An interesting blog of Gaspar Maldonado points out the evolution of the human resources in the administrations of Central america, through a comparative analysis of the regional tax administrations countries between 2010 and 2017, which allows building a regional comparative evolution of the human talent in four lines: the total number of employees, percentage of employees by gender, their age, and time within the organization.

The results of the comparison of the aspect analyzed stimulated me to investigate other factors that could be incorporated into the human talent assessment mentioned by Gaspar, whose inclusion could lead to new precisions. To begin, I adopted a definition of talent in the combination of characteristics or qualities that determine human resource capacity to use their skills for solving problems, ensuring a better assessment to complement the technologies currently available.

The lines analyzed in the blog: gender, seniority and perhaps age are appropriate to estimate a level of work commitment that could be complemented by integrating profession, specialized application, creative function, soft skills, or other capacities with implication in the institutional development.

From these considerations it seemed to me that the discrimination of the concept of human resources and human talent for their management could accelerate the adaptation of the administrations’ human resources to the latest technologies.

Talent management is strategic, it is aimed at those who will be in charge of the development of the institution, human resources management is tactical, it is limited to the supply of the current operational processes.

Technological progress advances rapidly and has universal scope, technology changes processes, so the operations generate a transformation of requirements in human competencies.

The progresses in robotics to autonomous systems more flexible and intelligent are leading many institutions to the automation of processes, however, this may collide with the lack of professional skills and abilities suitable to the new environments, forcing the organizations to attract experts in emerging technologies such as engineers specialized in artificial intelligence and to provide the resources and tools to enable their workers to acquire the skills needed.

The big data scientist, big data architect and the big data analyst are fundamental profiles for managing, analyzing and visualizing the data that can provide solutions and answers.   Data collection and interpretation through task automation and the use of robots within administrations is essential.

The growth of robotics will be exponential in the coming years but if an old or aging working population is maintained without the right talent, it may be inoperable.

How technology will affect work over the next few years has become a big conundrum, as well as those areas of knowledge such as leadership, effective communication, emotional intelligence, and critical thinking that are not linked to technology.

Some pessimistic currents assure that robotics will destroy millions of jobs. On the other hand, others assure that the tasks of the workers will change, and it will be essential that they learn to “collaborate” with the machines.

The human does what machines are not capable of, such as detect new possibilities in creativity and the ability of abstraction to generalize. The union of the human and the artificial generates intelligent cooperation that allows complementing and increasing human capabilities, but not replace them.

An example is the GPS used by taxi drivers, in which said collaboration can be verified, the driver does not need to worry about the orientation, his task is to transport passengers and manage the car.

Technology changes the type and number of tasks that must be performed and creates new tasks that humans must “take on”.

Meanwhile, it is necessary to review the human capabilities and the selection of human resources of the administrations to supply the technological currents that are quietly driving them, and this demands new skills and capabilities.

New practices and even new behaviors have transformed the creation and/or implementation of methodologies to manage resources more efficiently.

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