Data Governance
Enhancing AEC Data Governance: Aligning Technology with Task Requirements
Big data continues to transform decision-making processes in the architecture, engineering, and construction (AEC) industry. Recent studies have identified substantial deficiencies in existing data governance frameworks, which impede the realization of data-driven insights that are crucial for achieving optimal project outcomes.
One of the primary challenges identified was data fragmentation across multiple systems. In numerous AEC projects, information is gathered in isolated silos, resulting in inconsistencies and difficulties with data integration. This fragmentation not only impedes communication among project stakeholders but also undermines the reliability of the data used in critical decision-making.
In a study that applies Task-Technology Fit (TTF) theory as a structured framework, these challenges are explored. TTF suggests that aligning the capabilities of technological tools with the specific tasks they are intended to support, enhances performance. In the context of AEC, this implies that technology must be meticulously calibrated to manage the diverse and complex data generated during the design, construction, and operational phases. In this regard, misalignment can compromise decision-making, potentially resulting in project delays, increased costs, and greater risks.
The study's key recommendations emphasize three critical areas.
• Standardization: The establishment of uniform data formats and protocols is essential for mitigating inconsistencies and enhancing data integration. A standardized approach ensures that data from diverse sources are coherent and actionable.
• Quality Assurance: The enhancement of quality control measures is crucial. Rigorous verification processes can improve data accuracy, thereby strengthening the trust in analytics-driven insights.
• Security Enhancements: Given the significant risks posed by data breaches, updating security protocols is imperative. Enhanced security measures not only protect sensitive information but also foster confidence in stakeholders.
To implement these recommendations, establishing a flexible and adaptive framework that evolves in tandem with technological advancements is essential. This framework should be grounded in interdisciplinary collaboration, integrating insights from business management, engineering, and information technology to develop a robust governance structure specifically designed for the AEC industry.
This study underscores the fact that adopting a task-oriented approach to data governance can significantly enhance operational efficiency. By ensuring that technological tools are strategically aligned with the tasks they are intended to support, organizations can improve data reliability, optimize decision-making processes, and foster innovation in project management.
This study advocates for active dialogue between industry professionals and policymakers. Establishing open communication channels and continuous feedback mechanisms is essential for refining governance practices. As the AEC sector undergoes digital transformation, these insights offer a strategic framework for developing resilient and agile systems capable of addressing the challenges posed by big data while promoting sustainable growth.
In conclusion, the effective use of big data necessitates not only technological investment but also the strategic alignment of data governance frameworks with practical applications. This study provides a pragmatic, research-based foundation for re-evaluating data management practices within the AEC industry, thereby ensuring that decision-making processes are both secure and efficient.
Stakeholders are encouraged to consider how these strategies might be implemented within their organizations and to identify additional measures that could further enhance data governance in the AEC sector.
Written by Frederick Nana Yaw Ainoo, Ph.D.
Read full text here: https://www.proquest.com/docview/3179645891
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