Sankey charts are a powerful visualization tool that can help business leaders and analysts understand the flow and efficiency of their operations. By mapping out the flow of materials, services, or information, these charts can reveal bottlenecks and opportunities for improvement.
Sankey charts are named after their creator, Helmut Sankey, a German engineer and statistician who developed the chart in the early 20th century. They are widely used in various fields, including logistics, supply chain management, finance, and network analysis.
One of the key advantages of Sankey charts is that they allow you to easily identify the bottlenecks in your operations and prioritize areas for improvement. Additionally, they can help you identify opportunities for cross-functional collaboration and process optimization.
To create a Sankey chart, you need to have some basic data about the flow of materials, services, or information. The data should include the starting points, endpoints, and quantities or values for each step in the flow.
Next, you can use specialized software such as SankeyMator or Sankey Flowchart to create a Sankey chart. These tools allow you to input the data and generate a chart visualizing the flow, as well as other key metrics such as cycle time, lead time, and Throughput.
Once the chart is created, you can use it to identify areas for improvement and track progress over time. For example, if you notice that materials are flowing slowly through a particular stage in your supply chain, you can investigate the reasons for that bottleneck and work to address it.
Overall, Sankey charts are a valuable tool for business leaders and analysts seeking to understand and optimize the flow and efficiency of their operations. By visualizing the flow of materials, services, or information, these charts can reveal opportunities for improvement and help drive positive change in your business.
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.
