7:00 am Registration
7:45 am Chair’s Opening Remarks
- Ryan Hale CIO , Lithko Contracting
Gaining Buy-In Across the Company
8:00 am Keynote: How to Gain the Buy-In of Company Executives to Accelerate Your Analytics Roadmap
- Revealing the best applications and examples of analytics in the industry, the success stories that will excite your executives
- Quantifying the short and long term ROI of investing in analytics: why is it so critical to do this work now?
- Understanding what executives need to know when you’re requesting funding or support for investment in analytics
8:40 am Building Awareness Across Your Company & Project Partners on the Capability of Analytics to Widen the Adoption of Data Driven Decision Making
- Ryan Hale CIO , Lithko Contracting
- Understanding the mindset of non-technical staff and how to engage them in data analytics: what can your data team provide them that is actually valuable?
- Leveraging your relationship with company executives so they promote the role of analytics through departments for you
- Creating a consistent pro-analytics culture so new subcontractor and design partners recognize your firm as a leader in this field, and leverage your insights on your jobs
9:20 am Speed Networking & Morning Refreshments
Data Integration & Standardization
10:10 am Panel: Enforcing Firm Wide Data Standards with Robust & Understandable Rules to Better Organize Data & Ease Integration
- Michael Dugan Manager of IT Operations , Structure Tone
- DJ Phipps Director of Construction Technology , XL Construction
- Skylar Lyon Analytics , Katerra
- Understanding how your data should be optimally stored and formatted to enable cross-platform integration and analytics
- Assessing the realities of how data is captured and establishing easy to follow procedures so each job site and department can implement new standards
- Benchmarking standards across companies to determine whether formats can be agreed within your supply chain or the entire industry
10:50 am Integrating Systems & Automating Data Exchange to Reduce Manual Data Handling & Scale Up Analytics
- Jeremy Sibert Director of Technology , Hensel Phelps
- Cameron Jeffers Software Engineer, Hensel Phelps
- Examining the role of APIs and custom connections to enable the transfer of data in real-time and reduce fragmentation
- Developing an in-house data integration tool that allows various non-integrated tools to talk to each other in the same data language to make a unique record in a master database
- Determining whether solutions are best developed in house or outsourced to 3rd parties for data integration
- Reviewing the extent to which data quality can be improved when silos are connected to establish a single version of the truth
11:30 am Developing the Culture & Capability to Share Data Openly Between Project Partners Including Subcontractors & Design Firms
- John Jurewicz Leader Tech Optimization , Walbridge
- Creating a culture of data sharing to connect with a trade partner’s data for mutual benefit and ending a “us vs them” culture to maximize learning for all
- Understanding what insights can be determined when data is connected across the supply chain: what is the business case for this extra effort to integrate?
- Overcoming barriers around data ownership, privacy and concerns among partners to provide open access to their systems
- Reviewing technical best practices is connecting to data platforms in other firms: how do we actually do this?
12:10 pm Networking Lunch
1:10 pm Establishing a Data Repository That is Appropriately Indexed & Discoverable to Enable Staff Across the Company to Access & Leverage Data Independently
- Sean Browning Manager of Business Analytics , The Haskell Company
- Learning how to structure your database so everyone can quickly find and access the data they need
- Reflecting on common requests to the IT or data team to understand what use cases the company has for analytics and formatting your database so it responds well to these demands
- Training staff so they know what is possible through data analytics, what data they need to inform their decision making and how to access it
1:50 pm Audience Discussion: Data Standardization & Integration
This short discussion among your table will enable you to benchmark approaches across the country to data standards, integration approaches and accessibility. This is your opportunity to identify similarities and differences to your strategy with those of your peers.
2:30 pm Afternoon Refreshments
Case Studies: Improving Productivity
3:00 pm Application: Leveraging Analytics to Track Project Spend & Schedule Against Baselines to Identify Problems Early
- Frank Fralick Analytics , The Beck Group
- Creating systems to enable project tracking to occur in near real-time to identify problems early and maximize influence you can have on project success
- Using historic data to create robust baselines and more accurately determine what success looks like
- Crunching data across the entire company to determine early indicators of problems and mitigate overruns or overspend before they occur
Data Collection & Quality
3:40 pm Mapping Out Your Data Requirements to Inform the Decisions You Want to Make & Identifying Tools to Gather it
- Travis Voss Technology Manager , Mechanical Inc.
- How to review your existing data and perform a gap analysis to identify data that would be valuable in decision making, but which is not currently collected effectively
- Reality check: which data is actually driving useful insights, and which data are we collecting needlessly?
- Reviewing emerging technology such as photogrammetry, job site sensors and wearables: what are the possibilities for data collection?
- Providing connectivity on job sites so workers can update data pools in real time
4:20 pm Master Data Quality & Management, Analytics, Machine Learning and A.I. on the Job Site: Driving Operational Construction Excellence
- Brian Kmet Senior Manager of Business Technology , PCL Construction
- Danny Brunsch Artificial Intelligence/Analytics Specialist, PCL Construction
- Revealing methods for mastering construction data assets including craft workers, projects and subcontractors
- Automating data entry and improving data quality though visual analytics and natural language processing
- Business Data Optimization best practices and frameworks for continuous data quality improvement, governance and accountability
- The value chain: data quality to analytics to actionable insights to operational excellence