Maximize store sales with optimum allocation using Increff Allocation & Replenishment Solution

BESTSELLER, one of the leading casual wear brands of Denmark with 500+ retail outlets and selling in multiple retail formats across India, was experiencing difficulty in analyzing individual store demand, leading to imprecise inventory distribution. 

  • Allocating international-sized products to the domestic market was a challenge
  • The manual practice of allocating inventory through Excel was extremely time-consuming leading to inefficiency within the team, loss of sales opportunities at some locations, and blockage of working capital at others

The brand was looking for a solution that would allow them to analyze store capacity, revenue targets, and stock cover in a single view and facilitate optimum allocation across all stores.                                                                                                                                          


  • Increase ROS by precisely analyzing region-wise store-specific, category, and product demand to distribute inventory mirroring actual demand
  • Allocate and utilize bottom wear sizes without any wastages or understocking for 2D size combinations, an International sizing system unknown to Indian retailers
  • Automate inventory allocation to avoid human decision-making errors and free up resource time for market trends analysis, market visits, etc. thus increasing productivity in other areas
  • Optimize allocation of fringe sizes in Shop-in-shop stores to avoid overstocking in stores where certain sizes absolutely do not sell
  • Allow manual intervention in defining key sizes in new allocation for certain specific Store-Category combinations


Increff Allocation & Replenishment Solution was implemented to analyze store capacity, revenue target, & stock cover all at once, and to improve stock distribution & health through demand-based allocation.

  • Using in-built algorithms, the tool was able to analyze true customer demand served at every store format, with the correct approach considering all business constraints (different approaches for EBO, SIS, etc), and suggest intelligent inventory allocation for 2D sizes. 
  • As per the tool analysis, the brand was able to place the right stock in the required quantity, at the right location, and at the correct size curve. It also facilitated fresh season allocation and mid-season replenishments/replacements with inventory redistribution to increase revenue, reduce inventory holding and optimize sales. 
  • Considering the uniqueness of each store, the tool was able to predict store-wise demand based on the historical performance of attributes (category, MRP bucket, color, gender, etc). 

Other solutions:

  • Accurate fringe size measurement to enable fringe size allocation based on true demand since fringe size buys are limited in quantity
  • Maintain style health with 2D size measurements and solve for brokenness while replenishing stocks contingent on the presence of Warehouse inventory. This is also tailored in such a way that for 2D sizes if one of the key sizes is out of stock then the child SKUs for the same will be allocated.
  • Optimal management of key size input/override designed to handle continuity checks when odd/fringe sizes are in between key sizes in Replenishment, as well as to override key sizes detected by the tool in specific requirements.


Implementing Increff Allocation & Replenishment Solution resulted in:

  • Increase in ROS – By rectifying wrong allocation i.e stock getting distributed to location/region where it was not required while the store which had the demand was deprived of the same.
  • Increase in Efficiency – Reduction in resource time spent on MS excel led to better utilization of time and an increase in overall team efficiency.
  • Higher conversion – Increase in sales as a result of a reduction in stock brokenness and improvement of stock health by implementing replacement suggestions for SKUs in 2D sizes.
  • ~100% accurate analysis of store capacity, revenue targets, stock cover & store DNA by eliminating human errors.

Author: Richa Gupta