[00:00:08] Lauren Burke: Welcome to Women in Analytics After Hours, the podcast where we hang out and learn with the WIA community. Each episode, we sit down with women in the data and analytics space to talk about what they do, how they got there, where they found analytics along the way, and more. I'm your host, Lauren Burke, and I'd like to thank you for joining us.
Today, we have Jen Tedrow joining us. Jen is the Executive Director at Pathfinder Product. She is an extremely accomplished product leader with over 10 years of experience across a diverse range of industries and within a diverse range of companies from early stage startups to Fortune 500s.
As the Executive Director at Pathfinder Product, Jen leads a team of product managers while helping clients achieve successful business outcomes. She has joined us today for a very interesting conversation. We're going to talk about Data as a Product and some of the exciting things that they have going on at Pathfinder Product.
So thank you so much for joining us, Jen. I'm very glad to have you here with us.
[00:01:22] Jen Tedrow: Thanks so much for having me, Lauren. I'm excited to talk to you today.
[00:01:25] Lauren Burke: Absolutely. And so just to get things started, could you give us a quick overview of your background, career journey, and the path that's led you to product and product management?
[00:01:35] Jen Tedrow: Yeah. Yeah, definitely. I have been in product management, like you mentioned for over 10 years now. And, it's, it's been funny cause I love hearing people's path to product because for those of us that have been in there for a while, it's usually an interesting story. You know, now there's a little bit more, uh, colleges that are offering degree programs in product management, but for us, um, old school PMs, that was not the case.
So, for me, I started out in more client facing roles and then I became really interested in learning some additional skills to help better support my clients, which led me to, um, a role as a waterfall business analyst. And then from there I landed a role in a company where they wanted to try this new thing called product management. And, um, so I knew nothing about it. So I learned everything I possibly could about it. And I absolutely fell in love with it. I was a much better, more satisfying approach to doing what I was doing as a business analyst, but in a more customer centric way with my roots, you know, coming from that more client facing background that really resonated with me, um, and the empathy about it.
And I also ended up in a lot of data product management roles. And I've always loved working with data. So combining those two has been really satisfying. And like you mentioned, I've had a great opportunity to work in lots of different interesting industries like transportation management, retail, healthcare IT. Um, and I've done really super tiny startups and Fortune 500 companies. So it's been a really interesting ride.
[00:03:09] Lauren Burke: That's awesome. And you've already kind of connected what we are really here to talk about today, which is Data as a Product. Which honestly, in many industries is still a pretty new topic and mindset. So can you just share what it means to think of data as a product?
[00:03:27] Jen Tedrow: Yeah, definitely. There has been so much discussion about this. And I've been just getting more involved in groups that are working on defining it, talking about it. And it seems like there's a lot of nuance and people have different perspectives. But for me, um, especially when I'm talking about people on our The State of Data as a Product in the Real World survey and study. That's usually actually the first question that I would get asked, even if it's somebody who, you know, their whole world is around data as a product. Um, they're like, what exactly do you mean by data as a product?
And we actually do start off the survey with a quick overview about that. And the way we explain it is it represents a paradigm shift where data is not viewed as merely a byproduct of business operations, but a valuable asset. And this concept calls for planning, strategizing, and employing specific tactics to enhance the quality, accessibility, and usability of data. The primary purpose of data as a product really is to maximize its utility. And this could include supporting internal decision making processes, product development, data products such as dashboards or AI and ML models, or generating revenue through data monetization.
Um, the other thing I've found is that a lot of people tend to confuse data as a product with data products, and I think that they're similar and related, but I look at them a little bit differently. And this came up on the panel and the way I explained it was. Data as a product involves ensuring the data is fit for its intended use and the data product is the mechanism for utilizing that fit for use data.
[00:04:59] Lauren Burke: That's so interesting. I like that you are able to break it out because I think some of the terminology is where people are really getting stuck as they're trying to introduce this type of mindset and this type of process in their organizations. So what are some of the things that you think people should be doing, organizations should be doing as they begin to approach data as a product and invest in it?
