TribePod: How To Find Business Behaviors That Matter Most

In this episode of TribePod, Jim Stroud chats with Kerry Goyette about guiding business behavior and how artificial intelligence is shaping the world of work today and on into the future. Some of the topics we discussed...

How to find the behaviors that matter most for your business--do you know if you're focusing your time, energy, and resources on the right areas?  How humans can work WITH AI, instead of being afraid of it.  What does AI need to look like moving forward?  How to build culture in a #WFH environment

Tune in NOW for a very informative interview. 

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PODCAST TRANSCRIPT

Jim Stroud (8s):
You are listening to TribePod. A podcast series of interviews of interest to the HR community. It is hosted by Courtney Lane, produced by Jim Stroud, sponsored by Proactive Talent, and enjoyed by you. Today's episode begins right after this.

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Jim Stroud: Intro (2m 8s):
For more information on Proactive Talent, visit them online at proactivetalent.com or click the link in the podcast description.

Jim Stroud (2m 16s):
Hello, and welcome to another episode of the TribePod Podcast. Brittany and Courtney are both tied up with clients today. So, it's just me Jim Stroud. Yay, for better or worse. Hopefully not for worse. I have a special treat for you guys today, a very special guest. Special guest tell us who are you? And what do you do?

Kerry Goyette (2m 38s):
Yeah, thank you so much for having me, Jim. So, I am Kerry Goyette. I'm a behavioral scientist, and I work with organizations all over the world on, how do we create awesome cultures that can thrive?

Jim Stroud (2m 51s):
Now, are you that famous person I saw on the YouTubes? One of those TED Talk things? Is that you?

Kerry Goyette (2m 59s):
Yes, I have a TED Talk called Stop Trying to Motivate Your Employees. So, it's around the concept of motivation.

Jim Stroud (3m 5s):
Really?

Kerry Goyette (3m 6s):
Yeah.

Jim Stroud (3m 6s):
Tell me more about that for the sake of those who did not see it. The two or three people who have not seen it.

Kerry Goyette (3m 10s):
Yeah, yeah. So, my postgraduate studies were in Psychometrics and Neuroscience. And so, I've done a lot of research and motivation, and people are inherently motivated. And so, we need to stop kind of thinking about it from the sense of, you know, either it's on or it's off. Motivation is always on. The question is what type of motivation is it? And that's where we really need to look at and be cognizant of the fact that we are unique individuals, and we all have unique motivations. And the more we get to know our teammates, our people, the more we understand what they're motivated by, the more we can build trust, build cohesion, and build a culture that's intentional.

Jim Stroud (3m 52s):
Okay, well, that sounds great. But how do I go about finding the behaviors that matter the most for my business?

Kerry Goyette (3m 59s):
Yeah. Absolutely. That's a question I get asked a lot by a lot of the CEOs that I work with. How can I start really driving performance? And I've seen this really kind of interesting, kind of this interesting trend happen throughout COVID. And I mean, it really started pre-COVID. I think COVID accelerated. But you know, as humans, we have this innate bias in us that, you know, it's the loss aversion bias. So, as leaders, what do we tell our people to do? We want them to do this. Oh, and by the way, and this, and this. And we just like keep piling it on.

Jim Stroud (4m 32s):
By Friday.

Kerry Goyette (4m 34s):
Exactly. And then we kind of wonder why we're left with employees that are kind of burnt out and worn out. And so, we really need to get better about looking at, what are the key behaviors that drive performance? And that's honestly Jim, that's the question I've been really studying and analyzing for over two decades now. Because I think people, we look at culture and we look at our people and say yes, people are important, and they're over here in this bucket. Oh, and then we have these business outcomes. And I think that we just haven't been able to really kind of figure out, what is it that are the things that behaviors that people are doing that are actually driving those business outcomes? And almost more importantly, what are the things that are distraction that's noise that's not helpful?

