Building a Dynamic Supply Chain Dashboard in Power BI: A Step-by-Step Guide

Introduction

In today’s fast-paced global economy, managing supply chains efficiently is crucial for businesses to stay competitive. Supply chain management tracks numerous metrics, from sales and order fulfillment to delivery times and return rates. However, manually analyzing and interpreting this data can be time-consuming and prone to errors. That’s where Power BI comes into play.

Power BI is an incredibly powerful business intelligence tool that allows users to create visually engaging and interactive dashboards. By leveraging Power BI’s robust features, you can transform raw supply chain data into meaningful insights, making it easier for decision-makers to take timely actions.

In this project, I’ll walk you through the step-by-step process of building a Supply Chain Dashboard using Power BI, which I developed as part of my portfolio. This dashboard tracks key performance indicators (KPIs) such as total sales, order fulfillment rates, on-time delivery, and top-selling products across various regions. Its data-driven insights can help businesses streamline their operations and improve customer satisfaction.

Additionally, I’ll explain the essential Power BI features that I used to create this dashboard, including:

• Display Folders: These help in organizing and managing complex DAX (Data Analysis Expressions) measures, making it easier to navigate and maintain the dashboard.
• Field Parameters: A feature that allows dynamic switching between different dimensions (such as regions or categories) without needing multiple visuals, improving both the interactivity and efficiency of the dashboard.
• Custom Visuals: To enhance the user experience, I utilized several custom visuals to provide better clarity on performance metrics such as on-time delivery rates and delivery status by shipping mode.

Whether you’re a beginner or an experienced Power BI user, this guide will give you insights into how to create a comprehensive supply chain dashboard while learning advanced features that enhance dashboard functionality and ease of use.

Let’s dive into the process and learn how to build a dashboard that turns complex data into actionable insights.

Step 1: Understanding the Dataset

Before creating a meaningful and insightful dashboard, it’s crucial to fully understand the dataset you’re working with. For this project, I used a Supply Chain dataset, which contains transactional data from various regions, customer segments, and product shipments. This dataset provides a comprehensive view of sales, orders, fulfillment, and shipping performance, making it ideal for tracking and optimizing supply chain operations.

The dataset is structured around several important fields that serve as the foundation for the dashboard visuals. Here’s an overview of the key fields and their descriptions:

1. Type of Transaction

• Type: This field categorizes the type of transaction made, such as Debit, Transfer, Payment, or Cash. Each of these types reflects a different way customers made payments for their orders.

2. Shipping Time Efficiency

• Days for Shipping (Real): This field tracks the actual number of days it took to ship the purchased product, providing a real-world measure of shipping efficiency.
• Days for Shipment (Scheduled): This field represents the scheduled number of days for the shipment, which is the expected or promised delivery time.

Example: If the real shipping days are consistently higher than the scheduled shipping days, this indicates delays in the shipping process.

By comparing the real shipping days to the scheduled shipping days, we can measure shipping delays and identify bottlenecks in the fulfillment process. This is a critical metric for improving customer satisfaction.

3. Profitability Metrics

• Benefit per Order: This field tracks the profit or earnings made from each order, which is vital for understanding the financial performance of the business at the order level.

Example: By analyzing this data, you can quickly identify which orders or product categories contribute the most profit, allowing for better resource allocation and pricing strategies.

Profitability is one of the most important KPIs for any business, and tracking it at the order level gives valuable insights into which products, customers, or regions are most profitable.

4. Sales per Customer

• Sales per Customer: This metric calculates the total sales made per individual customer, allowing us to track which customers are generating the most revenue for the business.

Data Objectives

With these key metrics in mind, the objectives for building the dashboard are clear:

• Track sales and profitability across different customer segments and regions to identify high-value areas.
• Monitor fulfillment and shipping performance, with a focus on reducing late deliveries and improving on-time delivery rates.
• Optimize shipping processes by comparing real shipping times with scheduled shipping times and identifying trends in late or canceled deliveries.
• Understand customer behavior by analyzing sales per customer and identifying which customers are driving the most revenue.

By gaining a deep understanding of this dataset, we can now proceed to the next step: preparing the data and starting to build the visuals in Power BI.

Step 2: Data Preparation and Cleaning

Once you’ve gained an understanding of the dataset, the next crucial step is to prepare the data by importing, cleaning, filtering, and organizing it for effective analysis in Power BI. This process ensures that you work with the most relevant and clean data, and that you have a well-organized structure for your DAX measures.

1. Importing the CSV File into Power BI

To begin, follow these steps to import the dataset into Power BI:

1. Open Power BI Desktop.
2. Click on Home > Get Data > Text/CSV.
3. Select the CSV file that contains the supply chain data (SupplyChainDataset.csv) and click Load.

