About the course
Program Overview
Demand forecasting involves using historical data to estimate and predict future demand by predictive analytics. Thus, it helps individuals to make better - informed decisions in the areas like sales & marketing, budgeting, production planning, inventory and supply chain management for the organization. This course is intended towards understanding the basic and advanced techniques of time-series forecasting and their use in industries. Participants will learn how to read time-series data to build appropriate models for demand forecasting and to optimize the model parameters for forecast accuracy.
Target Audience
This program is primarily meant for senior specialist and supervisors working in planning, sales & marketing, budgeting and supply chain management areas to enable them to take data-driven decisions.
Program Outcomes
1. Develop an analytical mindset
2. Building spreadsheet forecast models based on historical data
3. Optimization model parameters for forecast accuracy
4. Identify areas in organization where forecasting can be used for improvement
Enrolment options
Program Overview
Demand forecasting involves using historical data to estimate and predict future demand by predictive analytics. Thus, it helps individuals to make better - informed decisions in the areas like sales & marketing, budgeting, production planning, inventory and supply chain management for the organization. This course is intended towards understanding the basic and advanced techniques of time-series forecasting and their use in industries. Participants will learn how to read time-series data to build appropriate models for demand forecasting and to optimize the model parameters for forecast accuracy.
Target Audience
This program is primarily meant for senior specialist and supervisors working in planning, sales & marketing, budgeting and supply chain management areas to enable them to take data-driven decisions.
Program Outcomes
1. Develop an analytical mindset
2. Building spreadsheet forecast models based on historical data
3. Optimization model parameters for forecast accuracy
4. Identify areas in organization where forecasting can be used for improvement
- Enrolled students: 164

