Edited by John P. Meyer and Benjamin Schneider
The chapter, begins by framing the traditional practice of measuring employee engagement, as well as approaches to establishing engagement’s importance and impact. We discuss the merits of traditional approaches as well as identify challenges. The second part of the chapter describes new data sources that have become available, such as always-on measurement and ambient or passive data sources. This section includes a treatment of multiple categories of engagement-relevant data, including outcomes of interest, with special attention to novel data sources that can complement traditional sources. The third section outlines new approaches to storing, analyzing, reporting and taking action on those data. We touch briefly on data management, multiple analytical methods including a discussion of text analytics, and the opportunities raised through automated reporting and recommendation engines. We include a discussion of risks and other considerations for practitioners as they explore the use of new data science methods in their own employee engagement research practices. We address privacy and security concerns throughout and offer suggestions for ethical deployment of these approaches as well as suggest future research horizons.
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