Duluth Trading Co. reduced inventory levels by 25% year over year in Q1 2026, marking its fourth consecutive quarter of year-over-year inventory improvement. The retailer achieved this through an 18% reduction in active SKUs, elimination of low-performing items, and deployment of an integrated enterprise planning platform launched in late 2025. Gross margin dollars per square foot rose 12%, markdowns fell 21%, and the cash conversion cycle shortened by 22 days — from 114 to 92 days. CFO Heena Agrawal emphasized "healthier inventory" defined by higher velocity, margin, and customer relevance.
The workwear retailer reduced inventory levels 25% year over year due to rightsizing buys, clearing excess stock and optimizing receipt scheduling.
Fourth consecutive quarter of improved inventory health
Duluth Trading Co. achieved its fourth consecutive quarter of year-over-year inventory gains in Q1 2026, a result directly tied to strategic SKU management and implementation of its enterprise planning process. Heena Agrawal, SVP and CFO, confirmed the milestone during a June 8 earnings call.
The company reported sustained progress in inventory health metrics across multiple dimensions — including inventory turnover, sell-through rates and aged stock reduction — all contributing to the 25% year-over-year decline in total inventory value. This improvement followed a deliberate multi-quarter initiative to align product assortment with actual demand patterns, rather than historical purchasing habits or vendor-driven push strategies.
SKU rationalization as core operational lever
Duluth Trading cut its active SKU count by 18% over the past 12 months, eliminating slow-moving, low-margin, and redundant items across apparel, footwear and work accessories categories. The effort targeted SKUs with less than 3% contribution to total category revenue and those with inventory turns below 2.5x annually.
analysis shared in the earnings presentation, the top 20% of SKUs now generate 68% of total gross margin — up from 59% two years prior — confirming sharon high-performing items. The retailer also consolidated packaging configurations and reduced color variants by an average of 40%, lowering complexity in procurement, warehousing and replenishment cycles.
Enterprise planning drives synchronized execution
The company deployed a unified enterprise planning platform in late 2025, integrating demand forecasting, supply planning, inventory optimization and financial modeling into a single system. This replaced three legacy tools previously used across merchandising, supply chain and finance functions.
The new system enables daily reconciliation of forecast accuracy at the SKU-store level, with automatic alerts triggered when forecast error exceeds 15%. Receipt scheduling is now dynamically adjusted based on real-time point-of-sale data, warehouse capacity constraints and carrier lead times — reducing late deliveries by 37% and early receipts by 29% compared to the prior fiscal year. As a result, the average time between purchase order issuance and in-stock availability dropped from 14.2 days to 9.6 days.
Financial and operational outcomes
Beyond the 25% year-over-year inventory reduction, Duluth Trading reported a 12% improvement in gross margin dollars foot of retail space and a 21% decrease in markdowns as a percentage of sales in Q1 2026. These gains contributed to operating income growth of 8.3% versus Q1 2025, despite flat comparable store sales.
Working capital efficiency rose markedly: cash conversion cycle shortened by 22 days, from 114 days in Q1 2025 to 92 days in Q1 2026. Inventory carrying costs fell $4.7 million year over year, primarily driven by lower storage fees, insurance premiums and obsolescence reserves.
“We’re not just chasing lower inventory — we’re chasing healthier inventory. That means higher velocity, higher margin, and higher customer relevance. Every SKU we keep must earn its place on the shelf and in our warehouses.” — Heena Agrawal, SVP and CFO of Duluth Trading Co.
Source: Supply Chain Dive
Compiled from international media by the SCI.AI editorial team.
