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How to Create a Supply Chain Dashboard in Excel with AI

Cody Schneider•

A great supply chain dashboard is the control panel for your entire logistics operation, but building one in Excel often feels like a week-long data-wrangling project. You're pulling CSVs from your ERP, cleaning up formatting, and wrestling with pivot tables just to get a basic view. This guide will walk you through building a functional supply chain dashboard in Excel and then show you how AI can automate the heavy lifting, turning hours of work into seconds.

Why Build a Supply Chain Dashboard in the First Place?

Before jumping into cell formulas and charts, it’s worth clarifying what a good supply chain dashboard actually accomplishes. It’s not just about creating pretty graphs, it’s about making smarter, faster decisions. A well-designed dashboard provides:

  • End-to-End Visibility: See what’s happening from procurement and manufacturing to warehousing and final delivery, all in one place.

  • Proactive Problem Solving: Spot bottlenecks, delays, or cost overruns before they snowball into major issues. Identify that a specific carrier is consistently late or that inventory for a key product is dropping faster than forecast.

  • KPI Tracking: Measure what matters most to your business. A dashboard makes it easy to monitor key performance indicators (KPIs) against goals and historical performance in real-time.

  • Clear Stakeholder Communication: Easily share performance insights with your team, management, or clients without sending them a dozen messy spreadsheets.

Building Your Supply Chain Dashboard in Excel: The Manual Method

Let’s start with the classic approach. While it has its limitations, it’s a foundational skill and a great way to understand the mechanics of your data. We'll build a simple dashboard to track order fulfillment and carrier performance.

Step 1: Define Your Key Performance Indicators (KPIs)

You can't measure everything, so focus on the metrics that have the most impact. For a supply chain, this often includes:

  • On-Time Delivery (OTD) Rate: The percentage of orders delivered to the customer by the promised date. It's a critical measure of customer satisfaction.

  • Inventory Turnover: How many times inventory is sold during a period. High turnover is good, it means you're efficiently managing stock.

  • Order Fill Rate: The percentage of an order that is fulfilled from stock on the first shipment. It's a key indicator of inventory health and customer service.

  • Lead Time: The total time elapsed from when a customer places an order until it’s delivered. Shorter lead times mean happier customers.

  • Transportation Costs: Includes cost per shipment, cost per unit, or freight cost as a percentage of revenue. This directly impacts your bottom line.

For our example, we'll focus on On-Time Delivery Rate and Lead Time by carrier.

Step 2: Consolidate Your Data

This is where the manual work really begins. You need to gather all the relevant data into a single Excel sheet. This data often comes from various sources like an Enterprise Resource Planning (ERP) system, a Warehouse Management System (WMS), or a Transportation Management System (TMS).

Export your order data as a CSV file and open it in Excel. Your "master data" sheet should have clear columns like:

  • OrderID

  • OrderDate

  • PromisedDeliveryDate

  • ActualDeliveryDate

  • Carrier

  • ShippingCost

  • ProductCategory

  • DestinationCountry

Step 3: Clean and Structure Your Data

Raw data is rarely dashboard-ready. You’ll need to clean it up. A crucial first step is to format your data as an Excel Table. Click anywhere in your data range and press Ctrl + T. This makes formulas, filtering, and refreshing much easier.

Now, add a few calculated columns to make your analysis possible. To calculate our KPIs:

  1. Calculate Lead Time: Create a new column called "LeadTime." The formula will be =[@[ActualDeliveryDate]]-[@[OrderDate]]. This will give you the lead time in days.

  2. Determine On-Time Status: Create a new column called "OnTimeStatus." The formula here is =IF([@[ActualDeliveryDate]]<=[@[PromisedDeliveryDate]], "On-Time", "Late"). This tags every order as either late or on time.

Make sure dates are formatted as dates, numbers as numbers, and there are no blank cells where there shouldn't be.

Step 4: Create Pivot Tables and Charts

Pivot Tables are the engine of any classic Excel dashboard. They summarize large datasets without complex formulas.

