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Optimizing Project Robustness Assessment: A Case Study by Burns & McDonnell

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Description

Managing user-access control and evaluating project robustness within the Autodesk Construction Cloud hub presents formidable challenges. This case study dives into the innovative strategies devised by Burns & McDonnell, in collaboration with Autodesk Consulting, to confront these obstacles head on. We explore Burns & McDonnell's business requirements and key performance indicators (KPIs), assessing the capabilities of the Autodesk Data Connector and Insight module. The study showcases the development of project robustness assessments using data sets from Data Connector, and dives into the technical intricacies of the ELT process and data pipeline. Emphasis is placed on data engineering processes to curate consolidated tables tailored to customer KPIs. Resulting products include a user-access control tool and robustness scoring systems, transforming raw data into actionable insights. These systems offer detailed intelligence for strategic decision making at Burns & McDonnell.

Key Learnings

  • Learn about streamlining user access control and project robustness assessment processes, reducing time by 70% and 60%, respectively.
  • Learn how to relate users at account and project levels, ensuring data accuracy, and how to score projects based on user data hygiene.
  • Discover projects underusing Autodesk Construction Cloud services, and learn how to customize KPIs for robustness scoring and assess projects' vitality performance.

Speakers

  • Avatar for Stephen Brooke
    Stephen Brooke
    Stephen Brooke is a seasoned Digital Delivery Project Manager at Burns & McDonnell, with a wealth of experience in streamlining project execution through cutting-edge technology. With 17 years of expertise in digital model management, he specializes in integrating design-build and EPC (Engineering, Procurement, and Construction) teams across the lifecycle of complex projects, including aerospace, life sciences, commercial, and consumer product facilities. In his role, Stephen leads the implementation and management of the BIM Execution Plan (BIMxP) program, ensuring project teams are equipped to manage workflows efficiently. He champions the use of virtual and augmented reality (VR/AR) technology to enhance the design-build process, reduce requests for information (RFIs), and improve constructability, while focusing on long-term maintenance needs for owners. A recognized thought leader and experienced speaker at Autodesk University (AU), Stephen has delivered presentations on evolving client data requirements, cloud-based solutions, and the future of project delivery through data and BIM maturity ideologies. His sessions emphasize navigating digital transformation and driving innovation, with a focus on data-driven strategies for sustainable and successful project outcomes. Stephen also excels in improving interoperability between platforms like Revit, Civil 3D, and Plant 3D, sharing his field experience to enhance drawing accuracy and constructability for field teams. He actively trains field superintendents, project managers, and subcontractors to use Autodesk Construction Cloud (ACC) for better collaboration, project tracking, and progress monitoring throughout the construction phase. With a passion for integrating technology with project delivery, Stephen continues to inspire teams to adopt innovative tools that improve efficiency, reliability, and overall project performance.
  • Avatar for Liang Gong
    Liang Gong
    He is a structural engineer by training (PE) with a background in preconstruction/estimating, construction management, BIM/VDC and data science. He helps customers leverage the data they produce through the design and build process to generate actionable insights including forecasting and scalability. He also automates customized workflows with ACC Connect and Autodesk Platform Services. After graduating from Duke University, Liang is currently working on his second master's degree in Applied Data Science at University of Chicago, focusing on AI/ML as a part-time student.
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