[00:00:00] Trisha Price: If you build software or lead people who do, then you're in the right place. This is Hard Calls. Real Decisions, real leaders, real outcomes.

Hi everyone. I am Trisha Price, and welcome back to Hard Calls, the podcast where we bring on the best product leaders from across the globe to talk about those moments - the decisions that matter, the hard calls.

Today we have on the show the Chief Product Officer at Morgan Stanley at Work, Mark Mitchell. With over 15 years of experience in product management and technology, Mark has a deep understanding of the evolving needs of customers and the power of technology to transform their lives.

Mark's expertise lies in building high performance product teams, fostering a culture of innovation and leveraging data-driven insights to deliver exceptional customer experiences. Welcome to the show, Mark.

Mark Mitchell: Thanks for having me, Trisha How are you?

Trisha Price: Great. I'm super [00:01:00] excited to have you here. Mark and I have been working together for about four years. Mark's been a longtime Pendo customer and we've gotten to know each other through that, and and I've just been so impressed, Mark, with the way you lead your teams, the way you think about products, so I'm super excited for this conversation today.

Mark Mitchell: No, thank you. The feeling's mutual.

Trisha Price: Mark, this is the Hard Calls podcast.

So I like to start every one of these episodes where you get to talk about a hard call that you've had to make. So tell us, looking back over your career, or even just the past year, what's one really hard call that you've had to make and what made it so challenging?

Mark Mitchell: I feel like we're jumping in with the hardest part of the entire interview right off the bat.

Of course.

Trisha Price: Why wouldn't we? Why wouldn't we?

Mark Mitchell: I think I think there's a, so as I was thinking about this, there's a couple different answers to this, but I think what I would say is one of the hardest things for our business and for my role almost probably once a year, is we engage in a sales conversation with a really large client of ours and what we ultimately figure out after getting [00:02:00] into that sales conversation with this prospect is that we may not be a great fit for each other. Whether that's on their side or on our side, or maybe a little bit of both and it's this really tough decision that you have to like, ultimately come to, to realize as excited as we are and as long as we've worked on this thing, there just may not be a go forward path here for us. And it's super difficult and always, always, a hard kind of call to ultimately make, but that occurs about once every year or every other year. We get into one of those. We had one of those in the last couple of months, which is why it's top of mind for me at the moment.

Trisha Price: I am so glad you talked about that, and I know that's gonna probably weave through various conversations that we have today and man, that takes such discipline to be able to acknowledge that and, and I'm glad you brought that up because all of us as product leaders, there's always pressure for revenue, there's always pressure for customer happiness, and that's just such a hard and [00:03:00] difficult decision to make.

Mark Mitchell: Yeah, when you look when you look at those situations and it's it's kind of, it's kind of the again, it's, it's more of an exaggerated version of what we do every day, right? It's, you look at the situation and you say, the effort that we're going to have to put out, right?

Whether that's cost or development time or product team time, whatever, however you wanna think of it is gonna be huge in this situation, let's just say. And, and then you start to pencil out, okay, so how does that look over the longer term for revenue and for this and for that, and all the different dynamic parts of kind of like how these things fit together.

And sadly, sometimes you just come to this conclusion that it just doesn't really, it doesn't really pencil and that, the upstream swim to build the things that this particular client's gonna need, find ways to do that, that in a way that they add value to other customers and other [00:04:00] clients.

Like, like that story just doesn't it, it ultimately just doesn't tell, you know. Yeah.

Trisha Price: Which isn't good for either of you. Right. It's not good for you, but it's also not good for the customer, right?

Mark Mitchell: That's right. That's right. That's right. And most, we find most of our best customers and the best relationships we have. there's this mutual investment in, Hey, we, we have some particular functionality that we need for us, but we wanna work with you and commit to building that in a way that can be leveraged by all clients. It's ultimately better for everybody and that's, that's the best case scenario.

Trisha Price: Yeah. Well, I wanna get into that a little bit more and think about, and talk about how you make those kinds of decisions. But before we do, maybe just share with our listeners for a minute, who is Morgan Stanley at Work? What you do and, and what makes you a leader in your industry?

Mark Mitchell: Yeah. Yeah. Perfect.

Yeah. Morgan Stanley at Work is really the, the market leader, in, in equity comp plan [00:05:00] administration, right? So if you work at a large company that offers stock as part of your compensation, those plans, while on the surface are pretty simple, issuing stock to employees on an annual or semi-annual basis on the surface, fairly simple in reality, can get quite complex to administer. There's a lot of tax implications, there's a lot of global rules and laws and regulations and things that need to all get accounted for. So our platforms, allow companies to issue stock to their employees in a relatively seamless way, those employees then receive those shares and can sell them across our platforms. So that's the business in a nutshell. We, we serve, about 3000 large companies. We tend to operate with, with mostly public, a chunk of private companies usually US-based, brand names that you know across [00:06:00] all of the key sectors of the economy.

And we fit within Morgan Stanley more broadly. Of course, Morgan Stanley offers a lot more services than, than just that, but that's the area of, of platforms that I lead up.

Trisha Price: Well, Mark, I just logged into one of your products yesterday, to use it and, and it's a great tool and has provided a lot of value for one of the organizations I'm involved with as a board member.

So I can speak personally, on the complexity that you solve and the value you bring, to these organizations.

Mark Mitchell: No, I appreciate it. Thank you.

Trisha Price: So Mark, coming back to the hard call that you talked about and, and making those difficult decisions around specific customer asks and nuances, tell me what factors do you consider when deciding how to balance your product investments?

Mark Mitchell: Yeah, it's it's, I always think of this this like multi-variate kind of math equation a little bit, you know?

I'm a math major.

Trisha Price: Mark, so nobody [00:07:00] loves there. Go, yeah, nobody loves this more than me. Let's go, let's go.

Mark Mitchell: And I say that 'cause it's like, it's, it's it, there's not one single lever that matters more than another, you know?

So I think the first is there's all I, I think of it as like, what is the impact that this particular thing is gonna have, right? So that's the first measurement that I like to think about. And the thing that I kind of push the team on is what is the impact this thing is gonna have? So, in other words, like how wide is the radius of this particular ask gonna have?

And so the ones that jump to the forefront is, okay, this is a small ask and a small radius, right? So that kind of is one bucket of, okay, it's, it's not gonna impact many customers besides this particular kind of niche need, but it's really small. So those are relatively easy to kind of sort through, you know.

Then the next, the next group are, okay, this one's gonna be really big, but the impact is gonna be super massive as well, right? It's something that will [00:08:00] make every client more successful, it'll speed up processes, it'll reduce risk, it'll do this, it'll do that. Those, again, are generally pretty easy 'cause you say, it's easy to justify the time, the effort, they expense, and all of those things.

And this one, those are easy. So those are the two easy ones. Right now, the hard ones, are the ones where it's massive size, small impact, right? Those are the ones that you really have to spend time kind of wrestling with, because, there's gonna be a big investment and there's not gonna be a big impact wider than this specific need that's being addressed here.

So we have to take those really carefully. When you start to get into looking at those, that's when it can get it can get complicated. You start to weigh, okay, so this particular client is how big, how many participants do they have as part of the plan? So if this is something that's gonna touch all of their employees, how many do we have there?

What are the [00:09:00] sizes of the plan and what, how does that translate through to some of the KPIs and the revenue metrics and the other things that are downstream for us? So there's really no simple answer, but what I will say is the, the goal is to have that functionality impact as many clients or as many of their plan participants as possible.

That's the goal really, almost every single time and if we can achieve that, generally speaking, almost regardless of cost, we know we're heading down the right the right path.

Trisha Price: And so is that a big part of how you measure the success of your investments is how many people the feature you deliver impacts or how many use it?

Like how do you think about success once you've shipped a feature?

