We implement quantitative and qualitative analysis between a specific industry, its technology growth patterns and the human capital that drives it.
Our methodology first establishes and identifies the specific industry and or sector along with the required discipline per that job requirement, function, business objectives and culture of an organization. The data sets are extrapolated to establish the critical mass of the organization e.g. the system as a whole.
The data is compressed into a statistical design and correlation model that filter and find the ideal candidate using probabilistic amplitudes and stake holder analysis via observables e.g. behavioral metrics that define the candidate criterion.
The selection rubric is define by two probabilistic distributions; critical mass (CM) and candidate criterion (CC). We characterize the state of our system by giving quantum amplitudes to possible outcomes of measurements.
The range of possible outcomes of observations form a spectrum of observables which we restrict by discretely validating that the performance is statistically related to subsequent job performance (empirical validity) or logically related to job performance based on the results of the job analysis itself (job content validity).