Smart data and business analytics: A theoretical framework for managing rework risks in mega-projects

State of Science: Why Does Rework Occur in Construction? What Are Its Consequences? And What Can be Done to Mitigate Its Occurrence?

“…Determining the costs of rework is not a straightforward process, especially when such costs have seldom been considered a formal key performance indicator by construction organizations in their projects [25,[27][28][29][30]71]. Moreover, rework data is often located and stored in disparate repositories in projects (e.g., site diaries, non-conformances, site instructions, and punch lists), rendering it complicated to calculate the actual costs and consequences [71].…”

“…Determining the costs of rework is not a straightforward process, especially when such costs have seldom been considered a formal key performance indicator by construction organizations in their projects [25,[27][28][29][30]71]. Moreover, rework data is often located and stored in disparate repositories in projects (e.g., site diaries, non-conformances, site instructions, and punch lists), rendering it complicated to calculate the actual costs and consequences [71]. For example, in a monthly project review report for the construction of a liquified natural gas jetty, made available to us by a Tier 1 contractor, the following comment was made under the heading 'Quality': ''The true costs of rework are not being captured, particularly the consequential cost of traveler delays due to cracked welds hold up.…”

“…It is reasonable to suggest that communication is the key to containing and reducing errors and violations, but Ye et al [20] overlook the question of how to mitigate rework. Without a doubt, this is a challenge, but improving communication requires an understanding of how information flows in an organization and within projects [71].…”

Beyond digital shadows: A Digital Twin for monitoring earthwork operation in large infrastructure projects

“…Descriptive analytics addresses questions arising from the past until the present moment. For example: “What has happened?” and “What is happening now?” Diagnostic analytics examines data to explain the reasons of underlying events and addresses the question of “Why did it happen?” Predictive analytics attempts to provide future trends by answering such questions as “What will happen?” and “Why will it happen?” Finally, prescriptive analytics provides foresights to decision makers by informing them of answers to “What should be done?” and “Why should it be done?” This categorisation of data analytics types is a modified version of the theoretical framework provided by Matthews et al ( 2022 ) for utilising smart data. The modified version consists of separating the diagnostic elements from descriptive analytics to form a distinct cluster.…”

“…and "Why should it be done?" This categorisation of data analytics types is a modified version of the theoretical framework provided by Matthews et al (2022) for utilising This study…”