In the bustling city of Addis Ababa, where construction projects often face a maze of uncertainties, a groundbreaking study offers a beacon of hope for more accurate and reliable project scheduling. Led by Soreti M. Liben from the Addis Ababa Science & Technology University, this research, published in the Journal of Asian Architecture and Building Engineering, introduces an integrated model that promises to revolutionize how public building projects are planned and executed.
The city’s complex environment, characterized by regulatory hurdles, site-specific challenges, and economic fluctuations, often leads to unreliable schedules and increased risks. Liben’s study addresses these issues head-on by merging deterministic and probabilistic approaches to enhance schedule accuracy. “Existing practices in Addis Ababa often result in schedules that are more wishful thinking than reliable forecasts,” Liben explains. “Our model aims to change that by incorporating a wide range of factors that influence project duration.”
The integrated conceptual model considers everything from project scope and regulatory requirements to site conditions, contractual terms, and even economic and political influences. Data collected from clients, consultants, and project supervisors highlighted key parameters such as the number of buildings, regulatory approvals, government shutdowns, project locations, risk management strategies, and site conditions. These factors are crucial in shaping the model’s baseline durations, which are then adjusted using historical data and expert judgment.
One of the standout features of this model is its use of probabilistic methods like Monte Carlo simulations and Program Evaluation and Review Technique (PERT). These techniques allow for a more nuanced understanding of variability, providing a comprehensive project duration estimate that accounts for the myriad uncertainties inherent in construction projects.
The practical implications of this research are vast, particularly for the energy sector, which often relies on public buildings for infrastructure projects. Accurate duration estimation can lead to better resource allocation, reduced costs, and minimized delays. “By integrating these methods, we can provide a roadmap for implementation that is both practical and adaptable,” Liben notes. “This approach can be a game-changer for how we plan and execute projects in the future.”
The model’s implementation in R and Python, validated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2) metrics, ensures its robustness and reliability. This integration of advanced statistical methods with practical construction data represents a significant leap forward in the field.
As the construction industry continues to evolve, the need for more accurate and reliable project scheduling becomes ever more critical. Liben’s research, published in the Journal of Asian Architecture and Building Engineering, offers a compelling solution that could shape the future of construction project management in Addis Ababa and beyond. By embracing this integrated approach, stakeholders can look forward to more predictable timelines, reduced risks, and ultimately, more successful project outcomes. This is not just about building structures; it’s about building a more reliable and efficient future for the construction industry.