Diagramming for
Supply Chain Management

Supply chain planning

Using network flows, Sankey diagrams, and gantt charts, yFiles can visually model all flows in a supply chain. This works for lean production, just in time and just in sequence production where the goal is minimizing time, labor, and materials.

Network flow algorithms can help ensure that resources flow from one location to another within a network as efficiently as possible. This visualization through time and space in the navigating graph (see the network flow demo) shows the capacity of each path, which can be indicated by its thickness in the graph. The nodes, which represent hubs, can help pinpoint potential bottlenecks. Depending on the case, the manipulation of the nodes can also be used to manage and control the supply chain.

Sankey diagrams are used for visualizing flow information, with the thickness of the edges proportional to the flow quantity. Here, ingoing and outgoing data points are visualized over time, facilitating the identification of problems in the flow. For example, in a lean production environment, managers can use Sankey diagrams to ensure that parts and resources are available precisely when and where they’re needed. The more complex the production flow gets, the more helpful visualization becomes in pinpointing potential problems.

Gantt charts can visualize an activity that has a start and end date, and optionally a lead time and follow-up time. Also, an activity can depend on other activities, which is very helpful in representing SCM dependencies, and how to resolve them. Gantt charts and the Sankey diagrams can link input/output volume to timestamps and geodata in the production process. This can assist in ensuring quality and compliance for a complete bill of materials (BOM), where a comprehensive inventory of materials and goods used in production is required.

Supply chain simulation

As supply chains grow in complexity, simulation becomes an increasingly valuable tool. By simulating various network and flow scenarios, teams can test and compare alternatives prior to investing in production facilities. Equally, individual variables or nodes in an existing network can be isolated in a simulation to determine the effects on the rest of the supply chain. The process mining and interactive maps features can be used to simulate upstream and downstream supply chain process issues. For example, when filtering for one node, the heat map in the process mining tool shows which elements are nearing capacity as a result. Interactive maps can also visualize relations in space as well as time – for example, when aggregating geodata about the location or origin of products.

Supply chain analysis

Analysis of the entire supply chain and network is perhaps the most impactful element of SCM. By breaking down the chain into phases and stages, from the acquisition of raw materials all the way through to delivery of a product to customers, it’s possible to find inefficiencies and improve the overall business outcomes. In the network monitoring graph, you can watch traffic flowing through the network and even influence the network by deactivating nodes. This ability to influence the data flow and see what happens when a node fails, is helpful in identifying points of weakness and failure. It’s also possible to connect a graph with real-time processes to manage SCM in real time, not just to perform analysis.

The neighborhood view graph can be used to show root cause analysis (predecessors) and dependency analysis (successors) of various phases and actors in a supply chain. This feature can be used for troubleshooting, e.g., product recall (based on units such as a production batch) or understanding and even predicting areas of inefficiency.

Critical path analysis is used in project and supply chain management to identify the individual tasks – and the time required for those tasks – that must be completed if a project or production process is to be successful. The critical path analysis demo shows how yFiles allows you to visualize all of the components and relations in a complex process and to map respective critical paths.

Supply chain optimization

The Fraud Detection Demo has three powerful components that can be applied to visualizing and optimizing SCM. The main visualization graph allows you to see related data points as nodes and rings which could be suppliers in a procurement process. (In the demo, the rings designate fraudsters in a financial services scenario.) Second, there is a timeline component, which shows when an event or incident was created or occurred. The final view combines the details of each ring with its timeline. You can show or hide specific time periods using the sliding time window. This selective data visualization is useful for analyzing details in a process that has a time component. For example, in an SCM scenario, you can visualize dependencies among the flow of parts and the sequence of parts suppliers in a production chain over time.

In the Large Graph Aggregation Demo, it’s possible to take huge amounts of data from complex supply chains and aggregate the data, e.g., by source country of products, or by continent or city. Thus, you can visualize on a map (using the interactive map tool) and zoom down to visualize specific nodes of a supply chain. Depending on the variables you are interested in analyzing, you can filter by narrow criteria to understand your supply chain data better. You can also modify the parameters of various processes to represent objects in detail and find what’s important to the process, such as pinpointing a machine capacity issue or a lack of raw materials.

The Interactive Aggregation Demo shows how to analyze a graph by aggregating nodes. As supply chains are often huge networks with related and unrelated nodes, with the mechanics of aggregation in this type of visualization (expand and collapse) it is easier to focus on individual areas of the supply chain. Areas that are not so relevant at the moment of observation can be "hidden" without disappearing completely.