Sr. Demand Planner

Fender•Phoenix, AZ

2d•Onsite

About The Position

Fender Musical Instrument Corporation (“FMIC”) is located in Phoenix, AZ. Our brand mission is to accompany each player at every stage with products and brand experiences that fuel the pursuit of musical expression. Within Global Demand Planning, we are focused on delivering operational excellence to the business and our customers by promoting collaboration, building trust, and setting high standards. Our mission is to support and enable the makers who fuel the pursuit of musical expression. We are currently seeking a Senior Demand Analyst – Americas to join our Supply Chain team. This is an analytics-focused role within Supply Chain, created to deliver actionable insights that strengthen the demand planning function. Leveraging AI and advanced analytics, the Senior Demand Analyst surfaces patterns, emerging trends, and recommendations that enable demand managers and planners to make faster, better-informed decisions in support of the consensus process of the Sales, Inventory and Operations Plan (SIOP) and the translation of reduced forecast bias, high fill rates, optimized inventory, and efficient manufacturing plans.

Requirements

Bachelor's degree in supply chain, Business, Operations, Finance, Data Analytics or Management Information Systems
5+ years of experience in demand planning, forecasting, inventory management, data analytics or financial planning and analysis
Demonstrated experience applying AI/ML or advanced analytics tools to forecasting, demand planning, or inventory optimization (e.g., predictive analytics, generative AI for data analysis, automated reporting)
Strong root-cause analysis skills, including Pareto and other structured problem-solving techniques
Strong analytical, problem-solving, and organizational skills
Proven ability to rapidly synthesize limited data and large quantities of data to effectively spot trends and shifts
Experience with statistical forecasting
Consumer goods planning experience for both wholesale and direct-to-consumer (DTC)
Proficiency building automated reporting and visualizations in Tableau (or Power BI), with the ability to design self-service dashboards and trackers
Knowledge of shipment demand drivers (base consumption, incremental consumption, trade inventory and life cycle planning)
Good communication and presentation skills: ability to report and present complex information/recommendations
Experience managing or analyzing a large SKU base across multiple distribution centers
Advanced MS Excel skills required
A continuous-improvement and innovation mindset — proactively identifying opportunities to automate, streamline, and enhance planning processes through technology
Knowledge of SAP ECC/Hana, Tableau, Power Query/BI, Logility and/or SAP Business Warehouse; with advanced data mining skills preferred
Ability to develop dashboards, agents and analysis tools using AI (e.g. Claude) a plus

Responsibilities

Leverage AI and machine-learning tools (e.g., generative AI assistants, predictive modeling, and automated analytics platforms) to develop tools, accelerate data analysis, and surface actionable insights for demand managers and cross-functional stakeholders
Identify patterns and emerging trends across SKU, channel, and category data using AI-assisted analysis, translating raw data into clear, decision-ready recommendations
Develop and maintain enhanced reporting and root-cause analyses — including Pareto analysis — to isolate the primary drivers of forecast error and excess and obsolete inventory, and recommend corrective actions
Design and automate analytical tools, spreadsheets, dashboards, and workflows that reduce manual effort, improve forecast accuracy, and scale insight generation across a large SKU base
Deliver advanced sell-through insights and trackers — designing automated, self-refreshing dashboards that monitor new item and factory special-run performance against plan, with early-warning flags on risks and opportunities
Build data-driven recommendations for New Product Introduction (NPI) launch quantities, incorporating analog/like-item modeling, load-in curves, and sell-through signals to reduce launch risk and optimize initial inventory placement
Review and analyze historical sales trends and research demand drivers — including NPI analysis, load-in curves, and sell-through demand trends
Selection and use of statistical models for forecast development
Analyze unconstrained / true demand, accounting for stockouts and unfulfilled orders, so the forecast reflects real demand — including pent-up demand — rather than constrained shipments
Provide awareness to activities and trends that impact the operational forecast
Prepare, maintain, and publish new item / factory special-run sell-through reports to monitor and assess performance and trend
Monitor, analyze and prepare key performance reports to include (but not limited to) inventory, forecast accuracy, MAPE, slow moving, excess and obsolete inventory, and new product introduction
Support the forecasting process by providing analysis, scenario modeling, and insights that inform the conversion of the unit-based forecast into a monthly revenue plan over a 12 to 24-month planning horizon
Provide insights to demand managers and the Supply Planning process regarding forecast changes, forecast accuracy, and upcoming risks and opportunities that can impact the supply plan and inventory
Develop alternate forecast scenarios and risk-mitigation analyses to support demand managers in decision-making
Monitor trends in customer orders (by create date and request date) against forecast and identify forecast improvements
Plan and execute large-scale analytical projects
Create monitoring templates and communicate monthly results and recommendations
Partner with Sales, Marketing, Supply, Finance, and IT to ensure all future programs, promotions, new item launches, and factory special runs are accounted for in the analysis and reporting
Serve as a power user and internal champion for AI/analytics adoption within Global Demand Planning — piloting new tools, documenting best practices, and mentoring planners on data-driven techniques
Develop tools/processes to aid in data analysis and to understand and optimize/improve processes; make recommendations for changes
Support the management of SKU status in SAP (working with the Master Data team)