Mark Mitchell: Yeah. It tends, it tends to come down to adoption. Adoption is a really key metric for us because if we're building something that again, really helps one customer really, really well. That's great. But [00:10:00] the adoption, obviously there is super, super di minimis and it's good to make one person happy, but that's always gonna be a tough one to justify, you know?

So, adoption for us is a KPI almost unilaterally, whether that's on the administrative, corporate client side of the platform or something that the individual two-legged employees are using. Adoption is always gonna be really for me, the top metric to track. For almost any investment that we make.

Trisha Price: And so Mark, I I always tell people it's not field of dreams, just 'cause you build it, they don't necessarily come. That's right. So tell me like, when, since adoption is so important to you, obviously step one as you've talked about, is building features that are widely applicable to your user base and your customer base.

But step two, okay, you built something, it's why it's, it's applicable to everybody. What do you do? How do you get adoption of these features?

Mark Mitchell: Yep. And I think that's what separates in some [00:11:00] ways a great product organization, and a great, from a great business, so to speak, right? And so what I mean is you can be a great product organization, but if the business that that product organization sits within is not as effective as the business should be, it's gonna be tough, right?

And so for us, it starts with us making sure that we understand the needs of the customer. Understand the needs of the problem and the problem that we're trying to solve, and spend a lot of time understanding the front side of discovery and planning and all the things that go into building a great product.

Then it comes to executing at a really high level on the actual build of the product and the delivery of it, right? Those are the parts I think that my team tends to largely be at the forefront of, but then there's this moment as you start to get close to kind of rollout and delivery where there's a handoff of kind of the activities.

[00:12:00] And we took, tend to take a little bit more of a, I think a passenger role in that. We have to drive it , but it's really the, the client facing teams, the marketing organization, the teams that create all of the learning and education content and all of those things.

It's our job to make sure that all that stuff effectively gets delivered, but truthfully, that lives outside of delivering the, the, the product, right? So, it's important that, that, and then I'd say I just layer over top of that I think it's important that through that entire process that the key stakeholders in the business and the stakeholders of the teams that deliver those things are also bought in on the, the, the product itself, the rationale behind it, and the fact that it's ultimately going to take all of us to be successful.

And all of those groups have to lock arms in that or, or it doesn't work.

Trisha Price: Mark, I love that. I, I often call that whole product.

Mark Mitchell: Yeah, yeah.

Trisha Price: Right, because it's easy for us as product [00:13:00] organizations and engineering organizations to think we're done when the feature, when the code is complete or the feature, has been shipped.

But, if customers don't know how to use it, if salespeople don't know how to sell it, it's not done. It's not there. And it's such a shame to use our precious engineering resources and build something so valuable, but not run through the finish line to make sure that it's available and easy for customers to use and everyone in the organization knows about it.

So I'm really glad you brought that up.

Mark Mitchell: Yeah. Yep, yep. Couldn't agree more. And, and on top of that, I'll say it's it's a loop, right? Because it's also going to be those same teams who a year from now are the ones hopefully coming back and saying, Hey, we think adoption could increase if we add this.

We're hearing this we're meeting with clients and they're saying that, and so I think it's important that it's, it's that closed loop all the time.

Trisha Price: For sure. Mark, how, [00:14:00] how do you. How do you close that loop? Is that a, a natural communication that happens from your product managers to those teams?

Is that like a regular cadence where leadership comes together and they've prepared a summary of what they're seeing? Like how do you make sure that, that that constant iterative feedback loop happens?

Mark Mitchell: Yeah, I, I think of it on two, two dimensions. I think one dimension is. There's the really data-driven aspect of it, which as we obviously use Pendo for, and I think Pendo and, and the data analysis side of it is one part of the equation.

No doubt about it, right? But that is only one side of the coin. The other one is this anecdotal, boots on the ground visiting with customers, engaging with customers directly, and involving as much of my individual product managers [00:15:00] with client facing activities as much as possible.

And so I think, it's easy to say, oh, we're gonna look at the data and just rely on the data and sit in front of our computers all day and do everything from that side. But the reality is you've gotta be out, you've gotta be part of the sales meetings, you've gotta be part of the client meetings.

You've gotta be part of all the different activities that happen, and you've gotta be willing to kind of accept whatever comes from that, which occasionally is not super pleasant, you know? But it is the only way to make sure that you know that you're getting everything out of that engagement that you can.

And then what I like to do is kind of cross over the two things. So, we'll have a conversation with a client. There'll be a lot of anecdotal takeaways from that conversation. They're important, they're meaningful, but they are singular in what they represent. Then I like to take those singular pieces of client feedback and check them against the data to widen out that perspective and validate that singular view with a more [00:16:00] holistic view that represents all the users of the platform.

That is how you cross over both dimensions of the feedback in my opinion.

Trisha Price: I love that. That's, that's a, a great approach because I do think most times when a customer is frustrated with something or even excited about something , it is applicable and other people are feeling it and you can't ignore it and, and wish it away as one noisy customer.

But there are times where while that might be only that customer or two or three customers, there are 10 other issues that you have sitting there that are applicable to more. And so I love thinking about that balance. I'm like you, I won't ignore it, even if only one customer is loud and noisy about it, or talking about it and asking for it.

It's just too important to turn the other way, but I do wanna validate it with data in terms of where do I work [00:17:00] it and how does it fit in my overall priority list? Because as product people, there's a never ending list.

Mark Mitchell: Never ending list. And it's our job to make those micro decisions, right? That switches item eight and nine, you know?

And, and it's gonna take that, that anecdotal blend with data in order to decide that eight and nine need to switch, you know? Yeah,

Trisha Price: When you think about the macro level of, of your investment decisions and, and not so much the switching of eight and nine, which is honestly where the hard part in execution comes in, but more at the big buckets of like, how many teams am I gonna put at this product or this part of the product, or towards this outcome versus how many teams am I gonna put at this?

How, how often do you do that kind of allocation and roadmap strategy, and who do you involve when you do those kinds of big rock decisions?

Mark Mitchell: Yeah. So I think the, I'll start with the [00:18:00] often and then I'll go to who gets involved. I think, I kind of like to think of this, kinda like little framework of nines that I use in, in my head, which is I like to think of everything on this 90 day, nine month and nine year scaling, right? So if you think about things across those time dimensions, it can really help you start to decide like, so from a nine year perspective, like that means we're changing the entire direction of our business.

Right. That's probably not happening from a singular decision we're making today, but we may be tacking gently towards a potentially different direction of the business, overall That's kinda like a nine year plan. Nine months is probably where we spend a lot more of our time that's where you're thinking a little bit more year to year. We often are thinking about what are gonna be some of the big things that we wanna [00:19:00] roll out next year? What are the things we need to wrap up and whatever the end of Q3 to make space for the things that we're talking about blah, blah, blah.

That's like a lot. I think it's where we spend a lot of our time in that kind of nine month zone, you know? And that's probably where most of our organization broadly spends a lot of their time. But then the 90 day thing is also super real because the 90 day thing is where you get into, okay, we just had a really tough meeting with a very large client who has what I'll call effectively an immediate need.

That's kind of like 90 day thinking, right? Like the response to them isn't, we're gonna do the best we can and we'll try to deliver it next year. Right? Like, this doesn't work. That's not, doesn't work. Right? So it's not how enterprise software works. Totally. Now, at the same time, you also have to avoid the trap, though, of falling into making every single decision a 90 day decision.

And it feels like you're never getting anything big done. You're never getting traction across big things. You're constant so you get it. It's really a [00:20:00] balance of those three, they, I think they build on each other. I think when you have really good 90 day decision making. It lends itself and leads towards really good nine month long decision making and a bunch of good nine months lead up to really good nine year long term thinking.

