8:15 am Morning Coffee & Registration

8:50 am Chair’s Opening Remarks

  • Jit Kee Chin Chief Data & Innovation Officer, Suffolk Construction

9:00 am Gaining & Securing Buy-In at Multiple Levels Across the Firm; Buy-in from leadership to implement strategy, concept & peer, labourer buy-in for data entry & adherence to standards

  • Loan Ngo Corporate Quality Leader, Mortenson


• Communicating the value/ROI of data analytics and the investment in technology to executives to ensure financing and drive the business in the direction of data analytics
• Getting overworked project managers and project executives to value and want the innovation process even if it increases their short term workload to ensure
• Motivating field staff towards data capture processes that feel simple and natural
• Transitioning the firm to a culture that understands that data is an important decision making tool; Getting the company to input data and prioritize inputting data

9:40 am Panel Discussion: Maximizing the Data Analytics Potential from a Data Warehouse

  • Ryan Hale Chief Information Officer, Lithko Contracting
  • Andrew Herd Software Development Manager, Kimbel Mechanical
  • Stacy Scopano Chief Technology Officer, Skender Construction


• Lessons learned and value gained after creating a data warehouse; what to do and not do with hindsight
• Identifying data sets that bring value, how they can be leveraged and preparing data for AI & ML
• Identifying meaningful trends and patterns for strategic insight and leveraging algorithm creation to identify metrics and shift through data to recognize potential issues
• Unexpected metrics developed from creating the data warehouse and how that changed strategy

10:30 am Morning Refreshments

Track 1: Data Management
Data Quality, Warehouses, Integration & Security

11.00 Creating & Securing the Data Warehouse; How Does a Business as a Whole Gather all that Knowledge into a Single Source for Analytics

  • Utilizing the cloud, in-house solutions or other 3rd party products to create a data warehouse; determining the infrastructure of a data warehouse
  • Structuring the back end of a Data Warehouse to ensure ease of access
  • Cleaning data before it is entered into the data warehouse to protect it’s integrity as a source of truth
  • Ensuring the security of the company data repository and managing data storage with security requirements; security with the cloud

Cameron Jeffers, Software Development Manager,
Hensel Phelps

Spencer White, Business Intelligence Engineer,
Hensel Phelps

Track 2: Data Applications
Productivity, Scheduling & Safety

11.00 Tracking Productivity in the Field to Innovate in the Face of a Labor Shortage & Gain More Production Per Hour

  • Determining methods to track work being done on the job site
  • Getting the consensus on understanding and quantifying counts to not get trapped over bureaucracyt
  • Tracking production through BIM Models and using analytics to notice and implement efficiency changes

Joshua Mercado, Director, BIM and Technology Integration,
The Boldt Company

Aviva Tang, BIM Specialist,
The Boldt Company

11.40 Presenter Led Audience Discussion: Best Practice in Integrating Different Platforms to Unsilo data to gain actionable data for Analytics

  • Determining whether to have a centralized data warehouse or identify and integrate different platforms for analytics
  • Taking data out of spreadsheets into the data model(s)
  • Realising enterprise data integration and determining the architecture of this integration
  • Overcoming the interoperability issue with multiple software’s to connect data for analytics; deciding on inhouse tools or utilizing third party solutions to integrate data

Chris Tyler, Senior Software Developer,
Performance Contracting Group

11.40 Presenter Led Audience Discussion: Continuing to Leverage Safety Analytics to Make Job Sites Safe & Preparing Your Firm for the Higher Safety Standards

  • Strategies to predict a safety event and its accuracy; Utilizing data to make job sites safer to ensure the safety of field staff
  • Understanding how data analytics actually changes behaviour
  • Comprehending the legal and ethical risks associated with predicting potential safety incidents
  • Demonstrating the impact of safety analytics being done, the business decisions that can now be made and securing lower insurance costs

Lynda Willis, Director, Corporate Data and Analytics,
Clark Pacific

12:20 pm Lunch

1:20 pm Ensuring Data Quality to Trust Insights from Analytics


• Normalizing data; standardizing to ensure historical data is usable
• Successes from third party solutions and improving data quality
• Developing methods to monitor data quality and communicating with the firm to more accurately input data
• Determining how deep to go to get accurate data and what is “good enough” to make data sets reliable and trustworthy

2:00 pm Automating Tasks & Workflows to Ensure Staff’s Time is Used Efficiently; Making Automation a Reality

  • Dustin Burns Director, Information Technology, McCOWNGORDON Construction


• Identifying menial tasks to cut out and automate, reducing duplication and streamlining to ensure time is being dedicated where it matters and to end repetition of work and training with processes
• Automating data into the data warehouse; replicating, refining and considering the data flow
• Utilizing AI to speed up the response to RFIs and the process of work being done
• Software, technologies and apps to revolutionize business and streamline productivity; Understanding the possibilities of user-friendly apps and what they can be used for

2:40 pm Chair Led Audience Discussion: Reflections & Looking Ahead


At the end of the conference all will gather in the main auditorium to discuss what they have learned and what take-aways we have gained. How will you go back to your firm and adapt strategy to ensure your business is harnessing data analytics to make smarter business decisions?

3:20 pm Chair’s Closing Remarks

  • Jit Kee Chin Chief Data & Innovation Officer, Suffolk Construction

3:30 pm End of Conference