📌 At a glance: A top Indian home and furnishing brand implemented Increff's Merchandising Software across three warehouse locations — using demand planning and business intelligence to optimize regional inventory allocation. Overall RU fulfillment improved from 78.5% to 91% in five months. The Delhi warehouse — the most underperforming at 65% — climbed to 92%.
What Is This Case Study About?
Furniture is one of the hardest categories to manage across a multi-warehouse network. Units are bulky, logistics costs are high, and getting the wrong inventory to the wrong location is expensive to fix. This case study is about how a leading Indian home and furnishing brand used Increff's demand planning and inventory management software to solve a regional distribution problem — getting the right products to the right warehouses based on actual local demand, not assumptions.
Client Overview
- Type: Home and furnishing retail brand
- Region: India — warehouses in Bengaluru, Delhi, and Mumbai
- Industry: Home décor and furniture retail
- Solution: Increff Merchandising Software — Regional Utilization (RU) module
- Objective: Optimize inventory allocation across warehouse locations using pincode-level demand planning, reduce logistics costs, improve fulfillment rates, and lower unfulfilled orders across all regions
Challenges Faced: Why Regional Inventory Misallocation Is Especially Costly in Furniture Retail
In most retail categories, sending inventory to the wrong location is an inconvenience. In furniture, it's a significant cost. Bulky, high-value items that need to be reshipped between warehouses eat into margin fast — and customers waiting on a sofa or dining table don't have the same patience as someone waiting on a T-shirt.
1. Warehouse network limited to three locations — with uneven demand coverage
The brand operated from Bengaluru, Delhi, and Mumbai. That works if demand distributes evenly across those three regions. It doesn't. Customer pincodes don't align neatly with warehouse catchment areas, and without data mapping demand to location, inventory was being allocated based on guesswork rather than evidence.
2. Delhi warehouse fulfillment stuck at 65%
The northern region was being underserved. The Delhi warehouse had a fulfillment rate of just 65% — meaning more than one in three orders couldn't be fulfilled from the nearest location. Those orders had to be sourced from Bengaluru or Mumbai, adding logistics cost and delivery time to every one of them.
3. No pincode-level demand visibility
Without business intelligence mapping customer pincodes to actual purchasing patterns, there was no reliable way to forecast which SKUs were needed at which warehouse. Inventory decisions were based on aggregate data that masked the regional variation driving the problem.
4. Inter-warehouse transfers were reactive, not planned
When a warehouse ran short, inventory was transferred from another location. But because demand hadn't been forecasted at the SKU level per warehouse, these transfers were firefighting — expensive, slow, and often leaving the donor warehouse underprepared for its own demand.
5. Logistics costs rising as orders sourced from non-optimal locations
Every order fulfilled from the wrong warehouse — because the right one didn't have stock — added unnecessary shipping distance and cost. In a category where last-mile logistics for bulky items is already expensive, this compounded quickly.
Increff's Solution: Pincode-Level Demand Planning and Smart Inventory Allocation
Increff implemented its Merchandising Software with a focus on Regional Utilization (RU) — using historical sales data and business intelligence to map demand at the warehouse level and allocate inventory accordingly.
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Pincode-Level Demand Mapping and Forecasting
Customer pincodes from historical sales data were mapped to each of the three warehouse locations. From there, Increff's system forecasted demand for each SKU at each warehouse — not as a national aggregate, but as a granular, location-specific demand signal. This is the foundation of effective regional inventory management. You can't allocate correctly if you don't know where the demand actually is.
Style Ranking for Warehouse-Level Inventory Optimization
Increff's merchandising software ranked styles by their estimated selling potential at each warehouse location. Fast-moving SKUs for a given region were prioritized for that region's warehouse. Slower movers weren't sent to locations where they'd sit. This alone meaningfully improved inventory turns and reduced the holding cost of misallocated stock.
Data-Driven Inter-Warehouse Transfers
Based on forecasted sales, Increff recommended inter-warehouse transfers — moving inventory from the Bengaluru and Mumbai donor warehouses to Delhi to cover the demand gap in the northern region. Critically, the transfers were sized to maintain optimum inventory levels at both the receiving and donor warehouses simultaneously. No longer reactive. No longer based on gut feel.
Business Intelligence for Ongoing Regional Utilization Decisions
The platform gave the brand's merchandising team ongoing visibility into week-on-week fulfillment rates by warehouse — the data visible in the WoW RU Fulfillment charts. With that business intelligence layer in place, future allocation decisions are made from evidence, not estimation.
Results: Measurable Impact Delivered by Increff
"In five months, the Delhi warehouse went from a 65% fulfillment rate to 92% — a 27-point improvement driven entirely by better demand planning and targeted inventory transfers, not additional warehouses or headcount."
