Hello, and welcome to another episode of the Product Thinking Podcast.
Joining us today is Karthik Suri, the Chief Product Officer at Cornerstone On Demand, where he leads transformative efforts in workforce management and talent development.
Named among the Data Economy Power 200, Karthik is a thought leader in leveraging AI to bridge skill gaps and create personalized career development experiences.
Today, he'll share his insights on product strategy, implementing responsible AI, and designing adaptable enterprise software that meets the evolving needs of modern workforces.
But before we talk to Karthik, it's time for Dear Melissa.
So this is a segment of the show where you can ask me all of your burning product management questions.
Go to DearMelissa .com and let me know what they are.
Here's this week's question.
Dear Melissa, what advice do you have for making moves to the next PM role after getting your foot in the door?
I worked my way towards attaining the software PM title, but in a non -tech company that doesn't understand the value of the role.
A lot of leadership has McKinsey or Big Consulting on their resume.
They are amazing at BSing and deflecting, but very action adverse unless it's cost cutting.
The climate is so political that any effort to create positive change generally leads to retaliation until the proposal is either railroaded or hijacked by a senior leader.
My role is too narrow and there is no transparency or visibility on the product portfolio.
I see my SVP of product winning awards and speaking at conferences on LinkedIn more than I see her communicating internal messages and leading on the inside.
I know I need to leave this organization, but also feel like I need to clock time with the title.
I hate this situation, but feel like I'm stuck in a catch 22.
Is it asking for too much that I want to be a part of a team where I work with talented engineers, designers, and leaders that want to build great products and win together?
How or when do I move on from here?
Help. All right. Well, this sounds like a frustrating situation and I have to say that I've been in less than ideal situations as well, but let's talk about what you can learn from it.
A lot of organizations that I've worked in or with have not been doing ideal product management.
I've gotten frustrated before.
When I was very early on in my career, I thought I knew better than everybody and wanted to go out there and just do great product management.
And what I learned day after day of trying to push through this is that every company has its own BS going on.
You're never going to walk into a place that's actually picture perfect.
Sure, there are companies that are doing product management way better than what you're describing.
And then there's ones that are doing it even worse.
But you're never going to have just a super clear path in many places.
You're going to have to deal with people.
You're going to have to deal with situations that are less than ideal.
So what I learned along the way is to reframe how we think about the situations that we're in that are less than ideal?
What if I don't know everything that's going on here?
What if the leaders have some kind of agenda that I don't really understand?
Now, maybe their agenda is not aligned to great product management.
Okay. But once I first start to understand what that agenda is or what they're being judged for success on, then I can start to justify what those actions are.
And then I can see if product management is going to work here or not.
This also helps explained rationale and decision -making.
So you might be sitting there going, wow, these leaders are crazy and they're doing this and they're doing that.
Maybe there are things that you don't quite understand at work here.
Can you figure them out?
Can you ask questions about it?
Can you see why people are motivated to work the way they are?
How are they being judged for success?
A lot of understanding those decisions is about understanding how people operate.
And when you understand how people operate, especially in these types of conditions, you can understand and how to work with them.
So when I was in situations like you described, I approached it like, hey, let me see if there are ways I can test different strategies to get people on my side, or instead of get people on my side, convince them that this is a better way of working.
Maybe I can push forward just a little bit.
The problem is early on in your career, of course, you're going to want to build great products.
That's a really important thing that you really should nail when you're an early product manager.
You want to build and deliver great products.
If you haven't had the product title on your resume for a while, it might be hard for you to transition into another job.
So I want you to think about what you can do and what you can control in that situation and what you do have autonomy over.
And I want you to treat the way that you operate at this company, the same way that you would test a product, right?
What if I try this to get my senior leader on board?
What if I ask one question?
What do we think we will achieve by doing X, Y, and Z?
What if I start that conversation?
Can I get a little bit further?
How should I frame it?
Who should I bring into this conversation?
How should I work with this difficult person?
How should I do this?
All of those are leadership lessons that will become invaluable to you along the way.
I've also worked with my share of top company leaders who have been from the big consultancies and their political powerhouses.
I sucked at politics when I was younger.
And it was by working with those people and trying to figure out how to get them on my side, how to get them to listen to me, a lot of trial and error that allowed me to figure out how to play politics.
That maybe wasn't the most useful thing when I was a junior PM, but now it's extremely invaluable later on in my career.
You may not get all those opportunities later on.
Can you start to leverage those now?
Because those are the type of skills, leadership skills, skills that might help propel you in the future.
So while I understand that the situation is really bad and it sounds pretty bad, what can you do to learn from it?
What can you take away that will make you a stronger leader, a stronger person, a stronger career later on?
That's how I would treat it while you're there.
I think it's really important to understand people's motivations, to understand how to work with different types of people.
I guarantee you this is not the last time that you walk into an organization and there's a senior leader that's from a big consultancy.
I work with them every single day, and some of them are super, super smart.
