Development of a Badge System to Visualize Communication States

Toyota Motor Corporation's Frontier Research Center (hereafter referred to as Toyota) and the Toyota Central R&D Labs., Inc. (hereafter referred to as TCRDL) are working on visualizing communication through conversation using sensing data, with the aim of enhancing the vitality of individuals and organizations. This project emphasizes theoretical research and the pursuit of value, focusing on real-world experiments in settings like internal training and workplaces. In this article, would like to share the details of this initiative.

- What kind of experiments did you conduct using the Badge System?

Mitsuda

The challenge and interesting point is how to extract useful information in the field from the simple data of the sound pressure of the subject's voice and the body acceleration data obtained from the Badge. For example, while analyzing sound pressure data, the quantity of conversation often draws attention, but silence can also be an important indicator, depending on the situation.

To specify the indicators and validate their value, we visited workplaces where people faced problems, had them use the Badge System for a certain period, and collected their feedback. We focused on the characteristics of individuals and groups, introducing a case study on group work in internal training (conducted by Toyota) as an example focused on individuals and a case study on everyday workplace applications (conducted by TCRDL) as an example focused on groups.

- Now, could you tell us about the case study on applying the Badge System to group work in internal training, focusing on the issues at the site?

Sugata

In this internal training, there is one instructor for about 20 participants, who are divided into groups of four or five to discuss their mindset about work. Since the instructor is an employee and not a professional evaluator, there are limitations to evaluating each participant carefully and objectively.

So, we had the participants wear the Badges during group work. We analyzed the sound pressure and acceleration data collected from the Badges and created communication analysis reports for each participant, as shown in Figure 2. We developed 11 indicators to evaluate participants from multiple perspectives.

- Were there any difficulties in determining the communication indicators?

Sugata

Understanding the instructor's perspective was challenging. For example, it was difficult to verbalize how the instructor viewed the participants regarding the evaluation item "Do you respect the other person?" and translate that into a quantitative indicator. As a result, we set indicators for the number of nods during others' speech, speech occupancy rate, and posture during spontaneous speech.

- How was the feedback on the communication analysis report?

Sugata

Not only when the instructor advises participants but also by presenting this report to the participants' workplace supervisors, we were able to provide an objective explanation of the participants' communication tendencies. This aspect has been very well received and has significantly contributed to improving the participants' communication skills.

- Next, please tell us about the case study conducted at TCRDL, focusing on the group.

Nagaya

Yes. At TCRDL, to visualize daily communication in the workplace, we had about 100 employees in the administrative department wear the Badges for about three months, collected communication data during work hours, and visualized the data for two months that were analyzable.

- What kind of visualization did you perform?

Nagaya

For example, based on the conversation time between pairs of individuals, we created and analyzed a communication network. Figure 3 shows the communication network based on all conversations that occurred over the two months. Each circle represents one person.

Nagaya

From this communication network, we calculated indicators used in social network analysis, such as "betweenness centrality," which shows who is mediating information between workplace communities. Figure 4 illustrates the changes in betweenness centrality over time. The left side shows the first month, and the right side shows the second month. The orange arrows in the figures indicate that a certain person's betweenness centrality was overwhelmingly high in the first half of the experiment but blended with other managers in the second half.

- What changed?

Nagaya

The communication networks for each period are shown in Figure 5. From Figure 5, we can see that a new community (in blue) emerged in the second half, including the individual with high betweenness centrality, indicating that this community is acting as a new mediator of information. We could say that the pathways through which information flows have diversified.

- I see, it seems we've gained insight into group communication. What other visualizations were performed?

Nagaya

We conducted a detailed analysis of communication within meeting rooms. In regular conversations, it can be difficult to determine what constitutes a continuous conversation, but in meetings held in meeting rooms, it is relatively clear when the conversation starts and ends. At TCRDL, we can check everyone's schedules on Outlook, so with the participants' consent, we obtained scheduled data and linked it with conversation data. Over two months, we extracted and analyzed more than 3,000 meetings and discussions.

- Even within conversations held in meeting rooms, there are various types, such as formal meetings, team discussions, and casual chats. In what situations would this be useful?

Nagaya

Actually, that was our concern. After some trial and error, we concluded that one-on-one conversations between managers and members would be ideal. Therefore, we extracted meetings explicitly titled "1-on-1" in the scheduler. Figure 6 shows the analysis results of four such one-on-one meetings.

Nagaya

In cases (1) and (2) in Figure 6, it is evident that the manager spoke more than the member. Generally, it is said that during 1-on-1 meetings, the manager should focus on listening and allow the subordinate to speak as much as possible, with a guideline of 80% subordinate and 20% manager. However, analysis shows that this is not often the case. On the other hand, cases (3) and (4) had the same manager, but they both had less speech than the members, meaning they followed the theory of 1-on-1 meetings. In cases (3) and (4), longer silence times were also characteristic, suggesting that this manager consciously refrained from speaking and was not bothered by silence.

- Did you share these results with the managers?

Nagaya

After the project ended, we held explanation sessions for the approximately 100 employees who cooperated, sharing the analysis results of the acquired data by the workplace. When we conveyed the results of the one-on-one meetings, managers who spoke a lot reflected, "I might not have been doing that," while those who spoke less seemed indifferent, saying, "Is that so?"

- I see. Communication analysis can indeed be approached from various angles. Finally, could you tell us about future prospects?

Mitsuda

Clarifying the correlation between communication characteristics (such as leadership) and psychological states (positive or negative) with indicators calculable from the Badge System will be a research task. Additionally, the relationship between non-verbal signals and communication is a fascinating academic theme with implications for exploring the origins of sociality, mental health, robotics, and education. We also plan to use the Badge System for measuring the effects of plant greenery in our other articles on this site titled "Genki-Kûkan^TM."

References

Contact Information (about this article)

Frontier Research Center

frc_pr@mail.toyota.co.jp