Problem Statement

In the retail industry, Category Managers and Buyers often rely on their experience and instincts when planning the allocation of space in a store. However, these traditional approaches may not be accurate or adaptable to changing market dynamics. Furthermore, numerous factors influencing space planning decisions may go unnoticed by decision makers.

To address these challenges and enable data-driven decision making, the Space and Presentation Data Science team has developed the Space Models. These models incorporate historical trends and consider various factors that impact space planning decisions.

Impact / Value

The Space Models provide optimization recommendations for space allocation across 1800 full-format stores and 200 small-format stores, and it covers about 40 divisions and thousands of categories. This enables us to achieve gradual and continuous improvements in sales.

Solution

The Space Models have been developed at two levels of granularity:

1. Enterprise Models are built at the division level, focusing on specific categories such as Beauty.
2. Category Models focus on individual categories within the divisions, such as Haircare and Skincare.

The process of building Space Models involves the following steps:

1. Building regression curves using Multivariate Regression techniques that predict sales and gross margin based on the allocated space.
2. Determining the optimal space allocation on these curves to maximize sales and gross margin. The optimization involves Mixed Integer Linear Programming to solve a 0/1 Knapsack problem.

Outline of the Talk

1. Illustrating the impact of incorrect space allocation in a store on Guest experience and sales.
2. Highlighting the challenges faced by decision makers and how the Space Models address these issues.
3. Description of the models used and an explanation using diagrams and formulas.
4. Explaining how the recommendations generated by the models are utilized by decision makers to inform their space planning decisions.

Presentation Deck

https://docs.google.com/presentation/d/1mDkiVizkvKK_j2JhVfvvfrxzdcvAnZRG/edit?usp=sharing&ouid=112931649329195659849&rtpof=true&sd=true