Some of them don't know how to run product teams, and that's okay because some of them are humble enough to understand that, and they bring in the right people.
If you want to be the right person, that person brings in one day to run their product team, you better understand how to work with them because they may hire you in the long run.
So what can you do to get more up to speed on how to work with people like this, to work with people in those backgrounds, to rally people to a cause, to start to make a dent, to start to make a show of success in this way of working in your current environment?
And then when I say that you have enough on your resume, let's say like a year or two, and you want to get out, which I do not blame you for, then you can look at going to another company.
But you have already amassed these skills that a lot of people just don't take credit for.
These skills where it comes to interpersonal dynamics and politics and all of this stuff, product management is full of politics.
You're never going to get away from that.
That's just the job.
I wish we could all sit back and just say, hey, I'm going to build amazing things for our customers.
But you need to get that done internally.
And that's what separates a great product manager from just an okay one.
It's somebody who's going to push to really deliver the value from the customers.
And in order to do that, you got to play politics.
You got to figure out how to win over stakeholders and get people on your side.
So can you treat this as your learning opportunity?
I'll also say I attribute like 50 % of my success to seeing what not to do in organizations so I don't repeat those mistakes one day.
And also so that I can identify what the causes are and figure out how to fix them.
So by learning what not to do and observing what not to do, you're also learning here, right?
You're also growing.
So of course, we want to get you into a place where you could do great product management.
But don't be remiss to think that there aren't things that you can learn here along the way that may pay off in the long run.
And hey, maybe in like 10 years, 15 years or so, you are leading a product team at an organization like you describe and you're turning it around.
You're overseeing 5 ,000 product managers.
You're in a big software -enabled company.
You institute the process, but you know how to play politics with the rest of them, right?
You know how to work with the rest of that leadership team because you observed, you studied, and you tried.
And that's the only way you're going to learn those skills.
So I do feel for you that you're not feeling like you're able to practice your craft and that hurts and that sucks.
And I don't want to dismiss that.
You should want to go to a place where you can actually get things out the door and show you're doing great product management.
But while you have to be at this company, think about what you can learn there.
Think about all the other stuff that goes into product management and what you can take away.
So I hope that helps.
And I wish you the best of luck.
All right. That's it for Dear Melissa today.
But again, if you have any product management questions for me, go to Dearmelissa .com and let me know what they are.
Now let's go talk to Karthik.
Welcome to the show, Karthik.
How are you today. Outstanding, Melissa.
How are you? I am doing great.
And I'm really excited to talk to you.
I just mentioned right before we jumped on, I have a lot of clients who are using Cornerstone.
So I have been dying to learn more about your journey and what you're doing.
Can you tell us a little bit about your position at Cornerstone and what you guys do?
Absolutely. Hey, everyone, my name is Karthik Suri.
I'm the chief product officer at Cornerstone.
A quick confession, I am a recovering engineer.
I've been with Cornerstone for about two and a half years right now, and it's an amazing opportunity to bring to life and unleash people's potentials, powering people and organizational potential to thrive in a changing world.
And I couldn't be more thrilled to be part of this mission.
My journey has been, I started off my career, as I said, as an engineer in General Electric in the Jack Wall Sheeter, then spent, did my tours of duty in the Silicon Valley at Yahoo, eBay, PayPal, went to GE back again as the CEO for the digital platform business unit, spent time in health sciences,
and now I'm at Cornerstone.
Through the course of this journey, one thing was absolutely evident, Melissa, to me, having looked at inviting the next generation of health sciences and healthcare and genomics or helping people move and manage money or level the playing field for commerce or drive the safety and productivity of the industrial
workforce. The one absolute common thing is the following across all these verticals is that when human potential is earnest and when advancements in technology is responsibly made, the world is a better place.
And it is with this spirit that 4 ,000 of us, corner stars, as we call it, wake up every single morning to make a dent in the world.
Love Corner Stars. What a fun term.
So you are really focused too on this concept of workforce agility.
Can you tell us a little bit about what workforce agility means and why is it so important today?
Yeah, absolutely. Look, let's take a step back and see what's happening in the world, right?
Particularly in the context of workforce.
A, we have a multi -generational workforce right now.
About five generations of workforce are in motion at this point in time.
There are massive geopolitical shifts right now, right?
We have, at this point in time, we have a couple wars that are ongoing.
Therefore, the supply and demand of labor is not what it used to be.
Three is there's emergence of skills that are unforeseen before, clean energy, gig economy, generative AI.
Four, the computational power and the things that you can do with data and technology is immensely expanded.
So all of these together has put a $14 trillion opportunity globally in front of us, about $8 to $9 trillion in terms of untapped opportunity, and about $5 trillion that we lose because of either attrition or an inability to go do certain things that we were able to do.
Just with respect to the multigenerational workforce, I have two kids, 18 and 16.
One of them is in college right now, a freshman.
He applied for his entire college application process using his mobile phone.
We call them the screenagers.
Their approach to coming into work and doing work is extraordinarily different.
