Proactive and Data-Driven Decision-Making Using Earned Value Analysis in Infrastructure Projects
Abstract
1. Introduction
- A tool to monitor and control the cost, time, and work conducted of a construction project.
- Provides an “Early Warning” signal for immediate corrective action.
- Forecasting the total project cost.
- It compares the planned amount of work with what has actually been completed to determine if cost, schedule, and work accomplished are progressing as planned.
- The present study aims to show the theoretical dimension of performance measurement on construction projects and thereby contribute to its wider practical application.
- The coding and implementation of these analyses were performed using MATLAB and Excel.
2. Visual Methodology Map
2.1. The Earned Value Management
Basic Concepts of Earned Value Method
3. Numerical Simulations Application
3.1. Real-Life Project (Case 1)
- Cost losss:
- ○
- Final EAC = MYR 774,992,828;
- ○
- Estimated BAC (based on trends) ≈ MYR 700,000,000;
- ○
- Cost overrun = 774,992,828 − 700,000,000 = MYR 74,992,828;
- ○
- Percentage cost overrun = (74,992,828/700,000,000) × 100 ≈ 10.71%.
- Schedule loss:
- ○
- Best SPI = 0.997, final SPI = 0.924;
- ○
- Percentage schedule inefficiency = (1 − 0.924) × 100 = 7.6%.
3.2. Real-Life Project (Case 2)
- Cost Savings:
- ○
- Initial EAC (July) = MYR 3.19 million;
- ○
- Final EAC (September) ≈ MYR 2.70 million;
- ○
- Savings = 3.19M − 2.70M = MYR 490,000;
- ○
- Percentage cost savings = (490,000/3.19M) × 100 ≈ 15.36%.
- Schedule Savings:
- ○
- SPI improved from 0.96 to 1.06;
- ○
- Percentage schedule improvement = (1.06 − 0.96) × 100 = 10.42%.
4. Conclusions and Discussion
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Miscellaneous | [36,37] | EVM methodology revision | 2003, 2019 |
Chemical | [38] | Improving forecasting models | 2016 |
Building construction | [39,40,41,42] | Financial risk evaluation in project budgeting, holistic project management methodology combining financial, quality and risk parameters | 2002, 2015, 2018, 2020 |
Cement factory | [27] | Time-cost–quality trade-off method | 1999 |
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Terms | Abbreviation | Description |
---|---|---|
Planned Value | PV(BCWS) | The budgeted cost of work scheduled to be completed by a specific date. |
Earned Value | EV (BCWP) | The budgeted cost of work actually completed by a specific date. |
Actual Cost | AC (ACWP) | The actual cost incurred for the work performed by a specific date. |
Cost Variance | CV | EV − AC, shows if you are over or under budget. |
Schedule Variance | SV | EV − PV, shows if you are ahead or behind schedule. |
Cost Performance Index | CPI | EV ÷ AC, indicates cost efficiency. |
SchedulePerformance Index | SPI | EV ÷ PV, indicates schedule efficiency. |
Estimate at Completion | EAC | Forecast of total cost at project completion, based on current performance. |
Estimate to Complete | ETC | The expected cost to finish all remaining work. |
Budget at Completion | BAC | The total budgeted cost for the entire project. |
BAC | MYR 668,153,392 | ||
---|---|---|---|
Duration | BCWS (Planned) PV | BCWP (Earned) EV | ACWP (Actual) AC |
Quarter 1 | 839,184 | 821,000 | 952,280 |
Quarter 2 | 6,789,683 | 6,771,000 | 7,391,301 |
Quarter 3 | 14,268,639 | 13,951,000 | 14,870,257 |
Quarter 4 | 21,528,478 | 19,220,074 | 22,142,755 |
Quarter 5 | 29,102,452 | 27,159,074 | 29,716,702 |
Quarter 6 | 37,867,842 | 34,990,074 | 38,587,439 |
Variance | Indices | Forecasting | Status | ||
---|---|---|---|---|---|
CV | SV | CPI | SPI | EAC | |
−131,280 | −18,184 | 0.862 | 0.978 | 774,992,828,421 | Slightly delayed and over budget |
−620,301 | −18,683 | 0.916 | 0.997 | 729,363,880,438 | Still over budget but improving |
−919,257 | −317,639 | 0.938 | 0.978 | 712,179,245,535 | Delayed but better cost control |
−292,2681 | −2,308,404 | 0.868 | 0.893 | 769,755,457,834 | Severely over budget |
−2,557,628 | −1,943,378 | 0.914 | 0.933 | 731,074,823,845 | Still over budget but improving |
−3,597,365 | −2,877,768 | 0.907 | 0.924 | 736,846,919,971 | High risk of budget overrun |
BAC | MYR 2,828,241 | ||
---|---|---|---|
Months | BCWS (Planned) | BCWP (Earned) | ACWP (Actual) |
July | 229.999 | 220.831 | 249.077 |
August | 210.840 | 201.672 | 229.918 |
September | 143.731 | 152.878 | 145.791 |
Variance | Indices | Forecasting | Status | ||
---|---|---|---|---|---|
CV | SV | CPI | SPI | EAC | |
−28.2 | −9.2 | 0.886 | 0.960 | 3,189,994 | Cost overrun, behind schedule |
−28.2 | −9.2 | 0.877 | 0.956 | 3,224,362 | Cost overrun, behind schedule |
7.1 | 9.1 | 1.048 | 1.064 | 2,697,132 | Under budget, ahead of schedule |
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Ateş, B.; Eirgash, M.A. Proactive and Data-Driven Decision-Making Using Earned Value Analysis in Infrastructure Projects. Buildings 2025, 15, 2388. https://doi.org/10.3390/buildings15142388
Ateş B, Eirgash MA. Proactive and Data-Driven Decision-Making Using Earned Value Analysis in Infrastructure Projects. Buildings. 2025; 15(14):2388. https://doi.org/10.3390/buildings15142388
Chicago/Turabian StyleAteş, Bayram, and Mohammad Azim Eirgash. 2025. "Proactive and Data-Driven Decision-Making Using Earned Value Analysis in Infrastructure Projects" Buildings 15, no. 14: 2388. https://doi.org/10.3390/buildings15142388
APA StyleAteş, B., & Eirgash, M. A. (2025). Proactive and Data-Driven Decision-Making Using Earned Value Analysis in Infrastructure Projects. Buildings, 15(14), 2388. https://doi.org/10.3390/buildings15142388