MedTech AI Case Study
Client Data Profile
• Predictive algorithms for disease impact using AI
• Data and tech driven user experience and insights
• Partnered with Large Pharma, NHS GP’s and UK universities
• Data Valuation was rebalanced twice because more data was generated
Objectives
• Leverage data for an already established data strategy
• Validate current data value ideas and philosophies
• To demonstrate the complete and full value of the business for leverage in investment and exit negotiations
Our approach
Methodologies Utilised
A mathematical hybrid of:
Consumption Method: This was a cost-inclusive, consumption-based method, which relies on data ownership, a repository or platform with consumable data and consumers to consume the data.
Adapted Shapley’s Value Method: To calculate the value of an data set used for AI, based on its contribution to algorithms. This method is specifically used for AI data valuation
Why it was selected
Patient records can be both created for the intention of sale and consumed via a repository. The client values both the existence of marketable data and values the consumers who use the algorithms. Data produced from the algorithms is seen as unique data that can be leveraged and consumed to gain advanced insights and inform better predictive power for algorithms. This led DVP to believe that the data can be both sold and consumed without sale, incentivising a hybrid between consumption and Shapley’s method.
Insights & Recommendations
• Rebalancing to update and forecast data value trends
• Per click revenue model, by understanding the value of data
• Recommendations on data funding and leverage
• Data monetization strategies revealed such as data licensing
• An indicative sale price for the data should the client introduce data sales as a business line.