Building a pricing architecture that protects margin and brand positioning while staying competitive.

Day to day: RRP ladders and price brackets by category; GM targets; landed cost & duties; competitive benchmarks and psychological price points; price testing; markdown planning.

KPIs: GM%, ASP vs target, markdown cost % of sales, terminal margin, promo ROI, discount dependency.

Translating brand strategy and demand signals into the right SKU mix by channel/region/cluster - optimising breadth vs depth to maximise full-price sell-through and minimise markdown.

Day to day: category mix; option counts and target depths by drop; attribute mix (fit, fabric, colour); size curves; cluster tailoring (store grading, channel strategy, exclusives); gap & cannibalisation analysis; newness vs continuity balance.

KPIs: sell-in adoption (WHS); full-price sell-through, option productivity, depth-to-breadth ratio, WOC, on-shelf availability by size, markdown mix, missed-demand (stock-out) rate.

A rolling governance system that reconciles budget with on-hand, on-order and planned receipts to control how much you buy and when you land it.

Day to day: category/channel OTB by month & drop; BOM/EOM/WOS targets; receipts phasing & intake calendar; committed vs uncommitted OTB and contingency; in-season reforecasting (sales, markdowns, returns); vendor/lead-time/MOQ constraints.

KPIs: OTB variance (value & %), uncommitted OTB %, receipts vs plan, intake phasing adherence, WOS adherence, aged stock %, cash consumed vs budget, cancel/late-delivery rate, stock turn.

Producing a rolling, multi-level view of demand (brand → category → style/colour/size/door) that sets buys, flow and risk.

Day to day: hierarchical forecasting with reconciliation; seasonality curves and trend; newness modelling via analogues/attribute twins; launch curves; size distribution; demand sensing from forward signals (traffic, waitlists, pre-orders, search/social, wholesale orderbook), price/promo/weather uplift; cannibalisation checks; channel/geo mix; inventory-aware “true demand” (lost-sales uplift).

KPIs: forecast efficiency, forecast bias (ME%), lost-sales rate, launch-week accuracy, sell-through variance vs plan, inventory turns vs target, markdown dependency.

Keeping stock in the right place at the right level to meet demand at full price while protecting cash.

Day to day: WOS targets; safety-stock and review policies (min/max, reorder-point, target-WOC); network balancing across DC ↔ store ↔ e-com (incl. omnichannel services such as BOPUS or click & collect); inbound scheduling; launch reservations/pre-allocations; inter-store/DC transfers and consolidations; ageing control and exit routes (RTV, outlet, markdown); stock accuracy (cycle counts and stocktakes).

KPIs: availability/in-stock %, stock turn, WOC vs target, lost-sales rate, transfer success rate & cost, inventory accuracy/shrink %, RTV recovery %, markdown cost % and terminal margin.

The first distribution of launch inventory across stores and e-com using door grades, capacity and demand signals to maximise early sell-through while protecting availability.

Day to day: door grading & capacity; presentation minimums/visual standards; e-com vs store split; cluster-level size curves; key-door seeding and exclusives; launch reservations/embargoes; holdbacks for read-and-react; logistics timing & store readiness checks; post-launch reforecast with rapid rebalancing (top-ups, transfers, PO pulls/cancels); exception handling for late/short/QC issues.

KPIs: week-1/4 sell-through; on-time launch availability (% doors live day-1); size availability & broken-size rate; stock-out incidence in launch window; allocation accuracy vs demand; reallocation speed (days to action) and impact; full-price sell-through at week-4; presentation-minimum compliance; key-door sell-out vs target; launch return/QC rate.

Rules-based, system-driven refills of proven styles to keep availability high at full price with minimal inventory.

Day to day: policy design (min/max, target-WOC, reorder-point); review cadence and lead-time mapping; vendor SLAs & OTIF; DC→ store and DC→ e-com logic; demand-sensing & promo uplift; substitution/like-for-like rules (size/colour); backorder & waitlist handling; automation in RMS/OMS with human override; exception workflows (stock-outs, spikes, supply delays).

KPIs: on-shelf availability (OSA) %, lost-sales rate, out-of-stock rate, fill rate, WOC targets, replenishment accuracy (order vs need), time-to-recover from stock-out, vendor OTIF %, inventory turns, end-of-season stock on proven lines, backorder rate, size-breakage rate.

Designing a promo architecture that moves risk and drives demand without eroding brand or margin.

Day to day: promo framework by objective (launch acceleration, in-season traffic, clearance); eligibility rules by lifecycle; customer segmentation (VIP/loyalty, new, staff, wholesale); channel/region rules (e-com, retail, marketplaces); mechanics and depth (thresholds, %-off, bundles/multi-buy, GWP, vouchers, dynamic markdown walls); duration & cadence guardrails; stock targeting (aged, size-broken, end-of-line); creative/messaging standards.

KPIs: incremental sales & margin lift, promo ROI (incremental margin ÷ discount cost), price realisation vs RRP, markdown/promo mix %, UPT & AOV uplift, traffic & conversion vs baseline, cannibalisation vs halo effect, pull-forward & post-promo dip, aged-stock burn-down, discount dependency.

Designing the org and operating rhythm so decisions are fast, accountability is clear, and planning scales across channels and regions.

Day to day: role design across Merchandising, Planning, Buying, Allocation, Replenishment, Pricing/Promo, and Analytics; spans & layers; competency framework and career paths; decision rights/RACI with Design, Product Development, Sourcing, Retail, E-com, Finance and Logistics; operating cadence (weekly trade, monthly OTB, quarterly range/strategy; S&OE/S&OP); hand-offs (brief → range build → buy → launch → in-season); headcount modelling and hiring roadmaps; onboarding and training plans; meeting architecture and escalation paths; peak/holiday readiness and cover plans; change management for new processes.

KPIs: decision cycle time (brief→buy, trade actions), plan adherence (OTB, intake, range guardrails), forecast accuracy/bias, availability & sell-through vs target, promo compliance, aged-stock %, intake phasing adherence, team capacity/utilisation, time-to-fill/time-to-productivity, engagement/retention, SOP adoption & audit scores.