Analysing Big Data for a $5m claim
Before – – –
- Industry: Hospital
- Engagement: Finance Director
- Main Issue: Data accuracy
- Problems: They needed a tight model which was allowing to quickly evaluating different scenarios. The previously used manual calculation was too time consuming and prone for errors.
- Main Goal: Effective reporting
After – – –
- Evaluating and filtering over 1m data-records down to 200K. Creating a model using these 200,000 determining the initial claim amount for the last year and forecasting the next two years. By allowing the flexibility to work through different scenarios with the model we created a kind of sensitivity analysis helping the client to evaluate the best scenario for their claim.
- My client gained a seven digit figure by using this robust model allowing them to optimise their claim to Queensland Health.
- The claim my client applied for was accepted by Queensland Health without any reductions.