[00:05:23] Jen Tedrow: Yeah, that's a great question. Um, it's funny because Cassie Kozyrkov, who was the keynote speaker at the conference, she just posted this really great piece on Medium the other day called Data: A Hoarder's Storage Locker, Not a Magical Museum. Great title. Um, and I love that article so much, because it basically called out that data is, um, more data is not going to necessarily result in more value because all of that data may be accumulated just in case it may not be well documented, understood or fit for use.
And I think a lot of us can relate to that challenge, you know, and making data fit for purpose or fit for use definitely takes resources, which means it's an investment. So it really should be tied to outcomes and measured, um, the value should be measured and people should really prioritize that investment where they're going to get the most bang for their buck. You can't eat the elephant all in one bite. You have to do it one bite at a time. So you really should, you know, make sure that it's valuable data that you're prioritizing when you're, when you're trying to make it fit for use. And a lot of this effort will require buy in, especially for companies that are just kind of, you know, migrating towards this mindset from those who hold the purse strings and they may not be necessarily those that understand what that tactically entails.
And Wendy Batchelder said on the panel, and I just, I love this so much. She said, remember, you're a business leader first and a data professional second. And I, I just, I love that because. The folks that I have worked with on the data side who have been business minded are really good at helping folks understand that, you know, there's, there's a lot of value tied to the data and connecting that back with business objectives and how it can help accelerate decision making and all the value that, that you can get from that in a way that resonates with that audience, they're going to have the best um, outcomes, I think, and they're going to be able to make the best, um, changes for their organization in order to get to that place where you can treat data as a valuable asset.
[00:07:31] Lauren Burke: That is so true at the core. Good data makes good data products and good data and good use of that data makes good outcomes.
[00:07:39] Jen Tedrow: Absolutely.
[00:07:40] Lauren Burke: I love everything you just said because a lot of it comes back to basically the principle that we hear a lot in machine learning, right? Garbage in means garbage out. And I think we need to really bring that focus to our data.
And when we're not modeling, when we're not doing predictive analytics, when we're doing any type of analysis with our data. And thinking about it instead of bad predictions as being bad outcomes, bad analyses.
[00:08:06] Jen Tedrow: Yep. Yeah, I love that. That makes so much sense to me as a product manager from my mindset. Yes, that resonates a lot.
[00:08:14] Lauren Burke: Yeah, I think there's a lot of overlap between product and data analysis, the data people. So I love just data as a product as a whole, because this mindset is definitely bringing us closer together. Not just in how we work and how we work together, but how we think about things.
And I think it's really going to help people align on some of the things that you mentioned as being the core values, right? What's success? What are the outcomes? What is the business value that you're going to get as a business leader, as a data person?
[00:08:45] Jen Tedrow: Yep. Agree completely.
[00:08:47] Lauren Burke: That's awesome. And so what are some of these benefits that we can see as people start to adapt a data as a product mindset?
[00:08:56] Jen Tedrow: Yeah, yeah, I love this question. And I refer back to Gartner on this because it's one thing for me to say it. And I do have some experience. And I actually agree with a lot of what Gartner is touting. They're saying that, you know, companies that invest in treating data as a product will have so many benefits.
And I've seen this in action myself, um, such as I think the probably one of the bigger ones is improved decision making. When your data is accurate, it's reliable and up to date, you can have better decision making and quicker decision making across an organization, you can increase customer satisfaction, reduce your costs, enhance your ability to innovate, improve compliance, which is really important specifically in, in particular, uh, industries that are highly regulated. And have increased agility. And that's really important. And from my perspective, what I've seen is that companies that really invest in treating their data as a valuable asset rather just than a byproduct, um, I've seen, like, amazing increased speed to market with valuable data products. Which is so beneficial to the, to the organization as a whole.
[00:10:02] Lauren Burke: And one of the things that I know we mentioned a lot with analytics and data organizations is the maturity. So as you're thinking about getting into those higher levels of maturity, the predictive, the prescriptive analytics, how does data as a product benefit that?
