What is the difference between a banana and a high fashion shoe?
We use the term “supply chain” to broadly describe the path that all products must take from their origin through to the end consumer. But as experts in this space, we know that not all products follow the same path. To paraphrase my earliest SCM professor “the logistics of a banana will look very different than that of a high fashion shoe” - yet we use the same term to define it all: “supply chain”. Even within a single organization in a single industry, products may require very different approaches to inventory management, manufacturing, transportation, or sales. This is how we can find value in segmentation!
Segmentation allows us to divide products into categories, or types, so that we can make more relevant operational decisions and better leverage and analyze our collected data. Tools like Power BI are wonderful for visualizing supply chain data and when combined with segmentation techniques, can significantly enhance our analysis. In this blog, we’ll explore three key segmentation techniques related to products, all within the context of Power BI. As always, we’ll start with a business scenario to help ground these techniques in a real-world application.
Business Case: Segmentation for Supply Chain
Imagine you’ve just been hired as a data analyst at a retail company that relies heavily on data-driven decision-making. With thousands of products in your inventory, the company needs answers to the following questions:
Which products should we focus on as our top performers?
Which products should we move away from and try to liquidate through discounts?
Which products dependably have consistent sales throughout the year?
Lifecycle Segmentation
Products, like living beings, go through different stages in their lifecycle—they’re introduced, they grow in sales, and eventually, they may decline. In Power BI, you can define as many lifecycle stages as needed to suit your analysis. For our business case, we’ll focus on three common stages: New Product, Core/Line Product, and Exit Product. By categorizing products according to these stages in Power BI, you can enrich your analysis and make more informed decisions.
For instance, New Products might require more aggressive marketing and closer inventory management to ensure they gain traction and fill rates stay high. Core/Line Products may instead need supply chains optimized to cost efficiency to maintain profitability. Lastly, Exit Products call for strategies focused on minimizing stock and phasing out quickly, perhaps by applying discounts to accelerate the decrease in stock levels. By using Power BI to track and visualize these stages, you can adjust your strategies in real-time and ensure your resources are allocated appropriately.
ABC Classification
The traditional ABC classification is a widely used method for categorizing products based on their importance, often determined by contribution to overall sales. This technique helps prioritize resources and focus efforts on the most critical items. While you can customize the classification as needed, it typically includes:
A products: The most valuable items, contributing the most to total sales.
B products: Moderately valuable products contributing a reasonable percentage to overall sales and requiring less attention than A products.
C products: The least valuable items with minimal impact on overall sales.
There are specific methods to compute and classify these categories, but we’ll stay high-level for now. Instead, we’ll focus on how you can use this classification system in Power BI to create tailored dashboards that highlight areas for focus. For example, you can set up automated inventory alerts for A products to ensure they are always in stock or use historical sales data to identify potential discount schedules for B and C products to boost sales. This segmentation not only streamlines your inventory management but also helps in making informed decisions that directly impact your bottom line.
In our business case, every product that falls into the A category can be considered a top performer. Power BI allows us to establish automated alerts for low inventory on these items, ensuring that we can act quickly to avoid stock-outs and maximize sales.
Demand Segmentation
Demand segmentation is a technique used to classify products based on their sales consistency throughout the year. By analyzing demand frequency, variation, and standard deviation, you can identify which products have steady demand and which are more variable. This segmentation can help you tailor your inventory management and promotional strategies. There are specific techniques to calculate these demand patterns, but we’ll keep it simple and focus on the practical applications. The following images will illustrate the different types of demand you might encounter using this technique.
Though there is some variation, this product has a fairly consistent sales pattern throughout the year. A continuing trend like this means this product could benefit from an inventory system that prioritizes cost savings and logistical efficiency. Economic Order Quantity or Just in Time Inventory might be good approaches to consider here.
Conversely, this product has intermittent, highly variable, and unreliable demand. The inventory plan for this product would need to be more elastic and dynamic than the one above. Perhaps we hold a higher level of inventory on hand to ensure that we are prepared for these large spikes. Alternatively, is this a product we could convert to manufacture-to-order and only produce for established customer orders?
With Power BI, you can easily visualize demand patterns, identify trends, variability, seasonality, and more. With that information you can better formulate operational systems that meet the needs of the business while being tailored to the specific product segment.
Bringing It All Together
By combining these segmentation techniques—lifecycle, ABC classification, and demand segmentation—you can gain a comprehensive understanding of your products and make more informed decisions. While these segmentation techniques are independent, you can combine them into a segmentation matrix to enrich your analysis further through various perspectives on your products. Power BI is a powerful tool in this process, offering the flexibility and actionable insights needed to manage a complex supply chain effectively, whether tracking the performance of new products, prioritizing your most valuable inventory, or adjusting to demand fluctuations. So, while we may all exist under the “supply chain” umbrella, let's use product segmentation to keep our bananas away from our fashion when it comes to operations.
I hope you found this blog post informative and valuable. Stay tuned for the next one while diving in to our interactive demo:
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