So, to answer the second part of it around the stakeholders, I'm a, a huge believer that, that everyone that works on the team from, from me, all the way down to some of the newest, most junior people have, an extremely close and really, really frequent engaging relationship with the stakeholders of their respective areas so for us, that's usually, their respective development partners, it is their respective business folks, it is their respective legal risk and compliance folks, and then I would throw clients and customers into that bucket as well so it's not super uncommon for someone on the team who's mid-level [00:21:00] to be interfacing with the client directly on things that they're building for them and kind of carry those things all the way through those different groups. And so when it comes to that 90 day, nine month and nine year thinking, like, I, I really expect everyone on the team to think across those dimensions that way and apply that framework to every decision that they're making really every single day with the stakeholders.

Trisha Price: I love that nine, nine, nine that's, that's a really memorable way to think about it. And, a great way to make sure that you're balancing the, the long-term strategy with the short-term needs. That's great. Well, when you think about a nine, nine, nine and it wouldn't be a product discussion if we didn't talk about AI.

And I wanna talk about AI a couple of different ways with you, but, I think for most of us over the last two years at [00:22:00] least, AI has forced us to rethink all three of those nines, most likely in some capacity. Certainly the, the longer of the two nines, that's for sure. So maybe talk to us about how you have thought about AI and AI as a part of your product experience and innovations. You're in a highly regulated industry and an enterprise, but at the same time, we can't turn our heads on AI, so how does, how does that impact you in your nine, nine, nine? Yeah,

Mark Mitchell: We could spend hours on this topic, as you probably can imagine.

So I'll try to be quick about, it.

Trisha Price: I'm excited to hear.

Mark Mitchell: Yeah. Yeah. I think AI is going to truly change everything, you know? I think it is gonna change everything, our personal lives over time. I think it's certainly changing life at work largely, and how [00:23:00] we do our jobs.

I really think everybody's gonna be impacted in some way, in some form. I don't think it's all negative. I think there's actually a lot of positive there. I think in our space specifically, I think we can see really quickly how AI is an incredibly powerful tool for doing feedback analysis, right?

Requirement writing, test, test creation. I mean, obviously all the way through the tech stack for development and and the relationship between those two activities. I think there's a ton of ways that AI can be applied. I've personally used it for some fun personal projects and just learning, experimenting, I've done tons of coding with it and tons of the things I just talked about, and it's, it's clear how powerful it's gonna be.

Now the challenge becomes, as you touched on, okay, so when you move into an enterprise environment, where you've got regulatory oversight and you've got [00:24:00] control processes that need to be adhered to, and all of the realities of the world, at least in a financial services space that I operate in.

It's trickier, it's much trickier. So I can tell you, at Morgan Stanley, some of the ways that we're using it and some of the plan, the ways we're planning to use it. So, currently we have, a large amount of our developers using it, to write code or to check code or to speed up code writing.

In some ways, obviously our code bases are enormous and in some cases decades old, you know? And so I think they're trying to figure out ways to use it so that they can kind of get individual tasks done without having to load this massive, massive code base into the tools to get total value. So there's a lot of interesting work happening there, and I think we're finding a lot of really interesting use cases

And then, on, on the platform side and in some, in terms of some of the things that we're gonna start rolling out to our [00:25:00] clients, we announced at our user conference, about a month ago, some of our long-term views on where we think AI starts to come into the platforms.

And I think in some ways it's kind of what you would expect. We think that there's an opportunity to roll out an AI tool that allows you to kind of chat with your data and take some of that chat with your data use cases and start to automate different activities that that data ultimately in the platforms will lead to and a number of others.

There's a bunch of, I think, really interesting use cases where AI across the platforms. We are probably a little slower to some of that, I think, than than others just because in this regulated environment we have to have a lot of confidence in what these AI tools are out are, are outputting and we can't have a lot of hallucination or frankly just wrong stuff coming out of them when you're talking about people's finances and that stuff.

So I think it's something the financial services industry largely is trying to grapple with, and I think we'll get there, I think [00:26:00] as the models get better and as they get high tuned more finely and as we kinda learn what they really are truly great at and what they're not so good at, I think we'll get there.

I think you're gonna start to see more of these tools start to surface here, probably in another year or two in the financial services industry.

Trisha Price: Yeah, that makes sense. I've always said for us at Pendo as we've developed AI features and rolled them out specific to customers like you who are in a highly regulated environment.

Even some of our banking customers, they wouldn't buy Pendo if we didn't have the AI features, but them going through the processes to actually be able to use them is complicated and takes quite a while compared to let's say another tech company or a startup or something like that. Right. And it's just such a funny balance and I know you feel this is like you have to invest in AI as Morgan Stanley at Work to think about your nine, your longest nine and [00:27:00] making sure you're delivering, but knowing if you just jam something out there and put it in beta, like the likelihood of your customers being able to use it and you keeping their confidence is probably pretty low.

Which is not, not necessarily true for other industries.

Mark Mitchell: Yeah, it's true. And we are, we're seeing that, I'll call it conflict even with our clients too, right? Some of the largest companies in the world are trying to figure this out, where it's, how can we in a nine month timeframe start to see efficiencies from these tools?

But how can we do that in a way that doesn't throw security and privacy and our risk and control processes totally out the window? And I don't know that anyone's fully figured it out yet. I think a lot of people are kind of kind of getting closer and closer, but it is an interesting challenge to kind of solve.

It kind of reminds me a little bit of the like early two thousands when cloud software first became a thing, right?. And it's like, are we [00:28:00] really gonna put our data like on a server that we don't own on some random website somewhere? Like

Trisha Price: yeah.

Mark Mitchell: Are we really gonna do that?

Obviously the answer's yes. You know?

PEN-E005_mixdown: Yeah.

Trisha Price: I mean Mark, before I came to Pendo, I was the Chief Product Officer at nCino, and our customers were only banks and they're putting lending data in the cloud and most of them were moving from manual on-prem type solutions into the cloud, and it was incredibly scary for them.

Now, the efficiency gains and modernization of experiences for their customers and employees ended up well worth it. And now we look back and you think like, what was the big deal? But it was a big deal as we went through that time period and, and I know AI is the same way.

Mark Mitchell: Yeah, a hundred percent.

We have those conversations all the time. I sometimes remind people, I use this thing. I go, I say AI is really just gonna be the internet. [00:29:00]

Trisha Price: Yeah,

Mark Mitchell: I agree. And like when you think about it that way, like it, all of a sudden it's like, oh, right, yeah,

Trisha Price: yeah, yeah, yeah. Do you think for your product managers who are most of them, many of them probably used to being in a highly regulated environment. Are they excited and like chomping at the bit, like, Mark, let's go. I want, I have got all these ideas, and I wanna build this agentic interface and I here's what I wanna do or are they like, are you dragging 'em along, or is it a mixture of both?

Like, how's that feeling?

Mark Mitchell: A little frustrating 'cause it's exactly both of those things. It's, you've got this one group over here who are like, they're ready to work nights and weekends, right? Like they're at home on the weekend playing with the tools and becoming educated and they're experts across every advancement that happens every single day. And I fall into that group a little bit myself personally, and I'm frustrated by the other group. So the other group are the ones who are like I [00:30:00] don't know, I don't, I don't know if they don't know what's coming or if they're just not yet interested or if they haven't had the breakthrough moment.

I don't know that I can say the thing, but they're really kind of sitting a little on the sidelines. They haven't really explored the tools deeply. They've maybe kind of played with ChatGPT, like as a little bit of a toy to kind of try it or something, you know? But they haven't gotten close to learning the real power of it and seeing the real future of it and so I'm mainly just kind of, I'm mainly just thinking of it as like my main job right now is to just evangelize the fact that this is gonna impact all of us really, really soon. And think of it like the internet like, in 2025, you are using the internet and I don't know how you got there, or when, but you're using it, you know?

So I think that's...

Trisha Price: Even my mom uses it, Mark.

Mark Mitchell: Totally.

Trisha Price: Yeah.

Mark Mitchell: Totally. Totally.

