In this episode
Daniella Harkins, SVP Product GTM at LiveRamp (NYSE: RAMP), joins Greg Kihlström to cut through AI vendor hype and lay out what enterprise marketing leaders should actually do first. The through-line: don’t chase a flawless AI strategy — start from the business problem, get your data foundation and identity strategy right, and treat identity resolution as more important in the AI era, not less.
Key takeaways
- There is no perfect AI strategy today. If your multi-year AI strategy feels flawless, it’s too early — expect it to change dramatically. Start now, but hold it loosely.
- Start from the business problem, not the technology. Name the challenge, pick one or two use cases, and test into them. Don’t get lost in tech-speak.
- Your data foundation is the prerequisite, not a nice-to-have. AI lets you decide faster — but on a weak data foundation you just make the wrong decisions faster.
- Identity matters more, not less. “Email is good enough” is a blind spot. A real identity strategy — with all your data connected to it — is what protects both marketing ROI and consumer trust.
- Nothing is standardized yet, so tolerate duplicated work. Let teams build and experiment, even overlapping agents. The learning compounds; the space is nascent.
- AI moves marketing leaders from tactics to strategy. Automating tactical work frees leaders to guide strategy, get fluent in data, and show marketing’s broader business impact.
- The measurement unlock is cross-channel, real-time optimization — turning measurement into action, with reach/frequency visibility across publishers, not just within them.
- Three steps to prepare your team: (1) get closer to your org’s data strategy; (2) pick a few AI/agent partnerships and lean in; (3) give every team member one concrete task using an AI tool — specificity accelerates adoption.
Chapters
- 01:47 — The AI hype problem: distinguishing innovation from marketing spin
- 03:45 — Daniella’s role at LiveRamp
- 04:56 — Cutting through the noise: why there’s no perfect AI strategy yet
- 07:28 — Trust and transparency: the data foundation comes first
- 09:13 — Demystifying and simplifying AI for marketing teams
- 15:18 — Data readiness and why identity matters more, not less
- 17:57 — Real-time optimization and cross-channel measurement
- 20:40 — How AI reshapes the senior marketing leader’s role
- 23:38 — Three practical steps to prepare
- 25:38 — Closing: one year out, and staying agile
Why there’s no such thing as a perfect AI strategy yet
Leaders feel pressure to have an AI strategy, and that pressure drives rushed, confused decisions — even paralysis. Harkins’ advice: if you think you have a flawless, multi-year AI strategy today, you’re being dishonest with yourself; it’s too early and it will change. Start from the business challenges you’re solving, pick one or two high-value use cases, and test into them. And lean on partners — you don’t have to do it alone.
Why the data foundation is the prerequisite for AI
Speed without the right data foundation just produces wrong decisions faster. Before building an AI strategy, validate the foundation: the data infrastructure, the privacy posture, and the organization’s stance on the ethical use of data. That foundation is what makes personalization trustworthy rather than reckless.
Why identity matters more, not less
Harkins pushes back directly on the industry narrative that identity no longer matters. Email addresses and similar signals are a component of identity, not a substitute for a strategy. Real people carry many emails, devices, and touchpoints; treating “good enough” as the plan is a blind spot that erodes both marketing ROI and consumer trust over time.
How AI shifts marketers from tactics to strategy
The real unlock is time. Automating tactical and repeatable work lets marketing leaders move from campaign-level firefighting to strategy — understanding data, guiding the business, and demonstrating marketing’s impact across the organization.
The measurement unlock: cross-channel optimization in real time
What Harkins is most excited about is turning measurement into action: near-real-time optimization driven by AI and agents, and cross-channel reach/frequency visibility across major publishers rather than siloed within each one.
Three practical steps to prepare your team
- Get closer to your organization’s data and data strategy — it unlocks everything downstream.
- Identify a few partnerships driving AI and agent development, and lean in to learn from them.
