Connecting employee survey data to organizational performance indicators using micro-macro multilevel regression

Many organizations employ yearly employee surveys to monitor employee attitudes and engagement. Indeed, a specialized line of HR consultancy exists to assist organizations with employee survey design, data collection, processing, results feedback, discussion, and action follow-up (Knapp & Mujtaba, 2010; Huebner & Zacher, 2021). Several rationales underpin such employee survey-based processes of results feedback, discussion, and action follow-up. For example, how employees think and feel about their work and employment conditions, their team, their supervisor, and the organization as a whole is expected to influence their work engagement and work behaviors, thus impacting the effort invested in and the level and quality of their individual performance, and ultimately contributing to organizational performance (Cascio & Boudreau, 2010; Fulmer et al., 2003). This reasoning also underlies the HR process model (Nishii & Wright, 2008). Another rationale, more geared toward service organizations, is rooted in the service-profit chain (Heskett et al., 1994). It suggests that employees’ experiences of the organizational service climate affect their attitudes and behaviors toward customers, thereby influencing positive financial returns for the organization through customer loyalty.