Trisha Price: And you know [00:31:00] it's funny you say that, I've been such a big part of my job and a part of the job that I love is to go out and talk to product teams across the world. And one of the things people ask me all the time is from a career perspective, can I help them? Can I give them career advancement advice? How do they continue to progress as product people into product leaders, as product managers into overseeing with more autonomy, a broader set of the product?

And I tell them right now, like, if you are not playing with AI tools every day, at least multiple times a week, like, don't even talk to me about career advancement because you know, yes, there's more to like, especially if you're trying to go down to people leadership and some of the investment strategy concepts and business concepts that you and I were talking about earlier are equally important as, and that's what I used to talk to people about. I used to talk to people about the fact that [00:32:00] you can't just know how to work with engineering and build a good feature. You can't even just know how to meet with customers and do great discovery and understand the business problem. You have to actually understand your business, and you have to understand how what you're delivering drives business outcomes.

And that is obviously as critically important as ever, and probably the number one piece as you move up in your career and product. But right now, if you aren't playing with these tools and actually yourself coding, building experiences and prototypes with them, I think you're gonna be woefully sad about your career over the coming, and I don't wanna say years, I mean weeks and months.

Mark Mitchell: Couldn't agree more. I, I could not agree more. And I think, you know what that really pins back to, Trisha is I believe that the best product managers are those who are curious. And the best of the best are the ones who take the curiosity and turn that into this constant learning. You know? And when you're constantly curious and you're constantly learning, [00:33:00] you're effectively gonna, you almost have no choice but to effectively be great, right?

Because you're just going to be continually curious about the problems that then need to get solved and then curious about how can I learn to find solutions to solve those problems. That's like product management at the end of the day, right, in a nutshell. And I think for those people who are, always curious and always learning, AI is like a blue sky, right, of stuff for that mindset, you know? So it's interesting that it's also kind of sorting out those, those who are curious and always learning versus those who kind of just like pound on product requirements for eight hours and then go home and go to sleep, or whatever they do.

Trisha Price: Right? Yeah. I mean, like writing requirements, I'm not sure we really need to be doing that anymore. Yeah. Right. And even whether you're talking about Jira tickets and user stories, you're talking about traditional PRDs. I mean, do you need to be able to articulate the business outcome and the [00:34:00] why a hundred percent, right? That, that, that, that, that decisioning, that prioritization, that what you're trying to solve and the outcome you're driving needs to be articulated and written down, but the, what you're trying to build.

You can do it so much more clearly through a prototype and so quickly through a prototype using AI with no engineering today than you can with words and words and words and documents. And you can do it so much quicker and you can get customer feedback so much more clearly and quicker. It's just, it's incredible.

Mark Mitchell: Agreed. Agreed. And what's fascinating too, is the mindset that it takes to, to, to use those tools successfully, It is ironically, a bit of a product management mindset, right? If you've seen like, and if you've used those tools successfully, it really kind of comes down to like thinking like a product manager.

And what, what's been interesting is to watch like non-product people use those tools. Regular folks from the business or just the outside universe in [00:35:00] general. And the ones who figure it out the most end up just starting to realize that they need to prompt the tools and think about the tools and use the tools in a way that ultimately is product management, you know?

So I think I think of it a little like, when it comes to my team, like, you guys already have that skillset,

Trisha Price: Right??

Mark Mitchell: You're experts in that domain, right? So, my thing is like start to figure out how to harness the power of already being an expert in that domain, in this new universe or you're gonna have a lot of people who come in and realize that with just a, a little bit of product expertise and a lot of AI knowledge, and they can really start to become very, very powerful, very, very quickly.

Trisha Price: Yeah, it's, to me it's like such a special time to be in product to your point, right?

We are the people who've been trained and who have been thinking for years about taking a hard business problem, truly [00:36:00] understanding the why, the job to be done behind it, and then breaking that down into simpler pieces, and then turning that into an innovative solution to solve the problem. That's what we do, and now we have these magical tools to help us.

It's just like, to me it's like this golden age and the best time to be in product ever.

Mark Mitchell: Totally agree. And what's beautiful is those AI tools generally are shrinking down the middle part of what you just described incredibly dramatically. Right? So the, the nice thing is the timing it takes now to go from concept to crisp requirements to problem solved, to delivery right, has been greatly compressed, which I think just makes our jobs more power that much more powerful and that much more exciting, you know?

Trisha Price: I do too. I mean, because that kind of coming back to what we've been talking about originally around product bets, product investments, how do you know which ones to prioritize? How do you know to flip eight and nine?

Or even once you're [00:37:00] focused on that, that item number eight in your list and you know that's the right one. What's the solution that's actually gonna drive the best outcome? I truly believe that this new iterative approach and these tools, these are changing the game in terms of, of that

Mark Mitchell: A hundred percent because I think in a future state, and I kind of joke with my team about this all the time, like in a future state, clearly we're using AI to do all of those things. It doesn't mean that AI is like totally just like running the show and it's just spitting out like, reverse eight and nine, right?

Like, but I do think like there will be a time in the not too distant future where you turn to the AI tools probably as almost an automatic prerequisite for every decision that you're about to potentially make or at least execute upon. We're not doing that yet today, but I think we're, I think we're gonna be there.

Trisha Price: And Mark, not just AI, but all the things that we've just talked about - customer feedback, revenue impact, nine, [00:38:00] nine, nine, strategy and roadmaps. Yeah, like how do you just think about like the best product leaders as you think about advice to our listeners who would love someday to have a job of your magnitude with that kind of impact.

How do you think about, there's gut instinct, which all great leaders have some gut instinct. There's data, right? There's company strategy. Like what do you think about, what are, what are, what is like for you, the scale, the tip? Like how you weight those various things when you make decisions every day?

Mark Mitchell: Yeah. I think, I mean, I don't think there's a singular answer. I mean, I think the main, the main thing that I would say and the advice that I, I try to give is: When you start to operate at, at a fairly high scale, I think the thing that really becomes the answer is you need to become a bit of an expert across all of those things, right?

So in my job, like I have to be an expert, of course, on the platforms and the functionality and the capabilities and the nitty gritties of the, do you know what it does and doesn't, [00:39:00] all those things. That's fine. I also have to have a pretty good understanding of the technical capabilities of the platform.

A deep understanding, I would say even of the technical infrastructure the way that the different platforms are connected together and all that. I won't go through all that. You guys kind of all know kind of what that stuff means, but then there's this whole other dimension of stuff, which I think is where product managers start to evolve to product leaders, and that is understanding the business very deeply, the business metrics, understanding really the core business that you're in and the core revenue and KPIs and metrics and things that matter.

I think if, if, if there's one piece of advice that I could give to someone who's sitting in like, what I would call like a standard day-to-day product manager seat and wants to move into product leadership, I would say deepen your understanding of the business and the, the revenue, the metrics, the KPIs.

It's, [00:40:00] it's probably not stuff that seems like super exciting. Like most people who are like product managers, the really good ones I think do that stuff. I don't think the average one is sitting there like, oh, let me dig into like how our revenue works and get a deep understanding of our revenue and how that ties back to, you know.

But I do think if you wanna make the leap, that's the thing I would tell you to probably spend some time on. And what you'll uncover through that process is not only an understanding of the revenue, but you'll, get an understanding of the entire business at large. And you'll start to understand how small decisions that you might make in Jira actually drive all the way through to true revenue on the other side or not.

Trisha Price: Yeah. Great. Well, Mark, thank you so much for sHard Calls E005-FINAL EDIT

[00:00:00] 

Trisha Price: If you build software or lead people who do, then you're in the right place. This is Hard Calls. Real Decisions, real leaders, real outcomes.

Hi everyone. I am Trisha Price, and welcome back to Hard Calls, the podcast where we bring on the best product leaders from across the globe to talk about those moments - the decisions that matter, the hard calls.

Today we have on the show the Chief Product Officer at Morgan Stanley at Work, Mark Mitchell. With over 15 years of experience in product management and technology, Mark has a deep understanding of the evolving needs of customers and the power of technology to transform their lives.

