1. Demand Forecasting and Analysis
- Develop rolling 18-month forecasts using historical sales, promotions, seasonality, events and relevant demand drivers
- Apply appropriate statistical, predictive and business-judgement methods based on business requirements and data availability
- Evaluate forecast accuracy, bias, stability and explainability
- Investigate forecast exceptions and distinguish baseline, promotional, event-driven and exceptional demand
2. Forecast Alignment and Stakeholder Collaboration
- Work with Commercial, Marketing, Operations and Supply Planning to develop and align the consensus demand plan
- Review and challenge assumptions using data and business evidence
- Present forecasts, assumptions, risks and opportunities to management
- Translate analytical findings into clear business implications and recommended actions
- Influence stakeholder adoption of improved planning methods and controls
3. Promotional and Event Planning
- Forecast promotional and event uplifts to determine incremental and net demand
- Track business activities and events that may affect demand
- Support promotional allocation decisions by balancing demand, inventory availability and operational constraints
- Conduct post-event reviews to improve future forecasting assumptions
4. Inventory and Replenishment Alignment
- Assess the inventory and replenishment implications of demand forecasts
- Balance product availability, service level, inventory exposure and operational risk
- Identify potential shortages, overstock and obsolescence risks arising from demand changes
- Coordinate appropriate planning actions with Supply Planning and relevant stakeholders
5. Performance Monitoring and Correction Action
- Monitor Demand Planning KPIs, including forecast accuracy, forecast bias, forecast value add, inventory days, urgent-order rates and material planning exceptions
- Investigate material performance gaps and potential causes
- Recommend corrective actions and monitor their effectiveness
6. Data Quality and Planning Controls
- Validate planning data for completeness, consistency, duplicates, missing values, abnormal demand and master-data issues
- Confirm calculation logic, business definitions and data sources before using or reporting analytical outputs
- Coordinate resolution of material data-quality issues with data owners and technical teams
- Document analytical logic, assumptions, data sources and material manual adjustments
7. Reporting, Automation and Continuous Improvement
- Prepare and maintain reports covering forecast performance, inventory position, risks and material planning exceptions
- Automate recurring data preparation, analysis and reporting through practical and maintainable tools, dashboards or workflows
- Improve forecasting methods, planning processes, reporting reliability and analytical controls
- Assess demand and supply risks and coordinate appropriate contingency actions
- Validate material improvements through back-testing, representative data or pilot implementation
- Support implementation and stakeholder adoption while ensuring outputs remain traceable and aligned with approved business rules
Core Competencies
1. Analytical Thinking & Problem Solving
- Analyses complex datasets, challenges assumptions and identifies relevant demand drivers
- Distinguishes evidence, assumptions, exceptions and business judgement
- Investigates potential root causes and develops practical, sustainable solutions
- Considers customer, service, inventory and operational implications before recommending action
2. Communication and Business Translation
- Communicates clearly with technical and non-technical stakeholders
- Explains forecasts, assumptions, limitations, risks and recommendations in practical business language
- Presents analysis and recommendations confidently to management and cross-functional stakeholders
4. Stakeholder Influence and Change Orientation
- Builds support for improved methods, tools, controls and processes
- Challenges existing assumptions constructively and uses evidence to influence decisions
- Supports implementation and adoption rather than stopping at analysis or recommendation
5. Learning Agility
- Demonstrates curiosity and willingness to learn new analytical methods, tools and Supply Chain concepts
- Applies learning to actual business problems
- Adapts analytical approaches based on evidence, operational requirements and user feedback
Technical Competencies
1. Statistical Forecasting and Model Validation
- Understands statistical forecasting, model selection, time-series behavior and forecast validation
- Evaluates forecast accuracy, bias and model limitations
- Selects methods based on business relevance, data quality, performance and explainability
- Exposure to predictive modelling is preferred
2. Data Analysis Tools
- Strong Microsoft Excel capability
- Practical exposure to one or more tools such as Python, R, SQL, Power BI, Tableau or equivalent
3. Planning and ERP Systems
- Exposure to SAP or an equivalent ERP, Demand Planning or Supply Chain Planning system is preferred
- Understands planning parameters, master data, system outputs and relevant business rules
- System experience may be developed for candidates with strong analytical capability and learning agility
4. Automation and Data Control
- Identifies repetitive data preparation, reporting and analytical activities suitable for automation
- Develops or supports automated reports, dashboards, scripts, workflows or analytical tools
- Validates automated outputs and maintains appropriate controls
- Identifies missing, duplicated, inconsistent, invalid or abnormal data
- Ensures source-of-truth alignment, calculation validation and documentation
- Distinguishes technical errors from business-rule exceptions