Performance Based Studies Research Group

-Abstract-

The Performance Information Procurement System (PIPS), was tested on the procurement of the $2.96 million Bridgerland Academic Training Center (ATC) for the State of Utah’s Division of Facilities Construction Management (DFCM).  The artificial intelligent (AI), information based PIPS was run two ways; selection with biased subjectivity (similar to current best value processes), and without biased subjectivity.

Unlike other best value processes, PIPS minimizes the decision-making and subjective bias of the owner’s representatives.  The procurement test at Bridgerland ATC provides a comparison between the AI selection vs. the user agency’s subjective prioritization.  The result of the system was one of the “best” construction projects procured at the State of Utah (on-time, on-budget, high quality), with no contractor generated change orders for additional cost, minimized construction management requirements, and high customer satisfaction.

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-Abstract-

Paper: The role of A&E design firms is changing in response to changes in the construction industry. Five major construction industry changes are identified and discussed. They are as follows: the impact of alternate delivery processes, the impact of design being awarded based on price, the offering of design services by general contractors, the global competition of design services, and consolidation of A&E design services.

All the trends are based on the commodity of design services in the perception of owners who are the end users of construction. The study also discusses the similarities between the contractors and designers in this new industry environment. The paper addresses three actions A&E firms can take in response to these changes and industry structure changes that can maintain design quality.

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-Abstract-

The construction industry has had a poor performance record (on-time, on-budget, and meeting owner expectation). This paper proposes that the reason for poor construction performance is a lack of performance information and poor practices, such as user and designer subjective decision-making and resulting attempted control of the contractor.

The paper introduces the Information Measurement Theory (IMT) to explain the hypothesis. IMT is the measurement of information to minimize the risk of nonperformance. IMT states that the owner‟s subjective expertise and decision-making is a factor affecting the level of construction performance. The hypothesis was tested using the Performance Information Procurement System (PIPS) on the procurement of the $2.96 million Bridgerland Academic Training Center (ATC) for the State of Utah‟s Division of Facilities Construction Management (DFCM). The artificial intelligent (AI), information based PIPS, was run two ways; selection with biased subjectivity, similar to current low-bid processes, and selection without biased subjectivity. Unlike other processes, PIPS minimizes the decision-making and subjective bias of the owner‟s representatives. The procurement test at Bridgerland ATC provides a comparison between a minimized bias selection vs. a user agency‟s subjective decision-making prioritization. The user then quantifies the differential based on past construction performance and the results of the information based procurement. The results of the information based system were successful. Although the conclusions are preliminary and based on one case study, the results are in agreement with other ongoing tests. The research paper describes the development of the hypothesis to minimize subjectivity, the test of the hypothesis, the results, conclusions and recommendations.

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The procurement delivery system of choice in the construction industry has been the competitive "low-bid" award. The process includes specifications and drawings (design, construction means and methods, and legal terms of the contract.) As economies have moved into the information age and influenced by the price pressures of the worldwide competitive marketplace, contractors have been forced to leverage volume.

This process has affected the quality and capability of the construction industry. The construction industry has been quick to blame the effects of the low-bid system (construction that is not on time, on budget, meeting quality expectations of the owner) on the owners low-bid award process. However, when given an opportunity to change to a value added, information based performance procurement process, the construction industry components have been slow to embrace the change. This paper gives a theoretical explanation for the current construction industry position, and supports it with results from the State of Utah and the State of Hawaii to identify the construction industry’s resistance to moving to an information age, "best value" construction environment.

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The construction industry is composed of manufacturers, contractors, designers, inspectors, construction managers, and end users or facility owners. This article defines information as "nonbiased data that accurately describes an entity in relative terms and predicts the future outcome." It describes an information environment and explains how information that is generated by an artificial intelligent system will impact the construction industry.

An information environment will include the relative performances of contractors, construction systems, and constructor personnel (project managers and site superintendents). This information will alter the functions of designers, constructors, and construction managers. This includes the minimization of subjectivity and decision making (minimum standards), the identification of performance and value, and the minimization of non-value added functions (inspection, designers directing contractors with means and methods, designers subjectively deciding what works and what does not, and the low bid awards which assumes that all contractor services "are the same"). For the past six years, PBSRG has been researching the impact of an information environment created by the Performance Information Procurement System (PIPS) and an artificial intelligent processor which generates performance information. This article will use test results from three different environments, the states of Utah, Hawaii, and Georgia, to show the impact of information systems on the future construction structure and environment. It identifies the new structure, the new roles of the major participants, and how the transition may be accomplished.

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