Mark's expertise lies in building high performance product teams, fostering a culture of innovation and leveraging data-driven insights to deliver exceptional customer experiences. Welcome to the show, Mark. 

Mark Mitchell: Thanks for having me, Trisha How are you? 

Trisha Price: Great. I'm super [00:01:00] excited to have you here. Mark and I have been working together for about four years. Mark's been a longtime Pendo customer and we've gotten to know each other through that, and and I've just been so impressed, Mark, with the way you lead your teams, the way you think about products, so I'm super excited for this conversation today. 

Mark Mitchell: No, thank you. The feeling's mutual. 

Trisha Price: Mark, this is the Hard Calls podcast.

So I like to start every one of these episodes where you get to talk about a hard call that you've had to make. So tell us, looking back over your career, or even just the past year, what's one really hard call that you've had to make and what made it so challenging? 

Mark Mitchell: I feel like we're jumping in with the hardest part of the entire interview right off the bat.

Of course. 

Trisha Price: Why wouldn't we? Why wouldn't we? 

Mark Mitchell: I think I think there's a, so as I was thinking about this, there's a couple different answers to this, but I think what I would say is one of the hardest things for our business and for my role almost probably once a year, is we engage in a sales conversation with a really large client of ours and what we ultimately figure out after getting [00:02:00] into that sales conversation with this prospect is that we may not be a great fit for each other. Whether that's on their side or on our side, or maybe a little bit of both and it's this really tough decision that you have to like, ultimately come to, to realize as excited as we are and as long as we've worked on this thing, there just may not be a go forward path here for us. And it's super difficult and always, always, a hard kind of call to ultimately make, but that occurs about once every year or every other year. We get into one of those. We had one of those in the last couple of months, which is why it's top of mind for me at the moment. 

Trisha Price: I am so glad you talked about that, and I know that's gonna probably weave through various conversations that we have today and man, that takes such discipline to be able to acknowledge that and, and I'm glad you brought that up because all of us as product leaders, there's always pressure for revenue, there's always pressure for customer happiness, and that's just such a hard and [00:03:00] difficult decision to make.

Mark Mitchell: Yeah, when you look when you look at those situations and it's it's kind of, it's kind of the again, it's, it's more of an exaggerated version of what we do every day, right? It's, you look at the situation and you say, the effort that we're going to have to put out, right?

Whether that's cost or development time or product team time, whatever, however you wanna think of it is gonna be huge in this situation, let's just say. And, and then you start to pencil out, okay, so how does that look over the longer term for revenue and for this and for that, and all the different dynamic parts of kind of like how these things fit together.

 And sadly, sometimes you just come to this conclusion that it just doesn't really, it doesn't really pencil and that, the upstream swim to build the things that this particular client's gonna need, find ways to do that, that in a way that they add value to other customers and other [00:04:00] clients.

Like, like that story just doesn't it, it ultimately just doesn't tell, you know. Yeah.

Trisha Price: Which isn't good for either of you. Right. It's not good for you, but it's also not good for the customer, right? 

Mark Mitchell: That's right. That's right. That's right. And most, we find most of our best customers and the best relationships we have. there's this mutual investment in, Hey, we, we have some particular functionality that we need for us, but we wanna work with you and commit to building that in a way that can be leveraged by all clients. It's ultimately better for everybody and that's, that's the best case scenario.

Trisha Price: Yeah. Well, I wanna get into that a little bit more and think about, and talk about how you make those kinds of decisions. But before we do, maybe just share with our listeners for a minute, who is Morgan Stanley at Work? What you do and, and what makes you a leader in your industry? 

Mark Mitchell: Yeah. Yeah. Perfect.

Yeah. Morgan Stanley at Work is really the, the market leader, in, in equity comp plan [00:05:00] administration, right? So if you work at a large company that offers stock as part of your compensation, those plans, while on the surface are pretty simple, issuing stock to employees on an annual or semi-annual basis on the surface, fairly simple in reality, can get quite complex to administer. There's a lot of tax implications, there's a lot of global rules and laws and regulations and things that need to all get accounted for. So our platforms, allow companies to issue stock to their employees in a relatively seamless way, those employees then receive those shares and can sell them across our platforms. So that's the business in a nutshell. We, we serve, about 3000 large companies. We tend to operate with, with mostly public, a chunk of private companies usually US-based, brand names that you know across [00:06:00] all of the key sectors of the economy.

 And we fit within Morgan Stanley more broadly. Of course, Morgan Stanley offers a lot more services than, than just that, but that's the area of, of platforms that I lead up. 

Trisha Price: Well, Mark, I just logged into one of your products yesterday, to use it and, and it's a great tool and has provided a lot of value for one of the organizations I'm involved with as a board member.

 So I can speak personally, on the complexity that you solve and the value you bring, to these organizations. 

Mark Mitchell: No, I appreciate it. Thank you. 

Trisha Price: So Mark, coming back to the hard call that you talked about and, and making those difficult decisions around specific customer asks and nuances, tell me what factors do you consider when deciding how to balance your product investments?

Mark Mitchell: Yeah, it's it's, I always think of this this like multi-variate kind of math equation a little bit, you know?

I'm a math major. 

Trisha Price: Mark, so nobody [00:07:00] loves there. Go, yeah, nobody loves this more than me. Let's go, let's go. 

Mark Mitchell: And I say that 'cause it's like, it's, it's it, there's not one single lever that matters more than another, you know?

So I think the first is there's all I, I think of it as like, what is the impact that this particular thing is gonna have, right? So that's the first measurement that I like to think about. And the thing that I kind of push the team on is what is the impact this thing is gonna have? So, in other words, like how wide is the radius of this particular ask gonna have?

And so the ones that jump to the forefront is, okay, this is a small ask and a small radius, right? So that kind of is one bucket of, okay, it's, it's not gonna impact many customers besides this particular kind of niche need, but it's really small. So those are relatively easy to kind of sort through, you know.

Then the next, the next group are, okay, this one's gonna be really big, but the impact is gonna be super massive as well, right? It's something that will [00:08:00] make every client more successful, it'll speed up processes, it'll reduce risk, it'll do this, it'll do that. Those, again, are generally pretty easy 'cause you say, it's easy to justify the time, the effort, they expense, and all of those things.

And this one, those are easy. So those are the two easy ones. Right now, the hard ones, are the ones where it's massive size, small impact, right? Those are the ones that you really have to spend time kind of wrestling with, because, there's gonna be a big investment and there's not gonna be a big impact wider than this specific need that's being addressed here.

 So we have to take those really carefully. When you start to get into looking at those, that's when it can get it can get complicated. You start to weigh, okay, so this particular client is how big, how many participants do they have as part of the plan? So if this is something that's gonna touch all of their employees, how many do we have there?

What are the [00:09:00] sizes of the plan and what, how does that translate through to some of the KPIs and the revenue metrics and the other things that are downstream for us? So there's really no simple answer, but what I will say is the, the goal is to have that functionality impact as many clients or as many of their plan participants as possible.

That's the goal really, almost every single time and if we can achieve that, generally speaking, almost regardless of cost, we know we're heading down the right the right path. 

Trisha Price: And so is that a big part of how you measure the success of your investments is how many people the feature you deliver impacts or how many use it?

Like how do you think about success once you've shipped a feature? 

Mark Mitchell: Yeah. It tends, it tends to come down to adoption. Adoption is a really key metric for us because if we're building something that again, really helps one customer really, really well. That's great. But [00:10:00] the adoption, obviously there is super, super di minimis and it's good to make one person happy, but that's always gonna be a tough one to justify, you know?

 So, adoption for us is a KPI almost unilaterally, whether that's on the administrative, corporate client side of the platform or something that the individual two-legged employees are using. Adoption is always gonna be really for me, the top metric to track. For almost any investment that we make.

