In today's dynamic retail landscape, the ability to optimize inventory planning is crucial for retailers of all sizes. Store clustering has emerged as a powerful strategy to achieve this goal, offering benefits that extend across the spectrum of retail operations. In this blog post, we'll explore the role of store clustering in inventory planning and discuss when retailers of different sizes should start considering its implementation.
What is Store Clustering?
Store clustering involves grouping stores with similar characteristics together based on factors like customer demographics (fashion-forward vs. traditional), geographic location (cold vs. warm), store profile (large, medium or small) and sales performance. This segmentation allows retailers to tailor their strategies and offerings to meet the unique needs of different customer segments, driving enhanced inventory planning and operational efficiency.
Benefits of Store Clustering
Store clustering offers a range of benefits for inventory planning, including planning efficiency, improved forecasting accuracy, assortment localization and reduced supply chain costs. Below are few examples:
- Planning Efficiency and Improved Forecast Accuracy: Typical forecasting revolves around understanding the rate of sale (ROS) for a particular product by door and multiplying that with the time on offer and the number of stores involved. However, your stores will each have a different sales velocity. Do you then go down to plan at the store level to forecast sales by store? That will be very time consuming. That’s where clustering helps; so that you can forecast at the cluster level while maintaining the awareness of the unique characteristic for each store.
- Assortment localization: If you have 20+ stores and want to localize your assortment based on customer demographics, you surely wouldn’t want to plan store by store on which store will be getting a specific fashion forward product. Similarly, if you are planning the start and end dates of your outwear products, you would want to make sure that New York starts receiving Outerwear ahead of Miami. Clustering your stores by Warm-Fashion, Cold-Fashion, Warm-Traditional and Cold-Traditional for example, would help you manage this at a higher level.
- Reduced Supply Chain Costs: By tying your assortment strategy by cluster to your allocation process, not only you make sure that you get an appropriate buy amount, but also you make sure that you allocate your products to the appropriate clusters at the right time; so that you don’t take on the overhead of redistributing the products across your stores.
When Should Retailers Consider Store Clustering?
The decision to implement store clustering depends on several factors, including the size and complexity of the retailer's operations:
Small Retailers: Even small retailers can benefit from store clustering, especially if they operate multiple locations with varying customer demographics and demand patterns. Implementing store clustering early on can help small retailers optimize their inventory planning processes and drive growth.
Medium-Sized Retailers: As retailers grow in size and complexity, the need for more sophisticated inventory planning strategies becomes increasingly important. Medium-sized retailers with multiple stores or diverse customer segments should start considering store clustering to enhance their operational efficiency and competitiveness.
Large Retailers: For large retailers with extensive store networks and complex supply chains, store clustering is often a necessity rather than an option. These retailers typically have diverse customer bases and varying demand patterns across different regions, making store clustering essential for effective inventory planning and resource allocation.
At Toolio we recommend introducing store clusters once your door-count goes beyond 10 or the moment you start seeing different sales patterns (or geographical patterns) between your stores.
How Store Clustering Works
The simplest way to cluster stores is by sales. You can simply create a report of sales of your stores by door, put them on a scatter chart on Excel and try to identify if certain stores are behaving similarly. Accordingly, you can consider those stores as a part of the same cluster, so you can assign a cluster attribute to each store, say Tier 1, Tier 2, Tier 3. Below is what it could look like.
However, this is too simplistic. This surely doesn’t account for the fact that your sales show more variability by each store depending on the department or class of products that you’re looking at. So, to increase the sophistication here, you can do the exercise above by each Department (e.g. Apparel, Footwear or Accessories) or go even a step below and at the class level (e.g. Shirts, Dresses, Jeans, Pants, etc.).
Sales performance simply cannot be the only dimension you create clusters by though. For example, you’ll want to delineate between large stores and small stores, as each store profile will have different capacity considerations. So, you might want to add the store area as a second dimension into your clustering process. To achieve this, you will want to move to a 2-D scatter chart to drive the process. Below is what it could look like.
As you can see, the clustering process can be extremely manual and labor intensive, and the process outlined above is not even precise. That’s why ideally, instead of doing this process manually, you would need to use a clustering algorithm like K-means or other machine learning algorithms like unsupervised clustering in this process.
How Often to Update Store Clusters
Once you’ve defined your clusters, another important consideration is how often to update them. Behavior of your customers and stores will change over time, so you cannot keep your clusters static for too long. Ideally, at the beginning of each planning cycle (and definitely for each season), you update your clusters to account for your store openings, store closures and changing customer preferences over time.
Let’s Sum it All Up
Store clustering is a valuable strategy for retailers of all sizes seeking to optimize their inventory planning processes and drive sustainable growth. By segmenting stores into clusters based on shared characteristics, retailers can tailor their inventory strategies to meet the unique needs of different customer segments, leading to improved forecasting accuracy, reduced supply chain costs, and increased profitability. Whether small, medium-sized, or large, retailers should start considering store clustering as a key tool for maximizing their retail success in today's competitive market.
You can also see that creating clusters manually will be inaccurate and painstaking, especially at lower levels in your hierarchy. You will also have to keep updating them every season. Merchandising solutions like Toolio, fully automate this process, giving you accurate store clusters broken down by KPIs and store attributes over time. If you would like to learn more on how, we’d love to show you how!
