Senior Retail Merchandise & Inventory Planning Consultant — Apparel / Homewares Ecommerce

PLEASE READ THIS FIRST — only apply if you meet ALL of the following This is a senior role. We will ignore generic, templated, or copy-paste proposals. Apply only if you can clearly demonstrate every one of these: 10+ years working IN merchandise / inventory / demand planning — as your actual role, not an adjacent one. Hands-on planning experience for apparel, fashion or homewares ecommerce brands at large scale (8-figure revenue, thousands of SKUs). Small-store, dropship, or marketplace-reseller experience alone is not enough. You can run and explain Open-to-Buy (OTB) and merchandise financial planning without hesitation. A numbers-backed track record of reducing overstock and lifting inventory turns / GMROI / margin, with before-and-after figures you can show us. You build documented systems and SOPs that other people can run You can set up (or direct) automated, repeatable reporting, we want to stop pulling reports by hand. If that's not you, please don't apply. We're specifically after a seasoned operator who has fixed this before, at scale. About us We're Yarn (yarn.com.au) — Australia's largest First Nations fashion and homewares ecommerce business, based in Brisbane. We're a purpose-led brand that licenses contemporary First Nations artwork and pays royalties back to the artists we work with. We run both a B2C retail store and a B2B corporate division, on Shopify. We're an 8-figure business growing around 20% year on year, and our growth has outrun our planning function. The problem we need solved The problem we need solved Our inventory is sitting at roughly 2× where it should be, with hundreds of dead and slow-moving SKUs clogging the warehouse. A lot of our reorder and category logic currently sits with one team member who knows it inside out — it works well, but it isn't documented yet. We want to capture that knowledge, structure it, and build on it so the whole team can run it and the business isn't reliant on any single person being available. Our range has sprawled: 3,000+ SKUs with many variations per line, and we suspect we're over-ranged. We discount too much and sometimes sell at a loss, running frequent storewide promotions without a clear view of true landed cost or which products actually need a markdown. We have no automated reporting. Everything is manual, so we don't have a regular, reliable read on how our collections are moving. We use Inventory Planner (by Sage) and ShipHero, but Inventory Planner isn't fully configured or documented yet, so it isn't helping us make better decisions. What we want you to do First, tell us where we actually stand today. Then build, document and automate the frameworks we're missing so anyone on the team can run them. This is as much a documentation, automation and enablement project as an analytical one. You'll work closely with our existing team, who hold the operational knowledge — your job is to extract it, structure it, benchmark it, automate it, and make it repeatable. We'd like to run this in phases: Phase 1 — Inventory & margin diagnostic (fixed-price milestone) A clear, written picture of where we are: Total inventory vs. optimal, broken down by category, with age (how long stock has been sitting), and a dead / slow / healthy split. Current sell-through, inventory turns, weeks of cover and GMROI by category, benchmarked against what's healthy vs. genuinely poor for apparel/homewares ecommerce. A first read on our true landed cost and contribution margin by category (freight, artist royalties, fulfilment, payment fees, returns), and where we're likely selling at or below cost. A prioritised list of the biggest problems and quickest wins (e.g. what to clear, and how, to free up cash). Phase 2 — Build, document & automate the planning system Turn the diagnosis into repeatable tools, SOPs and automated reporting: Demand forecasting & replenishment logic, documented per category — lead times (our offshore manufacturing runs ~5–6 weeks including freight), safety stock, reorder points and forecast method — so it no longer depends on one person. SKU rationalisation & range architecture: a documented method for deciding which SKUs to keep, consolidate, or retire, and a clear rule for how much newness / how many new design drops a category should carry per year (we put new artwork onto core base products, so range refresh cadence matters a lot to us). Merchandise Financial Planning & Open-to-Buy: a working OTB framework/tool that caps how much we buy per category per period against sales and stock targets — so the overstock problem doesn't recur. A markdown & pricing framework: classify products by lifecycle and role (core vs. seasonal vs. clearance), set margin guardrails, and define when/how deep to discount — instead of blanket storewide sales. Automated reporting & alerting (we have none of this today): Automated weekly collection/category performance reports — how each collection is selling, with sell-through and weeks of cover, week on week, with no manual pulling. New-release tracking — how each new drop performs in its first weeks against expectation, so we spot winners and duds early. Threshold alerts — automatic flags when a category or SKU crosses a defined line (aged stock building, weeks-of-cover too high, GMROI falling, reorder due). Bringing our data sources together (Shopify, Inventory Planner, Triple Whale, GA4) into clear dashboards/reports, using AI-assisted automation where it speeds things up (e.g. auto-generated weekly recaps, anomaly detection). Tooling: properly configure Inventory Planner (lead times, safety stock, supplier settings, seasonality, promo uplift), define the handful of KPIs that actually matter for us, validate its reorder recommendations, and document how the team uses it alongside ShipHero. A clear planning calendar and reporting cadence (what we review weekly / monthly / by season). Phase 3 (optional) — Pricing & elasticity deep-dive / ongoing support A price-elasticity analysis to identify which lines should never be discounted, which need a deeper cut to move, and where we're leaving margin on the table. Optional fractional/ongoing support to embed the frameworks and coach the team. We're open to splitting pricing/elasticity into a separate, smaller engagement if it's not your core strength — the planning, documentation and automation work in Phases 1–2 is the priority. Must-have skills & experience 10+ years in merchandise / inventory / demand planning for apparel, fashion or homewares — seasonality, sizing and range refresh are core to us. Experience at scale — 8-figure revenue, 3,000+ SKUs — not small Shopify stores. Fluency in the fundamentals: Open-to-Buy, merchandise financial planning, sell-through, inventory turns, weeks of cover, GMROI, terminal/aged stock, safety stock, reorder points. A proven, numbers-backed track record of reducing overstock and improving margin with documented systems. Ability to set up (or direct) automated, repeatable reporting rather than manual weekly pulls. Strong Excel/Google Sheets and a genuinely structured, documentation-first way of working. Clear written English and the ability to explain frameworks to a non-specialist team. How we'll work Start with the Phase 1 diagnostic as a fixed-price milestone so we can both confirm fit before scaling up. You'll have access to our sales, inventory and cost data, and direct time with the team member who currently owns reordering. We value direct, specific recommendations with rationale over generic advice — tell us what you'd do and why.