Case Study: 98% Data Accuracy, 80% Election Model Accuracy & 30% Cloud Cost Reduction for Government Electoral Decision-Making

Industry: Government, Data Governance

Client

Prominent Data Analytics & Advisory Company

Goal

To optimize electoral insights by implementing robust data governance and developing advanced analytics models for government and corporate decision-making.

Challenges

  • Establishing robust data governance frameworks to ensure accuracy and reliability of electoral data.
  • Developing predictive models to generate actionable insights for government decision-making.
  • Delivering timely and relevant analytics to support electoral strategies and policy planning.

Solution

Implemented data governance strategies to ensure high data integrity across multi-jurisdictional projects.

Designed and deployed predictive models forecasting election outcomes with 80% accuracy, delivering real-time campaign insights.

Optimized cloud infrastructure on Azure and PostgreSQL to improve data processing efficiency and cost-effectiveness.

Impact:

Achieved 98% data accuracy across multi-jurisdictional projects, significantly improving data quality and decision-making processes.

Reduced cloud costs by 30%, enhancing the cost-efficiency of data operations while maintaining performance.

Delivered highly accurate election models with 80% accuracy, directly influencing key campaign strategies and improving political decision-making.

*Case studies reflect work undertaken by our Heads of AI either during their tenure with Head of AI or in prior roles before they were part of the Head of AI network; they are provided for illustrative purposes only and are based on conversations with our Heads of AI.