Career Advancement Programme in Demand Planning through Data Analysis

• Introduction to Demand Planning: Understanding the basics, importance, and benefits of demand planning in an organizational context.

• Data Analysis Foundations: Developing a solid understanding of data analysis concepts, including data collection, cleaning, and preprocessing.

• Statistical Methods for Demand Planning: Exploring various statistical techniques, such as time series analysis, regression analysis, and probability distributions, for demand forecasting.

• Data Visualization Techniques: Learning how to present data effectively through charts, graphs, and other visual aids to aid in decision-making.

• Machine Learning for Demand Planning: Delving into machine learning algorithms, such as neural networks and decision trees, to improve demand forecasting accuracy.

• Supply Chain Management Integration: Examining the role of demand planning in supply chain management and the importance of collaboration with other functions.

• Demand Planning Software and Tools: Introducing various software solutions and tools that support demand planning activities and data analysis.

• Performance Metrics and Evaluation: Measuring the effectiveness of demand planning efforts through key performance indicators and continuous improvement strategies.

• Change Management and Communication: Addressing the importance of effective communication and change management when implementing new demand planning processes and tools.