Enhancing Pre-Construction Decision-Making on Sustainable Commercial Building Projects

Overview

Architecture, engineering, and construction (AEC) teams need more efficient and effective decision-making methods, particularly during pre-construction of sustainability-focused projects when decisions have the most impact on sustainability performance. The multi-disciplinary nature of decision-making and the engagement of multiple stakeholders often result in decision problems with multiple objectives, calling for approaches referred to as multi-criteria decision-analysis (MCDA). There is little consensus on the best method for pre-construction decision-making. This work proposes the enhancement of pre-construction decision-making for sustainability-focused projects through design and implementation of a multi-criteria decision-analysis framework. The research, to be conducted with students and interested CIFE participants, will be used to evaluate the process and decision quality of different MCDA methods and study the treatment of sustainability objectives. Ultimately, by better integrating sustainability into pre-construction and developing more rigorous decision-making frameworks that are quick and easy to use, AEC professionals can help clients achieve sustainability goals with greater efficiency.

 

Project Background

I. Research Motivation

Over the course of a building project, architecture, engineering, and construction (AEC) consultants predict and evaluate the performance of many different design and construction options. The daily design-construction recommendations that these AEC consultants make to the client have significant impacts on the sustainability of the building throughout its life cycle. (Ugwu and Haupt 2007) With contractors and designers frequently working under strict budget and schedule constraints, AEC consultants need superior planning, design, and construction processes to achieve client goals. It is critical that AEC professionals have the appropriate tools and effective processes to integrate sustainability into their everyday decision-making processes.

One of the most active and important stages for decision-making is pre-construction. For the purposes of this proposal, pre-construction encompasses all of the phases in which changes to the design are minimal but design and construction details are still being finalized. This means that during pre-construction, decision makers are dealing with decisions that have fewer, better-defined alternatives to consider and more information to accurately evaluate those alternatives as compared to early-stage design. However, while decisions may be fewer and easier to model, the ability of decision makers to change project design and cost decreases and the cost of design changes (in terms of resources and budget) increases significantly.

II. Industry Case Study

AEC professionals and researchers are actively investigating formal decision processes in practice, primarily for early-stage design and pre-construction. A case study was conducted with a CIFE member company during the pre-construction phase of a single large-scale, sustainability-focused project, executed using Integrated Project Delivery (IPD). The company sought clear communication and desired a rigorous decision-making process to ensure that high-level performance goals, including cost, schedule, safety, and sustainability objectives, would be met. The multi-objective, multi-disciplinary nature of pre-construction decision meant that selecting an appropriate decision-making process was key. The team was concerned with identifying an appropriate process for project-related decisions that had a significant impact on project cost or schedule and required supporting information from AEC professionals. These decisions included, but were not limited to, trade partner selection, technology adoption, and detailed systems comparisons.

For several months during pre-construction, the company implemented two formal, value-based decision methods: first Weight, Rate, and Calculate (WRC), then Choosing By Advantages (CBA) (Suhr 1999). However, the company found that neither process led to decisions of satisfactory quality and eventually rejected both. In general, decision makers found that CBA enabled multi-disciplinary stakeholder participation and added value to decision-making for simple decision problems. However, decision makers also believed that CBA was inefficient and ineffective for more complex decision problems and did not adequately clarify decision rationale. The introduction of an online tool, Wecision Enterprise (DPI 2013), to support CBA improved efficacy, efficiency, and value of information derived from the decision-making process, but clarity of rationale remained an issue due to the inherent complexity of decision problems and inconsistencies in factor selection between decisions. These observations suggest the need for future research concerning the design and implementation of appropriate tools for pre-construction decision-making on lean projects. 

 

Research Objectives

This research has two primary goals. The first is to determine whether formal, value-based decision methods do in fact produce higher quality decisions and what data visualization techniques are best suited to representing the tradeoffs for pre-construction decisions on building projects. The second objective is to gain insight into the best way to integrate sustainability objectives into pre-construction decision support systems and to establish a foundation for further research to determine how integrated sustainability pre-construction decision-making can be enhanced.

 

Research Methods

I. Decision Methods and Tradeoff Visualization

A series of charrettes was conducted with industry professionals and graduate students in architecture and engineering. Participants were divided into teams of 3-5 and asked to solve a simple building design problem that minimized life cycle cost, capital cost, and construction schedule duration. Teams could alter six discrete design parameters, providing 144 unique design alternatives. Cost and schedule performance was available for each design. Teams were split into four experimental groups, each of which received up to two tools to aid their decision-making. The first tool graphically plotted design alternatives on two Pareto fronts: Life Cycle Cost vs. First Cost and Construction Schedule vs. First Cost. The second used simple additive weighting (SAW) to provide a normalized score (0-1) for each alternative relative to the complete population of designs, thus allowing teams to view the score for each alternative in each of the three objective categories, as well as an overall score. Participants also completed surveys before and after the charrette to gather qualitative data related to satisfaction with the organizational decision-making processes and level of consensus around the team’s final recommendation. 

II. Integrating Sustainability Objectives

To investigate the effect of sustainability objectives, a second series of charrettes will be conducted. These charrettes will be identical in design to the first series with the exception of the performance objectives: construction schedule duration will be replaced with total carbon impact, which encompasses embodied and operational carbon impacts.

 

Results

I. Decision Methods and Tradeoff Visualization

a) Improvement in Design Quality

  • Overall, teams wtih SAW and Pareto improved more than teams with one tool or no tools

  • Professional teams did better with SAW, alone or with Pareto

  • Students only improved with Pareto alone

Improvement in Design Quality

 

b) Recognition of Design Quality

  • Teams with only Pareto missed the best design 60% of the time

  • All teams with SAW and Pareto succesfully identified their best alternative


Recognition of Design Quality

 

c) Confidence in Design Quality

  • Confidence in quality of team solution was higher with formal, structured decision method (ie. SAW) 

Confidence in Design Quality

 

Project Team

Principal Investigators: 

      Michael Lepech, Assistant Professor of Civil & Environmental Engineering 

      Gary Griggs, Consulting Professor in Civil & Environmental Engineering

Research Staff:  

      Kelcie Abraham, PhD Candidate in Sustainable Design & Construction (kelcie@stanford.edu)


Downloads

Original Proposal  



Last modified Tue, 19 Aug, 2014 at 19:37