- Give every person on your team one concrete task to complete with an AI tool. Specificity, more than enthusiasm, drives adoption.
FAQ
How can enterprise leaders cut through AI hype? Start from the business problem, choose one or two use cases, and lean on partners. Accept that the strategy will evolve.
Is it possible to have a complete AI strategy right now? No. If it feels flawless, it’s too early — expect it to change dramatically.
What’s the biggest prerequisite for AI success in marketing? A solid data foundation. Faster decisions built on bad data are still the wrong decisions.
Does identity resolution still matter in the AI era? More than ever. “Email is good enough” is a blind spot that hurts both ROI and consumer trust.
How does AI change the role of a senior marketing leader? It shifts them from tactical execution toward strategy, data fluency, and proving business impact.
About Daniella Harkins
Daniella Harkins is SVP, Product Go To Market at LiveRamp (NYSE: RAMP), the leading data collaboration platform. She works at the intersection of product and commercial teams to drive the structure and transformation of the two functions team toward the next evolution — empowering them to achieve max productivity. She holds a deep understanding of the market and field and translating it into GTM activities such as pricing, product stories, salesplays, and launches. Daniella holds a Bachelor of Arts in French from Temple University and an MBA from St. John’s University Rome, and speaks French and Italian.
Daniella Harkins on LinkedIn: https://www.linkedin.com/in/dharkins/
Resources
LiveRamp: https://www.liveramp.com
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Transcript
[00:01:47] Greg Kihlström: Hi, I’m Greg Kihlström, host of The Agile Brand, and here’s a question for you. With every vendor claiming that their platform is a revolutionary AI silver bullet, how do enterprise leaders distinguish between genuine innovation and what’s essentially just marketing hype? Agility requires a clear-eyed strategy for adopting new technologies, especially with AI, focusing on practical outcomes over speculative promises. We’re gonna discuss how to demystify AI for the broader marketing organization so your teams can actually use it, moving beyond theory to discuss tangible applications that drive
[00:02:32] Greg Kihlström: efficiency and better customer experiences, and why a solid foundation isn’t just important for AI, but is the absolute prerequisite for its success. To help me discuss this topic, I’d like to welcome Daniella Harkins, SVP Product GTM at LiveRamp. Daniella, welcome to the show.
[00:03:32] Daniella Harkins: Thank you so much, Greg, for having me. I’m excited to be here.
[00:03:35] Greg Kihlström: Yeah, looking forward to talking about this with you. Definitely, definitely timely topics here. So, uh, before we dive in, though, why don’t you give a little background on yourself and your role at LiveRamp?
[00:03:45] Daniella Harkins: Yeah, absolutely. So I’ve been at LiveRamp for about eight years, but previous to that, I have really lived between product, commercial, as well as marketing, uh, always really in the data and technology space. But, uh, for the past eight years, as I said, I’ve been at LiveRamp. What’s really exciting about what I’ve been doing for actually just over three years now is leading a product go-to-market team, which is really focused on how do we better commercialize our solutions and make sure that they are solving the business needs that our clients and- and business challenges that our clients have? And so today, I lead product marketing, I lead our solutions marketing functions and our industry functions. I ut- lead our pricing transformation as well as all of the comm- the operational components of commercializing
[00:04:30] Daniella Harkins: our products and our solutions. So it’s an exciting role. And in this role, I literally live between marketing, I live between product and, uh, commercial. Obviously, always focused on the end needs of our clients. So it’s an exciting role.
[00:04:45] Greg Kihlström: Yeah, yeah, that’s- that’s- that’s definitely, uh… (laughs) And I- we’re gonna talk a little bit about all of that probably today,
[00:04:56] Greg Kihlström: So let’s dive in here, and I wanna s- we’re gonna talk about a few things, but I wanna start with, uh, this idea of, from- from a strategic standpoint, you know, a lot of leaders are feeling pressure to have an AI strategy right now, certainly, you know, it’s- we talk about AI all the time on the show, read about it all the time, it’s certainly, uh, everywhere at this point, but that pressure to have a- a- an AI strategy can often lead to making rushed decisions.