Kerry Goyette (5m 19s):
And I think when we can better answer that question, I think we actually do our culture's a favor, because we can start to eliminate some of the things that we're just throwing out them. And so, we've been getting into artificial intelligence, kind of interesting considering I'm a behavioral scientist. But I knew AI wasn't going away. And so, one of the advantages AI has is it's great ability to encode a lot of information. And so, we can actually take now all this data that we're collecting, like data from Slack. And we can actually look and see, what behaviors are driving these outcomes? Or we can look at financial data and look at, what are the activities that people are doing, that teams are doing that are truly driving those outcomes?

Kerry Goyette (6m 2s):
How much are they weighted, and why do they matter? And that why they matter is really critical, because then that helps us in training, it helps us when we're onboarding new employees. You know, here are the key three things that you really need to focus on. And when we do that, we really help people overall to be like, “Okay, because, gosh, I felt like 37 things were coming at me but now I know, like, these are the three things, the three key behaviors that drive that. And that's where I would say, you know, data in that space can be our friend. We have a lot of data on behavior that's out there.

Jim Stroud (6m 35s):
Do you find that human beings are nervous working with AI, and the robots and all that kind of stuff? Because we have images of the Terminator coming through the office shooting things up?

Kerry Goyette (6m 45s):
Yeah.

Jim Stroud (6m 45s):
What do we think about that humans, and robots and AIs, and all this stuff? I mean what do you think of that?

Kerry Goyette (6m 51s):
Yeah, it’s scary, which is why we decided to dive into it. I mean, it sounds kind of odd, because you think that we would kind of run the other way. And part of me wanted to run the other way because its potential is both exciting and scary. And so but that's the whole reason I decided to dive into it is, if we don't kind of bring the behavioral science aspect, if we really don't think about the humans that are involved in partnering if you will with AI, then I think we're really missing, we're missing a big equation. Because to your point, if we're not going to trust it, we're not going to build it ethically, and with the human in mind. And so that's where, that's the exact reason we wanted to dive into it.

Kerry Goyette (7m 34s):
So, absolutely, people should be fearful of it, but not so fearful that we don't engage in the conversation. It is here, it's here to stay. It's going to continue to be involved in our everyday lives. So, I think that that's where we really need to get in and be part of the conversation.

Jim Stroud (7m 51s):
Yeah.

Kerry Goyette (7m 51s):
And so, when we're talking about AI, that's why we've really researched the different types of AI. We're a huge proponent. And the AI that we use is explainable AI, it's transparent. It shows its work, just like humans have to do. I think where we get very kind of weary of AI is when it's in a black box, and it makes decisions, and we don't really know why it made those decisions. But that's where, we really need to look at, how can humans partner? How can humans stay in the driver's seat? AI has to show its work, it has to be transparent. All AI is biased, but even when it's transparent, we can look at it and say and be able to spot where the biases are, and then be able to address those biases.

Jim Stroud (8m 34s):
This is interesting to me. Let me throw this at you.

Kerry Goyette (8m 38s):
Uh-huh.

Jim Stroud (8m 38s):
So, I've heard a lot of about this concept called algorithmic management. And I'm thinking about Uber. For example, the way Uber manages their drivers and say, “You know, I go to the airport now because it's really crowded and they'll have search me and mean all that is done by AI, and not a human being. And Uber drivers just sort of go with the flow. Do you think we're gonna see more of this type of algorithmic management? I mean, Uber comes to mind. But do you see it in other sort of situations, too? And what do you think the pushback would be, if any?

Kerry Goyette (9m 15s):
Yeah, yeah. I do think we will see more of it. I think the push back to -- it's one thing, you know, when it's kind of like a GPS, or we know that it's telling us, “Well, there's traffic in this area. You better get to the airport earlier.”

Jim Stroud (9m 29s):
Yeah.

Kerry Goyette (9m 29s):
But when it starts to become, I would say either more personal or dealing with more complex environments. Like for instance, I have an insurance company. And so, when you look at how underwriters are making decisions, AI can certainly play a role in that. But if you rely, this is where I kind of see where things kind of go wrong. But you know, I have one client where they relied too much on AI. And then all of a sudden, they were kind of bleeding out because AI was doing what it was intended to do but there were some decisions, there still are decisions that humans have to make. And that's where they kind of went too far on the, “We're just going to give AI all the control and make all the decisions.” And that's not necessarily helpful.

