Why Engr Estimates Drift: Understanding Variance in Large Capital Projects

Speaker Bio: Ian Landry is the Managing Director for Engineering Excellence, where he provides strategic leadership to the engineering teams within the Project Delivery Group. In this role, he is responsible for setting direction and ensuring the consistent deployment of resources, processes, and tools that enable teams across the globe to deliver projects efficiently, safely, and with strong technical rigor. He plays a key role in advancing engineering standards and driving alignment across regions and disciplines.

Under Ian’s leadership, the Engineering Excellence function focuses on strengthening capability, improving consistency in delivery, and supporting high-quality project execution at scale. He works closely with global teams to embed best practices, enhance technical governance, and ensure the organization is equipped to meet the evolving needs of clients and projects across multiple sectors. Prior to this role, Ian held several senior leadership positions within the organization, including Global Director of the Mechanical discipline. His broad experience across large, complex projects and multidisciplinary teams continues to inform his approach, enabling him to drive practical, results-oriented improvements while fostering a culture of engineering excellence across the business.

Presentation Abstract

Engineering estimates form the foundation of project planning, performance measurement and investment decisions. Yet even well-developed estimates can diverge from actual engineering effort as projects move from definition into execution. Traditional reviews often focus on estimating accuracy alone, but practical experience suggests that a much broader set of factors influence engineering outcomes across the project lifecycle.

Drawing on lessons learned from large capital projects and published research, the discussion will explore how scope development, design maturity, execution strategy, information availability, and project controls practices influence engineering effort. The session will review common drivers of engineering variance, discuss the limitations of traditional benchmarking approaches, and present practical strategies for improving estimate reliability and forecasting, managing uncertainty, and establishing meaningful performance measures and feedback loops within engineering organizations.

Networking: This meeting will be held in person at the location below; however, access via Teams will also be provided for those who wish to join remotely. The link will be provided to those who registered for the remote option the day before the event.

Meeting location: Concordia University, 1455 De Maisonneuve Blvd. W., 2nd floor, Room EV 2.184

Access from the main entrance and proceed to stairs at the front or the elevators behind the security office, then head to the room. Signs will be posted.

Food and refreshments from 5:00 pm. Meeting Duration 5:45 pm to 7:15 pm