[00:05:25] Daniella Harkins: Yeah.
[00:05:26] Greg Kihlström: How do you… uh, how would you advise leaders to help cut through some of the noise, ’cause there’s a lot of-
[00:05:32] Daniella Harkins: Yeah.
[00:05:32] Greg Kihlström: … of noise, you know. There’s- there’s great things too, but there’s- there’s a lot of noise and hype. How do you advise people to cut through that and establish a clear, authentic vision for AI that aligns with actual business goals, not just, kind of, chasing trends?
[00:05:46] Daniella Harkins: Yeah, it’s a great question because I think it, not only can you kinda do this, if you’re doing this prematurely, it can lead to, um, changes or it can lead to challenges, but it also leads to a lot of confusion. And oftentimes, sometimes I see, like, we have clients-
[00:06:02] Daniella Harkins: … I have, I have partners where you almost get paralyzed with fear because you’re not exactly sure what to do or how to start. And I think, like, the first thing I would say is if anybody thinks that they are gonna have a perfect AI strategy today and, like, like, a flawless AI strategy, it’s too early. It’s too premature.
[00:06:20] Daniella Harkins: And if you think you do, chances are you don’t, and it’s going to change dramatically. And so instead of thinking about it across a multi-year strate- uh, uh, really building out the strategy across multiple years, I’m always, I say, “Listen, first and foremost, think about the business challenges that you’re trying to solve. Don’t get lost in the technology speak.” Everybody wants to jump right to the how and right to the technology, but instead, I would say, what is it that we’re… like, what is it we’re trying to solve for? Stay focused on that and pick one or two use cases that you can then start to test into, and you don’t have to do it alone. There are partners out there. Lean into your partners. You’re probably gonna hear me say that a couple of times because
[00:07:05] Daniella Harkins: it’s so critical to find those partners that can help you do that.
[00:07:09] Daniella Harkins: So sum- to, to sum it up, you’re not gonna have the perfect AI strategy today. Again, if you do, it’s gonna change dramatically, and you’re probably kinda, you know, you’re, you’re not being honest with yourself or with your organization and really figuring out those use cases that have maximum value to you and starting there.
[00:07:28] Greg Kihlström: Yeah. Yeah. Well, and, and another key component of not simply rushing to roll stuff out, a- a- again, admits the, the pressure to do so, is just maintaining that customer relationship, you know?
[00:07:43] Greg Kihlström: That trust is such a major component of that, that relationship. And so, you know, in the rush to do this, and I, I know this, I’m, you know… I talk with a lot (laughs) of companies they’re, they’re trying to roll out, they see the promise of AI-driven personalization-
[00:07:58] Greg Kihlström: … other things like that, but, you know, a- as they do these things, wha- what would you say some of the key principles are for maintaining transparency and trust while-
[00:08:10] Greg Kihlström: … again, taking advantage of, of some of these amazing technologies?
[00:08:13] Daniella Harkins: Yeah. Absolutely. I oftentimes say, you know, like, the technology and the AI and the capabilities that AI brings to us around efficiency and speed and decisioning and all the amazing things that are, that are, that we’re working through and learning with it… If you don’t have the right data foundation, you know, you might be making decisions faster, but you’re ma- you’re not making necessarily the right decisions or the right decisions for your customers.
[00:08:40] Daniella Harkins: And so to me, the pri- the first thing you have to really do is think about, do I have the right data foundation? What is my data infrastructure? And then what are… You talk about privacy, and you talk about transparency, but what is really my, my organization’s stance on the ethical use of data and how I can use that data? And so I think that is fundamentally the most important thing, that as you start to build your AI strategy, that you need to validate that you have the right foundation.
