Open Access
Dubler, Craig Richard
Graduate Program:
Architectural Engineering
Doctor of Philosophy
Document Type:
Date of Defense:
July 08, 2011
Committee Members:
  • John Messner, Dissertation Advisor
  • John Messner, Committee Chair
  • M Kevin Parfitt, Committee Member
  • Samuel Todd Hunter, Committee Member
  • Chinemelu Jidenka Anumba, Committee Member
  • Building Information Modeling
  • Information Managment
  • Lean Thinking
The Architecture, Engineering, and Construction (AEC) Industry has the potential to increase profitability through improvement of the information exchange (IE) process on building projects. According to a study performed by the National Institute of Standards and Technology (NIST) in 2004, the annual cost of inadequate interoperability is approximately 15.8 billion dollars on U.S. capital facilities. Because the AEC Industry is project centered, and many different organizations work towards design and construction goals, the information exchange process is constrained, and collaboration is required for success. Building Information Modeling (BIM) is a process that provides a means for owners, designers, contractors, and operators to generate, organize and use detailed information throughout a project life cycle. However, the success of BIM relies heavily on the accuracy and availability of the information exchanged between project team members. In some studies, BIM has been shown to save upwards of 30% in field labor costs due to increased productivity; however the full potential of BIM is currently being limited by the inefficiencies associated with unplanned information exchange procedures. This dissertation uses lean theory to identify and quantify the waste associated with the IE process from design to construction on projects using BIM. Through research, areas of waste were derived from lean principles and adapted to develop an information exchange waste taxonomy. The IE waste taxonomy was then used to identify the areas of IE waste on two case study projects. Additionally, quantitative metrics were designed to document the economic scale of the identified areas of waste. Finally, the identified waste on the two case studies was quantified, and the potential project impact was documented. This research provides a standardized method for the identification of IE waste on current building projects. The result of the IE waste on two case studies was estimated at 1.4 percent of the total Mechanical, Electrical and Plumbing (MEP) contract price. This value does not take into account the initial benefit of BIM, which is perceived to be substantially more than 1.4 percent. According to project team members, this research also prioritized high value added improvements to the IE process upon which they should focus their attention for future projects. In summary, the steps provided in this dissertation provide a structured method for project team members to identify and categorize areas of IE waste, quantify the potential impact, and evaluate the results for future project improvements. In order to improve project profitability, team members must first break through the BIM barrier, and then focus on designing efficient and effective information exchanges.