Cluster Suppliers Using K Means Clustering in Supply Chain Management 🏭📦

Описание: Hey supply chain and manufacturing professionals! 🏭📦
Today, let’s use K-Means Clustering to group suppliers based on their performance metrics. By grouping suppliers into clusters, you can quickly see which ones are performing well and which ones need improvement. Here's how it works:

Import Libraries:
We use pandas to handle the data, KMeans from scikit-learn to apply the clustering algorithm, and seaborn and matplotlib for visualization.
Load Data:
We have a dataset of suppliers with features like:
On_Time_Delivery_Rate: Percentage of on-time deliveries.
Average_Delivery_Cost: Average cost of delivery.
Product_Quality_Score: Product quality score (rating from 1 to 5).
Standardize the Data (optional):
Standardization is often used to put all features on the same scale, especially if there is a large range of values. In this example, we proceed without standardization for simplicity.
Apply K-Means Clustering:
We use K-Means to create 3 clusters (n_clusters=3). Each supplier is assigned to a specific cluster based on similarity.
Clustering helps us see natural groupings in the data. For example, suppliers with similar delivery rates, costs, and quality scores will fall into the same group.
Visualize the Clusters:
We use a scatter plot to visualize the suppliers and color-code them based on their clusters. This way, we can easily see which suppliers belong to which group.
Show the Cluster Centers:
The cluster centers represent the average values of the features in each cluster. These centers are useful for understanding the general characteristics of each group.
Output Example:

Clusters Visualization: The scatter plot groups suppliers into 3 clusters based on their performance metrics. Each cluster will be a different color, making it easy to identify the groups visually.
Cluster Centers: The cluster centers are printed, showing the average characteristics of the suppliers in each cluster.
Why Use K-Means Clustering for Supply Chain?:

Identify High and Low Performers: By clustering suppliers, you can easily identify high-performing suppliers (with low costs, high delivery rates, and good quality) and low-performing suppliers.
Supplier Segmentation: Clustering helps in segmenting suppliers for targeted improvements, negotiations, or prioritizing partnerships.
Improvement Opportunities: By analyzing clusters, you can identify where certain suppliers fall short and focus on improving those specific aspects.

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