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What the Data Says: Commercial Construction Delivery Methods

Writer's picture: Zach SimmonsZach Simmons

Introduction

The U.S. building construction industry, with its myriad stakeholders and intricate processes, is a complex web of operations. At the heart of this web are the project delivery systems, which serve as the blueprint for how construction projects are executed. But with a plethora of systems to choose from, how do stakeholders navigate this maze to ensure optimal outcomes? Let's embark on a comprehensive exploration into the U.S. Building Construction Project Delivery Systems to find answers.


Understanding Project Delivery Systems

The U.S. construction industry is characterized by three dominant delivery systems: Design-Bid-Build (DBB), Construction Manager at Risk (CMR), and Design-Build (DB). Each system has its unique characteristics:

  1. Number of Contractual Relationships with Stakeholders: The way each system sets up contractual ties with project participants varies, influencing the dynamics of stakeholder interactions.

  2. Timing of Stakeholder Involvement: The stage at which different stakeholders are brought into the project can significantly influence the project's flow and outcomes.

  3. Contract Payment Terms: Each delivery system has its patterns in outlining payments, affecting the financial dynamics of the project.

  4. Stakeholder Selection Criteria: The criteria for choosing stakeholders can vary, impacting the quality and expertise brought into the project.

For a more intuitive understanding, Figure 1 offers a visual representation of these relationships, highlighting the central figures and supporting roles in each system. This graphical representation aids in understanding the hierarchy and interaction patterns within each system.


Figure 1


Zooming into Each Delivery System

Each delivery system has its unique sequence, selection criteria, and oversight mechanisms:

  • Design-Bid-Build (DBB):

    • Sequence: This traditional system follows a linear sequence, starting with the owner contracting a designer. Once the design is almost finalized, a general contractor is hired to execute the project.

    • Selection of GC: General contractors are typically chosen based on competitive bid prices.

    • Oversight: Throughout the construction phase, the designer oversees the general contractor, ensuring the owner's interests are upheld.

  • Construction Manager at Risk (CMR):

    • Sequence: The owner first contracts with a designer. A GC or Construction Manager is then brought in when the design is between 20 to 60% complete.

    • Selection of GC or CM: The GC or CM is selected based on qualifications, proposed action plans, and fee structures.

    • Contract Modalities: The initial contract could be cost reimbursable but often transitions to a guaranteed maximum price or a lump sum as the project progresses.

    • Role: The early involvement of the GC or CM necessitates their close coordination with designers, providing insights into constructability, estimations, and scheduling.

  • Design-Build (DB):

    • Sequence: The owner signs a single contract with a design-builder, who might be a comprehensive firm or a collaboration between design and contracting entities.

    • Selection: Design-builders are often chosen based on qualifications or a combination of cost and technical proposal.

    • Contract Modalities: The contract might be lump sum or cost plus a fee, depending on the design completion stage.

Delivery system performance metrics

Research Revelations: A Deep Dive into Performance Metrics

Post the influential 1998 CII study, subsequent research has consistently shown DB projects outperforming CMR and DBB, especially in sectors like public infrastructure, sustainable projects, and healthcare ventures. However, the success of a project isn't solely dependent on the delivery system. Factors like team integration and group cohesion, representing the collaborative activities and interpersonal alignment among stakeholders, play a pivotal role.


Research Methodology: Behind the Scenes

The foundation of this research lies in a dataset sourced from a prior study, encompassing 212 projects. These projects, spread across the U.S., were concluded post-2008 and offer a comprehensive view of the industry's performance metrics. The dataset, segmented by project delivery system, size, funding, and complexity, provides a holistic view of the construction landscape.


Comparative Analysis: Numbers in Action

The research employed a robust methodology, delving into performance metrics like unit cost, cost growth, schedule growth, and delivery speed. The findings were illuminating:

  • Cost Analysis: The DB system showcased superior performance in unit cost and cost growth. Projects using DB were projected to be more cost-effective than both CMR and DBB. The coefficient of determination (R^2) for unit cost was notably high, indicating the model's robustness. However, cost growth's R^2 was lower, suggesting more underlying factors not captured in the dataset.

  • Schedule Performance: The Design-Build system consistently outperformed its counterparts in terms of schedule metrics. It delivered projects more swiftly both during construction and across the entire project duration. However, the R^2 value for schedule growth was substantially lower, indicating that a significant amount of its variance remains unexplained.


Additional performance metrics


Human Insights: The Pulse of Construction Projects

Interviews with top and bottom quartile performers revealed the undeniable importance of human and relational factors. Key takeaways include:

  • Early Team Formation: Early integration fosters collaboration and proactive problem-solving, setting the stage for success. This early collaboration allows for effective decision-making and lays a foundation of mutual understanding.

  • Relational Culture: Trust and mutual understanding lead to improved collaboration and reduced misunderstandings, emphasizing the project's success over individual achievements.

  • Clear Expectations: Ensuring everyone understands their roles leads to a streamlined workflow. Clear expectations also allow teams to pivot and address problems swiftly.

  • Repeat Clients: Familiarity reduces the "settling in" time and builds on past successes, emphasizing the importance of building and maintaining client relationships.


Contributing factors to project failure

What the Data Says:

1998 Case Study vs. This Study


Recommendations for Future Projects

Drawing from the research findings, here are some actionable insights for stakeholders:

  1. Prioritize Early Team Involvement: Engage all key players from the outset to ensure a cohesive approach. This early collaboration allows for effective decision-making and lays a foundation of mutual understanding.

  2. Foster a Relational Project Culture: Emphasize trust, mutual respect, and open communication. Repeated collaborations with the same designer and builder across multiple projects can bring a sense of familiarity.

  3. Set Clear Expectations: Use the early team involvement phase and the relational culture to set clear, realistic expectations. Engage all key players in the project goal-setting phase, ensuring everyone is aligned from the outset.

  4. Plan for Succession: Be prepared for inevitable changes to ensure project continuity. Engage in active planning for possible departures, training backups, and promoting a culture where team members are knowledgeable about each other's roles.


Concluding Thoughts

While the Design-Build system emerged as a frontrunner in this study, the real secret to successful construction projects lies in the human-centric practices. The right combination of system, processes, and people is pivotal for optimal project outcomes. As the construction industry continues to evolve, stakeholders must prioritize collaboration, communication, and continuous learning to drive success.

Citation:

Molenaar, K., & Franz, B. (2018). Revisiting Project Delivery Performance: Final Report. University of Colorado Boulder & University of Florida.


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