Tracks consumer stress signals using Google Trends to detect demand shifts before they appear in earnings reports — DoorDash case study.
PRISM (Planning Risk Insight and Scheduling Monitor) is a working behavioural analytics solution that exposes risky resource and forecasting practices across portfolios. Built for Challenge 5, it provides persona‑specific dashboards for planners, resource managers, project managers, and senior leaders, analysing utilisation, forecast accuracy,...
The team delivered a Power BI–based behavioural analytics solution that visualises forecast accuracy and resource utilisation to expose poor planning practices. By cleaning and transforming milestone and financial data, they created interactive dashboards that highlight generic resource use, under‑utilisation, over‑allocation, and forecast...
Transforming Garmin wearable telemetry into behavioural intelligence using Python, analytics, predictive modelling and Power BI.
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-fre...
The team focused on establishing strong data quality and analytical foundations for a Project Health and Behaviour Monitor. Using a structured synthetic dataset, they demonstrated how task-level schedule, cost, and resource attributes can be cleaned, validated, and analysed to identify volatility, critical path risk, forecasting accuracy issues,...
The team proposed a comprehensive behavioural analytics dashboard to expose hidden patterns in project scheduling and resourcing that undermine delivery confidence. Using defined schedule and resource integrity metrics, the solution highlights chronic under‑ and over‑utilisation, forecast inaccuracy, ignored dependencies, and reliance on gen...
The team explored persona‑driven behavioural analytics to address risky resource planning practices. By combining detailed persona definitions, behavioural metrics, and deep analysis of forecasting and utilisation data, they designed a dashboard concept that highlights over‑optimistic planning, generic resource use, and weak feedback loops,...
Add a description, image, and links to the behavioural-analytics topic page so that developers can more easily learn about it.
To associate your repository with the behavioural-analytics topic, visit your repo's landing page and select "manage topics."