[00:10:17] Jen Tedrow: Yeah. When we're thinking about things like that, like ML, like AI. I, I honestly think this is why the concept of data as a product is gaining such traction. I think organizations are just itching to take advantage of AI and ML, um, and predictive analytics and all of that.
And they're realizing that to do so, they need high quality data for those models. Like you said, garbage in, garbage out, right? And we did touch on this on the panel as well. You know, they can't do, uh, these wonderful things with data without a solid data foundation. So they do need to make these investments. And they're starting to realize as they're digging in without, you know, having the good foundation that they originally may have thought it's easy and cheap, um, because, you know, they, they play with chat GPT and they're like, this is easy.
Um, but then when they're trying to leverage their own data, internally in a secure way, it's a lot more challenging when they haven't taken the necessary preliminary steps to make that data fit for purpose.
[00:11:17] Lauren Burke: So it sounds like a big part of it is really focusing on how you're getting started and understanding the value of your data and the potential of the data.
[00:11:27] Jen Tedrow: Yeah, absolutely. And I think that's a critical way to start. And I think that that's a pitfall that not every, certainly not every company, but some companies may fall into. Is wanting to rush to leverage the latest, you know, shiny new thing. And without really having a clear understanding of the value or the desired outcome that they're trying to work towards, then they flail and when you're grounded in a, in a solid why and desired outcome, it's a lot easier to stay on the right path and make sure that you're investing in the right things, course correct when things go a little haywire, which, you know, they probably will at some point.
Um, but if you know what you're working towards and you can measure, your, your progress on the way. We're data driven people so, you know, and that also helps the folks on the ground be able to support the organization as a whole better as well.
[00:12:20] Lauren Burke: Absolutely. And I know that's something you do at your organization, Pathfinder Product, is helping people understand how they can think of data as a product and use their data and make sure that they're getting all of the value possible out of it.
[00:12:36] Jen Tedrow: Yeah. Yeah. We, we do. Pathfinder is really interesting, because it's, it is a consulting company. Which, you know, I was a little, uh, honestly reticent about at first. I had to, you know, fully understand it because I've heard, you know, about consulting companies that kind of throw bodies at any open position.
And I was like, that's definitely not for me. Um, Pathfinder is different because it's only focused on product management and we have a great team of very, very talented individuals. It's, it's honestly, it's tough to hire really solid product management, uh talent. And we have a lot of folks that have varying levels of experience. But you know, for the most part, very senior.
And, and there's folks that have expertise in different areas. I'm kind of known as the data girl. Uh, but we have folks that even have hardware product management expertise as well. And folks that are very well versed in behavioral design and folks that are very great at coaching and upskilling. And so it's, it's awesome because it's a team that has a common passion for product. And we are very invested in helping each other improve and always learning is one of our core values, which we take our core values very seriously.
And it's a great place to be a product manager, grow in your career, learn more from honestly, some of the best talent, product talent in Columbus. And we've just been so fortunate to work with amazing brands, amazing clients and do some really fun, innovative work.
[00:14:18] Lauren Burke: That's so cool. I love that it sounds like your organization is thinking about all of the different ways that industries can consider something to be a product. Because I think the definition, it seems really simple, but when you think about it, so many things, if we want to consider them that way, can be considered and approached as being a product.
[00:14:41] Jen Tedrow: Yeah, I think so. And a lot of it just, I'm going to oversimplify maybe a little bit. But a lot of it does have to do with what we had talked about just a few minutes ago. It's really thinking about the why and the what you want to achieve, what that desired outcome is. And figuring out what your leeway is to experiment to get there, which that varies depending on the organization.
But, um, you can really apply that approach in a lot of different use cases and scenarios. And we've gotten pretty clever and we've leveraged a lot of different frameworks that are out there and help each other kind of identify what works best and what scenario. But usually it's grounded in that outcomes based approach.
[00:15:26] Lauren Burke: That makes a lot of sense. How much does a design-thinking approach, design-thinking mindset, play into that?
