AI Driven Demand Forecasting and Production Planning Workflow

Demand Forecasting and Production Planning Process

1. Data Collection

1.1 Historical Sales Data

Gather historical sales data from ERP systems, CRM platforms, and other relevant sources.

1.2 Market Trends Analysis

Utilize AI-driven tools such as Google Trends and IBM Watson to analyze market trends and consumer behavior.

1.3 External Factors

Incorporate external data such as economic indicators, seasonal trends, and competitive analysis using platforms like Tableau and Power BI.

2. Data Processing and Cleaning

2.1 Data Normalization

Normalize the collected data to ensure consistency using AI algorithms for data preprocessing.

2.2 Outlier Detection

Implement machine learning models to identify and handle outliers in the dataset, ensuring data integrity.

3. Demand Forecasting

3.1 AI Model Selection

Select appropriate AI models such as ARIMA, LSTM, or Facebook Prophet for demand forecasting.

3.2 Model Training

Train the selected models using historical data and validate their accuracy through cross-validation techniques.

3.3 Forecast Generation

Generate demand forecasts for various time horizons (short-term, medium-term, long-term) using the trained models.

4. Production Planning

4.1 Inventory Management

Utilize AI tools like SAP Integrated Business Planning (IBP) to optimize inventory levels based on demand forecasts.

4.2 Capacity Planning

Assess production capacity requirements and align them with forecasted demand using AI-driven simulation tools.

4.3 Scheduling

Implement AI scheduling tools such as Optessa or Preactor to create efficient production schedules that minimize downtime.

5. Monitoring and Adjustment

5.1 Performance Tracking

Monitor actual sales against forecasts using dashboards created in tools like Microsoft Power BI.

5.2 Continuous Improvement

Utilize feedback loops to refine AI models and production plans based on performance data and market changes.

5.3 Scenario Analysis

Conduct scenario analysis using AI simulations to prepare for potential market fluctuations or disruptions.

6. Reporting and Communication

6.1 Stakeholder Reports

Generate comprehensive reports for stakeholders using tools like Google Data Studio, highlighting key insights and forecasts.

6.2 Cross-Department Collaboration

Facilitate collaboration between sales, marketing, and production teams through integrated communication platforms.