In this edition of NovusNorth’s thought leadership conversation, Dave Cowing had the opportunity to speak with Eddie Chin, Product Manager.
Eddie is a veteran product manager with years of experience helping companies define, release and sell their products. He’s worked across the life cycle of product management from strategy and research to design and implementation, as well as business development. He’s helped companies like JP Morgan in financial services, One Call Care in healthcare and many others successfully bring new or dramatically transformed products to market.
NovusNorth is a leading innovator in digital experience and platforms for the financial services industry and provides product management, user experience design, and development services.
Key Takeaways:
This post shares the highlights from the discussion between Dave and Eddie.
Read the Transcript
Dave Cowing
Our topic is the intersection of AI and product management. To get us started, can you share an overview of where AI can add value to product managers and what excites you the most? What are the possibilities that you’re imagining?
Eddie Chin
I think AI has proven itself so far. But there’s more for it to do to be really good at working with and extracting insights from data. I can query data, and I can say, “What’s the trend here and what’s happening here.” I think today’s product owners are very data centric, very specific to what are they seeing, what insights are happening, and how do they manipulate their product or create more value for their products to meet those demands and those insights. I think that product owners have a vested interest in making sure that the data that they get is viewable by AI. Something used as an AI assistant to get those insights and figure out what does their product mean, and how they can take advantage of those insights to make their product more valuable to their users.
Dave Cowing
I love the idea of an AI assistant for the product manager and kind of helping guide that journey, and indeed, that sort of keyword data
Q: Before we drive a little deeper, you mentioned something that got me thinking a little bit. The product manager role is one: defining strategy and executing strategy. But two is evangelizing strategy across a broader organization. How does this notion of AI as an assistant for the product manager tie into efforts across the broader organization?
Eddie Chin
I think that the product organization should draw their insights from the same set of data. There shouldn’t be one set of data that a product owner uses and another set of data that the designer uses, and another set of data that an engineer uses. So being able to say, here’s what we’re seeing, based upon the research we’re doing, and here’s how we think that impacts design. And having the designer be able to say, “Okay, I see that trend and here are other trends that we’re seeing based upon the research we are doing.” Then engineering wise, here’s trends that we’re seeing and how to best build what we’re trying to do. The product owner, in conjunction with the designer and the engineer, can help evangelize all of that throughout all the different groups, all drawing upon the same core set of data, and all being able aligned on where the product is headed. So, I think that the evangelization aspect that you’re that you’re mentioning here, is really not just a product owner saying this is what we do, and everyone just rallying behind it. It’s, here’s what the data is saying. You go prove it to yourself. This is where I think we’re heading. Do you agree with me? Let’s all rally there together. Much more collaborative, much more allowing everyone to be able to kind of see for themselves. Which I think kind of buys mind share much more quickly.
Dave Cowing
I’ve long believed the programmers should have direct access to the users, not to replace whoever’s talking to them, but to better understand, because everybody in that in that ecosystem, is making decisions.
Eddie Chin
I agree with you; it would be nice for everyone to be at the same place at the same time. That’s really, really hard. So one way that you can accomplish that, is to have representation from each discipline, go along for the ride. And that’s why the triumvirate of product owner, product designer, engineer, works out well. But yeah, engineers, the developers, everyone should be able to draw upon that data set and draw upon that understanding. You have no idea how many times back in the early days, you know a developer come to say, why are we doing it this way? What was the intent, and what’s the user? And that’s part of what design does these days, part of their role is to create designs that would communicate the intent, not just so the user understands what to do, but also so the developer can build what the designer is trying to have the user do. So they can talk to that developer and communicate that mindset. That’s an added step. Whereas if that developer were part of the of the research, part of the data gathering, and have access to that data in the very beginning, you probably have more insights and more people on board, much earlier.
Dave Cowing
So, you get buy in along the way, as well as better decision making for all the myriad of decisions that everybody’s making as you go through a program.
Q: Pivoting to something that you and I were talking about before. What is the interaction between an AI assistant and a coach, and how that has to work for it to be effective and actually help the product manager not just deliver a great product, and, by extension, the designers, the developers, but also enable that product manager to grow and become a better product manager?
“AI is most effective when it plays a coaching role.”
– Eddie Chin
“AI is most effective when it plays a coaching role.”