[00:15:33] Jen Tedrow: I think it does quite a bit. I think that when you're thinking about design thinking, a lot of that comes from just really understanding, again, what you are trying to achieve and the best way to achieve it. And I think you can really, I think of design thinking, maybe this is my own personal spin on it, but sort of like, agile. The right way to think about agile in my mind is not to take it very seriously, um, and prescriptively, but be more adaptive and flexible and look at it as these are tenants to kind of navigate by and apply them to a situation knowing, you know, constraints and dependencies that may be in mind.
And so I think if you understand kind of the principles, the main principles. Of understanding how to work with an audience, um, and what their needs are and how to get the best and most out of them. You can really do a lot and get to a really good outcomes by just being very empathetic, I guess, and understanding of that.
[00:16:41] Lauren Burke: Yeah, I know that's something we definitely touched on at the conference a lot. The DataConnect Conference that was held early this year in July. But when you start to think of things as a product, you really start thinking of the empathy and the human centered design approach, where you're really considering who this is for, who it will benefit, who will it affect if you make certain changes or if you add certain features. Which I think is really useful because so much of what we do when we're working with data is trying to find an outcome, trying to determine a result because of some decision we'll make or because of some effect it will have on someone.
[00:17:22] Jen Tedrow: Yeah. Yeah. One of the members are on our team, uh, Dom Michalec, he is an amazing, uh, just an amazing person all around, but he has a great experience in behavioral design and I've learned so much from him and just really understanding things like BJ Fogg's model, um, motivation, ability, and trigger.
There's so much you can unpack when you really just think about that, even from a data perspective. If you want somebody to really understand or contribute more to data documentation, how do you make it easy? How do you motivate them to do it? How do you give them the ability to do it?
And how do you trigger them to make sure that they're thinking about that as part of their workflow? I mean, these are principles that I think anybody would benefit from understanding and applying, um, if they want to get good results, especially when they're working with a cross functional team.
[00:18:11] Lauren Burke: Absolutely. Are those kind of principles things you're considering and thinking of as you are working with your clients at Pathfinder?
[00:18:19] Jen Tedrow: Yes, absolutely. Typically, you know, clients are coming to us because, uh, there could be several reasons. Like I mentioned, some clients, they have a great product team, but they're, maybe they're a little bit more junior in their career. And they're looking for some help upskilling them. Maybe their senior leadership is really involved with things like budgeting and you know, like the more tactical administrative side of strategic planning. And they really want to invest in their team. And they would like more time to do that. And they realized that if getting some outside coaching is the best thing for them.
And sometimes it's very tactical and we're a player coach where we're coming in and actually doing the product management work and helping to model good behaviors as well.
Sometimes we're actually recruiting and helping folks find a good permanent team member. So it really, it really varies, but we seek to understand what, again, the client's desired result is, and sometimes they need help really articulating that so we can help them do that as well.
We do everything from the early, super early discovery work to really validate, is this the right, is this the right direction to go? Um, how do we validate that? How do we course correct that? How do we find the right things to measure as we go? And really help them get set up for long term success.
That's one of our, that's one of our really like core tenets is to leave a client better than we found it. We don't want to be there forever. We don't want to, you know, be a long term, um, crutch for a client necessarily. You know, we definitely have had longer term engagements for sure, but ultimately, we're looking at how do we get them set up for very like long term success.
So when we leave, they're in a really good spot and they have as much support and knowledge to see it through on their own.
[00:20:10] Lauren Burke: That's awesome. And I know you currently have a pretty big project going on at Pathfinder that we at DataConnect are actually partnering with you on. Could you share a little bit more about that?
[00:20:22] Jen Tedrow: Yes, absolutely. We are so excited and thrilled to be partnering with Women in Analytics and the DataConnect Conference. It was actually, uh, Ben Blanquera's idea. When I told him that I had this idea for a study. I was like, you know, I get being on this panel and in a lot of the work that I've done recently with, with clients, very interested in data as product, and there's really nothing out there that has looked at what's the current state of the real world. How are companies investing in this? You know, what's the lay of the land essentially? And, um, I was like, you know, I think I want to look at that.