Ninety percent of them say that the equipment and the form tackle of the equipment that they use at work actually counts towards their job satisfaction.
What a phenomenal shift.
Same again, in the emergence of unforeseen skills, one of our customers, a large logistical provider, is now completely upgrading from fuel -based vehicles to deliver to battery or electric vehicles.
It's just not the drivers.
It's the maintenance staff.
It is their power grid that they manage.
Everything around that ecosystem switches.
So this is creating a skills gap that is unforeseen before.
World Economic Forum states that over the next five years, 50 % of the skills are going to be approximately turned around on their head.
So workforce agility is a real thing.
It's a clear and present aspect to address right now in terms of readiness.
That resonates so much with what I'm hearing from people, especially in this conversation too where we're talking about remote work or different modalities of how people actually want to interact with their companies.
You also said something too that sparked, I just answered this question on the podcast like yesterday I recorded it, People are asking me a lot about internal tools as well.
And they're saying, can we build tools for our employees and stuff?
Like it's not the same as product management.
It's just project management.
We don't have to worry about user experience.
We don't have to worry about that.
And I've been noticing a big trend, like you're saying too, where it matters to these people.
Absolutely. Absolutely.
The cognitive dissonance that people feel going home and seeing themselves play or their kids play fortnight or whatever and then coming into work and seeing a green screen that just doesn't compute for people right now nobody wakes up in the morning saying i want to open a purchase today right but we
wake up to our instagram our twitter feeds etc so that consumer grade experience is becoming the norm right now and again with the multi -generation workforce that just gets amplified more and more are you seeing any trends in the companies too where you mentioned the the stat of our younger generation is definitely
looking for those internal tools or devices.
Have you seen companies start to look more at fixing their internal tools or paying more attention to them?
Or are we still at this cusp where it's like the employees are demanding it, but the companies aren't really recognizing it yet?
Yeah. So that's a fascinating question, right?
With a multigenerational workforce, the concept of the employer -employee relationship, and it's just not tooling, but it is how much you invest in the person behind the professional is becoming a question that is escalating in terms of its importance.
We've heard the term called the employee confidence gap.
Employers think that they are investing in that employee's tooling and skills and development X percent.
Employees think that is Y percent.
The gap between X and Y is a stubborn 40 year after year.
Let me take a few examples and stories here.
Employees who have left the company, right, among those, we did this survey with Lighthouse Research.
89 % of the people that left the company said that they would have stayed if they had a tool through which they could understand their career mobility or their skills development landscape, their navigation with respect to that.
What is more fascinating, and I'm sure this sort of intuitively computes, underrepresented minority were disproportionately seeking more tools to interact with before having that career conversation with their manager.
Either they don't feel that sense of authority, or they don't feel like hurt, etc.
Therefore, the tooling, the capability, the opportunity that we place in front of people for either skill development, mentoring, coaching, career mobility, advancement, it's progressively elevating on a day -by -day basis.
This is important for engagement, this is important for retention, and frankly, it's smart business because you're upskilling and you're capturing a market that you're letting go right now with respect to this.
So your thesis, your analysis is spot on.
It is not just improved tools that they can use and build, et cetera, but it is also the so what and the now what that they can do with respect to this, the outcomes that they can see for themselves and for the organization.
I talk about it in this particular way, right?
if I thrive as an individual, you win as an organization.
If my aspirations map to your outcomes through this connective fabric called skills and workforce agility, then we all win together here.
And that synergy, that harmony, that symbiosis is the sweet spot that we want to bring everyone to.
That ROI writes itself.
Does it make sense?
Yeah, totally makes sense.
When you're thinking about Cornerstone 2 and your product strategy, how are you helping people understand those outcomes and those skill gaps?
And what are you doing to help both the employee and the employer kind of bridge that 40 % that you're talking about there, that difference?
Fantastic point. If you take a step back and analyze a problem, right?
And we want to fall in love with the problem, not with the solution.
There are three big aspects in the workforce readiness gap.
The first is the skills gap, right?
So the skills gap is what your organization needs to be successful and what skills you have, what skills you need, and what skills your employees want.
The second, so as I said, these are changing rapidly.
Four years back, I don't think prompt engineering would have been in a job description.
That's thing number one.
Thing number two is expectations gap, as I just mentioned.
That one size fits all is gone, right?
Like employees want to be invested in.
They want self -directed learning.
They just don't want to do your compliance training.
It's extremely important, but they want more with respect to that.
They want career mobility.
They want shadowing.
They want mentoring programs, et cetera.
And that is the expectations gap.
And the third is what I call the visibility gap.
What I mean by that is a CHRO was telling me recently, which was fascinating, that we know more about a person the day that they joined the organization because we see the welcome note, we see that LinkedIn profile, we see their resume, then we know about them a year after because their information gets dissipated
into a litany of systems, A, and B, we look at them in the context of their current role and not who they are as a person, a digital twin or their passport of their journey, et cetera.