Let’s create a Pivot Table to analyze the On-Time Delivery Rate by carrier:

  1. Go to the Insert tab and click PivotTable. Make sure it selects your data table.

  2. In the PivotTable Fields pane, drag and drop the fields:

    • Drag Carrier to the Rows area.

    • Drag OnTimeStatus to the Columns area.

    • Drag OrderID to the Values area (it should default to "Count of OrderID").

  3. You now have a table showing the count of late and on-time shipments for each carrier. From here, create a Pivot Chart. Just select your Pivot Table, go to the Insert tab and select a bar chart.

Repeat this process for other KPIs. For example, create another Pivot Table to show the average Lead Time by Carrier. This time, when you drag LeadTime to the Values area, make sure to change the summarization from "Sum" to "Average." Create a corresponding chart for this as well.

Step 5: Assemble Your Dashboard

Now it's time to bring it all together.

  1. Create a new spreadsheet and name it "Dashboard".

  2. Copy and paste your charts from the Pivot Table sheets onto your dashboard sheet. Arrange them in a clean, logical way.

  3. Add Slicers for interactivity. Select one of your charts, go to the Insert tab, and click Slicer. Add slicers for DestinationCountry or ProductCategory.

  4. Connect the slicers to all of your charts. Right-click the slicer, select Report Connections, and check the boxes for all the Pivot Tables you want it to control. Now, clicking a country in the slicer will update all your charts simultaneously.

You now have a dynamic, albeit manually constructed, supply chain dashboard in Excel.

The Challenge: Where Manual Excel Dashboards Fall Short

If you followed the steps above, you've likely spent a good chunk of time on this. That process highlights the fundamental problems with relying solely on manual Excel dashboarding.

  • Time-Consuming Updates: Your dashboard is static. To update it for next week's meeting, you have to download fresh CSVs, paste the new data, manually refresh all the Pivot Tables, and hope nothing breaks. It’s a repetitive weekly chore.

  • Prone to Human Error: A single copy-paste error, an incorrect formula, or a missed filter can cascade through the entire report, leading to incorrect analysis and bad decisions. It's difficult to audit and trust.

  • Lack of Drill-Down Capability: Your dashboard shows you what is happening (e.g., shipments from Carrier B are often late), but not why. Answering follow-up questions often requires going back to the raw data and building entirely new Pivot Tables.

Supercharging Your Supply Chain Analysis with AI

This is where AI changes the entire process. Instead of being an Excel "mechanic" who builds the engine from scratch, you become a "driver" who simply tells the engine where to go. AI analytics tools handle the data aggregation, calculation, and visualization for you, based on simple, plain-English questions.

Instead of manually creating Pivot Tables and charts, you can ask questions like:

Integrating AI Directly into Your Excel Workflow

You might be thinking this sounds great in theory, but how do you actually use it? There are a few different ways to bring AI into your supply chain analysis, especially if you’re used to working in Excel.

  1. Excel’s “Analyze Data” Feature: On the Home tab of newer Excel versions, there is an "Analyze Data" button. You can click this, and Excel’s AI will automatically suggest pivot charts and insights based on your data tables. It's a good starting point, but lacks the control and flexibility to ask specific, nuanced questions.

  2. Using Dedicated AI Analytics Platforms: The most robust solution is using tools designed to connect directly to your underlying data sources (like your ERP or Shopify store). These platforms understand how your data is structured, ensuring accuracy, and they allow you to create live dashboards that update automatically. This eliminates the manual work of re-doing CSV imports every time you need an update.

Final Thoughts

In summary, you can build a powerful supply chain dashboard in Excel, but the process can be time-consuming and prone to error. Leveraging AI analytical tools removes this manual burden, providing more accurate insights without the repetitive tasks.

For a tool that aids in tackling these challenges and enhances productivity, consider exploring Graphed. Graphed offers solutions for creating efficient and dynamic dashboards for your supply chain needs.