Project - Predictive Delivery Assurance
The industry project status de-facto of RAG is subjective, biased and coarse. Projects remain stuck in Amber for too long and people are scared to go Red, resulting in delivery inefficiencies.
Our Value Goal was to define an innovative quantitative measure of project delivery status and using machine learning to predict when projects are likely to deteriorate, driving proactive interventions and saving millions on overspend and rectification.
We created an innovative Health Score that complements RAG-based reporting of the delivery status of a multi-billion change portfolio. Project deterioration predictions are embedded into delivery dashboards to drive more efficient and better informed oversight and assurance.
Proof of Concept created to demonstrate our approach in just 6 weeks leading to request to productionise the models and build up a permanent capability, transforming the way they are transforming change.
Combine and enhance data
Crafted innovative metrics to enhance consolidated view of delivery status, standardizing, transforming and inputting into our machine learning models.
Health Score was used to uncover delivery risk under-reported by RAG.
Predicting a downward trend
Predictive algorithms were fed with historic data, applied Natural Language Processing to reveal hidden patterns to generate project deterioration predictions .