Power Automate RPA Implementation with Power BI for Empowering Stakeholders with Automated Production Insight

Empowering Stakeholders with Automated Production Insights Dashboards Power Automate RPA and Power BI

Client Overview

Our client is a leading?global e-commerce retailer focused on consumer electronics, fashion and household goods. The company operates in various countries and handles millions of transactions every month for a large?number of customers.

Challenge

Our client?had multiple plants but struggled to manage their production data, using inefficient, fragmented, manual processes instead. They had to sift through all the different legacy IoT applications to gather information and put it?into spreadsheets, a process that was time-consuming and prone to inaccuracies. The manual processes built these?bottlenecks in the operations and limited the productivity.

Data fragmentation was another?critical issue. Production data was in different formats and locations?across plants making it hard to standardize metrics and compare performance. The resulting diversity made the process complicated and delayed?data analysis.

Since the reports had to be compiled?and distributed which took many days to get insights. This latency limited access to important metrics around production output, operational efficiency and downtime, which hindered timely decisions and contributed to a?reduced response rate to problems on the plant floor.

Adding to these problems was an?absence of real-time data visualization. Without a centralized system, plant managers would have no means to access performance data in real-time?manner. Without access to real-time?insights, problems can be hard to spot and solve proactively, therefore affecting overall operational efficiency.

With business growth, the decentralized and manual process?revealed scalability issues. Given that the organization was still evolving, it was clear that the existing workflow would not support scaling up in practice without making significant investments in resources to support knowledge work in?the long run.

These challenges highlighted the need for an?integrated solution that could automate data collection, normalize metrics and deliver real-time insights. By eliminating these inefficiencies, the company would be able to enhance operational efficiency, improve decision-making and enable?seamless scalability.

Manual Data Collection: It was also very time-consuming as plant managers had to manually have the data collected from various legacy IoT applications and collated.
Data Fragmentation: Each of the multiple plants was storing production data in unique formats and locations, making it a hassle to standardize and?compare performance metrics.
Delayed Insights: 1-2 days delay in reporting metrics like production output, operational efficiency and?downtime.
Lack of Real-Time Visualization: The lack of a cohesive?system made it inefficient for plant managers to get the latest performance data and improved how quickly they can respond to issues.
Scalability Issues: The process was manual and fragmented which was not scalable and prevented the client from expanding operations without?significantly increasing resources.

Such challenges highlighted the need for an integrated?solution that automates data collection, minimizes error, and offers near real-time visibility.

Solution

For effective decision making, we identified inefficiencies in how production data was captured and consolidated and proposed an integrated automation and visualization solution using Power Automate RPA?and Power BI. This transformation replaced a fragmented, manual workflow with?a central system providing a significant increase in accuracy, operational efficiency, and scalability. The starting point was that?each plant’s legacy IoT system would automatically sync up its production logs, as CSV files, into a central network drive folder. It meant a single source of raw data from all the?plants was accessible. Next,?an unattended Power Automate RPA bot was scheduled to monitor this network drive, download any new log files, standardize the data, and sync it into a Power BI dataset. It replaced manual processes with automated insights with minimal errors leading to?a steady data stream.

The standardized data in the Power BI dataset was the basis for a custom-built Power BI dashboard to show real-time visualization of key production metrics, including?actual production output, operational efficiency, and machine downtime. The dashboard was set to refresh automatically, allowing plant managers and stakeholders to view insights live instead of relying on ad-hoc requests and making data-driven decisions on?time. In order to ensure an even better level of responsiveness, Power Automate was integrated to create automated?notifications whenever there were new/updated reports made available. These alerts helped relevant teams stay informed and?take action quickly when production performance changes occurred.

The result was a centralized and scalable solution that allowed for a single view of the production information across the entire?facility. The system was built for scale, easily integrating additional data?sources, more plant locations, and new log files without manual intervention or additional infrastructure. Overall, this solution achieved both the efficient management of production?data and built a solid platform for data-driven operation and future scalability.

Automated Data Collection with Power Automate RPA

RPA bots extracted production data from legacy IoT applications at each plant level.
The extracted CSV data was transformed into a standardized format and stored in Power BI Datasets.

Real-Time Data Visualization with Power BI

A custom Power BI dashboard was developed to visualize key production metrics, including:

Actual production output

Operational efficiency

Downtime

Power BI was configured to automatically refresh with the latest data collected by Power Automate, ensuring real-time access to insights.

Automated Notifications: Power Automate sent notifications to plant managers and stakeholders whenever new or updated reports were available, keeping them informed of the latest metrics.

Centralized and Scalable System: The solution provided a centralized view of production performance across all plants and was designed to scale effortlessly as the company expanded.

Results

The Power Automate RPA Implementation of the automated data collection and visualization solution brought transformative improvements to the client’s operations.

Key Metrics

Metric	Before Automation	After Automation	Improvement
Manual Data Collection Time	Hours per day	No manual effort	100% Reduction
Data Accuracy	Prone to errors	Near-perfect accuracy	Near-Elimination of Errors
Data Availability	Delayed, often outdated	Real-time updates	Instant Access to Data
Production Insights Access Time	1-2 days for reports	Available daily	100% Faster
Decision-Making Speed	Slow due to delayed reports	Faster, real-time insights	Significantly Improved
Scalability	Limited to current plant systems	Easily expandable to more plants	Unrestricted Growth

Detailed Benefits Analysis

Efficiency Gains: Data that was previously collected manually, taking up hours each day, was now fully automated, and plant?managers could focus on higher-value activities.
Improved Data Accuracy: Also, the possibility of errors was reduced since all data extraction and transformation was automated, providing reliable numbers?for analysis and decision making.
Real-Time Insights: Real-time data on critical metrics gave managers the?information they needed to respond quickly to production problems.
Faster Decision-Making: Metrics in?real-time visualization helped managers to make quick and informed decisions, leading operational agility.
Scalability for Growth: Newly added plants and new data?sources can be added without creating any efforts were scalable in the long term.