The science of meetings — which includes collecting sophisticated data that analyzes meetings word-by-word and phrase-by-phrase — is still in its infancy. Researchers from MIT, however, used an available database with a myriad of data to reach some tentative conclusions about different facets of meetings, from calculating average ‘wrap-up’ times once a decision is reached to identifying the most persuasive words used in meetings. They were even able to use language analysis to identify when participants in a meeting were about to make a decision
What can statistics and data-based analyses reveal to us about meetings that are effective (leading to consensus and decision-making) and efficient (goals achieved in optimal time)? Because the science of meetings is still in its early stages, the raw data for study is still being accumulated. However, two researchers from MIT’s Sloan School of Management, statistics professor Cynthia Rudin and graduate student Been Kim, used available data and related literature to explore four specific questions about meetings:
In addition to related research (for example, on persuasive words), the researchers analyzed a database of statistics drawn from a controlled set of 95 meetings. This database breaks the 95 meetings (which lasted less than an hour) down into 108,947 individual ‘dialogue acts’ — questions, statements, assessments of suggestions (“that’s a good idea”) — and 26,825 ‘adjacency pairs,’ which are connected dialogue acts. The combination of a question and an answer to the question, for example, is an adjacency pair.
Based on their analysis, the researchers offer some tentative answers to the four questions above, as follows:
Because the data for studying meetings scientifically is still being gathered — Rudin and Kim were limited to 45-minute meetings, for example — the conclusions of the research are tentative. Nevertheless, in addition to setting the table for more extensive research, the MIT research leads to some interesting applications for businesses.
Since scientific analysis of words reveals when a decision is about to be made, a software tool could be developed that alerts managers when they might want or need to join a meeting of their staff. Thus, managers can participate in the most important parts of the meeting without having to attend the full meeting.
Patterns of social dialogue can be instructive. Some less sophisticated managers might attempt to connect positive social dialogue to their negative assessments in an attempt to offer encouragement (“that information is useless, but thank you for the effort”). This only makes the speaker sound disingenuous, and would do more harm than good.
Knowing the approximate wrap-up time of a meeting once a decision is made could help with logistics; staff could 1) note when the decision is made, 2) estimate, based on this research, how much time is left in the meeting, and 3) arrange for transportation, or the next meeting time.
And, obviously, identifying persuasive words will help meeting participants frame their suggestions in a more effective manner.
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