Profit Visibility Optimization with Power BI & RPA Integration
Challenge
Our client, a professional services firm, used a Project Management System (PMS) to track key metrics like project hours, invoices, and partner assignments. However, generating monthly profit and utilization reports was a manual, error-prone process. It involved extracting data in Excel, cleaning and validating it, and cross-checking multiple variables—often taking over a full day per report and risking accuracy due to human intervention.
Our client, a professional services firm, used a Project Management System (PMS) to track key metrics like project hours, invoices, and partner assignments. However, generating monthly profit and utilization reports was a manual, error-prone process. It involved extracting data in Excel, cleaning and validating it, and cross-checking multiple variables—often taking over a full day per report and risking accuracy due to human intervention.
Solution
Difinity Digital addressed the client’s challenges by delivering a fully automated, system-driven solution by integrating Power BI, Robotic Process Automation (RPA), and SharePoint. A custom RPA bot was developed for monthly data extraction from the client’s PMS. The data was then cleaned, transformed, and stored in a structured format within SharePoint. We then applied business logic using Power Query and DAX to calculate key metrics such as total hours worked, invoiced amounts, client-wise and partner-wise profitability, average hourly rates, and banked hour summaries. The Power BI dashboard was set to auto-refresh, ensuring stakeholders always had access to the latest insights. Additionally, the RPA bot automatically distributed report links to relevant stakeholders. The entire solution was successfully completed within a five-week timeframe.
Difinity Digital addressed the client’s challenges by delivering a fully automated, system-driven solution by integrating Power BI, Robotic Process Automation (RPA), and SharePoint. A custom RPA bot was developed for monthly data extraction from the client’s PMS. The data was then cleaned, transformed, and stored in a structured format within SharePoint. We then applied business logic using Power Query and DAX to calculate key metrics such as total hours worked, invoiced amounts, client-wise and partner-wise profitability, average hourly rates, and banked hour summaries. The Power BI dashboard was set to auto-refresh, ensuring stakeholders always had access to the latest insights. Additionally, the RPA bot automatically distributed report links to relevant stakeholders. The entire solution was successfully completed within a five-week timeframe.
Results
- 90% Reduction in Reporting Time
Automated data consolidation and visualization significantly cut down the time required for report generation. What previously took hours or even days is now completed within minutes, allowing teams to focus on strategic decision-making instead of manual data preparation.
100% Accuracy in Financial Logic
The implementation of standardized financial models and automated validation ensures complete accuracy in calculations, eliminating human errors and maintaining consistency across all financial reports.
0% Manual Intervention
End-to-end automation of data extraction, transformation, and reporting processes means there is no need for manual updates or data entry. This not only enhances reliability but also frees up valuable analyst time for deeper business analysis and insights.
- 90% Reduction in Reporting Time
Automated data consolidation and visualization significantly cut down the time required for report generation. What previously took hours or even days is now completed within minutes, allowing teams to focus on strategic decision-making instead of manual data preparation.
100% Accuracy in Financial Logic
The implementation of standardized financial models and automated validation ensures complete accuracy in calculations, eliminating human errors and maintaining consistency across all financial reports.
0% Manual Intervention
End-to-end automation of data extraction, transformation, and reporting processes means there is no need for manual updates or data entry. This not only enhances reliability but also frees up valuable analyst time for deeper business analysis and insights.