– Eddie Chin
Eddie Chin
This is where AI improvements come into play. I think AI is most effective when it plays a coaching role. Having an AI, and I don’t think we’re there yet, be able to understand who that AI is talking to or interacting with and providing guidance based upon that persona, which I think would be very helpful in helping the team coalesce. Because the AI is able to say, I know you’re a designer, so here are the some of the usage trends that we’re seeing with the interactions that users are having with this application. I know that you’re a front-end developer, so here are some of the errors that we’re seeing popping up based upon the customer service calls that are coming in. Then for the product owner, here are the questions that people are asking; why doesn’t this feature exist, or why doesn’t it do this?
I think that, down the road, the AI coaching mechanism of being able to take in the Persona and being able to kind of give that insight, give insight and guidance with relevance to that persona will augment what everyone is doing and be able to augment the decisions they’ll be able to contribute and make. Right now, if I just take this data, product owner, may come to the same conclusion as a designer, as an engineer. But what if you presented a piece of data and a set of trends and insights, that are very specific to the role. Now you’re talking about bringing in multiple ideas, being able to work them together and all probably for the same problem.
Dave Cowing
It becomes, by definition, not just more collaborative but you can get through more of these tight iterations and get more interesting ideas and perspectives injected into the ultimate outcome.
“We’re democratizing product ownership by involving lead designers and developers in decision-making rather than relying on a hub-and-spoke model.”
– Eddie Chin
“We’re democratizing product ownership by involving lead designers and developers in decision-making rather than relying on a hub-and-spoke model.”
– Eddie Chin
Eddie Chin
Right, you’re actually democratizing the product ownership a bit. You’re presenting that product ownership responsibility to the lead designer, to the lead developer, so that they can also improve the product along with you. It’s not this hub and spoke mentality of there’s only one product owner and that product owner’s decisions kind of go out this way. It’s a collaboration of the product decisions that we should be making. I think there’s this engineering decision to make, which, unless the engineer brings that up, it’s likely the product owner doesn’t even know the decision needs to be made. And so being able to bring that up so that the group can properly prioritize them, I think makes for a better product.
Dave Cowing
If you look at a lot of big, scaled product organizations, they’ve sort of micro-fragmented roles, so you might have research ops, and you’ve got research, and even within there, you’ve got researchers doing strategic research and testing, and then you’ve got designers, design production and design ops and so one. You’ve got all these different roles that have been sort of fragmented and specialized and live in smaller compartments. Does what you’re saying reverse that trend to say all people need to think a little more holistically. Does it become the glue? How does it affect some of those org models we’ve been seeing evolve?
Eddie Chin
Two points there. First, if you’re in a product org, wherever you are in that product org, whether you’re DevOps, design ops, build, design, or research, your job is to help sell that product. That’s really how it works. So, your job is to help figure out how to make this product better so that everyone can benefit from it. I think that we should already have that mindset of everyone is helping make this product better. We may be fragmenting it, and there may be specialists, but those specialists have the same goal as everybody else, which is helping make the product better. Second, I think that we are fragmenting it a little bit, where it makes it hard to get everyone on the same page. Until we’re all accustomed to it, it’s probably best to start with the leadership level, like the lead engineer and the lead designer, and as those design ideas come up, it should be up to the lead designer to be able to share the right data with their team, so they can come up with ideas and insights too, that funnel up to the lead designer. There’s going to have to be some practice in communicating within the design group, within the engineering group and within the product ownership group for the time being, until we can get to the point where communication tools start beaming ideas into my brain so that we can all think as a collective. I think we’re just going to have to get really good at communicating within our teams and funneling that through the through the lead levels.
Dave Cowing
How should product managers be thinking about the evolution of the role, skills they need to build to be successful with the use of AI assistants?
“The product organization should draw their insights from the same set of data to align design, engineering, and product decisions collaboratively.”
– Eddie Chin
“The product organization should draw their insights from the same set of data to align design, engineering, and product decisions collaboratively.”
– Eddie Chin
Eddie Chin
A, I think that we should all get used to working with data, understanding where it’s stored in our work, figuring out how to get to it and how to pull what we need from it, and what it means when we pull specific pieces of data, what that data represents. B, we should start getting used to having AI not make decisions for us but be coaches and guides with us. Let’s take that data that we have, feed it into an AI engine and let that AI engine churn the turn those numbers and churn that data and help us understand what’s happening. I think a lot of people think about getting this data, they have to understand how to work with it. That’s not necessarily true. If there’s something that you don’t understand about it, it’s distinctly possible that you can use prompt engineering figure out a way to tell an AI to understand it for you and get those answers, and that helps you learn with the two. So, there’s getting the data, there’s being comfortable with having AIs be coaches to help guide and churn that data and being able to work with AI to help draw those insights out for you. So those are the skills I think everyone needs.