So we call this a lack of full understanding of a person's smart profile, their skills profile, as a visibility gap.
So your skills gap, your expectations gap, your visibility gap together form what we call the workforce readiness gap.
And the solve for that is a workforce agility platform.
You have a robust learn solution.
Some of the good work that you are doing as a part of product thinking is bridging that skills gap.
You're doing it in your function.
But imagine this is technical skills, hard skills all the way from driving forklift to managing a tough conversation with your employee, right?
Both the human skills and the hard skills.
Across the board, you need to bridge that with a robust learn solution.
Then, how do you bridge the expectations gap?
Expectations gap is bridged by giving clarity and objectivity to performance, having a robust succession plan.
Both of these are organizational structures and processes.
But then, the employee -initiated portion is going to be the career mobility tool, their personal journey mapping tool.
I'm a designer and I want to be a chief product officer or an engineer like me on their path to a COO with a stop at a CPO, et cetera.
What does that navigation system looks like?
What is their ability to go from to in terms of their journey?
That fulfills the expectations gap.
And then a robust jobs to skills mapping, a transformation by which you have the skills that your organization has, the skills the organization needs, and then how do you bridge that gap through learning, performance, coaching, development, internal mobility, external hiring.
All of that plugs your visibility gap.
Together, we believe that the workforce agility platform will bust all of this because learning, performance, mobility, and transformation are all beautifully interconnected.
That last piece too with the transformation, I'm curious how you're helping companies solve this.
So we just talked about all these different trends in an AI world, prompt engineering.
I run into so many companies that don't know what they need to get to the next level.
They know they want to be either digital or they want to play in these fields.
And then it turns into, okay, so how do we get there?
And that's usually where I've been coming in and helping on the product management side, but there's so many other things these days on this landscape.
What do you do or how do you approach your product strategy to help these organizations actually understand where they need to upskill?
Is that something in your Perview?
It's beautiful. That is the crux of transformation, frankly, Melissa.
So we have a product called Skyhive Cornerstone.
This is all about foresight, right?
This is about, we scour about 20 to 30 gigabytes of data every single day and understand the profiles, the job postings, the resumes, what have you.
And then we have, and with robust artificial intelligence, particularly generative AI, given the amount of language that this scans, understand what are the trending skills, what are the emerging skills by vertical, by geography, by function, so that people have an understanding of what's trending,
what is at an inflection point, where do we see the future going towards, where is going to be the supply demand shortage in labor in the longer term.
In the shorter term, do I have a person A who can drive a forklift B to be able to be deployed in a GOC, right?
Short and long term, having a full -blown understanding of the skills topography through labor market intelligence and generative AI and artificial intelligence is one product through which we understand and bring forth the foresight into what skills are emerging and what skills are readily available
right now. And a recent study that we put out through our Skyhub by Cornstrom product suite is that there has been a jump of 411 % in AI and generative AI -based job postings in the world.
That everyone can compute.
Here's a fun fact. Human skills are three times more in demand than digital skills.
Wow. So if you think about it, in a world where knowledge is completely democratized, wisdom and intuition now becomes the differentiator.
EQ becomes a value -added proposition, right?
That means that not only do you want to build your AI, generative AI, technical, ESG platform skills, but you need that fundamental human emotion, human interaction skills.
So those kind of aspects, like products and capabilities, help us tell our customers where they are, where they need to be, and what is the path to get from A to B.
Totally makes sense.
I think that the soft skills one too, especially when it comes to product management, as we both know, is so important.
And that one, I feel like it's hard to pinpoint, can someone do this?
How do you help organizations understand those skills in people when it's something that complex?
Yeah, absolutely. Skills detection is a combination of art and science, but we have enough scientific tools to extract the logic in the art, right?
So what? So people take your performance management tools and processes, your check -in tools and processes, your goals, and your ability to interact with people, et cetera, right?
If you're connecting all the data sources, including internal sources in a consented manner, right?
Not in a creepy way, but in a consented manner, With the power of generative AI, we are in a position to actually assess through their background, their profile, their declared intents, their undeclared intents, and their interactions and performance feedback, the type of the lessons and learning objects
that they have consumed, the type of instructor -led trainings that they have been exposed to.
You can start detecting what are the skills in people.
To some extent, have some algorithm to also extract our proficiencies in them with respect to this, right?
So now, in addition to that, then you add it to succession and 360 and engagement tools and feedback.
Now you have a holistic profile of a person.
So if you take product management, for example, you have your matrix, your skills matrix for product management capability, and then your capability model, then your success measures, your goals.
Now, applying a layer of AI on top of this, now you're able to detect and connect learning, performance, learning by doing, interaction, mobility, all of them come together, and then you have an effective coaching session and a career growth conversation.
How are you utilizing AI to bring those things together?
What's the strategy and the opportunity that you see between your different products?
Absolutely. First and foremost, most of us are not as lucky as some of us are in terms of living in a data -rich environment.
What if you just take Cornerstone's galaxy universe, right?
