09 // CASE STUDIES
Data Lab
Project Management Predictive Analytics
The Challenge
Delays and unbudgeted changes cost construction projects and developers in multiple ways.
Our Solution
We developed a machine learning model that analyses historical project performance and real-time site data to predict Schedule Variance and Cost Variance.
Key Outcomes
Early warning systems allow project managers to mitigate risks before they impact the critical path or calculate Variation Orders with appropriate parties, mitigating the 'shock factor'.
Who benefits?
- Executive Leadership
- Finance and Risk
- Project Management Office
Cost savings
- Root cause analysis for delays
- Reduced variation orders
- Compliance coverage checks
- Typical outcome: 97% success rate of detecting tasks that are going to be delayed in the future.
Time savings
- Reduction in project delays
- Identification of problem areas
- Time to resolution slashed
- Typical outcome: 30-50% time reduction in overall project timelines
Our People involved
Joshua Heckroodt
Data Scientist & Software Engineer
Gavin Britton
Co-founder & CEO
Mark Collin
Co-founder & CTO