“AI assistants should help product managers churn data, understand trends, and draw insights, acting as coaches, not decision-makers.”
– Eddie Chin
“AI assistants should help product managers churn data, understand trends, and draw insights, acting as coaches, not decision-makers.”
– Eddie Chin
Dave Cowing
Looking beyond the product manager and into the team itself, what skills does the product manager need to add to the team, add people to the team and think about? It sounds like it’s not just the product manager evolving, but new ways of working for the team.
Eddie Chin
For a long time, I’ve held roles like program manager and engagement lead, and I think that those roles are as much about organizing the group as making sure the group hit certain milestones. I think that that those skill sets are now necessary, if you will, for product owner. In orgs that I’ve seen where there was a program manager or a project lead and a product owner, the product owner simply made decisions on what the product should do, and it was up to the program manager to make sure it got done and evangelize it. I think now you’re seeing a combination of those two take effect, where the product owner needs to be that person that communicates why we’re doing something and what needs to be done and how it should be done, potentially, with the help of a program manager. But those kind of soft skills of rallying the group and bringing that group together and collaborating with them. I think a lot of those soft skills are now transitioning over to the product owner or product manager role to be able to coalesce the whole group and get them to collaborate together.
About The Experts
Eddie Chin
Product Manager
Eddie Chin is a seasoned product leader with over 20 years of experience in the financial services industry. He specializes in building and scaling innovative products, driving user-centric solutions, and leading cross-functional teams to deliver exceptional business outcomes. Known for his strategic vision and operational expertise, Eddie consistently aligns product development with organizational goals to create impactful solutions. He holds a degree in Mechanical Engineering from the Rensselaer Polytechnic Institute.
Dave Cowing
Chief Executive Officer, NovusNorth
NovusNorth is an outcome-oriented experience consultancy that drives business results by creating compelling experiences for customers and employees in the fintech and financial services industry. Dave has 30 years of experience helping companies ranging from Fortune 500 market leaders to disruptive startups envision and create new digital product experiences that drive meaningful outcomes.
In this edition of NovusNorth’s thought leadership conversation, Dave Cowing had the opportunity to speak with Eddie Chin, Product Manager.
Eddie is a veteran product manager with years of experience helping companies define, release and sell their products. He’s worked across the life cycle of product management from strategy and research to design and implementation, as well as business development. He’s helped companies like JP Morgan in financial services, One Call Care in healthcare and many others successfully bring new or dramatically transformed products to market.
NovusNorth is a leading innovator in digital experience and platforms for the financial services industry and provides product management, user experience design, and development services.
Key Takeaways:
This post shares the highlights from the discussion between Dave and Eddie.
Read the Transcript
Dave Cowing
Our topic is the intersection of AI and product management. To get us started, can you share an overview of where AI can add value to product managers and what excites you the most? What are the possibilities that you’re imagining?
Eddie Chin
I think AI has proven itself so far. But there’s more for it to do to be really good at working with and extracting insights from data. I can query data, and I can say, “What’s the trend here and what’s happening here.” I think today’s product owners are very data centric, very specific to what are they seeing, what insights are happening, and how do they manipulate their product or create more value for their products to meet those demands and those insights. I think that product owners have a vested interest in making sure that the data that they get is viewable by AI. Something used as an AI assistant to get those insights and figure out what does their product mean, and how they can take advantage of those insights to make their product more valuable to their users.
Dave Cowing
I love the idea of an AI assistant for the product manager and kind of helping guide that journey, and indeed, that sort of keyword data
Q: Before we drive a little deeper, you mentioned something that got me thinking a little bit. The product manager role is one: defining strategy and executing strategy. But two is evangelizing strategy across a broader organization. How does this notion of AI as an assistant for the product manager tie into efforts across the broader organization?
