Increasing Employees' Willingness to Share: Introducing Appeal Strategies for People Analytics

TL;DR

This paper develops a taxonomy of appeal strategies to enhance employees' willingness to share data in people analytics, addressing privacy concerns and promoting voluntary disclosure.

Contribution

It provides the first systematic overview and classification of appeal strategies for people analytics based on literature review and expert interviews.

Findings

Taxonomy of appeal strategies based on values, benefits, and incentives

Concrete options to increase appeal of people analytics for employees

Enhanced understanding of how to promote voluntary data sharing in workplaces

Abstract

Increasingly digital workplaces enable advanced people analytics (PA) that can improve work, but also implicate privacy risks for employees. These systems often depend on employees sharing their data voluntarily. Thus, to leverage the potential benefits of PA, companies have to manage employees' disclosure decision. In literature, we identify two main strategies: increase awareness or apply appeal strategies. While increased awareness may lead to more conservative data handling, appeal strategies can promote data sharing. Yet, to our knowledge, no systematic overview of appeal strategies for PA exists. Thus, we develop an initial taxonomy of strategies based on a systematic literature review and interviews with 18 experts. We describe strategies in the dimensions of values, benefits, and incentives. Thereby, we present concrete options to increase the appeal of PA for employees.