The Pareto Principle, known as the “80:20 Rule” states that 80% of the results come from 20% of the causes. It is therefore not surprising to find that in most companies 80% of the sales come from just 20% of the products which implies a long tail of low revenue products. How do they address this issue?
The answer is to apply a supply chain segmentation strategy, which means to consider the characteristics of your products, channels and service models in order to create the most profitable business. Segmentation not only helps to reduce the management complexities of a long-tail supply chain, but also to address other big issues such as demand variability and standardization as described in 6 reasons to consider supply chain segmentation.
We propose the following 3 steps to implement a supply chain segmentation strategy.
Step 1: Differentiate products by clustering analysis
The first step of segmentation is to differentiate products by groups. Products in the same group should have similar characteristics such as customer type, demand variability, profit margin, category etc.
It is intuitive to define groups by individual factors. For example, we can assume all the Andriod OS smartphones are similar to each other. This is probably the most common grouping method used by current supply chain managers.
However, it may be beneficial to consider the joining effect of different factors? For example, Andriod OS smartphones come with different brands, different prices, and different popularity. Does it make more sense to consider the [Name Redacted] as more similar to [Name Redacted] than to [Name Redacted] (an Android OS smartphone)? The joining effect will grow exponentially as the number of factors increases.
Fortunately, you can use clustering analysis to handle this difficult task. The goal of clustering is to organize every observed data point into meaningful structures. It depends on continuous and categorical variables to allocate each product in geometrical space. The most iconic product of each group will be at the center of each cluster, then all similar members will surround it. Eventually, multiple clusters will be formed, similar to different cloud formations in the sky.
Step 2: Design and implement differentiated programs for different clusters
The second step of segmentation is to design and implement differentiated inventory policies, replenishment programs, and networks for each cluster.
Products in the price sensitive market with many substitutions available should implement push-based supply chain. For example, groceries such as beer, pasta and food cans are good candidates for push based supply chain. These products have very stable demand and long sales windows.
Products enjoy high brand recognition but also require complicated customizations should implement pull-based supply chain. The manufacturer does not hold finished goods and only responds to specific orders.
Step 3: Create a Center of Excellence for continuous analysis, monitoring and learning
Most companies’ product portfolio consistently changes over time. The clustering analysis needs to be updated frequently to reflect the changes in the product life cycle. Supply chain polices also need to be automatically deployed and managed accordingly.
Leading companies today have started to build in house supply chain analytics capabilities often called Centers of Excellence (CoE). These establish, implement, and monitor segmentation policies, and then continuously learn as policies are executed over time. A CoE is usually managed by a small team, who is responsible to create the analytics behind the segmentation, and then monitor the implementation results against the design plan.
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