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Dig In is your go to source for insights innovation. It's for anyone with a genuine interest in fostering brand and product growth, exploring groundbreaking innovations, and embracing the dynamic world of expanding businesses and brands.
Jess Gaedeke (00:29)
Hi everybody, welcome to the Dig inspiration episode. This is where I get to talk with a colleague here at Dig about the episode that dropped last who better to talk to at Dig than Patricia King, who is our very own EVP global client partner, has, I think, some insight to share based on the conversation with Kendra. So Patricia, thank you for joining me.
Patricia King (00:49)
Thank you for having me.
Jess Gaedeke (00:50)
So we're gonna dig in. covered a lot of ground. You and I know Kendra, she is so inspiring. She has so much energy, so many great ideas. She talked about a lot of things. She talked about purpose. She talked about patience. She talked about the role of AI. And so I thought it'd be really cool to bring you here to chat about that because part of your role is making sure our clients that dig, we really understand those strategic priorities. We make sure that our relationship and our deliverables are landing.
So I'd love to talk about one of the things that Kendra brought up, which is this whole idea about the difference between answers and confident decisions. And so from your vantage point, what's the difference between those two things and how should senior clients be thinking about it?
Patricia King (01:30)
a very good question. I think everyone's all over the place on that right now because there's always the push and pull between fast, confident, better, all of those it's definitely a conversation I'm having weekly, maybe even daily. just got off vacation and it was actually the last call I had on Friday. It went until about 5, and was the last thing that came asked, your team using AI?
asked why and he said, because I just got a deliverable. It was great. Not even a much you're using AI. answer actually was, we haven't tested this in advance. So like your answer to this. I said, probably not been previously running the Qualteam.
the idea that, you know, we are very aware that AI can't do everything. We are aware how important the human is, what they're saying, being in the room with them, hearing the pauses, the eyes, looking around, seeing someone those open ends in context of how someone answered a survey earlier when as researchers, making some of statements at the end of a So I think fast is great. Fast is better. are...
able to conclusions faster, but we just have to make sure they're right because being confident in that information we're giving our clients is we give them an AI output, if we miss something, if there was an aggressive statement that wasn't actually as aggressive that got pulled out in those that's on us. And able to identify what AI can do.
and how fast we can get them the answers, but still make sure that we have a human lens on everything is gonna be the most important.
Jess Gaedeke (03:06)
Yeah, Kendra shared that example of her class that she's teaching and the, know, kind of focus group they did and how they used AI to generate the deliverable and that it was their ish. And I thought that was so powerful because did need to understand what's that body language? What was the conviction with which a certain, you know, opinion was shared? Those are the things that you lose if you don't bring in the human element. I thought those were great examples.
Patricia King (03:29)
so yeah, I think is key about being able to be faster and using AI is that we can use it where it's important, where it's we have the context. We've been working with some of our clients for 5, 10, even 15 years. So we, know their industry, we know their competitors and we know what's important to them. So being able to bring in the value and that partnership and that understanding of their business.
think is the value added on top of the AI that they can't see from just the one study.
Jess Gaedeke (03:54)
partnered with a lot of clients, one being Opella. know, Jennifer spoke with us at Quirks New year about this are really intentionally pursuing transformation. in those times of transformation, how do we make sure that leaders really stay aligned when their strategies and their structures that are still being built? Like, how do we do that?
Patricia King (04:12)
Well, that's an interesting I read that question, the thought that came to my mind is transformation is people think it's going to be fast and that we're going to put processes and structures in place and everyone's going to jump on board and everyone's going to follow them. And no matter if it's a large organization like Opella or a smaller company like just want things to move fast. And I think when we think about transformation, we have to think about
there's gonna be a lot of And being able to find the right person to lead that and the right partners to get on board and go with you on your whole entire journey is the I about early transformation, maybe not everything's completely that the researchers within your company, the brand strategists, not everyone's gonna necessarily be in the same place, same time.
going to have different processes. going to take a lot of work to get them on board, lot of trust, a lot of and a lot of support. So I think when we think about transformation, especially agile transformation, the place that many, partners are in now, knowing that we want to be agile and faster, but it might have to slow down before we get there.
Jess Gaedeke (05:20)
Yeah, sometimes you have to, what is it?
walk to run or whatever the saying is, I think that that's so true for agile transformation. And you know what I am thinking about? As you know, year, or maybe it was in 24, we lost a major global RFP for an agile program, which still really hurts, right? what's really interesting about that is they still have not gotten that program up off the ground, ⁓ which is telling, you know? so it is something where you need to have the right people in place to
Patricia King (05:35)
Mm-hmm.
Yeah.
Jess Gaedeke (05:50)
do the right level of I think deploying that program for it to be adopted but it's an ongoing hustle right have to make sure that users are engaged you need to make sure that the right stakeholders have the right success measures in place there's so many moving parts that's one of the things I think we tend to do pretty well at DIG I think that's why clients really love to bring us those opportunities so who knows that client that turned us down they might come back.
