Global Virtual teams performance data

A usual roadmap of such support ticket includes initial triage of criticality and complexity, analysis, code development, internal testing, user acceptance testing, deployment and post-deployment monitoring. Research data were extracted from the main company ticketing system using the default reporting system of ServiceNow software. Extracted data include necessary identification details that measure over 150 selected variables and KPIs of each ticket (work item).

Also, the technical nature of this extraction ensures high data quality and a unified measurement process for all examined tickets. Tickets with outlier values such as resolution time over one month were removed. Also, the work items that were not entirely up to the selected teams were removed (extensive interaction with a third party).

In total 59 267 individual work items from 58 teams consisting of 1 548 members were extracted and analysed to create the research database. The research data were gathered from an extensive period of January 2018 to December 2020 to ensure that the dataset covers high exposure periods of the ERP system (year-end closing of financial ledgers and monthly/quarterly production planning). The company’s internal ticketing system ensures the quality of the dataset; therefore, it depicts fully verified metrics.

Resolution time Mean time duration of work items for the team over quarter Communication ambiguity Mean number of updates per work items for the team over quarter Quality reworks Mean number of reworks per items for the team per quarter