We have 2 .5 billion registrations, learning registrations every single year.
We have 5 million logins into our system every single day.
That's the number of cups of coffee I'm sure major chains are selling right now.
We have 30 million learning hours every single month.
So with this kind of rich contextual deep data, of course consented responsible way that we are able to honor, we are able to understand the needs connected to your job profile, connected to the industry, connected to the function or the vertical that you are in, connected to your own learning patterns
and your smart profile of the skills that you're coming with, et cetera.
Now you have an extremely tailored solution, a coach for you that helps you all the way from making learning recommendations, career mobility choices, mapping adjacent skills and opportunities that you have there, connecting you with internal opportunities, connecting you with mentors and capabilities,
et cetera. All of these coming together to the power of this data.
Now map this against the 30 gigabytes of external data, albeit low fidelity because it's out there in the world, combine the richness, the mile -wide, inch -deep external data, the inch -wide, mile -deep internal data together, now we are in a position to have personalized, adaptive, curated experience
that meets you where precisely you are, right?
We all grew up with mentors.
We are all where we are because someone helped us, right?
Someone told us, throw your name in the hat for this project.
Sign up for this particular next gig.
It's really tough, but I think you can do it.
Take this course, register yourself for this, et cetera.
Now imagine I was super lucky to have these mentors.
I was privileged to have these coaches and these opportunities.
Imagine with AI, we can democratize this privilege, normalize this luck of having amazing mentors and productize it such that every person in the world, in the workforce, has an opportunity to control their destiny.
That is what we are trying to solve with Cornerstone Galaxy and the data richness that we have.
What I think is really exciting about the vision that you share, and I see this gap in a lot of organizations, is that you just described how all of your different components of your product came together across the portfolio.
Where I see so many companies make a mistake in product management is not thinking about how they can leverage their different products together or bring them together to enhance one part of the product with a different one.
How do you think about setting portfolio strategy that way?
And how do you make sure that your teams understand how to think that visionary and think about things being interconnected and build for that?
First and foremost, a deep confession that we all learn by mistakes.
So it is not like we woke up one, they said, oh yeah, they should all be journey mapped up front, you design thinking, et cetera, right?
Those are tools that we embraced as we started dealing with concepts of a portfolio or a collection of products versus a harmony of experiences.
That first and foremost realization that our customers look at it as an end -to -end journey, they look at it as job to be done, they want to be in, out, as much as we want them to engage, as much they are coming there to do what they need to do in the most effective way that they have to do.
So from that particular perspective, first and foremost, that revelation was fundamental to realizing that it has to be a harmony of experience towards delivering a robust outcome for our customers.
So which means that our products have to be highly interoperable, a unified user experience, especially this is, this becomes harder, and this becomes more important by having a fabric that connects all of this both at an experiential layer like common design systems in product management parlance a shared
data layer a unified data structure so that you can use the right data at the right time for the right context and then the right AI framework that transfers across products so a platform mindset a platform thinking becomes very core this is even more important because there are some pivots that we
did where we went from being a wall garden to a playground which means we open our platforms up to our external ecosystem, which means that others have to integrate into this such that the harmony is preserved.
Of course, there will be difference between first -party and third -party experiences, but it has to be seamless and unfragmented.
So that design thinking, end -to -end journey mapping, a common platform layer with the type of design systems, unified data structures, common algorithms for AI, and most importantly, identifying the person as a profile and their journey, and in more recent terms with generative AI, the chain of thought
has become really important in serving that up as a holistic, unified, converged experiences, whilst also staying humble that someone is out -innovating us as I speak right now in our space faster than we are, which means building a platform that can invite ecosystem partners, independent software vendors,
to augment our experiences and things that they do better than we do, yet preserving that holistic nature becomes extremely important.
So that is a big part of our product strategy, our product portfolio management.
For a short period of time, we created that end -to -end product engineering, product marketing, and design teams that just looked at end -to -end that did not own any specific product to build that muscle within that organization and to start thinking about this.
We bought portfolio planning tools that actually busted silos in certain ways because this has to become the ethos of product management and the craftspersonship that we wanted for them.
Then the next piece is it doesn't stop just across the products.
It stops with modalities, which means that you want it.
Our products have all evolved in general from pen and paper to point and click to tap and touch to gaze and hopefully soon enough think.
So your human -machine interaction has dramatically changing, and how we make that pervasive, particularly with generative AI and co -pilots and companions that we are all launching to make sure that is persisted as well.
So these are the two major factors, that platform mindset, and then the multimodality are the two things that we are pretty stringent about its religion to ensure that the end -to -end journey is preserved.
With the platform components of a product, there's always this debate about how much product management do we need on the platform side, right?
Do we need a head of product overseeing that?
Do we need somebody actually thinking about it from a product perspective, or is this all architecture?
What's your philosophy on like platform product management?
It starts with the journey and maturity, right?
I generally have very few one size fits all answer to a lot of these things.
