JDA Demand Planning
JDA demand planning is a system that improves the accuracy of your business and inventory plans by building an incorporated, synchronized picture of true demand signals across your trading network. This JDA Demand Fulfillment and Planning will help you to avoid unwanted items in your inventory. Synchronize demand forecasting across your trading network with collaborative scenario communication and mobile capabilities.
Users can create effective plans based on real-time collaborative scenarios.
This training will help you make accurate projections even when the slow-moving and hard to dispose of and new items are in your inventory. Users can Also access important data using mobile applications.
Why Should You Choose Nisa For JDA Demand Planning Training?
Nisa Trainings is the best online training platform where we conduct one-on-one interactive live sessions with a 1:1 student-teacher ratio. You can gain hands-on experience by working on near-real-time projects under the guidance of our experienced faculty. We support you even after the completion of the course and are happy to clarify your doubts anytime.
Job Assistance
If you are facing any problem while working on JDA Demand planning, then Nisa Trainings is simply a Call/Text/Email away to assist you. We offer Online Job Support for professionals to assist them and to solve their problems in real-time.
The Process we follow for our Online Job Support Service:
- We receive your inquiry for Online Job Support.
- We will arrange a telephone call with our consultant to grasp your complete requirement and the tools you’re using.
- If our consultant is 100% confident in taking up your requirement and when you are also comfortable with our consultant, then only we will agree to provide service. And then you have to make the payment to get the service from us.
- We will fix the timing for Online Job Support as mutually agreed by you and our consultant.
Course Information
JDA Demand Planning Online Training
Duration: 40 Hours
Timings: Weekdays (1-2 Hours per day) [OR] Weekends (2-3 Hours per day)
Training Method: Instructor Led Online One-on-One Live Interactive Sessions.
COURSE CONTENT :
1. Introduction to Demand Planning
- Overview of Demand Planning:
- Importance of demand planning in supply chain management.
- The role of demand forecasting in business operations.
- Challenges in Demand Planning:
- Variability in demand, seasonality, and trends.
- External factors affecting demand (e.g., promotions, economic conditions).
2. Introduction to Blue Yonder (JDA) Demand Planning Software
- Overview of the Software:
- Key features and functionalities of Blue Yonder (JDA) Demand Planning.
- Components of the system: Forecasting, demand sensing, collaboration.
- Navigating the Interface:
- User roles and permissions.
- Navigating through dashboards and modules.
3. Data Preparation for Demand Planning
- Data Requirements:
- Understanding historical sales data, external data sources (e.g., weather, market trends).
- Importance of clean, accurate, and complete data.
- Data Integration:
- Integrating external and internal data sources into Blue Yonder.
- Data transformation and preprocessing techniques.
4. Demand Forecasting
- Forecasting Methods:
- Time series analysis, statistical forecasting, and machine learning models.
- Types of forecasts: Statistical, judgmental, and hybrid forecasting.
- Techniques in JDA Demand Planning:
- Moving average, exponential smoothing, and regression models.
- Seasonal and trend-based forecasting.
- Using the Forecasting Module:
- How to configure and generate forecasts in Blue Yonder.
- Handling exceptions and anomalies in forecasts.
5. Demand Sensing and Collaboration
- Demand Sensing:
- Using real-time data to adjust forecasts and respond to changing demand patterns.
- Understanding the role of demand sensing in reducing the forecast error.
- Collaboration Tools:
- How to leverage collaboration features in Blue Yonder (e.g., communicating with sales, marketing, and operations teams).
- Demand collaboration across different teams and departments to refine forecasts.
6. Inventory Management and Optimization
- Demand and Supply Balancing:
- Balancing forecasted demand with available supply.
- Safety stock and inventory buffers.
- Inventory Optimization:
- Techniques for optimizing inventory levels based on forecasted demand.
- Managing stockouts and overstock situations.
7. Advanced Demand Planning Techniques
- Promotions and Events:
- How to account for promotional events, price changes, and other special activities that impact demand.
- Modeling promotional lifts and integrating them into the forecast.
- Scenario Planning:
- Creating different demand scenarios (e.g., best-case, worst-case, baseline).
- Simulating the impact of external factors or market changes on demand.
- New Product Forecasting:
- Techniques for forecasting demand for new products or SKUs.
- Leveraging historical data from similar products or market research.
8. Demand Planning KPIs and Performance Monitoring
- Key Performance Indicators (KPIs):
- Common KPIs for demand planning: forecast accuracy, bias, inventory turns, and service level.
- Performance Evaluation:
- Using Blue Yonder tools to track and analyze demand planning performance.
- Techniques for improving forecast accuracy and reducing errors.
9. Customization and Configuration in Blue Yonder
- System Configuration:
- Customizing demand planning settings (e.g., adjusting forecasting models, forecast horizons).
- Setting up user preferences and notifications.
- Integrating with Other Modules:
- How Blue Yonder Demand Planning integrates with other supply chain management tools (e.g., inventory, supply planning, order management).
- Data flow between modules and how integration supports end-to-end supply chain optimization.
10. Reporting and Analytics
- Generating Reports:
- How to generate demand planning reports using Blue Yonder.
- Types of reports: forecast accuracy, demand vs. supply, exception reports.
- Data Visualization:
- Using dashboards and visualization tools to monitor and communicate demand planning metrics.
- Advanced Analytics:
- Applying advanced analytics for deeper insights, like predictive analytics or demand segmentation.