Data Mining International has developed specific scientific methodologies for constructing high quality prioritizations models and risk rankings that can be used to aid portfolio management across different industries.

Human brain being unable to adequately manage more than 3 criteria at the same time, most of prioritization and risk assessment for portfolio management purposes is based on scoring. However, any scoring is unable to discriminate opposite profiles and to handle both quantitative and qualitative criteria.

The vector coordinates on the single projected main axis will be set up between 0 and 100 in order to generate a meaningful synthetic risk or priority indicator calibrated between 0 and 100.

This approach has been successfully validated and is currently used in innovative pharma and fast consumer goods multinational companies dealing with many development projects and many priority and risk criteria.

Data Mining International has developed innovative approaches based on multi-dimensional analyses. Each criterion is considered as one mathematical dimension, and the X dimensions representing the X criteria is considered as a “hyper-plan “, which will be mathematically projected into one single axis using the best possible “angle” in order to capture maximum relevant information.

Main features :

– no score based

– no arbitrary weighting system

– objective ranking

– reproducibility

– integrate both quantitative and qualitative criteria

– no over-weighing of potential correlated criteria

Some examples:

– Airline safety risk ranking

– Priority ranking

– Investment risk ranking

– Research project ranking

– University ranking

– Human resource ranking