Kerry Goyette (10m 14s):
And then you have people on the other end of the spectrum that don't even want to engage with AI at all. So, I don't think it's a one size fits all. And yeah, I do think we are going to see more of that. And I think we're going to see some areas where it's making some mistakes, and we kind of have to course correct.

Jim Stroud (10m 29s):
I'm glad people are thinking about it, but you're glad you're thinking about it. Because I've seen a lot of different articles which made me scratch my head. Because I've seen some companies experiment and go a little bit too far. I'm thinking about Amazon. For example, they had this thing where they want to do hire more people, and they use this algorithm that screened out women I think because they were just focusing on those random sample of data they had was all around men. So, it preferred men of a certain age and sort versus no women because it was tracking on the data that input into the system.

Kerry Goyette (11m 9s):
Right.

Jim Stroud (11m 9s):
And it took them a while to figure that out. But that's an example of how you can trust too much in the machine and take out human decision making.

Kerry Goyette (11m 20s):
Yeah.

Jim Stroud (11m 20s):
You know, I think that might be, you tell me, that might just be the main point in dealing with any kind of science, or any kind of new technology is. Don't let it become a crutch to you. You got to have the human part in there, yeah.

Kerry Goyette (11m 34s):
Right, you do. And technology in and of itself isn't necessarily good or bad. It's how the human uses it. How do we use it? How are we partnering with it? And in all fairness, like we're learning. I mean, humans, we're having to catch up. You know, the pandemic, I mean we advanced gosh, probably 10 years technology wise in about 10 months. And so, as humans, as people, we're kind of catching up. We're a little behind the curve there. So, there are going to be mistakes. We are going to bumble around a little bit. But I would say, yeah, the more that we're kind of catching those things, and we're seeing, “Yeah, that's bias.” Like if we're looking at all male data, then that's a problem. And again, it's another reason why I'm a huge fan of explainable AI.

Kerry Goyette (12m 17s):
Like, you know, AI really should be showing its work. We should be able to look at the data samples and see what it's comprised of because there are ways that you can easily address that all your current sample is all white men then that we need to be adding in additional samples of, yeah, different ethnicities, different genders.

Jim Stroud (12m 37s):
Yeah. For sure, for sure. As you say that, and maybe it's just this vibe, you're giving off this different thing. I am trying to imagine a situation where a job seeker applies for a job. Excuse me. They don't get the job for whatever reason. But they don't blame themselves. They don't blame their resume. They just said that the company discriminated against me in some way because I submitted my resume, and my resume is perfect for this job. And I started to get no one looked at me or talk to me or anything like that. And so the company can say, “You know what, it's not used, it’s just the criteria that we use of our magic algorithm AI, just think your resume made the cut.

Jim Stroud (13m 26s):
And so, the job seeker says, “You know what, I know I should get that job, or at least be interviewed for it and your algorithm discriminated against me. What's your secret sauce for how your algorithm picks out candidate? I want to see it because I demand to be hired because I know I'm perfect." Right?

Kerry Goyette (13m 42s):
Yeah.

Jim Stroud (13m 42s):
And so all that to say.

Kerry Goyette (13m 45s):
Um-hmm.

Jim Stroud (13m 45s):
Is there in the future maybe, or maybe it's happening that you know about it? Is there some kind of governing body that just randomly tests these different algorithms to make sure that they're not too biased or overly discriminatory or whatever?

Kerry Goyette (14m 1s):
Yeah.

Jim Stroud (14m 1s):
If not, it'd be a great site to somebody [crosstalk] your algorithms at.

Kerry Goyette (14m 6s):
Yeah, I mean, you're starting to see more government regulations around that, like the state of New York its kind of jumped in. Always, when you're dealing with like regulating things, there's always a lag. You know, regulation policy, that's always gonna lag behind the technology.

Jim Stroud (14m 23s):
Sure, it is.

