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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. 

OVERVIEW

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 

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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

Some Customer Cases

On the quantitative side, we have integrated the powerful Statistical and Graphical Modelling libraries of Python. We have also connected to ML / AI libraries of WML / Google / AWS to enables the application of a variety of statistical and ML/AI techniques for different situations

Consumer Electrical Company

Enhanced visibility and transparency via S&OP suite for a consumer electrical manufacturer

sales and operations planning
Speciality Tyre Company

Implemented Demand Forecasting and Demand Aggregation for the smooth function for the manufacturing unit

Other solutions that might interest you.

Sense - S Suite
Field force managment
Acquire - A Suite
Demand Aggregation Portal
Visualise - V Suite
BI, Dashboards and Analytics
Interpret - I Suite
Dispatch and Replenishment Planning

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