Trisha Price: And so Mark, I I always tell people it's not field of dreams, just 'cause you build it, they don't necessarily come. That's right. So tell me like, when, since adoption is so important to you, obviously step one as you've talked about, is building features that are widely applicable to your user base and your customer base.

But step two, okay, you built something, it's why it's, it's applicable to everybody. What do you do? How do you get adoption of these features? 

Mark Mitchell: Yep. And I think that's what separates in some [00:11:00] ways a great product organization, and a great, from a great business, so to speak, right? And so what I mean is you can be a great product organization, but if the business that that product organization sits within is not as effective as the business should be, it's gonna be tough, right?

And so for us, it starts with us making sure that we understand the needs of the customer. Understand the needs of the problem and the problem that we're trying to solve, and spend a lot of time understanding the front side of discovery and planning and all the things that go into building a great product.

Then it comes to executing at a really high level on the actual build of the product and the delivery of it, right? Those are the parts I think that my team tends to largely be at the forefront of, but then there's this moment as you start to get close to kind of rollout and delivery where there's a handoff of kind of the activities.

[00:12:00] And we took, tend to take a little bit more of a, I think a passenger role in that. We have to drive it , but it's really the, the client facing teams, the marketing organization, the teams that create all of the learning and education content and all of those things.

It's our job to make sure that all that stuff effectively gets delivered, but truthfully, that lives outside of delivering the, the, the product, right? So, it's important that, that, and then I'd say I just layer over top of that I think it's important that through that entire process that the key stakeholders in the business and the stakeholders of the teams that deliver those things are also bought in on the, the, the product itself, the rationale behind it, and the fact that it's ultimately going to take all of us to be successful.

And all of those groups have to lock arms in that or, or it doesn't work. 

Trisha Price: Mark, I love that. I, I often call that whole product. 

Mark Mitchell: Yeah, yeah. 

Trisha Price: Right, because it's easy for us as product [00:13:00] organizations and engineering organizations to think we're done when the feature, when the code is complete or the feature, has been shipped.

 But, if customers don't know how to use it, if salespeople don't know how to sell it, it's not done. It's not there. And it's such a shame to use our precious engineering resources and build something so valuable, but not run through the finish line to make sure that it's available and easy for customers to use and everyone in the organization knows about it.

So I'm really glad you brought that up. 

Mark Mitchell: Yeah. Yep, yep. Couldn't agree more. And, and on top of that, I'll say it's it's a loop, right? Because it's also going to be those same teams who a year from now are the ones hopefully coming back and saying, Hey, we think adoption could increase if we add this.

We're hearing this we're meeting with clients and they're saying that, and so I think it's important that it's, it's that closed loop all the time. 

Trisha Price: For sure. Mark, how, [00:14:00] how do you. How do you close that loop? Is that a, a natural communication that happens from your product managers to those teams?

Is that like a regular cadence where leadership comes together and they've prepared a summary of what they're seeing? Like how do you make sure that, that that constant iterative feedback loop happens? 

Mark Mitchell: Yeah, I, I think of it on two, two dimensions. I think one dimension is. There's the really data-driven aspect of it, which as we obviously use Pendo for, and I think Pendo and, and the data analysis side of it is one part of the equation.

No doubt about it, right? But that is only one side of the coin. The other one is this anecdotal, boots on the ground visiting with customers, engaging with customers directly, and involving as much of my individual product managers [00:15:00] with client facing activities as much as possible.

And so I think, it's easy to say, oh, we're gonna look at the data and just rely on the data and sit in front of our computers all day and do everything from that side. But the reality is you've gotta be out, you've gotta be part of the sales meetings, you've gotta be part of the client meetings.

You've gotta be part of all the different activities that happen, and you've gotta be willing to kind of accept whatever comes from that, which occasionally is not super pleasant, you know? But it is the only way to make sure that you know that you're getting everything out of that engagement that you can.

And then what I like to do is kind of cross over the two things. So, we'll have a conversation with a client. There'll be a lot of anecdotal takeaways from that conversation. They're important, they're meaningful, but they are singular in what they represent. Then I like to take those singular pieces of client feedback and check them against the data to widen out that perspective and validate that singular view with a more [00:16:00] holistic view that represents all the users of the platform.

That is how you cross over both dimensions of the feedback in my opinion. 

Trisha Price: I love that. That's, that's a, a great approach because I do think most times when a customer is frustrated with something or even excited about something , it is applicable and other people are feeling it and you can't ignore it and, and wish it away as one noisy customer.

But there are times where while that might be only that customer or two or three customers, there are 10 other issues that you have sitting there that are applicable to more. And so I love thinking about that balance. I'm like you, I won't ignore it, even if only one customer is loud and noisy about it, or talking about it and asking for it.

It's just too important to turn the other way, but I do wanna validate it with data in terms of where do I work [00:17:00] it and how does it fit in my overall priority list? Because as product people, there's a never ending list. 

Mark Mitchell: Never ending list. And it's our job to make those micro decisions, right? That switches item eight and nine, you know?

And, and it's gonna take that, that anecdotal blend with data in order to decide that eight and nine need to switch, you know? Yeah, 

Trisha Price: When you think about the macro level of, of your investment decisions and, and not so much the switching of eight and nine, which is honestly where the hard part in execution comes in, but more at the big buckets of like, how many teams am I gonna put at this product or this part of the product, or towards this outcome versus how many teams am I gonna put at this?

How, how often do you do that kind of allocation and roadmap strategy, and who do you involve when you do those kinds of big rock decisions? 

Mark Mitchell: Yeah. So I think the, I'll start with the [00:18:00] often and then I'll go to who gets involved. I think, I kind of like to think of this, kinda like little framework of nines that I use in, in my head, which is I like to think of everything on this 90 day, nine month and nine year scaling, right? So if you think about things across those time dimensions, it can really help you start to decide like, so from a nine year perspective, like that means we're changing the entire direction of our business.

Right. That's probably not happening from a singular decision we're making today, but we may be tacking gently towards a potentially different direction of the business, overall That's kinda like a nine year plan. Nine months is probably where we spend a lot more of our time that's where you're thinking a little bit more year to year. We often are thinking about what are gonna be some of the big things that we wanna [00:19:00] roll out next year? What are the things we need to wrap up and whatever the end of Q3 to make space for the things that we're talking about blah, blah, blah.

That's like a lot. I think it's where we spend a lot of our time in that kind of nine month zone, you know? And that's probably where most of our organization broadly spends a lot of their time. But then the 90 day thing is also super real because the 90 day thing is where you get into, okay, we just had a really tough meeting with a very large client who has what I'll call effectively an immediate need.

That's kind of like 90 day thinking, right? Like the response to them isn't, we're gonna do the best we can and we'll try to deliver it next year. Right? Like, this doesn't work. That's not, doesn't work. Right? So it's not how enterprise software works. Totally. Now, at the same time, you also have to avoid the trap, though, of falling into making every single decision a 90 day decision.

And it feels like you're never getting anything big done. You're never getting traction across big things. You're constant so you get it. It's really a [00:20:00] balance of those three, they, I think they build on each other. I think when you have really good 90 day decision making. It lends itself and leads towards really good nine month long decision making and a bunch of good nine months lead up to really good nine year long term thinking.

So, to answer the second part of it around the stakeholders, I'm a, a huge believer that, that everyone that works on the team from, from me, all the way down to some of the newest, most junior people have, an extremely close and really, really frequent engaging relationship with the stakeholders of their respective areas so for us, that's usually, their respective development partners, it is their respective business folks, it is their respective legal risk and compliance folks, and then I would throw clients and customers into that bucket as well so it's not super uncommon for someone on the team who's mid-level [00:21:00] to be interfacing with the client directly on things that they're building for them and kind of carry those things all the way through those different groups. And so when it comes to that 90 day, nine month and nine year thinking, like, I, I really expect everyone on the team to think across those dimensions that way and apply that framework to every decision that they're making really every single day with the stakeholders.

