Global Virtual Teams dataset 2020

Published: 23 April 2021| Version 2 | DOI: 10.17632/txhgch5cw2.2
Radek Liska


Data tracking KPIs for numerous global virtual teams.


Steps to reproduce

The teams in our research use their designated virtual working platform as a single source of the truth, all their operations and work tracking revolve around the platform. Therefore, the log of actions, communication, assignments, time stamps, and details can be used for a detailed analysis of behaviour in a real business environment. The virtual tool itself serves as a source of primary research data, and thanks to its computer-based nature it allows a flexible time scope, a high level of detail and precision, and stands as an overall bias-free dataset. All the teams in our study follow the same support process of a similar business IT application. The scope of teamwork includes a full care of ERP (enterprise resource planning) system. The nature of work includes the full service of the company information system, including resolution of any reported issues or defects found by users working with the system as depicted in Figure 1. Teams aim to deliver a solution for the system defects reported by a wide user base covering throughout operations of the supported business units (manufacturing, supply chain, accounting, planning, finance, warehousing). Data were gathered between January 1, 2018 and June 30, 2020, hence giving a full coverage of 2,5 years operations using the data gathering flow depicted in Figure 2. Subsequently, only the quarter two data were pulled from each year covering the period of Q2 2018, Q2 2019 and Q2 2020 while the latest one was impacted by the COVID-19 pandemic. The database went through multiple cleaning cycles removing work items such as administrator tasks, non-production issues (development of the system & testing). Tickets with outlier values such as resolution time over one month (2 600 000 seconds) were removed. Also, cases that were not entirely up to the selected teams were removed (extensive interaction with a third party). The research scope includes an analysis of 48 teams that were divided into 5 organizational units to facilitate the description and navigation of the dataset. In total, 43 650 tickets were processed in the selected time frame. The description below covers organizational framework and cultural composition on the main level of organizational units (naming was designated based on their main geographical focus). Five units cover standard geographically bounded operations and one unit branded as “cross functional” serves tickets across all other organizational units.


Social Sciences