Challenge 5
The team developed a proactive behavioural analytics solution focused on surfacing risky resourcing and forecasting behaviours early. Using Python-based analysis and clear visual storytelling, they translate schedule and resource data into behavioural flags and practical recommendations that support early intervention and constructive, blame-free discussions.
Please be aware that this content was generated follwing an automated review so may not be perfectly accurate; refer to the original challenge brief and team files for authoritative information
Earlier detection of resourcing and forecasting risks; clearer behavioural signals to prompt timely action; reduced likelihood of late-stage schedule or budget surprises; improved confidence and transparency in planning conversations.
PowerPoint Presentation/Storyboard write up.docx: Sets out the narrative, problem framing, and behavioural focus of the Forecast Force solution.Python Files/Risky_Resource.ipynb: Implements derived behavioural metrics and flags to identify risky resource and forecasting patterns.Source Data/Behavioural Output/Behavioural Analysis Output.csv: Provides example task-level outputs showing detected behaviours and recommended actions.
team: Forecast Force members: Stephen, Dan, Roger, Meg, Loraine topics: solution-centre, hack26, challenge5, python, pandas, jupyter, analytics, data-visualisation, resource-management, schedule-forecasting, behavioural-analytics, project-controls, data-quality technologies: python, pandas, jupyter, analytics, data-visualisation