After importing, you’ll see a preview of the data in the Power Query Editor. This is where you can begin to clean and transform the dataset to suit the needs of your dashboard.

2. Filtering Data from 2015 to 2017

Since we want to focus on analyzing data from the years 2015 to 2017, we’ll filter the dataset to include only this time range:

1. In the Power Query Editor, locate the Order Date or equivalent date column that indicates when transactions occurred.
2. Click on the Filter icon in the column header.
3. Uncheck any years outside the range of 2015, 2016, and 2017, keeping only the relevant years selected.
4. Click OK to apply the filter.

This will ensure that we are analyzing the correct time period, helping to keep the dashboard focused on the relevant data.

3. Cleaning the Data in Power Query

After filtering, the next step is to clean the dataset. This involves addressing any inconsistencies or null values and ensuring that data types are correctly assigned. Here’s how to do that:

• Remove Null Values: Identify any missing or null values in important columns such as Sales, Profit, or Delivery Status. To remove these rows, click on the Filter icon in the relevant column and uncheck null values.
• Fix Data Types: Ensure that columns like Order Date are formatted as Date, and columns like Sales or Profit are set to Decimal Number or Whole Number as appropriate. You can change data types by right-clicking the column and selecting Change Type.

Power Query Editor

Once you’re satisfied with the cleaning process, click Close & Apply to load the transformed data into Power BI.

4. Creating a New Table for DAX Measures

In order to maintain a clean and organized data model, I created a new table to store all DAX measures using the Enter Data function in Power BI. This table will not contain any raw data, but will serve as a dedicated location for your calculated measures.

Here’s how to create a new blank table for DAX:

1. In Power BI Desktop, go to the Home tab and select Enter Data.
2. In the Create Table dialog, leave the data field blank.
3. Give the table a name such as _Measure (the underscore ensures the table appears at the top of your field list).
4. Click OK to create the table.

Now that you’ve created the _Measure table, you can begin storing all your DAX formulas here.

5. Using Display Folders to Organize DAX Measures

As your list of DAX measures grows, managing them can become cumbersome. To improve navigation and organization, you can use Display Folders to group related measures together.

To create a display folder:

1. In the Model View, select the _Measure table.
2. In the Properties Pane, find the option to create a Display Folder.
3. Enter folder names such as Sales Measures, Profit Measures, or Shipping Measures based on the type of calculations you’re organizing.
4. Drag and drop the appropriate DAX measures into these folders for better structure and clarity.

Preview Display Folder

Using display folders helps you keep track of your DAX measures, especially when working on complex dashboards with many calculations.

Step 3: Building the Dashboard

With the data now prepared and your DAX measures organized, it’s time to start building the visuals that will transform your dataset into actionable insights. Power BI offers a wide variety of visualization options, and this step will guide you through creating the key charts, tables, and metrics needed for a comprehensive Supply Chain Dashboard.

1. Setting Up the Dashboard Layout

Before diving into the individual visuals, it’s important to plan the overall structure and layout of your dashboard. A well-organized layout ensures that your stakeholders can easily interpret the data without being overwhelmed. Here are some tips for setting up an effective layout:

• KPI Cards at the Top: Place key performance indicators (KPIs) such as Total Sales, Profit, Fulfillment Rate, and Return Rate at the top of the dashboard. These high-level metrics provide a quick snapshot of overall business performance.
• Visual Grouping: Group related visuals together. For instance, place Sales by Region and Sales by Product near each other to make it easier to compare geographic and product-based performance.
• Interactive Filters and Slicers: Place slicers in a dedicated space (often on the left or right sidebar) to allow users to filter data by time periods, categories, or customer segments.

Overview Page

Performance Page

Detail Page

2. Creating Key Visuals for Sales Metrics

a) Total Sales by Payment Type (Bar Chart)

This bar chart allows you to break down sales by the different payment methods used by customers, such as Debit, Transfer, Payment, and Cash. Here’s how to create it:

1. In the Visualizations Pane, select the Bar Chart icon.
2. Drag the Total Sales field (from your DAX calculations) to the Values section.
3. Drag the Payment Type field to the Axis section.

This bar chart will display the total sales for each payment type, helping you understand which payment methods contribute most to overall sales. You can further enhance this chart by:

• Conditional Formatting: Use color to highlight payment types with the highest or lowest sales, making it easier for viewers to quickly interpret the chart.
• Dynamic Titles: Add a dynamic title that updates based on slicer selections (e.g., “Total Sales by Payment Type for 2017”).

b) Sales by Region (Map Visual)

A map visual is an effective way to show sales performance across different geographic regions. Power BI’s map feature allows you to plot sales data on a world map, providing an intuitive overview of where your strongest and weakest markets are located.

