Inventory Planning Analyst

Red Bull•Toronto, ON

4d•CA$80,750 - CA$89,250

About The Position

The Inventory Planning Analyst is accountable for transforming data-driven insights into strategic operational actions by leading portfolio forecasting and supporting end-to-end inventory management for Red Bull Canada. This position partners cross-functionally with Operations, Trade Marketing, Sales, Brand Marketing, and Distribution to ensure accurate forecast planning and optimal inventory availability. In this role, the Analyst will act as the primary Red Bull Canada lead for developing, maintaining, and enhancing Trade Sales forecasts across the full product portfolio. The objective is to ensure appropriate inventory levels at retail, mitigate out-of-stock risks, and align inventory positioning with key commercial and programming periods. The position will also oversee forecast planning for all New Product Introductions (NPI), collaborating closely with Brand Marketing, Trade Marketing, Sales, and Distribution to determine launch quantities, support key account programming, allocate product to distributor warehouses, and evaluate ongoing performance. This includes full lifecycle management of Limited-Time-Offer (LTO) products, navigating operational complexities to maximize retail sales while minimizing Out-of-Code (OOC) exposure and ensuring timely product transitions at program completion.

Requirements

3-4 years professional experience - Consumer Goods or Retail industry preferred.
Advanced Excel skills including Pivot tables, Power Pivot, lookups, advanced formulas, etc.
Advanced skills in data analytics, forecasting, planning, developing projections and estimates.
Experience in statistics, including descriptive statistics, correlation, regression, hypothesis testing and inference.
Experience in data visualization tools like Power BI or Tableau.
Team player and strong communicator with plenty of time spent consulting with leadership and key stakeholders in the business.
Bachelor’s Degree preferred, advanced degree a plus.

Nice To Haves

SAP Spring (or other sales data systems) experience would be an asset.
Prior working experience in statistical modelling software packages (e.g., R or Python) would be nice to have.

Responsibilities

Responsible for SKU-level forecasts using historical sales, seasonality patterns, product lifecycle curves, and statistical models (e.g., moving averages, exponential smoothing, regression-based methods). Continuously refine models to improve accuracy and reduce bias.
Incorporate inputs from Sales, Marketing, Operations and Distribution—including promotions, pricing changes, new product introductions, and market shifts—to create a consensus demand plan.
Track key forecasting KPIs such as MAPE, WAPE, and forecast bias. Identify root causes of variance and implement corrective actions to improve future performance.
Responsible for forecasting approaches for new product introduction (NPI) launches, end-of-life items, seasonal assortments, and slow-moving SKUs. Use proxy products or attribute-based modeling when historical data is limited.
Oversee the full lifecycle of LTO products, from initial forecast through end-of-program transition.
Create scenario analyses to evaluate the impact of promotions, supply constraints, lead-time changes, and demand shifts. Provide recommendations to mitigate risk and optimize inventory positioning.
Identify emerging patterns early, such as accelerating demand, declining velocity, or SKU cannibalization, and communicate these insights proactively.
Support monthly Sales & Operations Planning (S&OP) or Integrated Business Planning (IBP) cycles by preparing demand insights, presenting forecast changes, and aligning on demand assumptions with cross-functional teams.
Act as the connective tissue between Sales, Finance, Operations and Distribution by ensuring all teams have a shared understanding of demand assumptions, inventory risks, and supply constraints vs forecast planning models.
Partner with Sales and Marketing to understand upcoming promotions, assortment changes, and product launches, translating business strategies into actionable demand plans.
Work closely with supply planning and logistics to communicate demand shifts, prioritize constrained supply, and support decisions on allocation, replenishment, and inventory positioning.
Encourage continuous improvement by sharing best practices, identifying process gaps, and helping teams adopt more data-driven ways of working.
Build strong relationships across the organization to improve information flow, reduce friction, and accelerate decision-making.
Translate complex data into clear narratives that non-technical stakeholders can understand, using visuals, storytelling, and business-focused framing.
Provide decision-ready recommendations, not just data—clearly outlining trade-offs, scenarios, and the expected impact on service levels, revenue, and working capital.
Lead discussions on portfolio forecast changes, explaining the “why” behind shifts in demand and ensuring stakeholders understand the implications for supply, revenue, and margin.
Support executive decision-making by presenting scenario analyses, risk assessments, and strategic recommendations in a concise, business-oriented format.
Enter/upload finalized inputs into Red Bull CPM forecasting system according to established planning cycles and cut-off timelines.
Ensure proper formatting and mapping so that system fields populate correctly and downstream processes (forecasting, replenishment, allocation) run without errors.
Validate system outputs (e.g., forecast runs, replenishment recommendations, allocation results) to ensure they reflect the submitted inputs accurately.
Document and present changes and rationale so stakeholders understand what was submitted, why, and how it impacts planning outcomes.
Automate recurring input processes where possible using system features, macros, or analytics tools.