Associate Mgr, Statistical Forecasting

Newell Brands • Huntersville, NC

5d

About The Position

The Associate Manager of Statistical Forecasting plays a key role in developing a base line statistical forecasts that serve as the starting point for the segment demand planner to build a consensus demand plan. A strong statistical forecast is the foundation of data driven, unbiased forecast that efficiently and accurately maintains a 24-month future forecast for the organization. This is a center led role that will manage statistical models, cleanse sales order history, and maintain life cycle data with a goal to maximize statistical forecast accuracy (WFA) and attainment. Statistical Demand Planners will partner with segment Category Demand Planners and Customer Demand Planners to gather the necessary information to maintain the models and recommend areas of opportunity for statistical forecast adoption. They will leverage best practices, and analytics developed by the center led team (GSC) to manage by exception and focus on the sku’s with the most impact to WFA.

Requirements

• 5+ years of Supply Chain experience (Forecasting, Demand Planning, Supply Planning, Inventory Management and Fulfillment)
• 5+ years of statistical modeling and demand systems (i.e. SAP APO, SAP IBP, JDA, Logility, etc)
• 3+ years of experience in data acquisition, spreadsheet or database development and analytics using business intelligence tools such as Power BI
• Bachelor’s degree of Supply Chain Management, Statistics, Mathematics, Business Administration or equivalent undergraduate degree, with related work experience
• Training (or equivalent prior experience) with demand planning tools like SAP APO-Demand, SAP IBP Demand, Oracle or equivalent constrained based supply planning tools preferred
• Proficiency with Excel, PowerPoint and other MS Office applications, and supply chain planning and optimization tools
• Training or prior exposure to supply planning tools like SAP APO/SNP, SAP IBP S&OP, Inventory Optimization
• Understanding of Supply Chain Performance Management/Metrics – WFA, Attainment, Bias etc
• Ability to understand the dynamics of the business – both commercially and operationally
• Understands the “why” and the business impact of commercial forecast drivers
• Ability to work with large datasets and develop diagnostic, predictive, and prescriptive analytics models
• Ability to influence decisions and translate business impact to stakeholders across different organizational functions well beyond the supply chain
• Demonstrated ability to solve problems and a passion for improving processes
• Ability to collaborate effectively with and manage execution across multiple teams
• Ability to thrive in a fast-paced environment and manage multiple priorities at once
• Strong communication (written, verbal and presentation) and organizational skills

Responsibilities

• Manage and cleanse sales order history by identifying known outliers, and make model adjustments to improve the accuracy of a statistical model
• Leverage Life Cycle Management parameters such as end of life skus/dates, linking supersession sku’s, and new product introductions to build statistical history and drive stat forecast improvements
• Conduct demand analytics by reviewing statistical outliers, segmentation (ABC/XYZ) and perform WFA and bias reviews to manage by exception
• Tune statistical models by managing the algorithm assignments to each sku, classify history patterns, update model parameters, evaluate best level of aggregation for statistical model output
• Leverage Apollo for statistical model recommendations outside of IBP Demand options
• Generate a baseline statistical forecast and adjust based on downstream data such as POS, incoming sales orders, and category/customer intelligence
• Employ statistical alerts to address models needing review
• Partner with customer and category teams to ensure statistical forecast solution effectively address the needs as well as provide any future business insights or learnings
• Lead continuous improvement activities including hypotheses development and test execution to drive both incremental as well as step-change performance improvements

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level