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How to Create a Maintenance Dashboard in Power BI

Cody Schneider•

Moving from a reactive to a proactive maintenance strategy flips the script on how you manage your assets. An effective dashboard is your best tool for making that change, shifting your focus from fixing what’s broken to preventing breaks in the first place. This guide will walk you through exactly how to build a practical maintenance dashboard using Power BI, from setting your goals to selecting the right charts.

First, Why Build a Maintenance Dashboard at All?

Let's be honest: building a dashboard takes time. It’s worth it, though, because a good dashboard transforms mountains of raw maintenance data into clear, actionable intelligence. Instead of digging through spreadsheets of work orders to spot a problem, a visual dashboard lets you see trends and anomalies instantly.

Here’s the payoff:

  • Reduced Downtime: By tracking metrics like Mean Time Between Failures (MTBF), you can spot which assets are failing most often and address the root cause, not just the symptom.

  • Better Cost Control: Visualize where your maintenance budget is going. Are you spending too much on parts for one machine? Is overtime labor creeping up? A dashboard makes this obvious.

  • Smarter Resource Planning: See which technicians are overloaded and which have capacity. Easily track the backlog of open work orders to schedule your team more effectively.

  • Improved Asset Lifespan: A healthy ratio of preventive to reactive maintenance means you’re taking care of your equipment, extending its life and maximizing your investment.

Step 1: Plan Your Dashboard and Choose Your KPIs

You can't build a useful dashboard without first deciding what questions you want it to answer. Before you even open Power BI, take a moment to define the key performance indicators (KPIs) that matter most to your maintenance operations. This ensures you’re tracking what’s important, not just what's easy to visualize.

Here are some of the most common and valuable maintenance KPIs to consider:

Operational KPIs:

  • Work Order Status: The simplest metric, but essential. A count of open, in-progress, and completed work orders gives you an immediate pulse check on your backlog.

  • Mean Time To Repair (MTTR): How long does it take, on average, to complete a repair from the moment a failure is reported? A rising MTTR could signal issues with technician skill, parts availability, or diagnostic processes.

  • Mean Time Between Failures (MTBF): For a specific piece of equipment, what's the average time it operates successfully between breakdowns? A short MTBF is a huge red flag that an asset is unreliable.

  • Preventive vs. Reactive Maintenance Ratio: This KPI compares planned maintenance to unplanned emergency repairs. A healthy maintenance program will have a high ratio of preventive work (around 80/20 is often considered a great goal).

Financial KPIs:

  • Total Maintenance Cost: Track the total cost over time, broken down by labor, parts, and contractor fees. Are costs trending up or down?

  • Cost by Asset or Department: Pinpoint which machines or areas of the facility are consuming the most maintenance resources.

Team and Impact KPIs:

  • Technician Workload and Performance: Track the number of work orders completed by each technician to monitor workload and identify top performers or those needing additional support.

  • Work Orders Overdue: A simple count of tickets that have passed their due date. This highlights bottlenecks and helps prioritize the most urgent tasks.

Pick 5-7 of these to start. You can always add more later, but focusing on a handful of metrics keeps your dashboard clear and effective.

Step 2: Get Your Data Ready

Your dashboard is only as reliable as the data behind it. Maintenance data often comes from a Computerized Maintenance Management System (CMMS) or, for many smaller teams, a series of Excel files or Google Sheets. For this tutorial, we'll assume your data is in a spreadsheet.

A good starting dataset for a maintenance dashboard would look something like this, with each row representing a single work order:

Example Spreadsheet Structure:

  • WorkOrderID: A unique ID for each job (e.g., WO-1001).

  • AssetID: Which machine or piece of equipment was worked on.

  • WorkOrderType: Preventive or Reactive.

  • CreationDate: When the work order was opened.

  • CloseDate: When the work order was completed.

  • Technician: The name of the person who did the work.

  • Status: Open, In Progress, or Closed.

  • PartsCost: The cost of materials used.

  • LaborHours: The number of hours worked.

  • LaborRate: The hourly cost for the technician.

