Key Responsibilities and Required Skills for Demand Planner

🎯 Role Definition

The Demand Planner is responsible for developing and maintaining accurate demand forecasts, partnering with commercial, supply and finance teams to translate market signals into optimized inventory and replenishment plans. The role leverages statistical models, business intelligence, and Sales & Operations Planning (S&OP) processes to balance customer service, working capital and supply constraints while continuously improving planning capabilities and tools.

📈 Career Progression

Typical Career Path

Entry Point From:

Supply Chain Analyst with experience in forecasting and inventory reporting.
Inventory Planner or Junior Demand Planner supporting replenishment processes.
Business Analyst with exposure to sales data, CRM systems, or ERP reporting.

Advancement To:

Senior Demand Planner or Demand Planning Lead responsible for high-value product families.
S&OP Manager or Integrated Business Planning (IBP) Manager overseeing cross-functional planning.
Director of Demand Planning or Head of Global Demand Planning leading strategy and capability development.

Lateral Moves:

Supply Planner or Replenishment Manager focused on order release and supplier coordination.
Commercial Operations Manager supporting promotional planning and channel analytics.

Core Responsibilities

Primary Functions

Own the end-to-end demand forecasting process for assigned product portfolios, delivering monthly and weekly baseline forecasts using a combination of statistical time-series models, causal inputs, and qualitative adjustments tied to commercial plans and promotions.
Maintain and improve forecast accuracy and bias metrics (MAPE, MASE, MAD, bias) through root-cause analysis, actionable corrective plans, and close collaboration with sales, marketing and category managers to align assumptions.
Lead demand planning input to the S&OP / IBP cycle including scenario modeling, consensus demand reviews, and presentation of demand risks and opportunities to senior stakeholders for decision-making.
Translate marketing plans, promotional calendars, new product introductions, and market intelligence into demand signals and volumetric impacts, ensuring timely incorporation into the forecast and inventory plans.
Build and maintain statistical forecasting models in tools such as SAS, R, Python, or advanced forecasting modules within ERP/APS systems (e.g., SAP APO/IBP, JDA/Blue Yonder, Kinaxis), and continuously validate models against actuals to tune performance.
Partner with inventory management and supply planning to optimize safety stock, reorder points and replenishment parameters, balancing service level targets with working capital and product lifecycle considerations.
Design and run demand-sensing and short-term reforecast processes to improve responsiveness to sudden market shifts, supply disruptions, or promotional uplifts, enabling faster replenishment and allocation decisions.
Own demand data hygiene and master data governance activities—SKU rationalization input, product hierarchies, lifecycle status updates and exception management—to ensure planning models have accurate inputs.
Create and maintain demand planning dashboards, KPI scorecards and executive reports using Power BI, Tableau, or Looker, delivering insights on forecast accuracy, inventory health, sell-through, and lost sales impacts.
Manage new product introduction (NPI) forecasting including launch phasing, cannibalization analysis, and ramp plans, coordinating with R&D, marketing and sales for accurate launch inventory allocation.
Conduct scenario planning and sensitivity analysis (what-if scenarios) to quantify the impacts of demand variability, price changes or promotional strategies on inventory requirements and service levels.
Coordinate with procurement and supplier management to align lead times, minimum order quantities and capacity constraints with forecasted demand and contingency plans during supply disruptions.
Facilitate regular demand review meetings with regional and cross-functional stakeholders to secure forecast consensus, track action items and ensure accountability for forecast changes and business assumptions.
Implement continuous improvement initiatives to streamline demand planning workflows, reduce manual effort via automation (macros, ETL, APIs) and drive adoption of best practices across the planning organization.
Evaluate external data sources (POS, distributor sell-through, syndicated data, economic indicators) and incorporate relevant signals into statistical models to refine demand inputs and reduce latency between demand and supply decisions.
Lead root-cause investigations into forecast variances by product, channel or geography and develop corrective action plans such as price/promotional adjustments, merchandising changes or supply reallocation.
Act as the primary planner for allocation during constrained supply scenarios, using fairness and priority rules to maximize customer service and minimize revenue loss while communicating trade-offs to commercial teams.
Define and maintain demand planning policies, playbooks and standard operating procedures to ensure repeatable forecasting methods, consistent assumptions and clear owner responsibilities across the planning lifecycle.
Provide training and mentoring to junior planners and cross-functional partners on forecasting techniques, demand analytics and ERP/APS planning modules to raise organizational planning maturity.
Drive periodic demand planning audits and compliance checks to ensure governance of planning inputs, segmentation, forecast overrides and approval workflows and to reduce process risk and data discrepancies.
Collaborate with finance to reconcile forecast-to-forecast, support budgeting and monthly financial close processes, and ensure alignment between demand plans, revenue forecasts and inventory valuations.
Identify and support pilot projects that apply machine learning, causal inference or advanced analytics to materially improve forecast precision and planning cycle times.