Here’s how to create a Sales by Region map:

1. Select the Map Visual from the Visualizations Pane.
2. Drag the Sales measure into the Size field.
3. Drag the Region field into the Location field.

Power BI will automatically plot sales data on the map, with the size of each bubble representing the magnitude of sales in that region. For example, if Western Europe has higher sales than South America, its bubble will appear larger on the map.

Consider adding a tooltip that displays additional information, such as profit or order count, when a user hovers over a region. This helps provide more context without cluttering the visual.

3. Shipping and Fulfillment Visuals

One of the key functions of this dashboard is to track delivery performance and fulfillment rates. These metrics help identify operational bottlenecks in the supply chain and give businesses actionable insights for improving customer satisfaction.

a) On-Time vs Late Delivery by Month (Line Chart)

Tracking the monthly trend of on-time and late deliveries helps highlight periods when deliveries were more likely to be delayed, offering clues to potential seasonal patterns or operational inefficiencies.

Here’s how to create a Line Chart to track delivery performance:

1. Select the Line Chart visual.
2. Drag Month to the Axis section.
3. Drag both On-Time Delivery Rate and Late Delivery Rate to the Values section.

This visual will display two lines — one representing the on-time delivery rate and the other representing late deliveries. By analyzing this chart, you can see how delivery performance fluctuated month-to-month. For example, on-time delivery might spike in certain months, while delays increase during peak seasons like the holidays.

b) Fulfillment Rate and Shipping Mode Performance (Stacked Bar Chart)

Understanding the efficiency of different shipping modes (e.g., Standard Class, First Class, Second Class, Same Day) can reveal which methods are most prone to delays or cancellations.

To create a Stacked Bar Chart that compares shipping mode performance:

1. Choose the Stacked Bar Chart visual.
2. Drag Shipping Mode to the Axis field.
3. Drag Delivery Status (e.g., On-Time, Late, Canceled) to the Legend field.
4. Drag Total Orders to the Values field.

This chart will show the proportion of on-time, late, and canceled orders for each shipping mode. For example, you might discover that Standard Class has a higher rate of late deliveries compared to First Class, providing a clear indication of which shipping methods are more reliable​.

You can enhance this visual by adding data labels to indicate exact percentages for each status, allowing for even deeper analysis.

4. Analyzing Top Products and Customers

a) Top-Selling Products (Table Visual)

To identify which products are driving the most revenue, you can create a table that lists the top-selling products and their associated sales and profit. This visual allows decision-makers to focus on high-performing products and evaluate inventory strategies.

Here’s how to create a Table Visual for the top products:

1. Select the Table Visual from the Visualizations Pane.
2. Drag Product Name, Total Sales, and Profit into the Values section.
3. Sort the table by Total Sales to show the highest-selling products at the top.

For example, in your dataset, Field & Stream Sportsman 16 Gun Fire Safe is one of the top-selling products, contributing $1.90M to total sales​. Adding a column for Units Sold can provide even more insight into product performance.

b) Top Customers by Sales (Bar Chart or Table Visual)

Similarly, identifying top customers can help inform customer retention strategies and targeted marketing efforts. This visual can display the customers who have generated the most revenue over a specific period.

To create this visual:

1. Select either a Bar Chart or Table Visual.
2. Drag Customer Name and Total Sales into the Values section.
3. Sort the data by Total Sales to rank the customers by revenue.

For example, Mary Smith might be the top customer, contributing over $1.33M in sales during the year​. This insight helps you focus on nurturing relationships with high-value customers.

5. Adding Slicers for Interactivity

Field Parameters in Power BI allow you to create a dynamic slicer that lets users switch between different dimensions (like Region, Product Category, or Customer Segment) in a single visual. This means instead of creating multiple charts for each field, you can use one chart that updates based on the slicer selection.

Here’s how it works:

1. Create a Field Parameter for the dimensions you want to slice by.
2. Add the Field Parameter as a slicer in your dashboard.
3. Users can then select different fields, and the visual will update automatically to show data for the selected dimension.

Example: Parameter Field As Slicer

This feature makes your dashboard more interactive and reduces the need for multiple visuals, keeping the layout clean and easy to use

Visual Design Considerations

Now that you’ve created the key visuals, it’s essential to ensure that the dashboard design is clear, visually appealing, and easy to navigate. Here are some design tips:

• Consistent Color Scheme: Use a consistent color palette throughout the dashboard to reduce visual clutter and make it easier to interpret the data.
• Use Conditional Formatting: Highlight important trends or outliers by applying conditional formatting to tables or charts. For example, you can use color scales to indicate high versus low sales.
• KPIs as Cards: Display high-level KPIs such as Total Sales, Profit, and Return Rate as cards at the top of the dashboard for quick reference.