Kerry Goyette (14m 24s):
So again, it's not surprising that we're not seeing a lot of that. But there is a lot of demand from the market that's saying, “How do we know? How do we know you're not biased?” And so that's where people are using the word transparent. My problem with that is when we dug into that a little bit more, what they're doing is like, they're being transparent about their process, and they're auditing it but it doesn't necessarily mean the algorithm is transparent by design. Whereas, when we, our algorithms are transparent by design, so from the way they're built, like every step of the way, you can see it rather than just us saying, “Here's the results that we got. Now, let's go back and audit it and you can see our process.” So, I mean, that gets technical and not everybody, most people don't understand the difference.

Kerry Goyette (15m 12s):
But that's kind of why we're in this space to help educate people and say, “No, you know, we really -- especially when you're dealing with human data, if you're making hiring decisions, you're making people related decisions, your algorithms really should be explainable by design, not just in process that we audit after.

Jim Stroud (15m 34s):
Good answer. Question for you. Going to throw a curve ball at you. Thinking about your TED talk. How do I build culture in a work from home environment? Because if everybody's remote and everybody's doing their own thing.

Kerry Goyette (15m 45s):
Yeah.

Jim Stroud (15m 46s):
How can you build a culture that keeps everybody together if we're not all in the same room? How's that possible?

Kerry Goyette (15m 52s):
Yeah. Number one, let me just state and just be honest and say, it is harder. I mean, it's just harder. When you're not there in person, there's a lot of exchanges that happen non-verbally. So even just the fact that while this podcast is only going to be audio but the fact that we're video, Jim, I can see you, I can see your facial expressions, but in person, I can see even more because it's a bit more three dimensional, and I can see different aspects of your expressions.

Jim Stroud (16m 19s):
Sure.

Kerry Goyette (16m 19s):
There's so much that passes through that. Also, when we know, that when we also know that when we're in person we do more brainstorming together, we also laugh a little bit more together. And there's some interesting research out on laughing, that that just creates an emotional bond, more trust. You know, Zoom people gets Zoom fatigue. And so, there's just kind of a little bit less creativity, a little less kind of just laughing and having fun together. So, I will say, yeah, there are some challenges. Now, that doesn't mean that they can't be overcome and we should be able to overcome them. But part of it is we have to create some sort of cohesiveness to build culture. We can't just throw words up on a wall and say, these are our core values.

Kerry Goyette (17m 1s):
They actually have to be lived out in in behaviors and actions that we take. So, if that's just like the way that we structure our meetings, kind of the fun that we have across the organization. So, think about like how we do our work? How we coordinate and collaborate? And how we just build relationships together? There has to be that sense of cohesiveness to where we feel like we're part of a team. The second thing I would say, is they've got, people have got to feel that what they're doing is meaningful work. It is so important to really unleash their motivation that they have to feel that it's meaningful.

Kerry Goyette (17m 41s):
And what I've seen from leaders over the pandemic is especially virtually, we're just kind of throwing tasks at them. Like, here are the 10 things I need you to get done this week. Well, that doesn't really create a sense of meaning. And people are coming to work for an organization. It may not say it on their resume, but we're all looking for meaning and purpose. We're looking for a culture where we feel like we get to do that. Now, we know that not every piece of work that we touch or do is going to be meaningful, but in general, it needs to be meaningful. And leaders can do this by just kind of talking about the why. This is really important. This is how it helps the team. Help them connect it to those outcomes. And then when those outcomes actually manifest, then you need to be saying, “Well, the work that you contributed on that project, we just got killer testimonials from our clients on it.

Kerry Goyette (18m 30s):
They were so happy." And that makes them feel like, “Wow, that work that I did was highly meaningful.” Talk about the progress. We all, I mean, just like if we go to a football game, we want a scoreboard because we want to see is our team winning or losing. Are they progressing? How many yards did they gain? Same thing we kind of forget to say like, “Gosh, look at how far we came since last month. On this project. Yes, it's a big hairy project. But look at the progress that we made." And so, there are multiple ways that we can create meaningful work. But sometimes in a virtual environment, we forget to do that as much. And then finally create a sense of clarity, we have to help employees cut through the noise.