Eddie Chin
I think that the product organization should draw their insights from the same set of data. There shouldn’t be one set of data that a product owner uses and another set of data that the designer uses, and another set of data that an engineer uses. So being able to say, here’s what we’re seeing, based upon the research we’re doing, and here’s how we think that impacts design. And having the designer be able to say, “Okay, I see that trend and here are other trends that we’re seeing based upon the research we are doing.” Then engineering wise, here’s trends that we’re seeing and how to best build what we’re trying to do. The product owner, in conjunction with the designer and the engineer, can help evangelize all of that throughout all the different groups, all drawing upon the same core set of data, and all being able aligned on where the product is headed. So, I think that the evangelization aspect that you’re that you’re mentioning here, is really not just a product owner saying this is what we do, and everyone just rallying behind it. It’s, here’s what the data is saying. You go prove it to yourself. This is where I think we’re heading. Do you agree with me? Let’s all rally there together. Much more collaborative, much more allowing everyone to be able to kind of see for themselves. Which I think kind of buys mind share much more quickly.
Dave Cowing
I’ve long believed the programmers should have direct access to the users, not to replace whoever’s talking to them, but to better understand, because everybody in that in that ecosystem, is making decisions.
Eddie Chin
I agree with you; it would be nice for everyone to be at the same place at the same time. That’s really, really hard. So one way that you can accomplish that, is to have representation from each discipline, go along for the ride. And that’s why the triumvirate of product owner, product designer, engineer, works out well. But yeah, engineers, the developers, everyone should be able to draw upon that data set and draw upon that understanding. You have no idea how many times back in the early days, you know a developer come to say, why are we doing it this way? What was the intent, and what’s the user? And that’s part of what design does these days, part of their role is to create designs that would communicate the intent, not just so the user understands what to do, but also so the developer can build what the designer is trying to have the user do. So they can talk to that developer and communicate that mindset. That’s an added step. Whereas if that developer were part of the of the research, part of the data gathering, and have access to that data in the very beginning, you probably have more insights and more people on board, much earlier.
Dave Cowing
So, you get buy in along the way, as well as better decision making for all the myriad of decisions that everybody’s making as you go through a program.
Q: Pivoting to something that you and I were talking about before. What is the interaction between an AI assistant and a coach, and how that has to work for it to be effective and actually help the product manager not just deliver a great product, and, by extension, the designers, the developers, but also enable that product manager to grow and become a better product manager?
“AI is most effective when it plays a coaching role.”
– Eddie Chin
“AI is most effective when it plays a coaching role.”
– Eddie Chin
Eddie Chin
This is where AI improvements come into play. I think AI is most effective when it plays a coaching role. Having an AI, and I don’t think we’re there yet, be able to understand who that AI is talking to or interacting with and providing guidance based upon that persona, which I think would be very helpful in helping the team coalesce. Because the AI is able to say, I know you’re a designer, so here are the some of the usage trends that we’re seeing with the interactions that users are having with this application. I know that you’re a front-end developer, so here are some of the errors that we’re seeing popping up based upon the customer service calls that are coming in. Then for the product owner, here are the questions that people are asking; why doesn’t this feature exist, or why doesn’t it do this?
I think that, down the road, the AI coaching mechanism of being able to take in the Persona and being able to kind of give that insight, give insight and guidance with relevance to that persona will augment what everyone is doing and be able to augment the decisions they’ll be able to contribute and make. Right now, if I just take this data, product owner, may come to the same conclusion as a designer, as an engineer. But what if you presented a piece of data and a set of trends and insights, that are very specific to the role. Now you’re talking about bringing in multiple ideas, being able to work them together and all probably for the same problem.
Dave Cowing
It becomes, by definition, not just more collaborative but you can get through more of these tight iterations and get more interesting ideas and perspectives injected into the ultimate outcome.
“We’re democratizing product ownership by involving lead designers and developers in decision-making rather than relying on a hub-and-spoke model.”
– Eddie Chin
“We’re democratizing product ownership by involving lead designers and developers in decision-making rather than relying on a hub-and-spoke model.”
– Eddie Chin
Eddie Chin
Right, you’re actually democratizing the product ownership a bit. You’re presenting that product ownership responsibility to the lead designer, to the lead developer, so that they can also improve the product along with you. It’s not this hub and spoke mentality of there’s only one product owner and that product owner’s decisions kind of go out this way. It’s a collaboration of the product decisions that we should be making. I think there’s this engineering decision to make, which, unless the engineer brings that up, it’s likely the product owner doesn’t even know the decision needs to be made. And so being able to bring that up so that the group can properly prioritize them, I think makes for a better product.
Dave Cowing
If you look at a lot of big, scaled product organizations, they’ve sort of micro-fragmented roles, so you might have research ops, and you’ve got research, and even within there, you’ve got researchers doing strategic research and testing, and then you’ve got designers, design production and design ops and so one. You’ve got all these different roles that have been sort of fragmented and specialized and live in smaller compartments. Does what you’re saying reverse that trend to say all people need to think a little more holistically. Does it become the glue? How does it affect some of those org models we’ve been seeing evolve?
