Illustrative Case Study — 110 bps of margin improvement with $3.2M less inventory
- Client profile: $220M omnichannel specialty retailer
- Footprint: 65 stores plus ecommerce
- Assortment: Approximately 18,000 active SKUs
- Core challenge: Revenue was growing faster than profit, while inventory and markdown exposure were increasing
- Engagement: 9 weeks across commercial diagnosis, financial modeling, and a category/store pilot
- Primary objective: Determine which products, promotions, customers, and channels actually created profitable growth
- Commercial data foundation — POS, ecommerce, ERP, inventory, loyalty, returns, and fulfillment information were combined into a consistent view of product and customer economics.
- True-margin analysis — Product and channel performance was evaluated after promotions, markdowns, returns, fulfillment, and other costs—not revenue alone.
- Demand forecasting — Historical sales and inventory patterns were used to improve replenishment and understand where stock was likely to become excess or unavailable.
- Promotion modeling — Promotions were analyzed to distinguish genuinely incremental demand from sales that likely would have happened without the discount.
- Assortment and allocation analysis — SKU productivity and store-level demand were used to identify where assortment complexity and inventory placement were hurting returns.
- Decision dashboard — Merchandising, finance, and operations teams shared the same view of margin, inventory, markdowns, and product performance when making category decisions.
The problem
Revenue had grown for three consecutive years.
Profit had not kept pace.
Merchants were running more promotions to protect volume. Inventory was growing faster than sales. Certain stores were marking products down while other locations stocked out of the same items. Ecommerce continued to expand, but returns and fulfillment costs were changing its economics.
The leadership question was deceptively simple:
Where are we actually making money?
What we found
Looking at sales alone gave the wrong answer.
Several high-volume products produced weak contribution after promotions, markdowns, returns, and fulfillment were included. Some lower-volume categories generated better economics and stronger repeat behavior.
Promotions also behaved differently than expected. Some generated meaningful incremental demand. Others mostly discounted purchases customers were likely to make anyway.
Inventory had a similar problem. The company had enough product overall, but the assortment was fragmented across too many slow-moving SKUs and poorly matched to local demand.
What we changed
We built a common view of product, customer, store, and channel economics.
Merchants remained responsible for brand, customer, and assortment judgment. The analytical layer allowed them to see the financial consequences of those decisions more clearly.
We tested:
- Promotion depth and timing
- SKU rationalization
- Store-level assortment
- Inventory transfers
- Replenishment rules
- Markdown timing
- Channel profitability
Three categories and 20 stores were used as the initial pilot.
The result
The modeled changes improved gross margin by approximately 110 basis points.
Average inventory declined around 8.5%, releasing approximately $3.2M in working capital.
Markdown dollars declined approximately 15% as inventory was positioned earlier and slower products were addressed before end-of-season clearance.
The company did not need fewer commercial ideas.
It needed to know which ideas deserved inventory, promotion dollars, and management attention.
