Wholesale Demand Planner

DEMAND PLANNER — SHOPIFY & TIKTOK (HYDROJUG)

Reports to:

Director of Demand Planning (when filled; interim to Jelena Minic, Demand Planning Lead)

You own the Shopify & Tik Tok demand forecast for Hydro Jug — every retail account, every SKU, every week — and you make sure the S&OP forum always has a current, trusted Shopify & Tik Tok demand number to plan from.

Hydro Jug's wholesale business spans Target, Walmart, Costco, Sam's Club, Dick's Sporting Goods, Scheels, Academy, Anthropologie, and TJX — and it's one of the most data-rich forecasting environments in the company. Retailers publish POS data weekly. PO pipelines are visible. Sell-through is measurable. The challenge isn't data — it's doing the work to reconcile it, clean it, and turn it into a forecast the business can act on.

That's your job.

You sit at the intersection of the demand planning team and the wholesale account operations team. The 5 Customer Planning Managers (CPMs) own account-level operational execution — PO timing, OTIF, retailer compliance, floor dates. The National Account Managers (NAMs) own the buyer relationships. You own the forecast underneath all of it. You pull POS data weekly, reconcile it against shipment data, manage the PO pipeline by account and SKU, and feed the Wholesale Demand Review with numbers the CPMs and NAMs can trust.

This is a focused, high-data-volume IC role. You're not building strategy — you're building models and running the numbers with discipline and consistency every single week.

• Builds and maintains the statistical baseline forecast for every Hydro Jug SKU across all wholesale retail accounts
• Incorporates promotional lift assumptions, seasonal curves, and new item ramps for each retailer
• Reconciles the statistical model against the PO pipeline to surface gap-to-forecast by account
• Maintains a 13-week rolling + 26-week horizon forecast by account and by SKU
• Pulls weekly POS data from retailer portals:
  Retail Link (Walmart / Sam's), POL (Target), Syndigo, DSG vendor portal, and others
• Cleans and normalizes POS data across different retailer formats — a Target POS file and a Walmart POS file do not look the same
• Reconciles POS sell-through against shipment data to track inventory at retail (IAR) and weeks-of-supply by account
• Flags early signals of at-risk SKUs (velocity trending down, inventory building, stockout risk) before the retailer calls

• Maintains the active PO pipeline by retailer account and SKU — what's ordered, what's in transit, what's past due
• Partners with the CPMs on PO placement timing — your forecast is the input that tells them when the next PO needs to be placed
• Surfaces PO pipeline gaps to the Director of Demand Planning and the CPMs weekly
• Tracks retailer reorder triggers and automatic replenishment programs (where applicable)

• Owns the weekly Wholesale Demand Review meeting — agenda, pre-reads, data package
• Presents the Shopify DTC + Tik Tok Shop forecast to the Director of Demand Planning and feeds it into the broader Demand Review that rolls into S&OP
• Brings variance analysis: where did last week's sell-through land vs. forecast, and why?

• Tracks MAPE and forecast bias by retailer account and top-50 SKUs weekly
• Publishes the wholesale accuracy scorecard to the Director of Demand Planning
• Does the root-cause work when accuracy misses: was it promo timing, a bad baseline, a lost floor space, or just noise?

• You’ve mapped every retailer portal you’ll be pulling from — you know where to find the data, how often it updates, and what format it comes in.
• You’ve introduced yourself to each of the 5 CPMs. You understand what data they’re already using and what they need from you.
• You’ve audited the current state of the Shopify DTC + Tik Tok Shop forecast — what exists, what the accuracy has been, where the biggest gaps are.
• You have not changed the model yet. You’re learning it first.

• You’re pulling POS data weekly from all major retail portals on a locked schedule.
• The Wholesale Demand Review runs with a clean pre-read: forecast vs.…