PMC : a classification of production metrics found useful by AEC professionals
Abstract/Contents
- Abstract
- A modern paradigm considers AEC projects to be temporary production systems. Through rapid feedback, production metrics (PM) provide a chance to project teams to control these production systems by adjusting their actions and decisions in a timely manner, making it more likely for projects to stay on track. Observation of PM reported (PMR) through the Virtual Design and Construction (VDC) certificate program conducted by the Stanford Center for Professional Development (SCPD) revealed that AEC professionals are missing a common PM vocabulary, which hinders establishing and reporting PM consistently. While a limited number of PM, such as PPC (percent plan complete), number of RFIs (requests for information), number of changer orders, and number of clashes detected, are gaining widespread adoption in the AEC industry, it isn't clear whether there are other PM which AEC professionals are finding useful and whether they are generalizable across a variety of projects. This thesis contributes a classification of production metrics found useful by ~600 AEC professionals managing a variety of project production systems. The professionals represent ~100 AEC companies engaged as owners, designers, and builders on ~300 projects of different types (building, infrastructure, industrial) in 10 countries on 2 continents. The contribution, presented in this dissertation as the production metrics classification (PMC), was generated through several rounds of content analysis and expert reviews of 1,971 PMR by professionals enrolled in the 1st large-scale VDC certificate program, and was validated through a survey administered at the 2nd program. It consists of 96 PM grouped into 3 categories and 17 sub-categories. 36 of the 96 PM relate to collaboration, 17 relate to information generation and use, and 43 relate to workflows for managing project production systems. 37 of the 96 PM relate to conformance while 59 relate to performance. 7 PM are likely to be measured daily and 70 are likely to be measured weekly. 33 PM can be measured immediately after an activity is performed and are therefore, likely to improve in the short term, i.e., within a week of adjusting actions and decisions, while others are likely to take longer. The PMC addresses a conceptual gap in the literature by providing clarity on specific PM found useful in project production systems. It provides a foundation for future research to establish control mechanisms in AEC production systems based on feedback provided by specific PM. In addition, it opens pathways for establishing correlations between specific PM and project outcomes.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2024; ©2024 |
| Publication date | 2024; 2024 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Majumdar, Tulika, (Engineer) |
|---|---|
| Degree supervisor | Fischer, Martin, 1960 July 11- |
| Thesis advisor | Fischer, Martin, 1960 July 11- |
| Thesis advisor | Jain, Rishee |
| Thesis advisor | Rajagopal, Ram |
| Degree committee member | Jain, Rishee |
| Degree committee member | Rajagopal, Ram |
| Associated with | Stanford University, School of Engineering |
| Associated with | Stanford University, Civil & Environmental Engineering Department |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Tulika Majumdar. |
|---|---|
| Note | Submitted to the Civil & Environmental Engineering Department. |
| Thesis | Thesis Ph.D. Stanford University 2024. |
| Location | https://purl.stanford.edu/mf908kw8349 |
Access conditions
- Copyright
- © 2024 by Tulika Majumdar
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...