[00:09:13] Greg Kihlström: Yeah. Yeah. And I think, um, to then act on, you know, to ge- to get a little more tactical, I guess, here as well-
[00:09:22] Greg Kihlström: … AI tools are maturing, right? Let’s just-
[00:09:25] Daniella Harkins: They sure are.
[00:09:25] Greg Kihlström: … let’s just put it that way, and so, you know (laughs) there-there are some that are, that are a little further along that maturity curve, but they’re, you know, they often come with, you know, anything from complex interfaces to needing to know a lot of things about jargon and protocols and, and all those kinds of things.
[00:09:41] Daniella Harkins: Yeah.
[00:09:42] Greg Kihlström: Um, what are some of the most effective ways that you’ve seen to standardize and simplify AI for marketing teams so they can really focus and, again, take advantage of all, all this… We don’t wanna reduce the, the functionality but to make it more seamless to use?
[00:09:59] Daniella Harkins: Absolutely. I mean, just like we can get lost in the technology, our industry is famous for all of our acronyms and the jargon and all of that.
[00:10:08] Greg Kihlström: (laughs) Right.
[00:10:08] Daniella Harkins: And, you know, when I talk about- like, leaning into your partners, lean into them and ask questions. And a- again, don’t get lost in the technology. Don’t get lost in the jargons. Um, and I think that’s really critical. I do think, you know, some of the things that I’ve personally done is, you know, I went through and said, “I’m gonna establish some best practices for my organization based on what I know and the research that I’ve done, and then I’m gonna solicit feedback, so at least we have a baseline to start with.” I then also went out and spoke to different people on my team and found someone that really acts as our AI expert. That helps when you don’t necessarily have the confidence to go out and maybe talk to your partners or where you feel like people are talking around you or you’re not understanding the conversation.
[00:10:55] Daniella Harkins: Having someone you trust on the team, I think, is critical. Um, I said lean into your partners. Also, there are highly repeatable operational tasks that can be automated and that can really free up your team’s time. Figure out what some of those things are. If you’re on the media side, you might wanna lean into media optimization, or if you’re on the data side, it might be modeling. It, there’s so many different areas that you could kind of lean into. Um, I think that’s critical. And then I s- start small. Don’t be afraid. And I go back to, like, asking the questions and not losing sight of what your end goal is, because once you do that, it, it, at least for me, it becomes
[00:11:41] Daniella Harkins: this, this conver- it becomes a swirling conversation of sometimes things I don’t understand. And I’m like, “Wait a second, are we solving this business problem or not?”
[00:11:51] Daniella Harkins: Um, and then the last thing I would say to everybody is nothing is standard yet. Nothing is standard yet. And be okay with people duplicating work. And I’ll give you an example that we’re faced with today, um, within our own organization. We’re doing a lot of AI transformation work internally across all of our different, uh, functions of the business, and somebody asked a question and said-
[00:12:15] Daniella Harkins: … “How do we know if we’re building an agent, how do we know somebody else hasn’t built an agent?” And my answer was, “It doesn’t matter.” We’re going to be learning together. We’re potentially going to be doing work that somebody else has done, but it’s so important for us all to test it out, to get our hands dirty, and to not worry about what other, what other people have done, but now start to learn that from other people. And so the idea of standardization, we’re not there yet.
[00:12:46] Daniella Harkins: Not even close.
[00:12:46] Greg Kihlström: And I think that’s, that’s a valuable thing to embrace as opposed to, you know, uh, the, probably to be transparent about, right? If, uh, because, you know, if there are different people working on different things, to your point, they can learn from one another, and there isn’t one right way to do this stuff-
[00:13:07] Daniella Harkins: There isn’t one right way.
[00:13:08] Daniella Harkins: There’s not one right tool. We’re all learning and changing and evolving right now as we go. It’s all nascent. It’s exciting, but it’s nascent.