With all visuals in place and interactive elements added, your supply chain dashboard is ready to provide actionable insights to business stakeholders.

Step 4: Finalizing the Dashboard

At this stage, you’ve created key visuals that provide insights into your supply chain’s performance. However, building a high-quality Power BI dashboard doesn’t end with just adding visuals. Finalizing your dashboard involves refining the design, ensuring optimal performance, and generating actionable insights. In this section, we’ll cover the steps required to enhance your dashboard’s usability, performance, and presentation, ultimately making it more effective and valuable for stakeholders.

1. Design and Layout Optimization

A well-designed dashboard is one that conveys information clearly and efficiently. While you’ve already built the key visuals, refining the design can significantly enhance user experience and ensure that insights are easy to interpret.

a) Arranging Visuals for Clarity

When finalizing the dashboard, think about how the visuals are arranged. A good practice is to follow a top-to-bottom or left-to-right flow for your users, ensuring that they can quickly move from high-level KPIs to more detailed analyses. Here are a few key points to consider:

• KPI Placement: Place high-level KPIs (like Total Sales, Profit, Fulfillment Rate) at the top of the dashboard. These provide an at-a-glance overview of overall performance and should be the first elements users see.
• Thematic Grouping: Group related visuals together for easy comparison. For example, keep all sales-related visuals (like Sales by Region and Top Products) near each other, while delivery performance charts (like On-Time vs Late Delivery and Fulfillment Rates) should also be grouped.
• Space Allocation: Give more space to important visuals. For example, if the Sales by Region map or a bar chart provides the most critical insights, make sure it is large enough to be easily interpreted.

b) Consistent Visual Design

Maintaining a consistent design is essential for a polished and professional dashboard:

• Color Scheme: Use a unified color scheme across all visuals. Power BI allows you to customize colors for each chart, so choose a palette that reflects the company’s branding or one that makes it easy to differentiate between categories (e.g., green for positive growth, red for negative trends).
• Font and Text Size: Ensure that text labels, axis titles, and KPIs are legible. Stick to a single font and adjust text size based on visual importance. KPI cards should have large, bold numbers, while table headers and data labels should be medium-sized and clear.
• Icons and Tooltips: Power BI allows for the addition of icons and tooltips to improve the user experience. You can use tooltips to provide additional insights without overcrowding the visuals. For example, when hovering over a region on the sales map, a tooltip could display more detailed information like profit margins or order quantities.

2. Enhancing Interactivity

While you’ve already added slicers for filtering data, further interactivity can be incorporated to allow users to explore the data more freely and generate their own insights.

a) Drill-Through Pages

One of Power BI’s most powerful features is the Drill-Through capability, which allows users to right-click on a visual and navigate to a separate page that provides more detailed information on a specific data point. This feature is particularly useful for a supply chain dashboard where users may want to investigate further into specific regions, products, or customer segments.

For example:

• Drill-Through by Region: You can set up a drill-through page that provides a detailed breakdown of sales, profit, and shipping performance for a selected region.
• Drill-Through by Product: A separate page could show detailed insights into a specific product’s performance, including units sold, profit per order, and return rates.

Here’s how to implement a drill-through feature:

1. Create a new page in Power BI dedicated to the drill-through (e.g., Region Detail).
2. In the Visualizations Pane, drag the field (e.g., Region) to the Drill-Through Filters section.
3. Format the page with detailed visuals that will only show data filtered by the selected region.
4. In your main dashboard, right-click on a region in the Sales by Region map to activate the drill-through.

Drill-Through by Product

b) Dynamic Titles and Conditional Formatting

Dynamic titles are an advanced feature that updates visual titles based on slicer or filter selections, making the dashboard more interactive and intuitive. For example, if a user selects only the year 2016 from the Date Slicer, the title of the Total Sales chart can automatically update to “Total Sales for 2016”.

To create a dynamic title:

1. Write a DAX formula that combines text with a selected filter, such as:

Title Month Week Day = 
"Total " & FORMAT(MAX(Metric[Metric]), "text") & " by " & FORMAT(MAX('Month Week Day'[Month Week Day]),"text")Title Departement = 
"Total " & FORMAT(MAX(Metric[Metric]), "text") & " by " & FORMAT(MAX('Departement Category'[Departement Category]),"text")

2. Apply this dynamic title to your visual through the Title settings in the Visualizations Pane.

Similarly, conditional formatting can highlight outliers or important trends in tables or bar charts. For instance, you can format sales values that are below a certain threshold in red, or use a color gradient to show the highest and lowest performing products.

