Frustrated by incomplete data in Power BI?
Do you wish you could add missing data directly into your reports without expensive and drawn-out IT projects?
Well, the good news is - you can! In this video, you'll learn how to use tools you likely already have (SharePoint, Power Apps and Power Automate) to build a solution in about an hour.
Here's the 3-step plan:
➡️ Step 1: Create a Data Home: Securely store your data in a SharePoint list and connect it to Power BI.
➡️ Step 2: Embed a Data Capture App: Build a user-friendly Power App and embed it directly in your report for quick and easy data entry.
➡️ Step 3: Automate for Efficiency: Use Power Automate to automatically refresh your reports when new data is added, ensuring you always have the latest data.
Stop letting gaps in your data hold you back from creating impactful reports that support and drive better data-driven decisions.
Check out this video, follow the 3 step process to set up the system and start getting the most out of Power BI and your data.
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Case Study Details: Chemical Plant Production Loss Analysis
🤔The Problem:
A chemical processing plant tracks equipment breakdowns using a CMMS (Computerised Maintenance Management System). The CMMS lists maintenance work orders related to fixing equipment failures that have caused plant shutdowns. However, it doesn't capture the financial impact of the lost production caused by these breakdowns.
This critical data exists in a separate production management system that isn't connected to the CMMS or the data warehouse. Plant management also wants to capture root cause information, corrective actions, and the status of these actions – all within the context of the work order. They are losing money! They need the data quickly and don't want to spend a fortune on drown out, expensive IT projects.
🎯The Goal:
As a reliability engineer, you have been tasked with coming up with a solution. You need to analyse the total cost of failure for each piece of equipment, so you can identify which equipment items are the 'bad actors[add a full stop]' This analysis requires more data in order to prioritise maintenance efforts, investment in new equipment, training, etc.
The overall goal is to use the data to drive data-driven investment decisions with the aim of reducing unplanned breakdowns and costly downtime. This starts with adding the production loss value associated with each breakdown. Next it's finding a way to record further details of the failure to improve the root cause analysis process and reduce the risk of repeating issues.
🥳The Solution in Action:
This video demonstrates how the 3-step system described above was used to solve this exact problem. You'll see how a Power App, embedded directly within the Power BI report, allows users to add the missing production loss value, root cause codes, cause descriptions, follow-on actions, and status updates directly to each breakdown work order.
By connecting this app to a SharePoint list and automating the data refresh with Power Automate, the plant now has a complete picture of the financial impact of each breakdown, enabling them to make data-driven decisions to improve maintenance strategies, minimize future losses, and improve their failure analysis process.
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🎓 Power BI Dashboard Training
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👉FREE Power BI Quick Start Course - Learn how to create your first dashboard in around 90 minutes!
https://effectivedashboards.com/power-bi-quick-start-create-a-pbi-dashboard-in-90-minutes/
👉 Power BI Quick Start PLUS - Learn how to craft KPI management dashboards that help you, your boss, and your peers make better decisions!
https://effectivedashboards.com/power-bi-quick-start-plus/
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📁 Resources
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👉Access to the source PBIX file for this YouTube video:
https://effectivedashboards.com/course/enhance-power-bi-reporting-manually-add-data-without-leaving-the-report/
👉Other free resources:
https://effectivedashboards.com/courses/free-resources/
👉Article series on creating a maintenance management system data model and how to address the human factors of data collection for improved data quality. (This is not just relevant to maintenance and reliability data).
https://effectivedashboards.com/data-articles/