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[00:15:18] Greg Kihlström: Well, so let, let’s talk a little bit about, um, how we measure success, and certainly, you know, in, in, a lot of these conversations, you know, it often comes up that AI is only as good as the data that it’s trained on, so-
[00:15:31] Greg Kihlström: … garbage in, garbage out. Um, w- what’s a common blind spot that you’re seeing that enterprise teams can make when it comes to being ready, you know, data readiness for AI, and-how does a company make sure that it’s, it’s, you know, tapping the right signals?
[00:15:48] Daniella Harkins: Yeah. I think there’s two areas that I would say. First of all, it is the abili-… One of the blind spots, I think people do a good job of, let’s say, ingesting data and trying to connect it internally, but then there’s so many other signals, there’s so many other partners that you wanna be able to connect that data to. So that becomes massively critical to any of this. The other big thing that I would say is I am hearing over and over again in the industry that identity just doesn’t matter as much anymore. And I actually think that that is a false narrative, because I think it matters more than any, uh, more than any time in the, in the past. I think it’s more critical to running our businesses than we’ve, it’s ever been. And I think part of it is because there’s an Easy Enough button. You can
[00:16:33] Daniella Harkins: use email addresses. You can use things like that, which are absolutely a component of identity. But I think if you walk into it saying, “I’m just gonna do what’s good enough, I’m gonna do this because it’s easy, and I’m not gonna worry about really building an identity strategy, and then connecting all of my data to that identity strategy,” regardless of who your identity partner is, I think that is a blind spot, and I think it is something that will hurt organizations longer term as they, one, need to drive effective marketing strategies that have a return on investment. But equally as important is, is ensuring that they have consumer trust. And I have multiple different email addresses. I have multiple different touch points. I have multiple different cell phone numbers. Uh,
[00:17:18] Daniella Harkins: I’ve, I’ve moved around. There are all of these different dynamics that are really important to understand about me as a human to make sure that you can deliver that personalized, that experience that I want as a consumer.
[00:17:30] Greg Kihlström: Yeah, yeah. I mean, con- consumers are not on one device, on one channel-
[00:17:36] Daniella Harkins: Yeah.
[00:17:36] Greg Kihlström: … on, you know, uh, and that, yeah, that definitely, um, I, I agree with you (laughs) there. It’s, it’s, uh, to reduce it to an email or, you know, I, I don’t even, I lost track of how many emails I actually have. So, um-
[00:17:50] Greg Kihlström: … you know, trying to track me on that would be, um, not, uh, n- not, not the right approach. (laughs)
[00:17:55] Daniella Harkins: Not accurate, right. Yeah, exactly.
[00:17:57] Greg Kihlström: Yeah. So, uh, you know, in, in other terms of measurement… You know, whether we’re talking about real-time optimization or, or other things, certainly, you know, and to, to, to the last thread of conversation, um, you know, attribution becomes difficult, not only when-you don’t have a strong and cent- centralized identity, but, you know, what, what should leaders be paying attention to that, uh, is kinda potentially opened up when you can have-
[00:18:27] Daniella Harkins: Yeah.
[00:18:27] Greg Kihlström: … real-time optimization and, and, uh, ideally better attribution?
[00:18:32] Daniella Harkins: Yeah. I, I think from a… I think one of the things that AI does really well, or that AI will empower, um, is the ability to turn measurement, to your point, Craig, into, uh, the ability to optimize. So it’s not just about taking those insights and learning from them and applying them to future campaigns, but it’s actually being able to take audience information, to take biddeding in- inf- eh, bidding information, whatever the case is, creative, uh, measurement and information, and then be able to turn that into just a more seamless, actionable, uh, process, so that we don’t have the delays, we don’t ha- h- you know, that we’ve had in the past. So I think that’s incredibly exciting, right? It’s just the actionability
[00:19:19] Daniella Harkins: and the speed with which AI and now agents are making decisions to now optimize campaigns based off of measurement. I think that’s incredibly exciting. The other thing I think that I get excited about is, I think we’ve been moving away from a lot of the, you know, um, the, the older models around measurement, and obviously have had, uh, I think over the last few years, a much richer, better way of measuring. But I think what AI is now unlocking beyond, um, some of our attribution models and, uh, medium ex- and all of that is the ability to do better cross-channel. And so, building the partnerships
[00:20:04] Daniella Harkins: so that you can have visibility into your reach and frequency across your different major publishers, not just looking at within publishers. And so, I think, to me, what I get most excited about, it’s the intera- it’s, it’s really the intersection of the cross-channel opportunities that exist that we can apply our attribution models on, and we can do all of that with now the ability to really optimize in a much more frequent and fast, you know, a faster way than we’ve done in the past. And I think that is what I get excited about around measurement for… and what, what’s being unlocked.
