This study investigates the impact of remote workplace factors on employees’ social and technical self-assessed performance during the COVID-19 pandemic. The impact of the variables belonging to the employee’s profile, organizational environment, and work-life balance categories on social and technical performance were analyzed, based on a survey of 801 Romanian employees, using ordinary least squares and quantile regression techniques. While the first method provided summary point estimates that calculated the average effect of the explanatory variables for the “average employee”, the second approach allowed us to focus on the effects explanatory variables have on the entire conditional distribution of the response variables, taking into account that this effect can be different for employees with different levels of performance. Job autonomy, engagement, communication skills, trust in co-workers, occupational self-efficacy, and family-work conflict, significantly influence both social and technical performance. PhD education and trust in management significantly influence social performance, while motivation, stress, the share of time spent in remote work, organizational commitment, children in the household, and household size, influence only technical performance.

The recent COVID-19 pandemic has accelerated the interest in new software tools to monitor the computer-based activities of employees working remotely (teleworking), and the demand for better analytics functionalities to be offered, focusing on employees’ performance and work-life balance. In this paper, we aim to analyze the habits of teleworking employees based on their interaction with the computer: how the employees are involved in different types of activities (actual work, recreation, documentation), and which are the most intensive periods. A conceptual framework for workforce analytics was developed for this purpose, together with tools and applications, that can provide useful information on different categories of activities where employees are involved. Knowledge generation is performed in four phases: collecting, processing, organizing, and analyzing the data to create valuable insights for the organization. Based on this framework, we developed a case study in an IT company, where two categories of employees, developers and software consultants, were monitored for 114 days, with 3.5 million events being generated and processed. The results showed different habits for consultants and developers, in terms of working activity structure, working schedule, inactivity time and interaction with the computer. Differences were also identified when we compared our results with previous research that monitored software developers working in-house: remote workers tend to organize their program for a longer period during the workday, and spend less time on meetings but longer time for programming. On the other hand, both categories of employees (in-house and teleworkers) show highly fragmented work, switching windows after very short periods of activity, with a potential negative impact on productivity, progress on tasks, and quality of output. The research results can be used in future employee productivity studies when searching answers to a fundamental question for workforce analytics – why are some employees more productive than others?

The paper investigates experiences of employees and middle managers in relation to the transition from working from office to working from home in the context of COVID-19 pandemic in Romania. Three online focus groups were conducted to explore working experience in the new mode of work. The conclusions are multifaceted, covering four dimensions: time, spatial, social and technical, and point out how employees and middle managers understand the transition and what impact telework had on their job satisfaction and work productivity.