  With increasingly digitalized workplaces, the potential for sophisticated
analyses of employee data rises. This increases the relevance of people
analytics (PA), which are tools for the behavioral analysis of employees.
Despite this potential, the successful usage of PA is hindered by employee
concerns. Especially in Europe, where the GDPR or equivalent laws apply,
employee consent is required before data can be processed in PA. Therefore, PA
can only provide relevant insights if employees are willing to share their
data. One potential way of achieving this is the use of appeal strategies. In
the design of PA, the core strategy that can be used is the inclusion of data
owner benefits, such as automated feedback, that are given to employees in
exchange for sharing their own data. In this paper, we examine benefits as an
appeal strategy and develop four design principles for the inclusion of
benefits in PA. Then, we describe an exemplary set of analyses and benefits,
demonstrating how our principles may be put into practice. Based on this
exemplary implementation, we describe and discuss the results of a user study
($n = 46$) among employees in the EU and UK. Our study investigates the factors
that foster or hinder employees' consent to sharing their data with PA. Then,
we introduce our data owner benefits and analyze whether they can positively
influence this consent decision.
  Our introduced data owner benefits were, contrary to our expectations, not
suited to motivate our participants to consent to sharing their data. We
therefore analyze how participants judge the benefits. Participants generally
appreciate having them, confirming the value of including data owner benefits
when designing PA. Some of our introduced benefits negatively influenced
participants' sharing decision, though, meaning that careful consideration of
potential risks is required when conceptualizing them.