[00:20:40] Greg Kihlström: Yeah, yeah. Well, and, and in that, to that general thread, I mean, looking, looking towards the future a bit, with all of the automation that’s, that’s unlocked here, uh, you know, I, I definitely take your point as far as we are… I know I am personally in the experimentation mode in-AI, um, mu- much of (laughs) much of m- more of my days than I care to admit some days, but, but we’re still automating a lot more than we, than we have been previously-and we’re going to be o- over the months and, and years to come. What does this do? You know, how does this change a, a senior marketing leader’s role over the next few years? You know, what, what are the skills that become important when so many things that, you know, are, are automated, or at least partially automated?
[00:21:29] Daniella Harkins: I, in the most simplistic way, I, I was, I was writing something the other day, and we were, eh, you know, almost like a roadmap, and one of the things I said was, “This is powering us and me to go from tactics to strategy, and it’s giving me more time-“
[00:21:45] Greg Kihlström: Mm-hmm.
[00:21:45] Daniella Harkins: “… to think, to learn, and spend more time really kind of guiding the strategy and aligning the business.” And I think that is really critical. As marketers, we oftentimes get so focused on what our ROI is, or we get campaign-focused, and now really being able to unlock the impact that marketing can have across the organization I think is really, really critical, and we just don’t give ourselves enough time to do it. And so, just more broadly, being able to go from that tactical view of something, and as much as we like to say, as senior leaders, “We’re spending our time on strategy,” none of us are spending as much time on strategy as we want to.
[00:22:25] Greg Kihlström: (laughs) Right.
[00:22:25] Daniella Harkins: Right? It’s just the nature of what we’re doing. I think it also… I, I think it also starts to unlock opportunities for marketers to really understand more around consumer data and the use of data and things like that, because that’s then gonna be able to drive and becomes their foundation for that kind of longer-term strategy. So I think it’s a massive opportunity. I think it’s a massive opportunity for us to remove the blinders, to learn the different aspects of the business, and then also kind of not prove, but also share the broader impact that our organization is having on, um, on the business. I also think we need to collectively challenge ourselves to do more,
[00:23:13] Daniella Harkins: and my, my hope is that-
[00:23:16] Greg Kihlström: Mm-hmm.
[00:23:16] Daniella Harkins: … with now tools that will help us, um, do a lot of the tactical work, automate a lot of the work, help us make decisions faster, that it will also allow us time to learn and challenge ourselves more.
[00:23:31] Greg Kihlström: Yeah, yeah. I lo- I love that. So, you know, for those, for those marketing leaders out there listening, what would you-
[00:23:38] Greg Kihlström: … what would you recommend as a, as a step, uh, you know, obviously every org’s different, and, and, and-all the, all the, all that, but, you know, what’s, what’s a practical step they could take to, to prepare for this?
[00:23:49] Daniella Harkins: Yeah. I would say there’s probably three things, and I’ve said some of this, uh, earlier. I’ve actually probably said a lot of-
[00:23:57] Greg Kihlström: Sure.