Secondary Functions

Support ad-hoc data requests and exploratory data analysis.
Contribute to the organization's data strategy and roadmap.
Collaborate with business units to translate data needs into engineering requirements.
Participate in sprint planning and agile ceremonies within the data engineering team.

Required Skills & Competencies

Hard Skills (Technical)

Advanced demand forecasting techniques including time-series modeling, causal modeling, and hierarchical forecasting; hands-on experience with forecasting tools or statistical languages (R, Python, SAS).
Strong proficiency in Excel including Power Query, Power Pivot, complex formulas, and macros for ad hoc analysis and model building.
Experience with ERP and planning systems such as SAP (IBP/APE/APO), Oracle Demantra, Blue Yonder (JDA), Kinaxis RapidResponse, or similar APS platforms.
Data visualization and dashboarding skills using Power BI, Tableau, Looker or equivalent to deliver executive-ready insights and KPI tracking.
SQL skills for data extraction, transformation and large dataset manipulation from data warehouses or ODS systems.
Knowledge of inventory optimization concepts (safety stock calculation, service-level planning, EOQ, reorder points) and working capital trade-offs.
Familiarity with S&OP/IBP processes, cross-functional consensus-building methods and scenario modeling tools.
Experience working with point-of-sale (POS), distributor sell-through, CRM and syndicated data sources and integrating them into demand models.
Basic understanding of supply chain constraints: lead time management, capacity planning, allocation rules and multi-echelon inventory.
Ability to implement automation and ETL best practices; familiarity with APIs, data pipelines, and version control for forecasting artifacts.

Soft Skills

Strong stakeholder management and communication skills—able to present complex forecast scenarios and trade-offs clearly to commercial and executive audiences.
Analytical mindset with attention to detail and a continuous improvement orientation focused on measuring impact and iterating quickly.
Cross-functional collaboration and facilitation skills to drive consensus across sales, marketing, supply and finance.
Problem-solving and critical thinking—able to prioritize competing demands and navigate ambiguity in fast-paced environments.
Time management and project management capabilities to own multiple SKU families, month-end cycles and launch timelines simultaneously.
Influencing skills and commercial acumen to balance service objectives with inventory and margin considerations.
Adaptability and resilience in responding to rapid market changes, promotions, supplier disruptions and organizational change.
Coaching and mentoring aptitude to grow junior planners and transfer knowledge across teams.
Ethical judgment and data integrity mindset, ensuring quality of inputs and defensible decisions in planning outputs.
Customer-centric orientation to align planning priorities with end-customer service expectations and channel requirements.

Education & Experience

Educational Background

Minimum Education:

Bachelor's degree in Supply Chain Management, Operations Management, Business Analytics, Economics, Statistics, or a related quantitative field.

Preferred Education:

Master’s degree in Supply Chain, Operations Research, Business Analytics, or an MBA with a supply chain focus.
Professional certifications such as APICS CPIM/CSCP, ISM Certified Professional in Supply Management, or certification in demand planning/forecasting tools are a plus.

Relevant Fields of Study:

Supply Chain Management
Operations Research / Industrial Engineering
Economics
Statistics / Data Science
Business Analytics

Experience Requirements

Typical Experience Range:

3–7 years of progressive experience in demand planning, forecasting, inventory planning, or supply chain analytics.

Preferred:

5+ years of demand planning experience within consumer goods, retail, manufacturing, or high-tech industries with demonstrated ownership of S&OP cycles, statistical forecasting, and inventory optimization.
Proven track record improving forecast accuracy and reducing inventory carrying costs through process improvements, analytics or system implementations.