Human Capital and Competitiveness: Analytical Method to Strategic Management of the Man-Organization interaction

Giovanna Garrido, Marco Antonio Silveira, Rafael Damasco Silveira

Abstract


One of the management challenges is to understand the mutual relations between individuals and organizations, which promotes the emergence of methods that allow diagnosing and quantifying the impacts of the human factor in the organization. This challenge has been defining a new area of knowledge known as People Analytics, Human Resources Analytics, among other denominations. Thus, having People Analytics as the main subject of research, this study merges the Triple Bottom Line concept of sustainability, the core competences of the organization and some analytical techniques, with the goal of implementing an own strategic diagnosis method to quantify the impacts of the human factor in a multinational of the electronic sector. Aiming at integrating the technological, human and sociotechnical domains, this method integrates variables related to people, processes and competences. The correlation between these three elements with people management methodologies and analytical techniques facilitates the obtaining of quantitative information about the human factor in organizations, contributing to human management becoming assertive, strategic and oriented to the sustainable development of the business. The implementation was directed to the strategic improvement of competence management in the software development sector, aiming to improve the productivity of its developers. The method showed its potential to promote a qualified diagnosis by quantifying the impacts of the developers' competences on the productivity of the associated processes, enabling the improvement in the functional aspects of the area and subsidizing strategies of success for the company in terms of the assertive management of human capital.


Keywords


People Analytics; Human Capital; Analytical Method; Competences Development; Return on Investment (ROI)

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DOI: http://dx.doi.org/10.7867/1980-4431.2018v23n1p55-69

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http://pkp.sfu.ca/node/3747

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