient Python to take care of different distributions such as seasonality, promotions etc. Also allows for Outlier Detection

Classification of Products

Dynamic Classification of Products across Runner / Repeater / Stranger using different parameters of frequency, variability etc.

ML / AI Methods

Selection of different AI / ML Methods for cases where ML can be implemented 

Choice of Error Methods

Selection of Techniques based on different Error Measures with ability to add custom Statistical Techniques

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