Decisions for Retail
and Fashion

Natzka combines actuals, historical patterns, and real-time drivers (promotions, seasonality, markdown cycles, product launches, and phase-outs) to compare scenarios and align stakeholders on one plan. Commit to decisions with clear service-level targets, stock availability goals, and margin trade-offs, ensuring Merchandising, Supply Chain, and Finance work from the same numbers.

Natzka models demand variability, lead times, service-level targets, and replenishment logics to set optimal stock levels by SKU, store, warehouse or distribution channel. Segments inventory by velocity and margin contribution to prioritize working capital on high-performing items while right-sizing buffers on slow movers. What if analysis quantifies the impact of policy changes (safety stock adjustments, reorder points, MOQs) on cash, availability, and margin before you commit, turning inventory from a cost center into a strategic lever.

Natzka models assortment decisions across the full product hierarchy (SKU to department) and the store network (region, city type, format, cluster). Plans align to seasonal collections and OTB budgets, balancing width and depth against each location’s selling capacity and space constraints. Store grading simplifies planning at scale without losing local relevance. What-if scenarios let merchandisers test assortment options before committing buys, reducing markdown risk and keeping flagships, boutiques, and outlets in sync with demand.

Natzka models replenishment at SKU/size/store level, factoring in sell-through velocity, weeks of cover targets, size curves, and store capacity. Plans distinguish between continuative items (basics, carry-over) and seasonal pieces with short lifecycles, applying different service-level rules accordingly. When demand shifts mid-season, inter-store transfers and stock consolidation scenarios move units from slow locations to high-velocity ones, protecting full-price sell-through and reducing end-of-season markdowns. Replenishment proposals align with DC and supplier lead times, pack constraints, and delivery windows, keeping orders executable without manual rework.

Natzka models price elasticity comparingmarkdown paths against sell-through targets, inventory position, and timing constraints. Scenarios weigh trade-offs between revenue recovery, margin protection, and clearance speed, while respecting business rules like minimum margins and discount ladders. The result is a pricing trajectory that balances financial goals with inventory health.

Natzka segments customers using behaviour and economics, links segments to LTV, and makes decisions actionable and specific (where to target, what to offer, and what service level to provide).

Natzka measures true lift, cannibalization, and margin impact across products, stores, and channels, so commercial teams decide which promotions to run, where, and at what depth.

Natzka models profitability at SKU, customer, and channel level by connecting fulfillment costs, reverse logistics, return rates, and service policies to net margin. Scenarios expose how delivery options, returns behavior, and channel mix affect profitability, giving leaders the visibility to adjust pricing or service levels with full awareness of the margin impact. 
Natzka models profitability at SKU, customer, and channel level by connecting fulfillment costs, reverse logistics, return rates, and service policies to net margin. Scenarios expose how delivery options, returns behavior, and channel mix affect profitability, giving leaders the visibility to adjust pricing or service levels with full awareness of the margin impact.