I think you know, that's something that I would like to like to dig into. And Ben said, well, you should partner with the conference. That that would be great. It's you know, it's the theme of the conference, and we should keep that conversation going. And I couldn't believe I didn't think of it myself, but credit to Ben. That was his idea. I'm glad he had it. And so yeah, we got together and we decided that this was something that we were going to pursue. And we really put a lot of thought and effort into getting this study designed. The survey is the first part of it. And we really want to understand, you know, how and if companies are investing in data as a valuable asset, how data strategy decisions are made.
Um, data funding and investment trends and models. That's huge. We just talked about that. You know, it's a big, it's a big investment. How are these funding and investment decisions being made? Uh, and things like data teams, organizational structures. I, I've just from my own personal observation, that really makes a big difference into the ultimate success of an initiative, especially data initiatives. And the challenges, opportunities and impact and value. So it's it is a longer survey. It's pretty broad, but I think that there's a lot we can learn together, and it's really great to just kind of keep the momentum from the conference going around this topic.
[00:22:16] Lauren Burke: That's awesome. And so the full survey is actually called The State of Data as a Product in the Real World. And so I know there is a big focus on a lot of the things that you just mentioned, the real world, the industries, how people are using data as a product, thinking about it, investing in it.
So what are some of the things that you are really hoping to learn from this? What are some of the decisions you think people can make after looking at the results?
[00:22:41] Jen Tedrow: Yeah. We really, like I mentioned, tried to make it super comprehensive, cover a range of issues from strategy formation, implementation challenges. Um, really our goal is to paint a pretty broad picture of how organizations view, use, invest in, and derive value from data. And really kind of make the results valuable for a really diverse set of stakeholders.
So, when thinking about that, um, we would love to have it be leverageable for helping executives and decision makers understand the landscape of data utilization. And focus on where they can best invest resources, see evolving data strategies and prioritize decision making processes around data.
That's huge. You know, I talked to several folks at the conference and a lot of things I heard was, you know, I loved what you said about getting folks to understand the importance of data as a product. I wish my senior leadership was here to hear that message.
So giving some data points around here's a successful implementation. Here's how these organizations are structured, how they're making decisions. I'm hoping that we can get some senior leadership to pay attention to that and help guide folks in the right direction. Data and IT leaders can gain insight to best practice, common challenges, operational models .That can help aid them in refining their departmental goals and challenges.
The same for business strategy and operations teams. They can better align their projects and processes. For data product managers and data engineers this can provide a clear picture of successful processes as well, which can help give them a benchmark. Here's where I am versus here's where, you know, really successful folks are.
And allow them to refine their approaches. Um, and there, there's a lot of questions too around data governance and privacy, which can offer those professionals an opportunity to benchmark themselves, and evaluate their organization's approaches compared to the larger industry, and also identify areas of improvements. And of course, for industry analysts and consultants, um, this will provide metrics on how industries are progressing, and how they're investing, and the derived value.
And another thought is that, you know, there's, there's a lot of responses. I just kind of took a quick sneak peek before coming on here. We're getting a lot, mostly responses from larger organizations. So I also had a thought that this could be really super helpful for smaller organizations that are just trying to take advantage of learning from some of the larger enterprises who are maybe a little bit more ahead of the curve and give them some really good data points on how they can best take advantage of successful implementations and processes and practices.
[00:25:30] Lauren Burke: Yeah, especially for the smaller organizations, it makes so much sense what you just said, because likely, right, they're smaller, they might not have the budget and the resources. So they have to be very careful, very strategic about what they're going to invest in and how. So I imagine that something like this could be super valuable for them.
[00:25:50] Jen Tedrow: I hope so. We really wanted to put something together that would ultimately help companies maximize the value of their data and, um, really just understand the current state of where we are today. I did some digging before starting this effort, and I hadn't found anything that was out there that had done this already. So I thought, well, we could do it.
