Euroasia Training Euroasia Training
AR

Procurement and Supply Chain Management

AI-Based Demand Forecasting and Market Analytics

7 units

Please select a city/session before registration.

About this program

Precise demand forecasting and market analysis play a crucial role in ensuring supply chain resilience, effective inventory management, and sustainable business expansion. Conventional approaches often fail to keep pace with today’s rapidly evolving markets, characterized by shifting consumer behaviors, global disruptions, and swift changes that demand quicker and more intelligent insights. Artificial Intelligence (AI) offers robust solutions to predict demand trends, identify market patterns, and facilitate data-driven decision-making.
The AI-Powered Demand Forecasting and Market Analysis Training Course prepares participants with the necessary techniques and tools to leverage AI, machine learning, and predictive analytics in tackling real-world forecasting challenges. Through hands-on exercises, case studies, and simulations, learners will develop AI-based models, interpret analytical outcomes, and apply insights to improve planning accuracy, mitigate risks, and uncover market opportunities.
Upon completion, participants will be capable of integrating AI technologies into forecasting and market analysis workflows, enhancing precision, responsiveness, and strategic decision support.

Course benefits

  • Enhance demand forecasting precision using AI technologies.
  • Utilize predictive analytics for deeper market understanding.
  • Streamline inventory and resource management.
  • Identify emerging trends and shifts in consumer behavior.
  • Bolster decision-making through real-time analytical insights.

Key outcomes

  • Explain the significance of AI in demand forecasting and market analysis.
  • Implement machine learning algorithms for demand prediction.
  • Employ predictive analytics to forecast market developments.
  • Incorporate AI-generated insights into supply chain and business strategies.
  • Assess data quality and governance to ensure forecasting reliability.
  • Improve responsiveness by leveraging real-time analytics.
  • Formulate approaches for deploying AI-driven forecasting systems.

Who should attend

  • Professionals involved in supply chain and demand planning.
  • Procurement and sourcing specialists.
  • Business analysts and strategy leaders.
  • Executives spearheading digital transformation efforts.

Course outline

1

Unit 1: Overview of AI Applications in Forecasting and Market Analysis

  • Limitations of conventional forecasting methods.
  • Introduction to AI, machine learning, and predictive analytics.
  • The business advantages of AI-based forecasting.
  • Illustrative examples of AI in demand prediction and market intelligence.
2

Unit 2: Essential Data Principles for AI-Based Forecasting

  • Recognizing critical data sources.
  • Ensuring data quality, integrity, and governance.
  • Organizing data for AI-driven use cases.
  • Addressing difficulties in data acquisition.
3

Unit 3: Applying Machine Learning Techniques to Demand Forecasting

  • AI approaches to time-series forecasting.
  • Use of regression, neural networks, and deep learning.
  • Managing seasonality and fluctuations in the market.
  • Hands-on activity: creating an AI forecasting model.
4

Unit 4: Leveraging AI for Market Trend Detection

  • Employing AI to identify changes in consumer behavior.
  • Sentiment evaluation and social listening methodologies.
  • Predictive analytics for discovering market prospects.
  • Case example: AI-driven competitive market intelligence.
5

Unit 5: Dynamic Analytics and Scenario-Based Planning Using AI

  • Importance of real-time data in enhancing forecast precision.
  • AI-powered scenario modeling and simulations.
  • Real-time forecast adjustments.
  • Platforms for live data visualization and dashboarding.
6

Unit 6: Incorporating AI-Derived Insights into Corporate Planning

  • Integrating AI forecasts within supply chain management.
  • Applying insights across sales, operations, and procurement functions.
  • Aligning predictions with overarching strategic objectives.
  • Effectively communicating insights to key stakeholders.
7

Unit 7: Deploying AI Forecasting Solutions

  • Procedures for implementing AI in forecasting workflows.
  • Addressing challenges related to adoption and change management.
  • Assessing the return on investment of AI-enhanced forecasting.
  • Developing a strategic plan for advancing AI capabilities in forecasting.