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Department: | Sales Planning |
Location: | Naperville, IL |
Sr. Sales Forecast Planner (Hybrid based in Naperville, IL)
SUMMARY
As the liaison between customers/sales and internal forecasting team, this individual is charged to deliver a solid forecast that enables inventory planning to support industry leading fill-rates. As a part of the Commercial Sales organization, the role is responsible for providing data insights and analytical support for the collaborative development, monitoring, and communication of the demand forecast. Utilize strong analytical ability, business partner relationships, and data storytelling skills to drive value in a role that is essential to Highline Warren’s success.
ESSENTIAL FUNCTIONS
Strengthened Customer Relationships:
Act as a liaison between customers/sales and internal forecasting team
Proactive support and assistance across the entire customer value chain (replenishment to buyer)
Ensure timely communication and problem-solving to address customer needs
Use data-driven insights to optimize inventory levels and promotional planning
Inventory Management Excellence:
Accurate inventory tracking and replenishment to prevent stockouts and dips in in-stock rates
Anticipate inventory needs based on sales trends and weather forecasts
Monitor customer inventory levels aiming for a 98.5% fill rate
Data-Driven Forecasting and Planning:
Create forecasts based on historical data and customer conversations
Identify and correct forecast inaccuracies to improve fill-rate
Plan, monitor, and review for seasonal fluctuations, promotions, and modular/POG updates
Partner with internal IT team to find ways to integrate customer data into the forecasting model
Customer Interface:
Participate in all key customer Collaborative Planning, Forecasting, and Replenishment (CPFR) calls for forecast alignment
Understand customers’ forecasting capabilities and identify partnership opportunities
Provide timely assistance for feature store lists, special requests, and order fill information
Monitor customer inventory levels and communicate replenishment needs
Identify opportunities where more inventories could maximize feature/promo sales
Sales / Demand Forecasting and Planning (Integrated Business Planning process focus):
Conduct regular reviews and updates to forecasts based on historical data, customer supply plans, and external factors
Use Planalytics to proactively plan/push inventory to address changes in demand
Proactively identify and address potential forecast inaccuracies based on trends
Breakdown forecast / performance by customer location and roll up to supporting plant
REQUIRED KNOWLEDGE, SKILLS, AND ABILITIES
An individual qualified for this job must be able to:
Strong analytical and conceptual skills with a focus on business results
Proficiency in quantitative and qualitative data analysis linked to KPI’s
Motivated to drive business results versus personal preferences, and in group achievement rather than individual achievement
Meets deadlines and work under pressure, with limited supervision
Well-organized and high level of attention to detail
Knowledge of forecasting processes across various business functions
Proven ability to manage multiple projects at once
Evaluate scenarios in with end-to-end supply chain impact in mind
Excellent interpersonal, verbal, and written communication, including great presentations
MINIMUM EXPERIENCE, EDUCATION, AND CERTIFICATIONS
Bachelor’s degree (BS/MS in supply chain, engineering, operations management, or math/economics desired)
At least 7-10 years of prior experience in forecasting, supply chain planning, inventory management, manufacturing operations, or a field that demands complex quantitative analysis
Experience working with distribution and wholesale distributor models is a plus
Hands-on experience with modeling, forecasting, analysis and simulation tools
Excel Mastery: Advanced skills in Microsoft Excel, including pivot tables, VLOOKUP, and complex formulas for data manipulation and analysis.
Database Management: Understanding of database systems to retrieve and manage large datasets efficiently.