By Rob Enderle, Computerworld, 13 August, 2021
Sometimes, the loudest voice in the room (or on a video chat) dominates decision making in ways that aren't good. Technology could help stop that from happening.
I’ve recently started watching Ted Lasso on Apple TV+ and what fascinates me is how this sitcom doesn’t focus on the main character’s bad behavior, it focuses on the good. It is more about helping your team advance by helping team members become better versions of themselves.
That’s surprisingly similar to what is often taught to top moderators, mediators, and arbitrators: focus on the problem, not the person, the cause, not the symptoms. Meetings, particularly online meetings of late, can be dominated by the most obnoxious person on a call — with decisions made, not on the merits of various arguments, but by the loudest voice.
I’ve called this the “biggest jerk wins” method.
I’ve also observed that people in mixed groups are becoming too comfortable using salty language, which can form the basis of hostile workplace actions and abuse complaints. (Given that these online meetings are often recorded, they provide pretty compelling evidence.)
So I’ve come up with three features for future collaborative get-togethers that should help.
The ‘Jerk Meter’
Granted, “Jerk Meter” won’t be its final name, but with conversational computing gaining ground, we can now analyze what a person is saying and determine both tone and content. Letting a speaker know they’re sounding aggressive and dominating should help mitigate the issue. Clearly, some may not care. But most people I’ve spoken to after a meeting where this happened have apologized and said they wished I’d flagged it earlier. (Fewer fences to mend later.)
People at all levels can have bad days, and many can get angry when challenged on a subject they don’t know well. Neither reflects well on the speaker, and both can damage critical relationships.
The goal would be to let a speaker know they’re acting out, harming the collaborative nature of the effort (and their image) so they could correct the issue, or their manager could correct it, with minimal damage.
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I’m both a trained news anchor and a trained moderator — and moderating an online event is far more complex than it needs to be. You have to monitor at least two feedback windows, listen to and keep the speakers on track, foster discussion, and, at the same time, work to make the resulting content enjoyable. I haven’t seen anyone do this well. It is simply too much to manage.
Ideally, the moderator should be looking at comments and questions to gauge interest and steering the discussion to maximize engagement. Many can’t even keep up with the questions, let alone the rest of the responsibilities, which might include managing slides. Much of this could be moderated with artificial intelligence using a Conversational AI front end or providing a dashboard to the moderator that organizes information and provides speaker timing to keep things on track.
I was on a call the other day where the moderator pretty much gave up when one speaker went off-topic for so long that I had to step in and tell the person to stick to the subject. Another speaker got so upset he just started yelling at the guy to “shut up” — the entire thing went off the rails.
That’s why we need a focused set of tools to help moderators keep discussions going, focused, and interesting. If you were to imagine the perfect book to describe IT organizations right now, it might be entitled A Tale of Two Clouds.
Cross-pollination among teams
Particularly in large companies, you can have multiple groups working on similar efforts who are unaware of each other. In some ways, this can allow a better solution to bubble up. But most times it just results in redundant efforts and repetitive avoidable mistakes. Much as services like Netflix and Amazon extrapolate interests based on behavior, an AI could monitor meetings for standard content and then report to both groups their peer activity.
Granted, this would likely need to be opt-in for political reasons or it could get in the way of innovation. But it could bolster collaboration, foster intergroup discussions and reduce redundancy while improving access to internal and external experts uniquely available to each group.
A few years back, I was responsible for a bid process that led us to choose a new accounting firm; I then got a direct call from our CEO telling me to reverse the decision. Apparently, the old accounting firm was our largest customer, something that would have been good to know. (The sales side of the company knew it, but not the operations side. Sales could have provided that critical information before our CEO concluded that I was an idiot.)
Much as people are connected to interests in apps like Facebook and Pinterest, this kind of system would allow people to overtly and automatically, based on what they discuss, learn about activities in their interest areas. That way, they could weigh in as needed, and other folks making decisions wouldn’t get in trouble for things they didn’t know.
Smarter collaboration is needed
We have made incredible strides with rapidly improving collaboration systems, but many of the old issues with traditional collaboration efforts remain in place. We have technology to improve our performance in meetings over time, automate or improve moderation, and better connect currently disconnected groups.
There’s even something like IBM’s Watson Assistant, which could answer policy and strategy questions during a meeting. (Disclosure: IBM is a client of the author.) Many times, questions aren’t answered by the most knowledgeable person at the table, but by either the most obnoxious or most senior leader. Watson could steer the conversation toward the best outcome.
We are on the cusp of taking collaboration systems much farther than they have ever gone. It’s time to turn them into the productivity engines they can be.