Aluya, Joesph. Journal of Disruptive Technology, Vol 13(1), Jul 2022, X-XX


This paper examines how the seamless synergies and collaborative work of deft leaders, data analysts (DAs), data scientists (DS), and information analysts (IAs) used analysis gleaned from big datasets to maximize organizational profit. Various deft leadership styles used to illustrate this phenomenon: a) bad or dysfunctional, b) collective, c) situational, d) transformational, e) transactional, and f) trait approach to deft leadership. The core research problem was deft leaders in organizations’ inability to embrace radical changes within newly formed internet platforms. Embedded in this study were the internet of things (IoT) and the industrial internet of things (IIoT). Vignettes used to explain why deft leaders should form teams of managers of DAs, DS, and IAs to formulate new platforms to respond to the ever-changing technological business environment. Within the contemporary realm of data scientists, statistical models inextricably intertwined with the organizational profit. The computational cost, high dimensionality, incidental endogeneity, noise accumulation and spurious correlation linked to profit with the collaborativeness of the DA, DS, and IAs. The findings revealed that without the managerial teams of DA, DS, and IAs collaborating and reporting pertinent gleaned data analysis from big data to the deft leaders within actionable real-time, the trajectory showed that the business will cease to exist. The recommendation was for deft leaders to adjust with dexterity to the ever-changing technological pathways based on the situations within the global terrain.

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