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Few of the improvements to the issues highlighted in the previous post which the Tucareers framework addresses are

Workforce analytics (also called people analytics or HR analytics) is an upcoming approach which brings an engineering rigor to HR for improving individual and organizational performance. Modern age organizations (e.g. Google) are using the approach extensively (Sullivan, John, 2013) in managing their human resources across applications like resource selection, allocation and given its predictive capabilities even in performance management and attrition control initiatives.

O*NET is the world's largest occupational database and provides very comprehensive industry data about careers and individuals suitable in them. However O*NET, given a vast set of intended usages, is difficult for individual users to understand and use for their career planning. Even career guidance professionals find it difficult to understand and leverage methodically. Thus, there is a identified need for a phased model that is tuned for use with O*NET. Tucareers’s career planning model ONETCP^TM is based on the six–phased approach recommended in research. The six phases in our model are named Orient, Navigate, Explore, Track, Choice and Plan; these facilitate exploration and significantly remove decision making difficulties

As discussed in previous posts the worker characteristics domain in the O*NET content model defines abilities, work styles, work values and interests as attributes that are stable across an individual’s lifetimes. Research over the years has shown that matching a person with the environment based on these diverse attributes and traits can help identify occupations where he/she can best fit.

There are several benefits of an occupational classification system. The order imposed by a classification system allows working more efficiently with a large set of information items about different occupations, and allows organizing & describing the similarities and differences. The classification systems are thus critical for career exploration and counseling. 

Gati (1986) defines vocational choices as a particular case of decision making under uncertainty with the aim to reach an optimal choice among alternatives (a multi criterion decision making problem, MCDM in short). The uncertainties in the decision can be looked at in terms of the lack of clear preferences owing to lack of mental clarity by the decision maker or incomplete knowledge which can result in the uncertainty of a future outcome.