Key Outcomes Summary
- Overall regional fulfillment improved from 78.5% to 91% across the three-warehouse network in just five months
- Delhi warehouse fulfillment jumped from 65% to 92% — the biggest single improvement, driven by targeted inventory transfers based on northern region demand data
- Logistics costs reduced by minimizing orders fulfilled from non-optimal warehouse locations — particularly important in a bulky, high-freight category like furniture
- Unfulfilled orders decreased as inventory became available closer to actual demand — fewer customers waiting, fewer orders lost
- Pincode-level demand planning replaced assumption-based allocation, giving the merchandising team SKU-level clarity on what's needed where
- Business intelligence dashboards now track week-on-week RU fulfillment by warehouse, making regional inventory decisions continuous rather than periodic
Frequently Asked Questions
What is regional utilization (RU) in inventory management, and why does it matter for furniture retail?
Regional utilization measures how effectively a brand's inventory is distributed across its warehouse network relative to actual regional demand. In most retail categories, poor RU is a margin issue. In furniture, it's a margin and logistics issue — because moving bulky items between locations to cover fulfillment gaps is disproportionately expensive. A high RU fulfillment rate means the right products are in the right warehouses before the order is placed, not reshipped after the fact.
How does pincode-level demand planning improve inventory allocation?
Most inventory management systems plan at the city or region level — broad enough to miss the nuance of where customers actually are and what they're buying. Pincode-level demand planning maps historical purchase data to specific delivery zones, then forecasts SKU-level demand for each warehouse catchment area. The result is allocation decisions grounded in where demand actually exists, not where you assume it does. For a three-warehouse network serving a geographically diverse country like India, that difference is significant.
What role does business intelligence play in warehouse inventory optimization?
Business intelligence in this context means having visibility into fulfillment performance at the warehouse level — week by week, SKU by SKU — so that allocation decisions are made from data rather than periodic manual reviews. Without that visibility, a warehouse can be underperforming for weeks before anyone notices. With it, the merchandising team sees the gap, understands the cause, and can act before it becomes a customer satisfaction or logistics cost problem. It's the difference between managing inventory reactively and managing it predictively.
How does Increff's merchandising software handle inter-warehouse inventory transfers?
Rather than triggering transfers only when a stockout occurs, Increff's demand planning engine forecasts regional demand and recommends transfers proactively — sized to cover the receiving warehouse's need without depleting the donor warehouse below its own optimum level. This is a balance that manual transfer decisions rarely get right, because the data required to make that call accurately — forecasted demand at both locations simultaneously — isn't available without the right inventory management software.
Why is demand planning especially critical for home and furnishing brands?
A few reasons specific to the category. Furniture SKUs are expensive to hold, expensive to move, and slow to turn relative to fashion or FMCG. Misallocating inventory doesn't just mean a stockout — it means capital tied up in the wrong location for an extended period, logistics costs to fix it, and a customer who ordered a piece of furniture and waited longer than they should have. Getting allocation right the first time, using demand planning, has a compounding effect on margin, customer satisfaction, and logistics efficiency that's harder to quantify in faster-moving categories but very real.
Can Increff's inventory management software scale as a brand adds more warehouse locations?
Yes. The regional utilization module is designed to handle multi-node warehouse networks — analyzing demand at each node based on its catchment area and forecasting accordingly. Adding a new warehouse means adding a new demand catchment zone and a new set of SKU-level forecasts. The platform's business intelligence layer updates to reflect the expanded network, and inter-warehouse transfer recommendations adjust to include the new location. For a home and furnishing brand planning to expand beyond its current three warehouses, the system scales with the network rather than requiring reconfiguration.
Why Increff for Home and Furnishing Inventory Management?
Home and furnishing is a category where inventory management errors are expensive in ways they aren't in lighter, faster categories. Increff's merchandising software is built for that complexity:
- Pincode-level demand planning — allocation decisions based on where customers actually are, not regional assumptions
- Style ranking at the warehouse level — fast movers go to the locations where they'll sell fastest
- Planned inter-warehouse transfers — proactive, data-driven, and sized to protect both receiving and donor warehouses
- Business intelligence dashboards — week-on-week visibility into RU fulfillment by warehouse, making regional inventory performance measurable and manageable
- Proven results in Indian home and furnishing retail — 91% overall fulfillment and 92% Delhi fulfillment achieved in five months
Ready to Stop Guessing Where Your Inventory Should Be?
If your warehouse network is fulfilling orders from the wrong locations, your logistics costs are rising, or your regional fulfillment rates don't reflect your actual inventory levels — the problem is in the allocation, not the stock.
Book a demo with Increff today