Eddie Chin
Two points there. First, if you’re in a product org, wherever you are in that product org, whether you’re DevOps, design ops, build, design, or research, your job is to help sell that product. That’s really how it works. So, your job is to help figure out how to make this product better so that everyone can benefit from it. I think that we should already have that mindset of everyone is helping make this product better. We may be fragmenting it, and there may be specialists, but those specialists have the same goal as everybody else, which is helping make the product better. Second, I think that we are fragmenting it a little bit, where it makes it hard to get everyone on the same page. Until we’re all accustomed to it, it’s probably best to start with the leadership level, like the lead engineer and the lead designer, and as those design ideas come up, it should be up to the lead designer to be able to share the right data with their team, so they can come up with ideas and insights too, that funnel up to the lead designer. There’s going to have to be some practice in communicating within the design group, within the engineering group and within the product ownership group for the time being, until we can get to the point where communication tools start beaming ideas into my brain so that we can all think as a collective. I think we’re just going to have to get really good at communicating within our teams and funneling that through the through the lead levels.
Dave Cowing
How should product managers be thinking about the evolution of the role, skills they need to build to be successful with the use of AI assistants?
“The product organization should draw their insights from the same set of data to align design, engineering, and product decisions collaboratively.”
– Eddie Chin
“The product organization should draw their insights from the same set of data to align design, engineering, and product decisions collaboratively.”
– Eddie Chin
Eddie Chin
A, I think that we should all get used to working with data, understanding where it’s stored in our work, figuring out how to get to it and how to pull what we need from it, and what it means when we pull specific pieces of data, what that data represents. B, we should start getting used to having AI not make decisions for us but be coaches and guides with us. Let’s take that data that we have, feed it into an AI engine and let that AI engine churn the turn those numbers and churn that data and help us understand what’s happening. I think a lot of people think about getting this data, they have to understand how to work with it. That’s not necessarily true. If there’s something that you don’t understand about it, it’s distinctly possible that you can use prompt engineering figure out a way to tell an AI to understand it for you and get those answers, and that helps you learn with the two. So, there’s getting the data, there’s being comfortable with having AIs be coaches to help guide and churn that data and being able to work with AI to help draw those insights out for you. So those are the skills I think everyone needs.
“AI assistants should help product managers churn data, understand trends, and draw insights, acting as coaches, not decision-makers.”
– Eddie Chin
“AI assistants should help product managers churn data, understand trends, and draw insights, acting as coaches, not decision-makers.”
– Eddie Chin
Dave Cowing
Looking beyond the product manager and into the team itself, what skills does the product manager need to add to the team, add people to the team and think about? It sounds like it’s not just the product manager evolving, but new ways of working for the team.
Eddie Chin
For a long time, I’ve held roles like program manager and engagement lead, and I think that those roles are as much about organizing the group as making sure the group hit certain milestones. I think that that those skill sets are now necessary, if you will, for product owner. In orgs that I’ve seen where there was a program manager or a project lead and a product owner, the product owner simply made decisions on what the product should do, and it was up to the program manager to make sure it got done and evangelize it. I think now you’re seeing a combination of those two take effect, where the product owner needs to be that person that communicates why we’re doing something and what needs to be done and how it should be done, potentially, with the help of a program manager. But those kind of soft skills of rallying the group and bringing that group together and collaborating with them. I think a lot of those soft skills are now transitioning over to the product owner or product manager role to be able to coalesce the whole group and get them to collaborate together.
About The Experts
Eddie Chin
Product Manager
Eddie Chin is a seasoned product leader with over 20 years of experience in the financial services industry. He specializes in building and scaling innovative products, driving user-centric solutions, and leading cross-functional teams to deliver exceptional business outcomes. Known for his strategic vision and operational expertise, Eddie consistently aligns product development with organizational goals to create impactful solutions. He holds a degree in Mechanical Engineering from the Rensselaer Polytechnic Institute.
Dave Cowing
Chief Executive Officer, NovusNorth
NovusNorth is an outcome-oriented experience consultancy that drives business results by creating compelling experiences for customers and employees in the fintech and financial services industry. Dave has 30 years of experience helping companies ranging from Fortune 500 market leaders to disruptive startups envision and create new digital product experiences that drive meaningful outcomes.
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