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5 Ways to Map your Supply Chain (Part 2)


This is the Final Chapter of our '5 Ways to Map Your Supply Chain' blog post series!


Get ready to dive deeper! Part 2 takes the next critical step, guiding you through the practical implementation of these methods. We'll provide a step-by-step walkthrough for building each map, empowering you to harness the full potential of this data visualization powerhouse.


While Part 1 focused on Route Maps, Heat Maps, and Flow Maps, providing insights into supplier routes, national demand, and delivery analysis, today we delve into two powerful additions:


  • Choropleth Maps: These refined heatmaps incorporate geographical boundaries, allowing us to pinpoint cities with the highest demand in the US.

  • Synoptic Panels: Unlike traditional maps, these versatile visualizations go beyond geographical data. Imagine tracking movie theater occupancy or monitoring football stadium seats - all through images! The possibilities for personalization are endless.


 

Let's get started!


We will start by revisiting the scenario discussed in the last post. Imagine we're running a company with distribution centers across the United States. Each center should satisfy the demand of a specific region in the United States. Additionally, our hypothetical company deals with global suppliers from Asia or Europe, adding complexity to our logistics. Furthermore, each distribution center has its own inventory. Power BI will help us to have visibility of the following two aspects:


  1. Locating Most Popular Cities: Within the United States, which cities are generating our demand?

  2. Inventory Status: Within each distribution center, how are our inventory levels? Do I need to purchase more products?   


 

Option 1: Locate The Most Popular Cities Through Choropleth Maps


In part 1, a heatmap was used to find the location of our demand. While it is suitable for exploratory analysis, it lacks specificity to differentiate geographical regions, instead, it displays patterns or clustering. Now, our objective is distinct – we seek to pinpoint the cities with the highest demand within California. Our aim is to visualise each city's precise geographical locations and compare them with the placement of our distribution centers.

 

While heatmaps may seem like a logical choice, they fall short in effectively highlighting well-defined geographical areas. Look at the image below; it represents a heatmap showcasing demand across California.


Figure 1: Heatmap, visualizing demand in California.


As you can see, it does not differentiate the territory among cities. Choropleth Maps display data for predefined regions, countries, states or even districts. With this tool, we can correctly split the demand and locate it geographically in its corresponding state.


Look at the image!

Figure 2: Choropleth Map, visualizing demand in California.


Option 2: Visualize your Inventory with the Synoptic Panel


Let's get away from geographical maps for this last visualization. While the geographical location is essential for many parts of the supply chain, other areas can also benefit from using map visualizations. Inventory management could use these visualizations to map their warehouses and quickly get insights regarding their inventory levels.


Look at the following image, it is a diagram of our warehouse in California!

Figure 3: Warehouse diagram.

With the Synoptic Panel, we can create a powerful visualization in which we can monitor our inventory levels per product. In our warehouse we have a predefined inventory capacity per product, in the following visualization, we are highlighting those products whose stock is below 5% of their inventory capacity.


At a glance, we can identify that our AirDry inventory is almost over the threshold, suggesting that new stock must be purchased soon. This is a useful and accessible tool for monitoring and optimizing your inventory, allowing you to easily track your stock levels. Besides being more efficient and optimized, Power BI's flexible comparison system allows users to define the threshold for their analysis.


Go to the demo below and see it yourself!



Figure 4: Stock per product.


And there you have it!


We have managed to visualize our supply chain analysis using five different methods and maps available in Power BI.


Let's do a quick recap:

 

  1. Route Maps: Through this visualization, we were able to visualize the journey that our suppliers follow from their location to our distribution centers.

  2. Heat Maps: This was a quick way of finding the demand distribution across the United States.

  3. Flow Maps: Our distribution centers do tons of deliveries yearly in many locations; it is hard to keep track if they are doing it efficiently. With a Flow map, we identified certain deliveries that were far from the origin distribution center, they could have been made by another one closer to the destination.

  4. Choropleth Map: This map provided us with an accurate geographical location of our demand. A powerful alternative to Heat Maps.

  5. Synoptic Panel: Without geographical data, it allowed us to visualize our inventory levels in a friendly manner.

 

This concludes our exploration of mapping techniques for your supply chain! But our journey doesn't end here. Stay tuned for our upcoming series, "5 Ways to Visualize your Supply Chain Processes with Power BI," where we'll dig deeper into leveraging Power BI's full potential for supply chain management.

 

Before you go, interact with the demo, and discover the power of Power BI!




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