Why are we stuck in the data?

Nicki, the lead coach at MIT Leadership Center and I have been giving a lecture on cross cultural awareness to MIT Sloan Fellows students and MIT Executive MBA students, highly accomplished professionals from 60+ different countries. We have been sharing how different cultures have different ways of communicating through fun Q&As, sharing our experience, and using Erin Meyer’s The Culture Map framework, which shows where each country lies in the spectrum of hierarchical - egalitarian, confrontational - avoid confrontation, etc. We hope that through these frameworks, stories, and in-class discussion, students can understand the importance of perspective taking, patience, and humility in working with highly diverse team members. 

After one of the classes last semester, a student from Taiwan approached me and said, “What kind of people did the researcher survey? The study was probably conducted only with English-speaking individuals, not the real people from China. The data seems inaccurate.” He was talking about the frameworks we shared. Expected, but a little taken aback by a strong doubt, I asked, “Which part of the spectrum do you think is incorrect?” “All of it. I used to work at the largest company in Taiwan. And we were not like that.” I responded, “I’ve also worked with Taiwanese and Chinese professionals. From my experience, Taiwanese workplace culture seems quite hierarchical. Would you agree?” “Oh, yes, on that point, I agree—we are hierarchical. But on other spectrums, the data seems wrong. Among working level employees, we can be very confrontational, as long as there’s no boss around.” It seemed that he was particularly skeptical to see his own culture, China/Taiwan, represented as rather “avoiding confrontation” in the disagreeing spectrum. He reiterated his belief that the survey only captured a small, specific subset of people. 

I felt disappointed and annoyed that he wasn’t unwilling to and not be able to move past his frustration with what he saw as misrepresented data. It seemed to me that he didn’t really understand our core messages - culture’s impact on our behavior and the importance of understanding others. Or maybe, he understood the core points but wanted to challenge the data. But more importantly, I found myself trying to correct him in the same manner. Going into this little chat, I expected this type of feedback and thought to myself to bring the conversation up to the core messages. Only afterward did I clearly see the pattern I had fallen into—I had been drawn into the same data level debate, triggered by my own emotions.

Earlier in the class, Nelson Repenning, professor in the field of leadership at MIT Sloan talked about the importance of emotional regulation. Our emotions are much faster than our thinking. All along in human history, it has supported us to survive from threats. In the modern environment though, we can be suboptimal if we are not able to use our thinking brain because our emotions are connected to our historical fear, jealousy, annoyance that is no longer relevant. 

For a long time in my early career, I had been annoyed, sometimes very much frustrated, when someone was not to the point in the conversation and not answering my questions directly. I felt that the person was wasting the time, and not trustworthy. Those emotions led me to react in a way that was not helpful. My not so proud typical response was “You are not answering my question!” Or with someone I was afraid to be that direct, I disengaged. Overtime, I became more curious about what’s going on with this type of communication and the people’s motivation. It took me many years to notice this pattern and be cautious about the situation. Now it takes only an hour or, sometimes, minutes to see what has happened with my triggered emotions such as the one toward the conversation with this  Taiwanese student. 

Luckily, through anonymous feedback after class, we found most students understood our core messages and appreciated our lecture. But I hope I can help the ones who were stuck in the data level get back to the core messages too. How can I do that more effectively? Nicki and I are exploring different ways to move our minds from data to meta messages as well as learning the key data set at the same time.