They might come back calling up. Yeah, like, wake,
Patricia King (06:14)
You're hoping they hear this right now, aren't you? No,
and I think that at DIG, one of the big parts of transformation is being able to walk a little bit slow before you run, being flexible. And I would say, not necessarily as a sales pitch, but the fact that we do have the team we have in place, the support to be able to all of those teams that are different games at different times in many ways, they have the support to get them there regardless of what they need.
to become more agile because a lot of them, even those first few projects might not necessarily feel agile to them when it's a huge learning curve.
Jess Gaedeke (06:49)
you're right, exactly. you work across a lot of our enterprise clients. What do they increasingly want from Insights partners? Where do you think some of the gaps are?
Patricia King (06:57)
would say this is where maybe biggest thing that has moved because when you talk to a lot of our partners now and they talk about everyone's using AI, they think they can do a lot of things themselves.
But I would say a lot of the teams are moving faster and they're expecting us to move faster because they're expected to move faster and they have all these tools at their disposal, they can generate their own outputs and they can do their own searches and they can like look at data sets faster and looking at bigger data And I think it's a big realization that, you
They need support from us on how to move faster, but then how to move, I would say strategically, intelligently, not just using the tools for the sake of using them, and then pulling it all together because they have probably bigger expectations on them. And trying to bring that all together, needs a partner that understands how all the tools can be used, how all the different methodologies come together,
identify the patterns in all of that data and make it useful and not just have outputs, but have outcomes that they can use to help make better decisions.
Jess Gaedeke (08:01)
Ooh, that's good. Not just outputs, but outcomes. That's very good. And I think that is part of the reason that we observing this migration moment for clients, right? Because they do have this pressure to go faster, do things in a more efficient way, but they can't give up the strategic depth. I mean, that's the trade-off that they simply cannot make. So I I expect clients to become more demanding in that way, right? It's what the industry is telling them to do, which we're here for
Patricia King (08:04)
Yeah.
And I think one
of the things they want, a term I've used many times, is strategic courage. I use that, that comes from a qualitative background because with quantitative, you often see a table, some quantum researchers will disagree with me, but you see a table and here's what the table's telling you. 600 people did this survey, thousand people did this survey, and some said yes and some said I always say in qual, you you talk to 30 people, you saw their faces, you had a conversation and only 12 people said something.
have to have the strategic courage to say, this is what I think the recommendation is. This is why it's important to your business. And this is why I'm giving you the I'm giving you. And I think right now, lot of researchers again, are in the situation. There's a lot of self-serve DIY AI. They they're expected to do a lot on their own, probably more than ever. And they need the support and the knowledge and the POV from us that strategic courage to put the right recommendations forward.
Jess Gaedeke (09:19)
know, I was at a client a couple of months ago and we were demonstrating one of our newer within Dig One and this feature happens to take a few minutes to develop the deliverable and they said, why does it take a few minutes? Like that should only take 20 seconds. And a fair comment.
and it needs to be put within the context of what is the value of the output that you're getting? What is the outcome that comes from that And can we tie that back to the number of minutes that it takes? Because I do think that the expectation of immediacy is creating some interesting and pulls certain types of deliverables. So I guess it's just a comment on this whole trade-off between
Speed and substance, speed and strategic depth. Sometimes it is going to take a couple minutes, but you're going to get a bunch better answer than if it's immediate. Do you think clients are going to accept that? What's your...
Patricia King (10:09)
I think they last week I always call that the Amazon effect, how none of us want to wait for shipping anymore. And I wanted a pair of sneakers for my vacation, expensive pair of sneakers. And I ordered them on Amazon instead of the ones I the retailer. And I'm not as happy with do the job. Absolutely do the not what I wanted. And I think for clients that I think they'll realize that quickly.
Jess Gaedeke (10:24)
Bye.
Patricia King (10:31)
I think digs always shown that value in that, you have a more complex solution we have in the want to do it right. We'll push back on what we think is too fast, maybe not the right solution for the client and you end up with a better outcome. So I think that there'll be a bit of a pendulum swing, some point you'll realize that, you know, sometimes it's worth waiting for.
Jess Gaedeke (10:53)
There you go.
Okay, any words of wisdom you leave us with here today?
Patricia King (10:57)
well, I was thinking, you know, as I was reading that AI and I know most of this conversation is about speed that's, just the name of the game right now. And we do everything we can to, keep up and give the best solutions. But I think realistically, if you think about where we're going, future of insights is more human. we have a lot more being done effectively, efficiently from AI. we're speeding up, we can do things faster, but now we have more time to think.
So I think that all the pressures that we're seeing to use the computer just gives us a little bit more thinking time. And I don't think that's a bad thing.
Jess Gaedeke (11:29)
Yeah, there you thank you so much for joining me and sharing your perspective. Again, I you and I both really value Kendra a lot. It was a great conversation with her and a great follow up with you. So thank you.
Patricia King (11:39)
Yeah.
All right. Thank you.