Spend a few minutes cleaning this data before you import it. Ensure your dates are in a consistent format, work order types are spelled correctly (e.g., "Preventive" vs. "Preventative"), and there are no glaring gaps.

Step 3: Import and Model Your Data in Power BI

Now for the fun part. Open Power BI Desktop and let's get building.

1. Get Data

On the Home ribbon, click Get Data and select Excel Workbook (or Google Sheets, etc.). Navigate to your file and select the worksheet containing your maintenance data. Power BI will show you a preview. If it looks correct, click Transform Data.

This opens the Power Query Editor, a powerful tool for shaping your data before it even hits the report canvas.

2. Transform and Create New Measures

In the Power Query Editor, your first step is to quickly check the data types for each column. Make sure Power BI has correctly identified dates as dates and numbers as numbers. You can change these using the "Data Type" option in the Home tab.

Next, we need to create some calculated columns and measures to bring our KPIs to life. We’ll use DAX (Data Analysis Expressions), Power BI's formula language. It’s similar to Excel formulas but much more powerful.

After clicking Close & Apply in the Power Query Editor, go to the Data view (the table icon on the left). Select your table, then click New Column or New Measure from the ribbon.

Example DAX Formulas:

  • Total Labor Cost (New Column): Let’s calculate the total cost for labor for each work order.

  • Total Work Order Cost (New Column): Sum up the parts and labor for a total cost.

  • Repair Duration in Days (New Column): Calculate how long it took to close a ticket.

  • MTTR (New Measure): Now we can create an MTTR metric by averaging the duration of all completed reactive repairs.

Don't be intimidated by the DAX formulas. Think of them as recipes. The MTTR measure shows the real power of DAX - you can specify complex conditions, like averaging the repair duration only for closed, reactive work orders.

Step 4: Design a Visual and Intuitive Layout

Switch over to the Report View (the bar chart icon on the left). This is your canvas. A good dashboard tells a story, flowing from high-level summaries down to granular details.

Choosing the Right Visuals

Now, let's drag our data and measures onto the canvas using visuals that best represent our KPIs.

  • Cards for Big Numbers: For your most important, at-a-glance metrics like Total Open Work Orders, MTTR, and Total Maintenance Cost, use Card visuals. They are perfect for displaying a single, powerful number.

  • Pie or Donut Charts for Proportions: Use a Donut Chart to show the breakdown of Work Order Status (Open vs. Closed) or a Pie Chart for your Preventive vs. Reactive Maintenance Ratio.

  • Bar and Column Charts for Comparisons: A Stacked Column Chart is excellent for showing Total Maintenance Cost broken down by Asset ID over time. A simple Bar Chart is perfect for creating a Technician leaderboard displaying work orders completed.

  • Line Charts for Trends Over Time: Use a Line Chart to track the trend of something like Total Cost per Month or MTTR over the last year. This helps you instantly see if your performance is improving or declining.

  • Tables for Detailed Views: Include a Table visual that shows details for all open work orders. This is your action list. You can include columns for WorkOrderID, AssetID, CreationDate, and Technician.

Add Slicers for Interactivity

The magic of Power BI is interactivity. Add Slicer visuals to your dashboard so a team manager can filter the entire report for what they care about. Common slicers for a maintenance dashboard include:

  • Date Range (e.g., Last 30 Days, This Quarter)

  • Technician Name

  • Asset ID

  • Work Order Type (Preventive/Reactive)

When a user clicks on a technician’s name, for instance, all the charts and cards will instantly update to show data only for that person. This transforms your dashboard from a static report into a dynamic analytical tool.

Final Thoughts

Building a maintenance dashboard in Power BI involves clear planning around your key metrics, careful data preparation, and thoughtful visual design. By turning spreadsheet data into interactive charts, you give your team the power to move from reacting to problems to proactively managing asset health and performance.

While Power BI is incredibly powerful, we know it can have a steep learning curve and requires manual setup for every new report. We created Graphed for teams who want answers from their data without becoming dashboard design experts. You just connect your data sources (like spreadsheets or live databases) and use plain English to ask for what you need - Graphed builds the real-time dashboards for you instantly, enabling anyone to get immediate insights.