How We Build Supply Chain Network Optimization in Tableau I DataDev Day June 2024

Introduction

At the DataDev Day in June 2024, I had the pleasure of presenting how we developed a Tableau dashboard focused on supply chain network optimization. As a Tableau Data Dev Ambassador, my goal was to showcase the capabilities of Tableau extensions and how they can transform dashboards into comprehensive data products. I work at Baker Tilly, a leading accounting firm, and in our advisory practice, we frequently engage in supply chain network design, making this topic particularly relevant.

Understanding Tableau Dashboard Extensions

Tableau dashboard extensions enable users to enhance their dashboards by integrating new functionalities and behaviors. These extensions are exposed via an API, allowing us to write data back to third-party sources or create new forms of user engagement. The extensions can serve various business needs, and I believe the most valuable use cases often stem from specific business processes. The main focus of my presentation was on a supply chain optimization dashboard we developed for the Tableau Conference, which illustrates the effectiveness of these extensions.

Gamifying the Supply Chain Optimization Dashboard

The application we built centers on a common scenario in supply chain network design: optimizing the location of distribution centers (DCs) for a company called Tableau Logistics. Users are introduced to the game to determine where to place DCs around the country and how these decisions impact supply chain costs.

Upon loading the dashboard, users are welcomed with details about their objective and prompted to start a new game. They can explore customer data and associated costs while making decisions about where to build DCs. For instance, if a user clicks on a possible DC location, our extension provides options to choose different sizes of DCs, enabling interactive decision-making.

After finalizing their decisions and submitting their plans, users receive feedback on the outcomes of their choices based on an optimization model that evaluates the theoretical performance of the supply chain. Key performance indicators help users understand the implications of their decisions—such as cost savings associated with building specific DCs.

Technical Implementation

The dashboard was constructed using Anvil X, a framework that allows developers to create Tableau extensions with only Python. This accessibility empowered our non-web-developer team, effectively turning our dashboards into full-fledged applications.

During usage, user actions create events that trigger responses in the extension. For example, if users select a DC location, the extension updates the UI dynamically based on their decision. The application communicates between the dashboard and the extension, allowing for two-way interaction. Additionally, we utilized the T-Rex jacket, a wrapper over the JavaScript API, which simplifies many development tasks.

Key Coding Techniques

Here are a few coding practices that were vital in crafting the optimization dashboard:

Multiple Screens: The application utilizes various screens tied to specific dashboards, enabling tailored user experiences.
User Input Capture: We handle user actions through various UI components and modals, which are built using drag-and-drop functionalities.
Parameter Manipulation: Parameters in Tableau serve as a flexible resource for communication between the extension and the dashboard, storing essential user selection data for efficient retrieval.
Visibility Control: We made use of visibility properties to manage user interaction throughout the decision-making process, ensuring users only see relevant options based on their current actions.
Running Optimization Models: More complex models are executed using server-side Python functions, allowing us to integrate advanced computational capabilities beyond what Tableau directly supports.

Conclusion

The gamified supply chain network optimization tool we developed serves as a robust example of how Tableau extensions can enhance user engagement and decision-making processes. The combination of interactive visualizations and backend computation results in a comprehensive dashboard that not only helps users understand their data but also take actionable steps based on it.

If anyone is interested in learning more about building Tableau extensions or would like to see a demo, please feel free to reach out to me!

Keywords

Tableau extensions
Supply chain optimization
Dashboard development
Anvil X
T-Rex jacket
User engagement
Gamification
Interactive decision-making

FAQ

1. What are Tableau dashboard extensions?
Tableau dashboard extensions allow users to enhance dashboards with new functionalities, integrating external data sources, or creating interactive user engagement features.

2. How does the supply chain optimization dashboard work?
Users explore potential distribution center locations, make decisions about building them, and see the impacts of their decisions on supply chain costs through an optimization model.

3. What is Anvil X?
Anvil X is a framework enabling developers to build Tableau extensions using only Python, making it accessible for non-web developers.

4. How can users interact with the dashboard?
Users can interact with the dashboard by selecting locations for distribution centers, which dynamically updates the interface and subsequent visualizations to reflect their choices.

5. Can I build my own Tableau extension?
Yes! The techniques and methodologies presented can be adopted to create custom Tableau extensions tailored to specific business use cases.