Meeting Effectiveness and Inclusiveness: Large-scale Measurement, Identification of Key Features, and Prediction in Real-world Remote Meetings

Author:

Hosseinkashi Yasaman1ORCID,Tankelevitch Lev2ORCID,Pool Jamie1ORCID,Cutler Ross1ORCID,Madan Chinmaya3ORCID

Affiliation:

1. Microsoft, Redmond, WA, USA

2. Microsoft Research, Cambridge, United Kingdom

3. IC3-AI, Microsoft, Seattle, WA, USA

Abstract

Workplace meetings are vital to organizational collaboration, yet relatively little progress has been made toward measuring meeting effectiveness and inclusiveness at scale. The recent rise in remote and hybrid meetings represents an opportunity to do so via computer-mediated communication (CMC) systems. Here, we share the results of an effective and inclusive meetings survey embedded within a CMC system in a diverse set of companies and organizations. We correlate the survey results with objective metrics available from the CMC system to identify the generalizable attributes that characterize perceived effectiveness and inclusiveness in meetings. Additionally, we explore a predictive model of meeting effectiveness and inclusiveness based solely on objective meeting attributes. Lastly, we show challenges and discuss solutions around the subjective measurement of meeting experiences. To our knowledge, this is the largest data-driven study conducted after the pandemic peak to measure, understand, and predict effectiveness and inclusiveness in real-world meetings at an organizational scale.

Publisher

Association for Computing Machinery (ACM)

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