Screening for self-directedness: A method for recruiting savvy analysts in a dynamic business environment

Jennifer L. Dapko and Gregory J. Snyder
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Jennifer L. Dapko: Florida Southern College, USA
Gregory J. Snyder: Adjunct Professor, Florida Southern College, USA

Applied Marketing Analytics: The Peer-Reviewed Journal, 2021, vol. 7, issue 1, 73-83

Abstract: Analytics is changing at the speed of thought. If analysts are not capable of and motivated by self-directed learning, they will be left behind and their organisations will be left scrambling to keep up with their competitors. Even the best company-directed learning programmes cannot always keep pace with this change, and most analysts will find company-directed technical training falling short of their needs. Self-directed learning enables analysts to stay relevant and motivated in a quickly changing business world, and self-directedness is a key employee characteristic in creating adaptable and flexible organisations. This paper discusses ways in which hiring managers can screen analysts for self-directedness during the interview process. As important as it is for hiring managers to recruit a workforce with self-directedness, it is equally important to set up an environment where a self-directed learner can thrive and utilise those skills. Therefore, this paper will also discuss ways in which organisations can nurture selfdirected learners once recruited.

Keywords: self-directed learning; self-directedness; business analytics; analytics training; hiring analytics employees; employee motivation; employee learning (search for similar items in EconPapers)
JEL-codes: M3 (search for similar items in EconPapers)
Date: 2021
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