3. Optimizing Dashboard Performance

As your dashboard becomes more complex with numerous visuals and data sources, performance optimization becomes critical to ensure fast loading times and smooth user interaction.

a) Reducing Visual Load

One of the primary causes of slow performance in Power BI dashboards is an excessive number of visuals rendering simultaneously. Here are some strategies to reduce the load:

• Avoid Overcrowding with Visuals: Try not to overload the dashboard with too many visuals on a single page. Instead, use additional pages or drill-through features to divide data logically.
• Use Aggregated Data: Instead of pulling raw data into visuals, use aggregated or summarized data where possible. For example, instead of displaying every transaction, create an aggregated measure for Total Sales or Average Profit.

b) Managing Data Refreshes

Large datasets can cause significant slowdowns when refreshing data. To optimize refresh times:

• Scheduled Refreshes: In Power BI Service, you can set up scheduled refreshes to update data at regular intervals rather than on demand. This ensures users always see up-to-date information without needing to wait for refreshes during usage.
• Data Modeling: Simplify your data model by removing unnecessary tables or columns, and apply relationships only where needed.

c) Using Power BI Performance Analyzer

Power BI’s Performance Analyzer tool helps you identify bottlenecks by showing how long each visual takes to load. To use it:

1. Go to the View tab and click on Performance Analyzer.
2. Start recording to see which visuals are taking the most time.
3. Adjust or optimize visuals based on this feedback, such as reducing the complexity of DAX measures or filtering the dataset further.

4. Generating Actionable Insights

Once the visuals are in place and the dashboard is optimized for performance, the next step is to interpret the data and generate actionable insights for the business.

a) Identifying Key Performance Drivers

• Top Products and Customers: By examining the Top-Selling Products and Top Customers visuals, you can quickly identify which products and customers are driving the most sales. For example, if Field & Stream Sportsman 16 Gun Fire Safe is your highest seller, you may want to ensure sufficient inventory levels or prioritize marketing efforts for this product.
• Regional Performance: The Sales by Region map highlights geographical areas that are either excelling or underperforming. If Western Europe has significantly higher sales than Northern Europe, you might consider investing in more resources or marketing in the latter region to close the gap.

b) Addressing Operational Bottlenecks

• Fulfillment and Delivery Issues: Analyzing the On-Time Delivery Rate and Late Delivery Rate over time helps pinpoint when and where delivery issues are occurring. For instance, if late deliveries are spiking during certain months, you can investigate further to see if it’s due to staffing shortages, seasonal demand, or supplier delays.
• Shipping Mode Efficiency: By looking at the performance of different shipping modes in the Shipping Mode vs Delivery Status chart, you can determine which shipping methods are more prone to delays or cancellations. For example, if Standard Class consistently has a higher rate of late deliveries, you may want to adjust shipping policies or offer faster alternatives for critical customers.

5. Sharing and Publishing the Dashboard

Finally, once your dashboard is ready and fully optimized, it’s time to share it with your stakeholders.

a) Publishing to Power BI Service

To share the dashboard, you can publish it to the Power BI Service:

1. Click on File > Publish > Publish to Power BI Service.
2. Choose a workspace for your report.
3. Once published, you’ll receive a link that you can share with your team or embed in websites or internal tools.

b) Creating a Dashboard from the Report

In Power BI Service, you can create a dashboard by pinning visuals from your report. This allows you to compile key metrics into a single-page view that’s ideal for executives who only need high-level data.

c) Sharing and Collaboration

In Power BI Service, you can also set permissions for users, allowing them to view, interact with, or edit the dashboard. This makes it easy to collaborate with team members or share insights with decision-makers across the organization.

Conclusion

Building a Supply Chain Dashboard in Power BI is about turning complex data into clear, actionable insights. Throughout this project, we started by preparing and cleaning the data, focusing on relevant metrics like sales, profit, and delivery performance. We then used Power BI to create a series of visuals — bar charts, line graphs, and maps — that make it easy to understand key performance indicators.

The dashboard is designed to help businesses track their sales performance, identify delivery bottlenecks, and see which products and customers drive the most value. With features like slicers, drill-throughs, and dynamic titles, the dashboard is interactive, allowing users to explore data and uncover trends.

You can support me by purchasing my Supply Chain Dashboard through these links:

• International: https://ko-fi.com/s/9c99fd4b1b
• For Indonesian users, you can buy it here: https://clicky.id/gustiyaniz/dashboard-supplychain