The necessity of a platform is crystal clear, which means that the platform has to be product managed, whether it's product managed by someone called a product manager or it's product managed by someone called a GM of platform, or it's product managed with the right vision, mission, strategy, and objective
by someone who is an engineering lead, I'm indifferent to that.
Org structures are blunt tools.
If you ask me, yes, we need some product management is how we have organized it, but it's a critical part of that product engineering design and product marketing functionality.
And people often forget platforms need product marketing too, because to some customers, particularly in enterprise software, that becomes a big part of the value proposition, especially if you're building at a high velocity or you're acquiring companies that they want seamless integration to.
Putting that aside for a minute, what the platform does and how it serves up experience needs mapping, which means minimally you need an end -to -end product design and a product management specialist who looks at this end -to -end and then organize it to bust, I'm sure you know this better than I do, Conway's
Law. Your organizational design shouldn't be reflected in your product experience.
And again, this is a journey for new products that we built.
This is a journey for some of the acquisitions that you make because they run independently for a period of time, but they all ultimately have to be harmonized yeah if you ask me how i've organized i always have a platform data shared services product management team that ensures that golden threads
use cases inform what they are building so the field of dreams of build it and they will come is is gone and at the same time they are also thinking of one to many use cases rather than one -to -one use cases because then you're going to have a series of stuffed pipes.
I also know this really well because I've screwed up in this space so many times.
And platform is very hard, right?
Sometimes you feel like it's a trade -off in velocity.
Sometimes they become bottlenecked very quickly, etc.
So it is a very thoughtful and intentional approach.
Sometimes just for time to market, you want some mavericks in the team who are building on the side to give a little bit of internal pressure on the pace and velocity of building i couldn't agree more with that i've worked with a company that was transforming to a platform model very similar to what you
were talking about where we've got this central for you that employee and for them it was a different central person but went through all the different products it cut across and we wanted to collect the data on it and we started without they had started without product head on the platform and they
wasted millions of dollars building in the wrong direction like stuff that was not getting consumed by everybody else and there was no strategy for how it was actually going to go back and meet the commercial objectives of any of the other products that we were selling and then we had to go back and we
put a vp of product platform on it and then it just completely changed shifted everything made a very like user -focused mindset with its customers uh mindset and it just shifted everything which was amazing absolutely they even when the companies that have a very robust and clear platform leader more
often than not they think about a producer a consumer model with the platform.
They think about monetization even if they're not a P &L.
They think about it in terms of monetization.
Who's consuming what?
How do I meter it? How do I make sure that I provision and enable it in the most effective way, etc.?
Because ultimately, it is a discipline.
As I said, I get less antsy about whether they report to engineering or the report, immediately they go to where they report into and what is their title versus is that activity done in a thoughtful, intentional way, in such a way that their outcomes and their objectives are extremely clear and aligned
with the rest of the organization.
Otherwise, it becomes a science project.
Yeah, for sure. When you're thinking about the new technologies that are coming out like AI, we talked about that a little bit and all of, there's so many different things that are rapidly changing.
How are you, as the CPO, staying on top of these emerging trends and trying to figure out where do they fit into our product strategy?
It's a great question.
First and foremost, in this particular role and in this particular company, we are just super lucky because that is our product.
If there are others who are trying to get into, hey, what is an AI?
How do I get in front of it?
How is AI changing the world?
think about it. Actually, very distinctive courses that actually talk about, and I'm sure, Melissa, you teach a lot of this as well, is how do you fundamentally reimagine your existing capabilities?
Is it incremental or is it leapfrogging, et cetera, around those kind of the fundamentals of that?
There is a world of opportunity through any learning system and learning content that you have almost certainly making that near mandated, right?
It's self -directed, But making that as important as your compliance training becomes really important.
We have so many customers that have bought this, give me this one -on -one package so that we can upscale quickly our employees by function, right?
Whether it is your accounts receivable and payables analyst trying to automate things that they're doing right now, all the way up to product management, engineering, local and quality, right?
QA, all of that has dramatically been wrapped around.
So, working for a company where we can internalize and drink our own champagne has been hugely helpful where we are thinking through that.
Secondly, as I said, having this plethora of data, the strength in numbers, I had to say that as a Golden State Warriors fan.
Having the strength in numbers is super, super powerful because now you know what the art of possible is with respect to that with the right data scientists, et cetera, and what can be expanded through that.
Now, the most important is then your strategy, right?
How do you bring along the entire team to think about the AI strategy?
And the most difficult thing is how do you bust the tyranny of now?
Your massive backlog in an enterprise software, you have customer commitments, you have fewer releases because you can't push code because they have their own validation systems in our customers, in their endpoints, et cetera.
So how do you balance the tyranny of now?
So our approach is to actually traffic to this.
One is make sure that you have embedded experiences, companion type experiences in all of your products, whether it's your learning product, your talent mobility products, your performance, writing your goals, connecting it, getting baseball cards for each person about them, their structure, their check
-in, summarizing all of that.
