‘It's so fake’: Identity performances and cynicism within a people analytics team

Abstract

This article reports on a participant ethnography of a people analytics (PA) team operating within the human resources (HR) function of a European multinational corporation at the cutting edge of PA development. Despite their analytical expertise, this team experienced significant dissonance between their desired image of PA work and the actualities of PA practice. Our analysis explains this dissonance through two prevalent identity performance scripts: ‘customerization’ and ‘action‐orientation’. Taken together these scripts were identified as having a restrictive impact on the production of more scientifically rigorous PA work. Further, both of these scripts were found to be imbued with cynicism, whereby PA practitioners distance themselves from the commercial presentation of their work outputs. The article reveals how management preferencing of presentational and commercial considerations over those of scientific rigour may result in a failure to generate the level of organisational benefits promoted by the optimistic accounts in current literature, with negative implications for the reputational profile of PA.

The duality of HR analysts' storytelling: Showcasing and curbing

“…Decoupling is institutional work driven by a desire to protect the organisation and the integrity of HR analytics projects from the over‐enthusiastic selling of HR analytics. Contextual factors that underpin these protection‐based efforts include the duality of having leadership support and stakeholder enthusiasm on the one hand, while struggling with poor data quality and multiple HR systems on the other, all of which makes performing analytics projects at a high level consistent with professional norms (Jörden et al., 2021) difficult in the short term. Keeping stakeholders and observers enthusiastic about HR analytics as a broad policy means carving out time to tackle practical problems with systems and data quality so that HR analysts work can be performed to high levels of technical sophistication.…”

“…At what costs to HR analytics as professionals is decoupling achieved? Does it lead to emotional tensions and frustration (Jörden et al., 2021)? Is dualistic storytelling a key skill at all stages of HR analytics maturity and will it remain necessary even at later stages of development when data quality and systems alignment become less problematic, but where privacy and GDPR issues, for example, are not yet resolved?…”

“…Given concerns that the adoption of HR analytics has been slow in many organisations (Boudreau & Cascio, 2017; Fernandez & Gallardo‐Gallardo, 2020; Rasmussen & Ulrich, 2015), scholars have urged researchers to explore the experiences of HR analysts and to shift focus ‘from the macro‐level of demonstrating and evaluating the potential benefits….to the micro‐level of the social contexts in which PA [sic. People Analytics] work is performed’ (Jörden et al., 2021, p. 3). Accordingly, existing HR analytics literature has concentrated on exploring two broad skills required for HR analysts to perform HR analytics effectively.…”

“…While Jörden et al (2021) do not mobilise the concept of decoupling, this case hints at the kinds of policy-practice gaps that institutional theory helps to explain (Bromley & Powell, 2012). In their study, Ellmer and Reichel (2021) observed the complexity of HR analysts work due to outputs of analytics projects needing to meet different stakeholders expectations such as HR priorities and business priorities while also needing to be communicated in light of broader 'compliance issues, dependencies, political tensions, and a prevailing data-driven decision culture' (Ellmer & Reichel, 2021, p. 2622.…”

Magicians, unicorns or data cleaners? Exploring the identity narratives and work experiences of data scientists

“…Outward-facing, data scientists try to influence managers’ understanding of data science and how they see the role of the data scientist. Part of this is to counter too strong an “action orientation” (Jörden et al ., 2022) on the part of the managers. To do so, data scientists enact their “scientific mindset” and particularly emphasize the time and diligence it takes for their “sophisticated work” to be conducted.…”