Selection of one priority use case in collaboration with management (e.g., demand forecasting, customer churn prediction, lead scoring, workforce planning)
Data preparation and transformation (including cleansing and feature engineering)
Development of predictive model using low-code platforms (Power BI, Dataiku, Azure ML Studio, or equivalent)
Model validation and performance testing
Explainability analysis to ensure transparency and board-level confidence
Roadmap for scaling predictive analytics capabilities across the organisation
Deliverables:
Predictive model (prototype) with visual outputs
Model validation report (accuracy, limitations, and improvement areas)
Business case document outlining ROI potential and resourcing implications
Technical handover pack for internal or external teams