Make sure that it is sprinkled in every element of galaxy so we enable all of them with robust, usable, engaging, captivating tools to create that magical experience.
The second is then where do we then promote native experiences?
Where do we ensure that we are reimagining the product relative to the assets that we have right now in a way that others would come and do it if we don't?
So in other words, disrupt your business before someone else does, bust the innovators dilemma, do the double flip, et cetera.
So that is the second piece.
And then the third piece is for your existing experiences, how do you create that overarching usability factor that whether it is multimodal, whether it is personalized, whether it's adaptive, etc.
How do you create that layer on top of it such that it's highly unifying into the next -gen form factor?
So, we call all of these next -gen human experiences.
The one other thing that we've been lucky enough to do is we've been acquiring a couple of companies, very AI -native companies.
While we have a pedigree of about a better part of a decade of doing like AI and generative AI, getting the founders in and having them in our staff and doing some reverse integration is help us re -imagine some of these things.
So we hire, we quite sky have, and we have a little bit of reverse integration on that front, right?
The existing teams have gone there.
We've acquired Tailspin, which is an immersive company.
We're already on the forefront of generative AI for developing human skills, and we have the generative AI product leadership now blend that as well.
So helping us disrupt ourselves has been hugely helpful.
We also do design partnership program.
So our head of design, she organizes with a few hundred customers watching how they work.
This is more than just user groups.
This is more than basic design research.
This is co -opting our customers to co -author the future and also bring their friction points, reduce that as much as possible through existing and the product technologies that we have here.
So it is a journey, but all of this is on the foundation of something that we extremely we solidly believe in, which is responsible AI, responsible technology in general, accessible technology.
So first, so there are five, six ethos that we are really passionate about.
One is privacy and security, goes without saying, but accountability and explainability, which means that if you are making recommendations, how are we accountable to this fact that this recommendation is the right one?
How can we make it explainable in terms of the fact that it mitigates the bias, linguistic mitigations like salesman versus salesperson kind of stuff.
And then human in the loop.
If something needs to get kicked out, it can get kicked out.
So you can set and dial how much you want.
We also have a multi -LLM strategy, a composite LLM strategy to minimize hallucinations and adjust temperature settings.
And lastly, transparency.
We are very open in terms of explaining how we built architecturally and how our AI works.
So that is our broader story.
The platform portion, the innovation, founder mode, so to speak, and deep understanding and intimacy of our customers and their needs.
That's such a comprehensive, amazing approach to it.
You got into a little bit about the ethical sides of AI.
Skills, learning development, especially when you're doing performance reviews in companies?
That's all super sensitive stuff.
So, can you tell me a little bit about what are you doing?
What kind of considerations are you taking into account when you are actually evaluating people's performance or their skills on this area?
What are you keeping in front of mind?
And how are you mitigating the risk on those sides?
This is a great question, Melissa.
First and foremost, as I had mentioned, that the ethos of how we build our AI, our engines, et cetera, privacy, security, explainability, and accountability, human in the loop, and transparency, that permeate through the business processes and the tools and the software that we build.
So that is thing number one.
Thing number two is one of the powers of going from a pure job discretion -based world to a skills -based architecture, it creates a sense of objectivity.
So it creates a sense of very specific, tangible, measurable elements that generally is more bias mitigated than not it's not bias neutralized it's definitely bias mitigated than not so the prompt of how you drive your performance review your check -ins etc is on a basis of skills which means your objective
skill sets what have you done to move the needle on those skill sets how do you rate your proficiency your manager rates their proficiency, what is the outcome that comes out of this, and then your succession planning and career mobility tools then persist those bias mitigation elements and the objectivity
elements into them.
So this common language called skills and rating on basis of these skills and proficiencies actually creates that sense of objectivity, and therefore it makes it explainable, which ties back to our product dealers.
So these two together help us ensure that we are delivering it in the most objective, bias -neutralized fashion as possible.
When we get into talking about AI too, and you mentioned this a little bit with the hallucinations, sometimes we've seen unfortunate stories in the news and stuff when this happens to big companies, right?
Sometimes it's wrong.
So you talked a little bit about the human in the loop.
Tell me a little bit about why that's important and what happens if something comes back as a wrong recommendation, or how do you mitigate that risk there?
Yeah, as I mentioned, that is one of the reasons where we didn't want to put out vanity products, like on like when the wave came through and say, hey, here's a, it's not productivity, but productivity, it's a full.
So we didn't want to do that is because we wanted to spend all the time possible in actually building out a platform that we are actually proud of is defensible.
Some parts of our platform, particularly the SkyHair platform, actually has reversibility as an ethos as well.
What I mean by that is if there is a data source that we shouldn't be using, that we've used all along, the model can untrain or unlearn itself by reversing that data set and the entire thing will be regenerated.
Should those become an important aspect of how we thought about building the underlying AI platform?
Bias mitigation specifically and hallucination mitigation, A, there is temperature setting, B, there is the RAGs that are very specific to the world of HR tech, which makes it hugely helpful, right?
