In modern business and science, there’s a need to understand systems that emerge from different levels of interaction, known as complex systems. Sankey charts can be an excellent visual representation tool for understanding such systems. This article will explore the use of Sankey charts to understand hierarchical connections in complex systems.
A Sankey chart is a diagram that represents a flow network, a fundamental concept in network analysis based on the principle of conservation of flow. The flow network is represented by a series of interconnected pipes, each carrying a particular substance, from the source to the sink. Each pipe represents a flow direction in the network.
The Sankey chart is created using data that represents the flow rates and the direction of the flow.
Applications of Sankey charts
1. Analysis of complex systems – Sankey charts can be used to represent the flow of information, resources, or materials in complex systems. This makes it easier for stakeholders to understand the dynamics and relationships within the system.
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In engineering systems – Sankey charts can help engineers to visualize the distribution of resources, such as water or electric charges, within a system. It also helps to identify potential bottlenecks and optimize the flow of resources.
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Economics – Sankey charts are commonly used in economics to represent the allocation of resources, particularly in economies with multiple input-output relations.
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Biology – Sankey charts can help to visualize the movement of nutrients, oxygen, hormones, and metabolites in biological systems.
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Engineering – Sankey charts can help to visualize the flow of materials in the construction of civil, industrial, and infrastructure projects, such as roads, waterways, and airports.
Visualizing Hierarchical Connections through Sankey Charts
Sankey charts can help to visualize hierarchical connections between entities, which involves the use of arrows connecting different nodes at different levels of the hierarchy.
For example, consider a scenario where there is a network of companies in a supply chain, with each node representing a supplier, manufacturer, retailer, and end-consumer. Each node has input and output arrows, indicating the flow of materials from one level to another. The arrows can be colored, sized, and annotated to indicate the weight of the flow or the capacity of the system.
Alternatively, consider a scenario where a company is trying to optimize its supply chain to reduce costs and increase efficiency. This can be represented using a Sankey chart with the company’s suppliers representing upstream nodes, with the flow of materials represented by the arrows, and the downstream nodes representing the retailers and end-consumers. The arrows can be annotated with the amount of material being transported and the time it takes to move.
Advantages and Limitations of Sankey Charts
Sankey charts are a versatile visualization tool that can help to understand complex systems. However, they do have some limitations.
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Limited interpretability of data – Sankey charts can be difficult to read and understand the flow of information. The interpretation of the data can depend on the expertise of the reader.
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Need for more data to create informative graphs – The more data available, the more complex the Sankey chart can be to create. This can impact the time it takes to create a graph and the effort required to understand its content.
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Not suitable for dynamic data – Sankey charts are based on static data, which can limit their usefulness in understanding how a system is changing over time.
Conclusion
Sankey charts are a useful visual representation tool for understanding hierarchical connections in complex systems. They can help stakeholders to visualize the dynamics and relationships within the system and identify potential bottlenecks. The ability to use different colors and sizes for arrows enables more granular analysis. Nevertheless, limitations such as the need for more data to create informative graphs and the fact that they are based on static data limits their value in understanding how a system is changing.
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