Tracking Progress, Effort Hours, and Productivity in PowerBI
A Step-by-Step Guide
Tracking project performance is critical in large-scale engineering and construction projects, where every hour and every action contribute to overall success or delay. A key way to monitor and manage this is by linking Progress, Effort Hours, and Productivity—three vital metrics that, when visualized together, offer a comprehensive view of how well a project is advancing. By creating a 3-part curve using PowerBI, project managers can gain insight into not just what has been completed, but how efficiently it has been achieved, helping them make better decisions to keep projects on track.
This article will provide a step-by-step guide for creating and visualizing a 3-part curve in PowerBI that links project progress, effort hours, and productivity. We will also explore the importance of correlating these metrics and how Buro Matei ensures high-quality, actionable insights through a highly automated and data-driven approach.
Why It’s Important to Track Progress, Effort Hours, and Productivity Together
- Progress reflects how much of the project has been completed. It is often tracked as a percentage of work completed over time.
- Effort Hours represent the amount of labor invested in the project, including planned, actual, and predicted hours. These give project managers a clear view of whether the work is proceeding according to schedule and resource allocation.
- Productivity is calculated by dividing progress by effort hours, showing how efficiently labor is being used. A high productivity rate means the team is making significant progress with minimal effort, while a low rate could indicate inefficiencies or challenges in execution.
Visualizing these three metrics together provides a holistic view of project health. Progress shows how much work has been done, effort hours show how much work went into achieving that progress, and productivity links the two, revealing the efficiency of the labor force.
When used together, these metrics can:
- Identify areas where additional resources are required.
- Highlight inefficiencies or bottlenecks in the project workflow.
- Help predict future performance and whether the project is likely to meet its goals on time and within budget.
Further reading
↗ Progress Curves for Project Planning and Control
Steps for Building a 3-Part Curve in PowerBI
PowerBI is a powerful tool for visualizing project data, and when used correctly, it can present real-time insights into how progress, effort, and productivity are interacting over the course of a project. Below is a structured approach for building the 3-part curve.
1. Data Preparation
Before creating any visualizations, the data needs to be collected, cleaned, and formatted correctly. Since these metrics rely on consistent data sources, ensuring the accuracy and completeness of data is critical.
- Collect data on progress, effort hours, and productivity from various tools that track project execution (e.g., time sheets, engineering tools, and resource management systems). Buro Matei gathers insights as close to the source of action as possible to avoid redundant tracking.
- Standardize the data so that all metrics use the same time intervals (weekly or monthly, for instance). This ensures that when visualizing the data in PowerBI, the graphs align properly.
- Automate data updates to ensure that PowerBI dashboards display the most up-to-date information, allowing project teams to monitor performance on a daily basis without extra manual effort. This is a key feature of Buro Matei’s automated approach.
2. Setting Up the Data in PowerBI
Once the data is prepared, import it into PowerBI. PowerBI supports a variety of file types, databases, and direct integrations, allowing seamless data import from project management tools.
- Import the datasets for progress, effort hours, and any other relevant metrics (planned effort, actual effort, etc.).
- Create measures for key calculations:
- Progress: Use the percentage of completion over time.
- Effort Hours: This includes actual effort spent (e.g., number of hours worked), planned effort (hours scheduled), and predicted hours to go (hours required to complete remaining work).
- Productivity: This is calculated by dividing progress by the actual effort hours for each period (e.g., weekly productivity = progress achieved in that week ÷ effort hours in that week).
3. Visualizing Progress, Effort Hours, and Productivity
For effective visualization, use a combination of line charts and bar charts. This makes it easier to interpret how the three metrics relate to each other over time.
- Progress Curve:
Use a line chart for progress, with time on the X-axis and percentage completion on the Y-axis. This shows how much of the project has been completed at any given time.
- To ensure clarity, weight tasks based on their importance to the overall project using historical data. For example, tasks with higher Levels of Development (LOD) may carry more weight in terms of progress.
- Effort Hours:
Visualize effort hours as a bar chart, broken down by actual, planned, and predicted hours to go. Displaying this next to the progress line curve shows the labor effort required to drive the project forward.
- Productivity Curve:
The productivity curve can be visualized using another line chart that overlays the progress and effort graphs. Productivity is measured as progress divided by effort hours, providing insight into the efficiency of the labor. A higher curve indicates greater productivity, while dips in the curve can signal potential inefficiencies that need to be addressed.
4. Customizing the Visuals
While the traditional approach is to use a line chart for progress and productivity and a bar chart for effort hours, PowerBI allows for customization that can enhance the clarity of the visualizations.
- Use dynamic colors: For productivity, use color-coding to indicate periods of high and low efficiency. For example, a green line for high productivity, yellow for moderate, and red for low can visually alert project teams to areas that need attention.
- Dynamic filters: Buro Matei employs dynamic filters that allow users to drill down into specific project areas (e.g., by construction discipline, area, or activity). This level of granularity ensures that teams can analyze performance in detail without being overwhelmed by data.
- 4D visualization: For complex projects, integrating 4D (time + 3D) data with PowerBI charts can enhance planning by correlating construction activities with real-time performance data, ensuring logistics are fully accounted for.
5. Interactivity and Drill-Down Capabilities
PowerBI’s strength lies in its interactivity. Create filters and drill-downs that allow project managers and stakeholders to interact with the data on different levels.
- Drill down by area: For large projects, dynamic filters can break down progress, effort hours, and productivity by site area or phase. This enables project managers to pinpoint underperforming sections and adjust resource allocation.
- Discipline-specific insights: By drilling down into specific disciplines or activities, project teams can monitor the progress and efficiency of different trades and ensure that each part of the project is on schedule.
For example, a project manager can isolate the progress and productivity of structural work versus mechanical installations and compare how much effort is being consumed by each.
6. Using the Dashboard for Better Decision-Making
While the curves themselves provide an overview of how a project is performing, they do not offer actionable insights without further analysis. Buro Matei enhances these dashboards with deeper analytics and breakdowns, allowing teams to not only understand current performance but also take corrective actions.
- Identify trends: If productivity starts to decline while effort hours increase, project teams can investigate whether additional resources are needed or whether inefficiencies are creeping into the workflow.
- Forecasting: Use the progress curve to project future performance. If effort hours increase without a corresponding rise in productivity, the project may face delays, requiring immediate intervention.
- Efficiency metrics: Although closely related, productivity and efficiency differ, with the latter representing the ratio of resources consumed to the work produced. This distinction ensures a deeper understanding of how well resources are being used.
Conclusion
By correlating Progress, Effort Hours, and Productivity in a well-designed PowerBI dashboard, project managers gain a detailed, data-driven understanding of their project’s performance. Visualizing these metrics together not only provides a snapshot of where the project stands but also reveals trends and insights that can drive better decision-making. Buro Matei’s approach to data standardization, automated reporting, and advanced analytics ensures that this process is seamless, reliable, and highly insightful.
Key Takeaways:
- Progress, Effort Hours, and Productivity offer a holistic view of project performance when tracked together.
- Creating the 3-part curve in PowerBI allows for real-time monitoring, interactive filters, and drill-down capabilities, enabling teams to take corrective action before delays become critical.
- Weighting progress tasks and automating data updates ensures accurate and timely insights.
- Buro Matei’s expertise in data visualization goes beyond reporting, enabling predictive analysis and more efficient resource management across projects.
By following this structured approach, organizations can create powerful, actionable visualizations that keep projects on track and within budget.