The adage goes that an apple to a tech enthusiast is different than an apple to a fruit farmer or a grocery store vendor.
So that contextuality becomes very important.
Chain of pot becomes very important in all of this.
But active bias mitigation capabilities, active, we are in the content business, right?
So we have content, we have algorithms, AI -powered algorithms that go through the content for hate speech removal, right?
So our ability to actually get into the depths of the content beyond just the descriptors and the metadata, our ability to actually have a composite multi -LLM model with different temperature settings to bias neutralize it, or one of our core strength for the better part of two decades is the fact that we have a robust
workflow. The advantage of a robust workflow is that kickouts become easy to program in.
So from each of these, understanding and taking that feedback loop becomes very important.
And having that workflow, that manual workflow, has been generally the default, right?
Kicking that out becomes that much easier beyond your control parameters that go into that.
One of the reasons why we've been extremely thoughtful and you might even call intentional borderline slope is to ensure that the platform is extremely robust before rushing into a vanity feature.
That's really nice.
It's nice to hear that too, because I saw a lot of people rush into some vanity features if they failed epically.
Absolutely. And to me, that's the worst of both worlds, right?
Like you don't have business outcomes that come out of it.
It is a flash in the pan, nor are you doing it the right way, and you can't put the toothpaste back in the tube at that point in time, right?
So how do you balance both of those?
And we said that we're going to err on this side.
And we didn't take it lightly.
We spoke to both our customers, our prospects, and then folks in different segments of the market to see how they assessed each of this.
That mapped to our own conviction.
We would have still done this, but it also tested properly with our customers.
That's great to hear.
When you're looking at workforce agility over the next couple of years, what are you excited about and what kind of trends are you paying attention to?
Yeah. The first and foremost is this skills revolution, this objective skills taxonomy, or even ontology, whereby the skills and proximity of these skills to each other, that is picking up at a pace that is transformational.
That is an exponential change that is happening in the HR tech, the people business right now, where skills is the coin of the realm, and that makes it very objective.
Number one. Number two is experience.
It's just become this old, as I said, one -size -fits -all experience is gone.
It is the expectation of your next experience is as good or better than the last best experience that you have had.
So the cognitive dissonance that we spoke about between enterprise software companies and their complacencies versus consumer technology companies and their advancements, that is beginning to, essentially, that gap is beginning to close.
But there are also limitations, right?
The fail fast forward, when you are certifying people who can work on a vaccine manufacturer in line, you don't take that lightly.
When pilots can take off and land depending on their training completion, you don't take that lightly.
So you need both the robustness and governance of this, but you also want it in a consumable, spatial, adaptive, conversational, immersive form factor, right?
The next -gen human experience with the robustness of the underlying workflow and data is the next big trend that I think all of us will have to go for.
As I said, pen and paper, point and click, tap and touch, gaze, think we have to compete in that space.
We have 140 million end users, consumers.
I would say we are a consumer -grade company, right?
Like with 140 million users.
The third is connected.
I spoke about this briefly.
The fragmented experience, even with ecosystem partners, is starting to be a friction, right?
So ensuring that it's just not interoperable at a technological level, but it is surfaced up experientially in a most intuitive, logical way with design end -to -end design thinking and journey mapping becomes the third big trend that people are expecting.
This is even more true, and HR tech is unfortunately not high up in the market compared to, say, fintech or where we discussed our mutual backgrounds before, is this openness to ecosystem.
There are still pockets of wall garden, and people think they can solve everything on their own on a monolithic code base, buy everything from us, et cetera, versus buy whatever is best for your company in a way that it seamlessly interoperates with the other products.
that is what the modernness of a thinking that has to be so openness will become more and more pervasive I don't want to set out the obvious but generative AI and the employee experience re -imagination from adaptive learning to deeply personalized coaching this N of one, right?
like I am a unit of one don't just categorize me into a segment or a population, etc.
That in the flow of work conversational HR platforms are dramatically going to come up and more and more this AI unlocking substantial productivity for the HR professional, for the manager, and for the employee is going to come together.
Skills, experience, multimodal experience, connectivity, particularly with the ecosystem and within the products, and then the reimagination through AI are the four big things that I think is going to be at the inflection point of.
That's amazing. It's exciting to hear you talk about that too and how it's all coming together, and especially with what I deal with the product management training, I'm seeing a lot of those trends as well.
So thank you so much, Karthik, for being with us.
If people want to learn more about you, where can they go?
Yeah, cool. Hit me up on LinkedIn, cornerstoneondemand .com.
You'll learn more about Cornerstone Galaxy and everything that I'd said in a more digestible format.
And again, I would love to hear from you and your own guests.
Great. And we will put all of those links in our show notes at productthinkingpodcast .com.
Thank you so much for listening to this episode of The Product Thinking Podcast.
We'll be back next week with another amazing guests.
And in the meantime, send me all your questions to dearmelissa .com and I'll answer them on an upcoming episode.
We'll see you next time.
