Mandatory Prerequisites:
The learner must have attended the following Instructor-Led Workshops:
- o9 IBP Functional Workshop
- o9 Platform Technical - Basics Workshop

The learner ideally should have completed the following o9 Academy courses and their certification:
• Functional Insights into Demand Planning Core Solution Building Blocks
• What's New in Demand Planning Solution Building Blocks R2024.03?

Target Audience:
Demand Planners, S&OP and IBP Coordinators, Analysts, Solution Architects, Super Users, CoE Teams

About the Course:
The R2024.06 release introduces 17 key enhancements to the o9 Demand Planning (DP) Reference Product, improving forecast accuracy, workflow efficiency, and analytical capabilities. Updates include enhanced FVA metrics, forecast decomposition, expanded exception tracking, integrated NPI and cannibalization forecasting, and advanced assortment and demand assumption management. These features streamline forecasting, improve visualization, and enhance planners' decision-making.

The new features and enhancements covered in this course include:
• FVA Dashboard Enhancements
• Forecast Decomposition for CML
• Stat Process Summary & Exceptions Dashboard
• NPI Forecasts & Cannibalization Integration
• Cannibalization Profile Management
• Assortment Management Enhancements
• Demand Assumption Workflow Enhancements
• Automated CML Backtest Cycles
• Advanced Feature Engineering for Holidays & Indicators
• Synthetic History for Short-History Items
• Opt-out of Statistical Forecasting for Selected Intersections
• Enhanced Sell Out to Sell In Conversion


Learning Objectives:
• Utilize the FVA Dashboard to track adjustments and refine forecasts.
• Understand forecast decomposition for CML to analyze forecast components.
• Leverage Stat Process Summary & Exceptions Dashboard for workflow monitoring.
• Integrate NPI forecasts and cannibalization impacts into planning.
• Manage assortments, placeholders, and dependent workflows for NPI integration.
• Implement advanced CML backtesting, feature engineering, and synthetic history to enhance accuracy.
• Optimize Sell Out to Sell In Conversion by considering lead time and inventory policies.

The R2024.06 release delivers powerful tools to improve forecast accuracy, streamline workflows, and enhance decision-making. These updates provide planners with better analytics, automation, and forecasting precision, ensuring greater agility in demand planning and inventory management.

Please continue reading below to explore each feature and its practical applications.

FVA Dashboard Enhancements: New metrics improve forecast accuracy tracking, including a lag model and "Touched %" KPI to help planners refine forecasts.

Forecast Decomposition for CML allows planners to break down overall CML forecasts into individual components, allowing a clearer view of contributing factors.

Stat Process Summary & Exceptions Dashboard: A new workflow monitoring dashboard enables planners to track completion and identify failures, improving forecast execution efficiency.

NPI Forecasts & Cannibalization Integration: NPI forecasts now incorporate cannibalization effects, ensuring better alignment with the MECE principle for structured planning.

Cannibalization Profile Management: Centralized cannibalization profiles let planners define periods for assessing new product impacts.

Assortment Management Enhancements: Planners can create placeholders and new items, ensuring smooth NPI and dependent workflow integration.

Demand Assumption Workflow Enhancements: New capabilities include parameterized disaggregation, negative volume support, and file uploads for greater customization.

Automated CML Backtest Cycles: Planners can now automate backtest cycles, improving forecast validation and accuracy.

Advanced Feature Engineering for Holidays & Indicators: Users can enhance forecast precision by incorporating holiday flags and external indicators into the model.

Synthetic History for Short-History Items: Creates synthetic historical data for items with limited sales history, improving long-term forecasting.

Opt-out of Statistical Forecasting for Selected Intersections: Planners can now disable statistical forecasting for specific products or intersections, offering greater manual control.

Enhanced Sell Out to Sell In Conversion: New logic incorporates lead time, in-transit inventory, and policy constraints, ensuring more precise forecasts.

These updates enhance demand planning efficiency, improve forecasting precision, and streamline workflows, ensuring better agility and accuracy in decision-making.