[00:23:57] Daniella Harkins: … this earlier. But one is, challenge yourself to understand more about your, your organization’s data, data strate- and data strategy, because that’s gonna then unlock more of what you can do. And some marketers have a lot of access to data. Some marketers have more limited access to data. But there’s always more that we can do and learn and really understand more about that foundation. That’s one. Two- Figure out some key partnerships that are driving AI, that are driving the development of agents, that are coming up with new ideas to help you accelerate those. There’s gonna be a lot knocking on your door. Figure out a couple of them, and lean into them, and learn from them. And then, uh, I think
[00:24:42] Daniella Harkins: the, the last thing I would do is give everybody one task on your team to complete something using an AI tool, whether that’s building an agent, whether that is using, uh, Cloud or ChatGPT to better inform something, whether that’s building gems in Gemini. Whatever the case is, think about … Or, whether that is leaning in to different partners to help do, you know, AI-based modeling for data. Whatever the case is, pick something and have everybody complete a task. Because what I have found in trying to drive the ch- the transformation within my own organization is that being specific and helping them, one, helping everybody’s confidence, but being specific on what we want them to do has
[00:25:27] Daniella Harkins: really helped accelerate the adoption of AI across my organization.
[00:25:34] Greg Kihlström: Yeah, yeah, love that. Well, Daniela, thanks so much for joining today and, and-
[00:25:38] Daniella Harkins: Of course.
[00:25:38] Greg Kihlström: … sharing all this. I got a couple questions for you as we, as we wrap up here.
[00:25:43] Greg Kihlström: Uh, the first one, um, if we were having this interview one year from today, what is one thing that we would definitely be talking about?
[00:25:51] Daniella Harkins: I hope, I sincerely hope, that we are sitting here talking about how agents have tran- how we’ve had a proliferation of agents and they are transforming how we, the media ecosystem is run and how we as marketers are running our business. I think what we will be talking about, yes, that’ll be a component of the conversation, but this is not gonna happen overnight, and we are on a long journey here. I think, instead, there will be a proliferation of agents and like everything within our industry, we are going to now have to start to figure out, who are the partners? How do we use them? And I think we’ll be in a place of opportunity, still confusion.
[00:26:36] Daniella Harkins: We’ll have a little bit more clarity, but I do think the agentic workflows that are being built are incredibly exciting, but I do think that we will be having a conversation with the sh- about the sheer number of agents that are out there and what they’re doing.
[00:26:51] Greg Kihlström: Yeah, yeah. Well, we’ll have to, we’ll have to chat in a year to- talk through that.
[00:26:58] Greg Kihlström: Yeah, yeah, definitely. And, uh, la- last question for you, um, what do you do to stay agile in your role, and how do you find a way to do it consistently?
[00:27:06] Daniella Harkins: Yeah. Um, I don’t think it’s always easy to do it, Greg, consistently. You’d probably agree with me on that.
[00:27:14] Greg Kihlström: Yeah, yeah.
[00:27:14] Daniella Harkins: I think there are a couple of things that are core to me, right? When I think about agility, I think about a couple of things. One is, I constantly, I’m curious, and I’m constantly asking questions surrounding myself with people that are maybe smarter than me or maybe just know different things than I do or are stronger in different areas, because I think that’s really important, right? I think it’s important to stay curious. I think it’s important to ask the questions, but I think it’s important to surround yourself with people that are gonna push you to be better and to challenge you with different thought. So that, I think, is really important. The other piece of it is, and I’m running a lot of, I’m running a big transformation project right now, and as you can imagine, like, organizational inertia, you know, is really difficult when you’re working in larger organizations and it can kill, you know, progress and momentum. And so, I push.
I push, and I push even when I don’t have all the answers. I push even when I’m not sure, and I never wait for perfection. And I’m always looking at, what’s the v- immediate next step? Yes, I have a long-term plan, but unless we hit the next milestone or that next step, none of these other things matter. And so, it’s, for me, it’s really about pushing and being challenged that really drives at least the way that I approach the agility in my role and, and in my world.
