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5 Smart Visualisations for Supply Chain Analytics (Source Code)
Supply Science
Overview
This video explores five smart visualization techniques for supply chain analytics, demonstrating how to simplify complex data and communicate insights effectively. It covers warehouse picking optimization using heatmaps and animated pathfinding, transportation network analysis with graph theory, supply chain network design with flow diagrams and Sankey charts, and product segmentation based on turnover and demand variability. The goal is to empower learners with visual tools to improve decision-making in areas like network design, inventory management, and operational efficiency.
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Chapters
- Improve picking productivity by minimizing operator walking distance.
- Order batching groups orders to reduce travel time between pick locations.
- Pathfinding algorithms determine the optimal sequence of picks.
- A heatmap visualizes product volume distribution across warehouse zones, highlighting high-traffic areas for strategic placement and bottleneck avoidance.
Optimizing picking routes directly reduces operational costs and increases warehouse efficiency by saving time and effort.
A heatmap showing SKU volume distribution, where darker colors indicate zones with the highest picking frequency, guiding decisions on product placement to minimize travel.
- Visualize the sequence of picking locations chosen by a pathfinding algorithm.
- The animation shows the step-by-step route taken, illustrating how the algorithm minimizes total picking distance.
- This visual helps understand and validate the algorithm's logic.
Seeing the algorithm's path unfold provides a clear, intuitive understanding of how it works and why it's effective in reducing travel.
An animated GIF showing a dotted line connecting picking locations in the order determined by the algorithm, illustrating the path taken by a warehouse operator.
- Use graph theory to visualize and optimize a retail company's road transportation network.
- Nodes represent stores, and links indicate if two stores were ever on the same delivery route.
- This visualization reveals route planning patterns and helps identify areas for improvement, such as isolated store clusters or inefficient route groupings.
Understanding the connectivity and flow of your transportation network is crucial for identifying inefficiencies and optimizing delivery routes, saving fuel and time.
A graph where each circle is a store, and lines connect stores that have been part of the same delivery route, showing the overall structure of delivery operations.
- Employ linear programming to design optimal supply chain networks, balancing production and transportation costs against market demand.
- Consider factors like factory location, capacity (low/high), production costs (varying by country), and transportation expenses.
- Visualize the impact of demand variability on network design by showing how different scenarios select different facility locations.
- Sankey charts effectively illustrate the flow of goods from production sites to markets, highlighting cost-effective sourcing strategies.
Designing an efficient supply chain network is fundamental to minimizing costs and meeting customer demand, and visualizations help communicate the complex trade-offs involved.
A Sankey chart showing the flow of products from various potential factory locations (e.g., India, America) to different markets, with the width of the bands representing the volume of goods, illustrating where production is most cost-effective.
- Segment products based on their turnover (revenue generated) and demand variability (how much demand fluctuates).
- An ABC analysis (Pareto principle) identifies high-revenue SKUs.
- Combining turnover with demand variability (coefficient of variation) helps prioritize inventory management and resource allocation.
- This segmentation informs strategies for warehouse layout, planning, and inventory control.
Understanding product performance and demand stability allows for targeted resource allocation, optimizing inventory levels and operational focus for maximum efficiency.
A scatter plot with turnover on one axis and demand variability on the other, categorizing products into groups like 'high runners with unstable demand' (red square) or 'slow movers' (green square) to guide management strategies.
Key takeaways
- Visualizations transform complex supply chain data into understandable insights.
- Heatmaps are effective for understanding spatial distribution and identifying high-activity zones in warehouses.
- Graph theory provides a powerful way to analyze and optimize transportation routes and network connectivity.
- Sankey charts are ideal for illustrating material flows and understanding cost drivers in network design.
- Product segmentation based on turnover and demand variability is crucial for effective inventory management and resource allocation.
- Visual tools can simplify the communication of complex analytical results to stakeholders.
- Leveraging libraries like NetworkX, Matplotlib, and Pi Sankey can automate the creation of these insightful visualizations.
Key terms
Supply Chain AnalyticsVisualizationWarehouse HeatmapPathfinding AlgorithmGraph TheoryLinear ProgrammingSankey ChartProduct SegmentationDemand VariabilityTurnoverCoefficient of Variation
Test your understanding
- How can a warehouse heatmap help optimize product placement and reduce picking times?
- What is the primary benefit of using graph theory to visualize a transportation network?
- Explain how a Sankey chart can illustrate the results of a supply chain network design study.
- Why is it important to consider both turnover and demand variability when segmenting products in a supply chain?
- How does visualizing a pathfinding algorithm's route contribute to understanding its effectiveness in warehouse operations?