Abstract
In a world where most projects experience a 45% increase in duration the need to address late project completion is paramount (Rooholelm & Abourmasoudi, 2022). It is customary for project stakeholders to conduct comprehensive financial assessment, but the time aspect of the project is frequently overlooked (Glenwright, 2008). A project manager’s ability to design an ideal baseline for construction operations is crucial to a project’s success in a dynamic business environment like construction (Dasovic & Klansek, 2021).
The purpose of the study is to enhance the quality of baselines thereby reducing time-related risks and advance the discipline of project management by validating project baselines utilising a Design Science Research Methodology approach.
The correct solution to any problem is not “solving” it, but rather defining it (Wieringa, 2014). The literature review identified factors influencing project completion, pinpointing poor baselines as a critical problem. The research approach employed a Design Science Research Methodology to develop a Baseline Validation Model (BVM) aimed at improving the quality of baselines and reducing project time-related risks. This was achieved by evaluating baseline quality in terms of the current level of compliance with industry standards and best practices and then proposed enhancements.
The research methodology focused on theoretical concepts' impact on the BVM's development and evaluated the forward-looking nature of design research compared to traditional methods. The study's conceptual framework explored architectural structures and baselines' characteristics, highlighting the importance of understanding their components' interaction in achieving the desired system-level phenomena.
The BVM was developed applying a design cycle that emphasized the iterative nature of the design process and problem identification while outlining the model’s design principles, requirements, and contribution to the objectives. Maedche et al. (2019) highlights the importance of having a dedicated process model and a step for problem identification as part of the design science process. After the BVM was developed, an empirical cycle was followed to design the research setup and logically analyse data. The strategy aimed to answer the research question regarding the accuracy and conformance of the BVM development with industry standards and best practices.
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Overall, this research presents a systematic approach to address late project completion issues through the development of a BVM and the validation of project baselines aligned with scheduling industry standards and best practices.
To truly understand baseline behaviour, the study emphasizes the significance of understanding the architectural system structure and its interaction patterns. The similarities between the system architecture and Baseline (B) strengthen the viability of a design science methodology. In addition, the global problem of late project completion identifies the underlying causes of this issue. It suggests mitigating these factors with a Baseline Validation Model (BVM).
By enhancing baseline quality with the BVM, the research anticipates improved usability of updated baselines in delay and disruption (DD) analysis, leading to improved project management decisions and reduced project time-related risks. Lastly it was confirmed that the Baseline Validation Model (BVM) accurately evaluates and establishes the level of Baselines conformance to industry standards and scheduling best practices, thereby enhancing baseline quality in the field.
The key findings of this research have significant implications for project management and scheduling practices. The use of Design Science Research Methodology (DSRM) provided a structured approach to developing the Baseline Validation Model (BVM), ensuring its effectiveness in addressing complex project management challenges. Understanding a system’s architectural structure and interaction patterns is crucial for evaluating baselines, helping project managers assess risks more accurately.
The BVM, integrated as a plug-in for scheduling software, reduces validation costs and improves baseline quality. It identifies factors contributing to project delays and offers recommendations to mitigate these risks, leading to better scheduling and fewer delays. By improving baseline quality, the BVM enhances delay and disruption (DD) analysis, supporting better time-risk management. Additionally, it aligns with industry standards, raising the overall quality of scheduling practices across sectors.