- A Sankey diagram is a type of flow diagram used to visualize the movement or transfer of resources, values, or quantities between different stages, processes, or categories.
- It is distinguished by its use of arrows or paths whose width is proportional to the magnitude of the flow they represent. This proportionality ensures that the diagram not only communicates the direction of movement but also conveys the relative scale of the flows. Sankey diagrams are especially effective for understanding complex systems where multiple inputs, processes, and outputs interact simultaneously.
- The primary advantage of a Sankey diagram is its ability to clearly illustrate part-to-whole relationships and flow distribution. For example, in energy analysis, Sankey diagrams are used to show how primary energy sources—such as coal, oil, natural gas, and renewables—are transformed and consumed across different sectors like transportation, industry, and households. In this context, the varying thickness of the arrows highlights energy efficiency and losses, making inefficiencies or waste immediately apparent. This part-to-whole visualization provides insights that traditional charts, such as bar graphs or pie charts, may struggle to communicate effectively.
- Sankey diagrams are not limited to energy or resource analysis. They are widely applied in finance, logistics, marketing, and data science. In finance, they can represent the flow of funds across departments or investment categories. In logistics and supply chain management, they show the movement of goods between suppliers, distributors, and customers. Marketers use them to track customer journeys across touchpoints, while data scientists employ Sankey diagrams to visualize categorical transitions, such as user activity paths on a website or feature importance in predictive models. This adaptability makes them a versatile tool for both business and research.
- Another strength of Sankey diagrams lies in their ability to handle complexity with clarity. Unlike linear charts, which may oversimplify or obscure the dynamics of a system, Sankey diagrams highlight the interplay between multiple sources and destinations. By visually balancing direction, magnitude, and distribution, they help uncover patterns, bottlenecks, or imbalances in processes. Interactive digital versions of Sankey diagrams further enhance interpretability, allowing users to drill down into flows, hover over paths for details, and filter categories dynamically.
- Despite their benefits, Sankey diagrams have limitations. They require careful design to avoid becoming cluttered or overwhelming, particularly when the system has many categories or flows. Overlapping arrows or excessive branching can make interpretation difficult. Additionally, constructing Sankey diagrams often requires detailed and well-structured data on flows, which may not always be available. Choosing appropriate scales, colors, and labels is essential for accuracy and readability. Without these considerations, Sankey diagrams risk becoming visually appealing but misleading.
- In practice, Sankey diagrams are widely recognized as a communication tool as much as an analytical one. They are effective for presenting findings to both technical and non-technical audiences because of their intuitive and engaging design. Policymakers, business leaders, and stakeholders can easily grasp the proportions of flows, inefficiencies, and transitions without needing advanced statistical knowledge. This accessibility has made Sankey diagrams a popular choice in sustainability reporting, business intelligence dashboards, and educational materials.
- In summary, a Sankey diagram is a powerful visualization tool that represents flows between categories using arrows scaled by magnitude. It provides a clear and intuitive way to understand the distribution, direction, and relative importance of quantities within complex systems. While it requires careful data preparation and thoughtful design to avoid clutter, its ability to reveal inefficiencies, highlight relationships, and communicate part-to-whole dynamics makes it an indispensable tool in modern analytics and decision-making.
