Measuring team dynamics with computational methods. Based on expert interviews

Abstract

THE AIM OF THE PAPER

There is emerging demand in several scientific areas for measuring human behaviour, attitude and cognitive processes. We live the golden ages of computational modelling in medical sciences, engineering, psychology and marketing. Computational social psychological observations (video recording, sound recording, sociometer, GPS etc.) enable us to investigate human interactions more deeply. This study gives an insight into the possibility of measuring team dynamics with computational techniques, based on interviews with experts. The aim of research is to reveal werther it is possible to advance measuring team dynamics with computational techniques?

METHODOLOGY

To investigate the topic of measuring team dynamics I use a multiparadigmatic sequential research design.  In this paper I present an interpretative reveal study based on expert interviews. This is the primary, qualitative phase of the complete research and it serves as an input for the following functionalist phase. Data collection was based on a preset questionnaire and took place between November 2019 and March 2020 (Appendix 1). The interviews were semi-structured, which made it possible to enlarge knowledge by asking further questions.

MOST IMPORTANT RESULTS

Measuring team dynamics is still in its infancy and there is not enough focus on it within the organizations. While organizational development focuses on group processes, in daily activities of organizations observing and evaluating individual performance, motivating individuals is the main focus. Measuring team dynamics is often limited to self reported surveys and participant observation due to lack of time and budget. Computational measuring (webcamera, sound recording) is not widely spread. despite the fact that experts see it as a possible solution.

RECOMMENDATIONS

Computational techniques and machine learning make it possible to capture human interactions and exchanges, identify meaningful patterns and use them to predict important outcomes, to analyze complex team dynamic questions for organizational and HR managers, for trainers and organizational developers. Experts interviewed find it an important and desired, yet costly, complex and hard to decode solution.