Trisha Price: I love that nine, nine, nine that's, that's a really memorable way to think about it. And, a great way to make sure that you're balancing the, the long-term strategy with the short-term needs. That's great. Well, when you think about a nine, nine, nine and it wouldn't be a product discussion if we didn't talk about AI.

 And I wanna talk about AI a couple of different ways with you, but, I think for most of us over the last two years at [00:22:00] least, AI has forced us to rethink all three of those nines, most likely in some capacity. Certainly the, the longer of the two nines, that's for sure. So maybe talk to us about how you have thought about AI and AI as a part of your product experience and innovations. You're in a highly regulated industry and an enterprise, but at the same time, we can't turn our heads on AI, so how does, how does that impact you in your nine, nine, nine? Yeah, 

Mark Mitchell: We could spend hours on this topic, as you probably can imagine.

 So I'll try to be quick about, it.

Trisha Price: I'm excited to hear. 

Mark Mitchell: Yeah. Yeah. I think AI is going to truly change everything, you know? I think it is gonna change everything, our personal lives over time. I think it's certainly changing life at work largely, and how [00:23:00] we do our jobs.

I really think everybody's gonna be impacted in some way, in some form. I don't think it's all negative. I think there's actually a lot of positive there. I think in our space specifically, I think we can see really quickly how AI is an incredibly powerful tool for doing feedback analysis, right?

 Requirement writing, test, test creation. I mean, obviously all the way through the tech stack for development and and the relationship between those two activities. I think there's a ton of ways that AI can be applied. I've personally used it for some fun personal projects and just learning, experimenting, I've done tons of coding with it and tons of the things I just talked about, and it's, it's clear how powerful it's gonna be.

Now the challenge becomes, as you touched on, okay, so when you move into an enterprise environment, where you've got regulatory oversight and you've got [00:24:00] control processes that need to be adhered to, and all of the realities of the world, at least in a financial services space that I operate in.

 It's trickier, it's much trickier. So I can tell you, at Morgan Stanley, some of the ways that we're using it and some of the plan, the ways we're planning to use it. So, currently we have, a large amount of our developers using it, to write code or to check code or to speed up code writing.

In some ways, obviously our code bases are enormous and in some cases decades old, you know? And so I think they're trying to figure out ways to use it so that they can kind of get individual tasks done without having to load this massive, massive code base into the tools to get total value. So there's a lot of interesting work happening there, and I think we're finding a lot of really interesting use cases 

And then, on, on the platform side and in some, in terms of some of the things that we're gonna start rolling out to our [00:25:00] clients, we announced at our user conference, about a month ago, some of our long-term views on where we think AI starts to come into the platforms.

And I think in some ways it's kind of what you would expect. We think that there's an opportunity to roll out an AI tool that allows you to kind of chat with your data and take some of that chat with your data use cases and start to automate different activities that that data ultimately in the platforms will lead to and a number of others.

There's a bunch of, I think, really interesting use cases where AI across the platforms. We are probably a little slower to some of that, I think, than than others just because in this regulated environment we have to have a lot of confidence in what these AI tools are out are, are outputting and we can't have a lot of hallucination or frankly just wrong stuff coming out of them when you're talking about people's finances and that stuff.

So I think it's something the financial services industry largely is trying to grapple with, and I think we'll get there, I think [00:26:00] as the models get better and as they get high tuned more finely and as we kinda learn what they really are truly great at and what they're not so good at, I think we'll get there.

I think you're gonna start to see more of these tools start to surface here, probably in another year or two in the financial services industry. 

Trisha Price: Yeah, that makes sense. I've always said for us at Pendo as we've developed AI features and rolled them out specific to customers like you who are in a highly regulated environment.

Even some of our banking customers, they wouldn't buy Pendo if we didn't have the AI features, but them going through the processes to actually be able to use them is complicated and takes quite a while compared to let's say another tech company or a startup or something like that. Right. And it's just such a funny balance and I know you feel this is like you have to invest in AI as Morgan Stanley at Work to think about your nine, your longest nine and [00:27:00] making sure you're delivering, but knowing if you just jam something out there and put it in beta, like the likelihood of your customers being able to use it and you keeping their confidence is probably pretty low.

Which is not, not necessarily true for other industries. 

Mark Mitchell: Yeah, it's true. And we are, we're seeing that, I'll call it conflict even with our clients too, right? Some of the largest companies in the world are trying to figure this out, where it's, how can we in a nine month timeframe start to see efficiencies from these tools?

But how can we do that in a way that doesn't throw security and privacy and our risk and control processes totally out the window? And I don't know that anyone's fully figured it out yet. I think a lot of people are kind of kind of getting closer and closer, but it is an interesting challenge to kind of solve.

It kind of reminds me a little bit of the like early two thousands when cloud software first became a thing, right?. And it's like, are we [00:28:00] really gonna put our data like on a server that we don't own on some random website somewhere? Like 

Trisha Price: yeah. 

Mark Mitchell: Are we really gonna do that?

Obviously the answer's yes. You know? 

PEN-E005_mixdown: Yeah. 

Trisha Price: I mean Mark, before I came to Pendo, I was the Chief Product Officer at nCino, and our customers were only banks and they're putting lending data in the cloud and most of them were moving from manual on-prem type solutions into the cloud, and it was incredibly scary for them.

Now, the efficiency gains and modernization of experiences for their customers and employees ended up well worth it. And now we look back and you think like, what was the big deal? But it was a big deal as we went through that time period and, and I know AI is the same way. 

Mark Mitchell: Yeah, a hundred percent.

We have those conversations all the time. I sometimes remind people, I use this thing. I go, I say AI is really just gonna be the internet. [00:29:00] 

Trisha Price: Yeah, 

Mark Mitchell: I agree. And like when you think about it that way, like it, all of a sudden it's like, oh, right, yeah, 

Trisha Price: yeah, yeah, yeah. Do you think for your product managers who are most of them, many of them probably used to being in a highly regulated environment. Are they excited and like chomping at the bit, like, Mark, let's go. I want, I have got all these ideas, and I wanna build this agentic interface and I here's what I wanna do or are they like, are you dragging 'em along, or is it a mixture of both?

Like, how's that feeling? 

Mark Mitchell: A little frustrating 'cause it's exactly both of those things. It's, you've got this one group over here who are like, they're ready to work nights and weekends, right? Like they're at home on the weekend playing with the tools and becoming educated and they're experts across every advancement that happens every single day. And I fall into that group a little bit myself personally, and I'm frustrated by the other group. So the other group are the ones who are like I [00:30:00] don't know, I don't, I don't know if they don't know what's coming or if they're just not yet interested or if they haven't had the breakthrough moment.

I don't know that I can say the thing, but they're really kind of sitting a little on the sidelines. They haven't really explored the tools deeply. They've maybe kind of played with ChatGPT, like as a little bit of a toy to kind of try it or something, you know? But they haven't gotten close to learning the real power of it and seeing the real future of it and so I'm mainly just kind of, I'm mainly just thinking of it as like my main job right now is to just evangelize the fact that this is gonna impact all of us really, really soon. And think of it like the internet like, in 2025, you are using the internet and I don't know how you got there, or when, but you're using it, you know?

 So I think that's... 

Trisha Price: Even my mom uses it, Mark. 

Mark Mitchell: Totally. 

Trisha Price: Yeah. 

Mark Mitchell: Totally. Totally. 

Trisha Price: And you know [00:31:00] it's funny you say that, I've been such a big part of my job and a part of the job that I love is to go out and talk to product teams across the world. And one of the things people ask me all the time is from a career perspective, can I help them? Can I give them career advancement advice? How do they continue to progress as product people into product leaders, as product managers into overseeing with more autonomy, a broader set of the product?

