Job Accountabilities:

Build solid capacity plan for Nike Whole sales business, based on NSP door / concept modeling and door-level planning, across long-range forecast and seasonal gates. Lead, align and track NSP marketplace revenue.

Support NSP door / concept modeling & door-level planning across long-range forecast and seasonal gates.

Marketplace Capacity Forecast: Model different retail KPIs (e.g., fleet productivity, comp growth, traffic, conversion) and simulate multiple growth scenarios to support wholesale revenue planning and identify long-term opportunities. Seasonal RSV & Buy Plan: Lead door-level sales forecasting for Nike wholesale accounts and align with account MFP to facilitate door level OTB & seasonal door cluster plans. Fleet Plan Tracking: Collaborate with the MP team to monitor NSP fleet progress (new stores, renovations) and identify risks/opportunities.

Lead NSP in-season plan alignment, performance tracking, and post-season recaps. 

In-season key door revenue target: co-work with Acct planning on target alignmentPerformance Tracking: Review in-season door performance and cFOP & key product performance.Recap: conduct post-season analysis to evaluate results vs. plan/LY, including drivers of different door project type, and share insights.

Job Qualifications:

Business planning, buying experience with other apparel / footwear or FMCG brandsComprehensive understanding of retail mathAbility to create reports, sales plans based on business senseStrong and demonstrated ability to effectively communicate and influence othersAdvanced knowledge of MS office applications; proficiency in Excel including creating spreadsheets, complex formulas, pivot tables, etc.Good team player and ability to work with the cross functional partners on all aspects of the business

Critical Experiences Gained:

Finance knowledgeProduct insightsEffectively communication and Influencing skillsPlanning experience in sports/FMCG/fast fashion brands is a plusExperience of coding or big data analysis (eg: VB, SQL server, Python) is a plus