Evidence Engine built Evidence Engine, a web‑based Assumption Assurance platform that captures project assumptions, links them to evidence, and highlights drift through confidence scoring and visual alerts. The solution focuses on making assumptions explicit, traceable and continuously reviewed rather than static entries in documentation.

Assumption Assurance Pitch presented a concept‑led solution for managing critical assumption drift, focusing on clearly communicating the problem, proposed approach and value to portfolio leaders. Through a structured pitch and supporting materials, the team outlined how assumptions could be surfaced, monitored and reviewed to provide earlier...

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,...

Assumption Drift Monitor explored the use of live external data feeds to detect early signs of critical assumption drift. By integrating an RSS feed as a proxy for external signals, the team demonstrated how changing market, policy or industry conditions could be automatically surfaced and linked back to project assumptions.

WBS Cost Estimation Tool developed a desktop‑based Work Breakdown Structure (WBS) and Cost Breakdown Structure (CBS) estimation tool that supports structured cost entry, versioned change tracking, and comparison of estimates against actuals across the project lifecycle.

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,...

Forecast Input Cost App delivered a Power Apps and Power BI based cost‑forecasting solution that enables controlled forecast entry, integrates actual spend data, and provides clear visibility of cost performance against estimates across projects.

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,...

Assumption Drift Canvas focused on collaboratively mapping how critical assumptions emerge, drift and impact delivery confidence across projects. Using a shared visual workspace, the team structured the logic linking assumptions, confidence, external signals and portfolio‑level assurance to support earlier, clearer decision‑making.

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...

ProCost built ProCost, a Power Apps and Power BI prototype for intelligent cost management that integrates actuals, forecasts and requisition data to provide scalable, modular cost visibility across the project lifecycle.

Integrated Cost Data Platform delivered an end‑to‑end cost management architecture that migrates fragmented Excel‑based cost data into a structured PostgreSQL database and exposes a single, trusted cost model to Power BI for analysis across estimation and execution.