And I tell them right now, like, if you are not playing with AI tools every day, at least multiple times a week, like, don't even talk to me about career advancement because you know, yes, there's more to like, especially if you're trying to go down to people leadership and some of the investment strategy concepts and business concepts that you and I were talking about earlier are equally important as, and that's what I used to talk to people about. I used to talk to people about the fact that [00:32:00] you can't just know how to work with engineering and build a good feature. You can't even just know how to meet with customers and do great discovery and understand the business problem. You have to actually understand your business, and you have to understand how what you're delivering drives business outcomes.

And that is obviously as critically important as ever, and probably the number one piece as you move up in your career and product. But right now, if you aren't playing with these tools and actually yourself coding, building experiences and prototypes with them, I think you're gonna be woefully sad about your career over the coming, and I don't wanna say years, I mean weeks and months.

Mark Mitchell: Couldn't agree more. I, I could not agree more. And I think, you know what that really pins back to, Trisha is I believe that the best product managers are those who are curious. And the best of the best are the ones who take the curiosity and turn that into this constant learning. You know? And when you're constantly curious and you're constantly learning, [00:33:00] you're effectively gonna, you almost have no choice but to effectively be great, right?

Because you're just going to be continually curious about the problems that then need to get solved and then curious about how can I learn to find solutions to solve those problems. That's like product management at the end of the day, right, in a nutshell. And I think for those people who are, always curious and always learning, AI is like a blue sky, right, of stuff for that mindset, you know? So it's interesting that it's also kind of sorting out those, those who are curious and always learning versus those who kind of just like pound on product requirements for eight hours and then go home and go to sleep, or whatever they do. 

Trisha Price: Right? Yeah. I mean, like writing requirements, I'm not sure we really need to be doing that anymore. Yeah. Right. And even whether you're talking about Jira tickets and user stories, you're talking about traditional PRDs. I mean, do you need to be able to articulate the business outcome and the [00:34:00] why a hundred percent, right? That, that, that, that, that decisioning, that prioritization, that what you're trying to solve and the outcome you're driving needs to be articulated and written down, but the, what you're trying to build.

You can do it so much more clearly through a prototype and so quickly through a prototype using AI with no engineering today than you can with words and words and words and documents. And you can do it so much quicker and you can get customer feedback so much more clearly and quicker. It's just, it's incredible.

Mark Mitchell: Agreed. Agreed. And what's fascinating too, is the mindset that it takes to, to, to use those tools successfully, It is ironically, a bit of a product management mindset, right? If you've seen like, and if you've used those tools successfully, it really kind of comes down to like thinking like a product manager.

And what, what's been interesting is to watch like non-product people use those tools. Regular folks from the business or just the outside universe in [00:35:00] general. And the ones who figure it out the most end up just starting to realize that they need to prompt the tools and think about the tools and use the tools in a way that ultimately is product management, you know?

So I think I think of it a little like, when it comes to my team, like, you guys already have that skillset, 

Trisha Price: Right?? 

Mark Mitchell: You're experts in that domain, right? So, my thing is like start to figure out how to harness the power of already being an expert in that domain, in this new universe or you're gonna have a lot of people who come in and realize that with just a, a little bit of product expertise and a lot of AI knowledge, and they can really start to become very, very powerful, very, very quickly. 

Trisha Price: Yeah, it's, to me it's like such a special time to be in product to your point, right?

We are the people who've been trained and who have been thinking for years about taking a hard business problem, truly [00:36:00] understanding the why, the job to be done behind it, and then breaking that down into simpler pieces, and then turning that into an innovative solution to solve the problem. That's what we do, and now we have these magical tools to help us.

 It's just like, to me it's like this golden age and the best time to be in product ever. 

Mark Mitchell: Totally agree. And what's beautiful is those AI tools generally are shrinking down the middle part of what you just described incredibly dramatically. Right? So the, the nice thing is the timing it takes now to go from concept to crisp requirements to problem solved, to delivery right, has been greatly compressed, which I think just makes our jobs more power that much more powerful and that much more exciting, you know? 

Trisha Price: I do too. I mean, because that kind of coming back to what we've been talking about originally around product bets, product investments, how do you know which ones to prioritize? How do you know to flip eight and nine?

Or even once you're [00:37:00] focused on that, that item number eight in your list and you know that's the right one. What's the solution that's actually gonna drive the best outcome? I truly believe that this new iterative approach and these tools, these are changing the game in terms of, of that 

Mark Mitchell: A hundred percent because I think in a future state, and I kind of joke with my team about this all the time, like in a future state, clearly we're using AI to do all of those things. It doesn't mean that AI is like totally just like running the show and it's just spitting out like, reverse eight and nine, right?

Like, but I do think like there will be a time in the not too distant future where you turn to the AI tools probably as almost an automatic prerequisite for every decision that you're about to potentially make or at least execute upon. We're not doing that yet today, but I think we're, I think we're gonna be there.

Trisha Price: And Mark, not just AI, but all the things that we've just talked about - customer feedback, revenue impact, nine, [00:38:00] nine, nine, strategy and roadmaps. Yeah, like how do you just think about like the best product leaders as you think about advice to our listeners who would love someday to have a job of your magnitude with that kind of impact.

How do you think about, there's gut instinct, which all great leaders have some gut instinct. There's data, right? There's company strategy. Like what do you think about, what are, what are, what is like for you, the scale, the tip? Like how you weight those various things when you make decisions every day?

Mark Mitchell: Yeah. I think, I mean, I don't think there's a singular answer. I mean, I think the main, the main thing that I would say and the advice that I, I try to give is: When you start to operate at, at a fairly high scale, I think the thing that really becomes the answer is you need to become a bit of an expert across all of those things, right?

So in my job, like I have to be an expert, of course, on the platforms and the functionality and the capabilities and the nitty gritties of the, do you know what it does and doesn't, [00:39:00] all those things. That's fine. I also have to have a pretty good understanding of the technical capabilities of the platform.

A deep understanding, I would say even of the technical infrastructure the way that the different platforms are connected together and all that. I won't go through all that. You guys kind of all know kind of what that stuff means, but then there's this whole other dimension of stuff, which I think is where product managers start to evolve to product leaders, and that is understanding the business very deeply, the business metrics, understanding really the core business that you're in and the core revenue and KPIs and metrics and things that matter.

I think if, if, if there's one piece of advice that I could give to someone who's sitting in like, what I would call like a standard day-to-day product manager seat and wants to move into product leadership, I would say deepen your understanding of the business and the, the revenue, the metrics, the KPIs.

It's, [00:40:00] it's probably not stuff that seems like super exciting. Like most people who are like product managers, the really good ones I think do that stuff. I don't think the average one is sitting there like, oh, let me dig into like how our revenue works and get a deep understanding of our revenue and how that ties back to, you know.

But I do think if you wanna make the leap, that's the thing I would tell you to probably spend some time on. And what you'll uncover through that process is not only an understanding of the revenue, but you'll, get an understanding of the entire business at large. And you'll start to understand how small decisions that you might make in Jira actually drive all the way through to true revenue on the other side or not.

Trisha Price: Yeah. Great. Well, Mark, thank you so much for sharing your expertise on how you make big decisions and little decisions, how AI is starting to impact you and, and your team in the day to day. I really appreciate your time today, and [00:41:00] thank you for joining us on Hard Calls. 

Mark Mitchell: This is fun. Thanks for having me.

I enjoyed it. 

Trisha Price: Thank you for listening to Hard Calls, the product podcast, where we share best practices and all the things you need to succeed. If you enjoyed the show today, share with your friends and come back for more.

haring your expertise on how you make big decisions and little decisions, how AI is starting to impact you and, and your team in the day to day. I really appreciate your time today, and [00:41:00] thank you for joining us on Hard Calls.

Mark Mitchell: This is fun. Thanks for having me.

I enjoyed it.

Trisha Price: Thank you for listening to Hard Calls, the product podcast, where we share best practices and all the things you need to succeed. If you enjoyed the show today, share with your friends and come back for more.