Sankey charts are a type of flow diagram that are used to represent the flow of materials, information, or ideas between objects or processes. They are often used in operations research, logistics, and supply chain management, as well as in other fields such as finance and project management.

One of the benefits of using a Sankey chart is that it allows you to easily see how different objects or processes are connected and how they flow into each other. This can be helpful in identifying bottlenecks or areas where improvements can be made.

Another advantage of Sankey charts is that they are easy to create using various flowcharting tools such as Microsoft Visio, Lucidchart, SmartDraw and many others. These tools allow you to create a Sankey chart with just a few clicks, making it easy to create and update diagrams as needed.

When creating a Sankey chart, it’s important to keep in mind the following tips:

1. Identify the key objects or processes that you want to include in the diagram
2. Determine the direction of the flow, starting and ending points of each process or object
3. Use arrows to show the flow of materials, information, or ideas between objects or processes
4. Include details such as quantities, frequencies, or other relevant information to help understand the diagram
5. Make sure to label and organize the diagram for easy understanding
6. Test the diagram to ensure it’s accurate and complete

Another important aspect to note is that Sankey charts can be used to represent both material and information flow, and it can also be used to present the flow of decision and actions.

In summary, Sankey charts are a valuable tool for representing the flow of materials, information, or ideas between objects or processes. By following the tips outlined above, you can create effective diagrams and gain valuable insights into your operations, supply chain or any other process.

SankeyMaster

SankeyMaster is your go-to tool for creating complex Sankey charts . Easily enter data and create Sankey charts that accurately reveal intricate data relationships.