8:00 am Morning Networking & Breakout Discussions

9:00 am Chair’s Opening Remarks

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

9:00 am Keynote – Case Study: Developing a Corporate Wide Data Strategy Centered Around Analytics as a Tool for Smarter Business Decisions

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


• Moving data analytics away from individual projects to a corporate wide strategy of leveraging analytics for business decisions and preparing the business for that now
• What does the company need to do support the effort and ensuring the business is actually using data analytics in their business planning?
• Understanding what risk factors are added to jobs to increase efficiency and make more accurate decisions on each jobs long term value
• Reflecting on failures and how the lessons learned has changed strategy

9:30 am Panel Discussion: Enabling Inter-Company Large Scale Data Sharing to Make Analytics a Reality

  • Dustin Burns Director, Information Technology, McCOWNGORDON Construction
  • Chris Martin Director – Technology Services & Information Technology Manager, Mycon General Contractors


• Overcoming legal, cultural and logistical issues around sharing data with subcontractors/owners to ensure project-level analytics can smoothly occur and insights can be taken for longer term strategies
• Making industry-wide data sharing a reality to everyone’s benefit to form large data sets for identifying trends, analytics and apply AI & ML tools
• Companywide practices around data governance and getting resistant departments to share data and managing that sensitive information appropriately

10:00 am Analytics, AI & Human Bias – Power Struggles in the Age of Big Data

  • Cutler Knupp Director of Strategy & Technology Investments, Haskell


The planning fallacy – statistics are only a placeholder for knowledge. How to understand human bias of your reporting before layering in AI to provide manipulated results to optimize upon. It is evident that the changes brought to the construction industry by data science will continue and become even more productive but only if
well understood, aligned and structured for success. Join this session to discover the real experience shared around the mistakes, misjudgements and eventual success in seeking artificial intelligence solutions to enhance existing reporting.

10:30 am Speed Networking & Refreshments

Track 1: Data Management
Data Collection

11.20 Presenter Led Audience Discussion: Strategic Data Capture - Developing Long-Term Planning & Implementation to Efficiently Obtain Data

  • Recognizing existing data entry processes and its place in long term data capture strategy
  • Understanding what data to use, capture, structure and the effort to do so
  • Organizing projects for data capture, naming conventions, standardizing processes and getting staff to log data accordingly to collect better data which support the various analytics tools
  • Recognizing the resources needed to capture data efficiently; connecting platforms, creating custom in-house applications and purchasing solutions & technologies

Sharon Noyce, Data & Senior Business Intelligence Analyst,

Track 2: Data Applications
Historical Cost Data
& Risk

11.20 Presenter Led Audience Discussion: Creating a Benchmark Based on Historical Costs to Measure Future Projects

  • Leveraging historical data to decide what a healthier project looks like and normalizing that data to today’s dollars and locations
  • Using historical data to determine when and how costs are going to hit and what the health of a project will be based on in the future
  • Using historical data to analyze safety statistics, profit margins and profitability going forward and forecast that out
  • Implementing image software that stops manual input from field staff

Jennifer Yang, Software Developer, Data Solutions, Mortenson

11.50 Unburdening Staff to Ease Data Collection Requirements & Make Sure Data is Collected for Analytics

  • Recognizing the labor shortage in data collection to get data without burdening field or hiring more people
  • Simple, cost-effective solutions for data capture from the field that take into consideration the labor force’s technological acumen
  • Implementing AI that allows passive data collection and bridge gaps in data
  • Utilizing visual data capture to cut out the need for human data capture

Andy Leek, Vice President – Technology & Innovation, Paric

11.50 Case Study: Leveraging Data Analytics as a Risk Mitigation Tool to Identify Potential Issues Early in a Project

  • Determining early warning signs, inflection points and KPIs to decide when a project’s not going well and create alerts
  • Utilizing BI to measure a project against the bid and ensure it is staying within the estimation
  • Utilizing predictive analytics to gain early warnings of complications and evaluating problems before they get out of hand
  • Combining estimates with project maintenance software

Ed Littleton, Senior Vice President – Risk Management,
Balfour Beatty

12:20 pm Networking Lunch Break: Breakouts & Activities Ongoing

Track 1: Data Management
Company Preparation for the
Future of Analytics

1.20 Leveraging Visual Data Capture for Analytics & Speed Up Inspections & Processes

  • Capturing and utilizing model data from a BIM model to create a digital representation and leveraging analytics on that model through ML & computer vision
  • Using drone photography and drone video cameras for engineering inspections to ensure that the asset built confirms to the design documents and to create a visual representation of the job site; making use of a point cloud
  • Using visual data capture to track the location of workers,
    productivity and identify safety issues
  • Overcoming union issues with labor data tracking; ensuring consent and ethical practice

Brendan O'Reiran, Business Intelligence Manager, Suffolk

Track 2: Data Applications
AI & ML Case Studies

1.20 Utilizing Historical Data to Accurately Estimate Projects & Identify Profitable Jobs

  • Using historical costs and estimating software to accurately and quickly estimate the cost of a project
  • Taking scope change into consideration and getting owners to precisely outline scope when forming estimates to accurately predict the cost of project
  • Building models that predict the profitability of the job you are chasing to ensure you are maximizing company revenue
  • Moving from descriptive to predictive analytics to select profitable projects

Brent Pilgrim, DESTINI Applications Director,
The Beck Group

Greg O’Bryan, Preconstruction Engineer & Senior Engineer,
The Beck Group

1.50 Teamwork Through Analytics; The Human Aspect

  • Together we will explore how data-driven decision making
    can affect teamwork and how we can use these methods
    to gain further positive results

Angel Steimert, Business Operations Management,
Ryan Companies US, Inc.

1.50 Advancements in Applying Data Analytics, AI & ML to Schedules to Set Projects Up for Success

  • Leveraging data analytics and AI&ML to optimize baseline schedules and get the job done as quickly as possible
  • Uncovering how analytics can be and has been used to improve the scheduling processes itself
  • Using data analytics to discover root causes in problems in the schedule before they delay the project

Chris Heger, Chief Information Officer & Vice President,
OAC Services

Akshita Tyagi, Project Engineer (Data Analytics),
OAC Services

2:30 pm Afternoon Networking & Breakouts

3:30 pm Realizing the Potential of ML & AI & Preparing Your Data


• Examples of applying ML & AI to data and how to make decisions in business with AI & ML
• Using AI & ML to create predictive data testing trends
• Forming strategies on future analytics, structuring data for AI & ML and preparing your business now

4:00 pm Panel Discussion: Determining the Right Metrics & KPIs to Track for Success

  • Nicole Waits Insights Analyst, Ryan Companies
  • Brian Tighe National Director of Project Analytics, Skanska
  • Jason Bedogne Chief Information Officer, Kimbel Mechanical Systems
  • Adam Krob Director of Information Technology, Boh Bros Construction


• Creating the right KPI’s through correct categorization of projects for appropriate benchmarks to be created
• Identifying KPIs and creating data capture/mining strategies appropriately so unnecessary data capture does not burden staff
• Integrating various KPIs together to give more information on the potential success of projects and reveal key business insights
• Lessons Learned: KPIs that gave value & KPIs that did not

4:50 pm Chair’s Closing Remarks

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

5:00 pm End of Day Networking & Breakout Discussions