Kerry Goyette (19m 11s):
And this came out loud and strong in the pandemic when everybody went remote, just we lose a little bit of clarity. We lose a little bit of resolution. So, we those conversations around the water cooler, around the coffee bar, you know, little bitty conversations, just add additional data and clarity to what we're doing. And when we don't have that we're just missing some of the puzzle pieces. So, we need to make sure we're never going to create a sense of certainty because we have no idea how things are going to roll out but we can help them create clarity. And I can't say that enough because the brain is striving for clarity, it wants clarity. It will help people move forward. We know with motivation to act, they have to go towards something and we're more likely to act and go towards something when we have a sense of clarity for it, because our brain is just doing calculations and it's like, “Okay, I know I'm supposed to be headed that direction go.” But if it's just like, “Oh, which direction do I go?"

Kerry Goyette (20m 6s):
We sit, and we kind of look. And we may overanalyze, and we may just kind of wait for additional clarity. So, if we really want to unleash motivation, we've got to create that sense of clarity. So those are the three big things I would say that are absolutely integral in creating a culture in a work from home environment.

Jim Stroud (20m 26s):
Cool. You mentioned about losing clarity and losing a few things. One other thing too that, I think we've lost, or at least has been my experience in dealing with some customer service people I've had to deal with recently. Is that, I wonder if we're losing our emotional intelligence.

Kerry Goyette (20m 46s):
Um-hmm.

Jim Stroud (20m 47s):
Being able to just talk to somebody and having some kind of empathy as to why my computer broke down. They could have just said, “You know, what we're on it. Sorry about that. Have you tried this, try turn it on and off again?” Like, yeah, I tried that. Things like that. But I think a lot of us, because of the remote space, and the mask, and the not touching the six feet apart, I think we're losing that emotional intelligence. Can you speak on that? Do you have any insight on AI at all?

Kerry Goyette (21m 18s):
Yeah, yeah. You know, again, it's somewhat anecdotal right now as kind of that we continue to collect data. But yeah, I would say we are losing that. That's why we're seeing like even on airlines, we're seeing people be really verbally abusive to flight attendants.

Jim Stroud (21m 34s):
Yes.

Kerry Goyette (21m 34s):
And we're just, you know, we have a lot of pent up frustration, a lot of burnout. And on top of that, as you said, all those factors having to socially distance, we're remote. It just decreases our empathy. And again, the fact that we're not building relationships, we're not telling those stories, we're not laughing together. I mean, all of those things are what helps make humans, humans. It gives us that sense of empathy, that sense of wanting to build relationships. And so yeah, I would say that's absolutely true.

Jim Stroud (22m 5s):
You know, it makes for interesting times.

Kerry Goyette (22m 8s):
It does.

Jim Stroud (22m 9s):
You have a wealth of knowledge wise woman, you. It's so unwanted more of your knowledge. You want to connect with you. What are ways they can find you online?

Kerry Goyette (22m 21s):
Yeah, you can go to our website at thinkaperio.com. We have a lot of free resources. I've written a lot of articles, HBR articles and articles in many different publications that are free. We also have a free download from my book, The Non-Obvious Guide to Emotional Intelligence. So, there's a free download there. And then of course, you can find my book on Amazon, as well. So, encourage you to do that as well.

Jim Stroud (22m 45s):
Cool.

Kerry Goyette (22m 46s):
So, lots of places to interact with us, and of course, social media as well.

Jim Stroud (22m 51s):
Yes, yes, yes. Thank you so much for being in the TribePod Podcast. We appreciate you. Thank you.

Kerry Goyette (22m 57s):
Yeah. Thank you, Jim. Thanks for having me.

Jim Stroud (23m 7s):
Thank you, thank you, thank you a thousand times. Thank you for listening to the TribePod Podcast. If you have a question or comment, please email us at TribePod that's T-R- I- B- E-P-O-D @proactivetalent.com operators are standing by. Thank you so much again for listening, and please share this podcast with a friend.