[00:26:19] Lauren Burke: That's awesome. I mean, it sounds like it's going to be an incredibly valuable resource for so many people. Uh, I know it's open for another couple of weeks, but one thing I, I want to mention is that it doesn't sound like it's just for executives to be filling out. It's for anyone practicing data as a product, thinking about it. All levels of contributors.
[00:26:43] Jen Tedrow: Absolutely, yeah. Great call out, Lauren. Um, we are looking for responses from anyone who is a member of a data team, anyone who's leading a data team, or anyone who even works closely with a data team. Basically, anybody who has a perspective on how data decisions are made and how data is being leveraged in an organization can definitely be a valuable contributor to this survey. 100%.
[00:27:09] Lauren Burke: That's awesome. And I know we actually have, some prizes for people who are willing to help out by filling the survey out. Could you tell us a little more about those?
[00:27:18] Jen Tedrow: I would be happy to. Yes, we are offering some incentives. So, the survey is completely anonymous, but optionally respondents can leave their email. And if they do so, they will be able to get, um, exclusive early access to the study once we publish it. Which we're targeting end of September, early October to have that publicly facing study available for consumption.
And they will also be entered to win one free in person pass to DataConnect 2024, or one of three virtual passes to DataConnect 2024. And we are also offering it from Pathfinder, a free workshop or coaching session, and that can be for either themselves or for their team.
[00:28:03] Lauren Burke: That's awesome. A lot of great incentives. And honestly, you kind of win something just by filling it out because you do get those early results that you might be able to make some actionable decisions and make some interesting progress in your organization on.
[00:28:18] Jen Tedrow: Yeah. Yeah. We were hoping to provide some thanks and value back for people taking their time. You know, the survey is a little little bit on the longer side. It takes, you know, 5 to 7 minutes, usually on average to complete. So we definitely, we appreciate everyone, you know, giving us a few minutes of their time and we wanted to show how much we value that that.
[00:28:39] Lauren Burke: That's amazing. And just as a small data person call out, I love that you have the data on how long it takes people to complete on average.
[00:28:47] Jen Tedrow: That was important to me to share. Yes, I'm right there with you.
[00:28:52] Lauren Burke: I appreciate it. It's great to know. Um, but just before we start to wrap up, I always ask every guest on the podcast, what is a resource that's helped you in your career and you think could help others listening today?
[00:29:06] Jen Tedrow: I love this question. I love that you asked this question. I was thinking about this, cause you know, I listen to the podcast and I know you're going to ask this. Um, and I was like, oh man, cause honestly I could list so many.
I'm a huge reader and there's been a ton of books that have really helped me in various different areas. But I kept coming back to the one that I find myself recommending over and over. And not just to product managers that I mentor or talk to, but really anyone looking to up their presentation skills.
It's a book called Presenting to Win: The Art of Telling Your Story by Jerry Weissman. Um, we talked earlier about how important it is to understand how to position the value of data as a product to decision makers. And this book, super approachable about how to craft a compelling narrative and presentation, and it's, I feel just it's a skill that will benefit anyone in their career. And it's been so helpful to me.
And I honestly, I feel like I should get a commission for this book because I've recommended it to so many people, but, um, it's truly an easy read and I find myself referring back to it year over year and refreshing myself on these tips. And it's super great, so I would highly recommend that one.
[00:30:18] Lauren Burke: That's awesome. We will definitely link that in our resources section, because I think anyone in the data space, honestly, in the tech industry can work on their presentation skills and really driving home the value and impact of whatever project they're working on.
So I think that's a great resource. I appreciate it.
[00:30:35] Jen Tedrow: Awesome.
[00:30:37] Lauren Burke: And so finally, how can our listeners keep up with you and with Pathfinder Product?
[00:30:42] Jen Tedrow: Yeah. Yeah. I'm available on LinkedIn, just LinkedIn Jen Tendrow. And Pathfinder is also on LinkedIn. You can follow Pathfinder on LinkedIn, and you can also find Pathfinder online at pathfinderproduct.com.
[00:30:56] Lauren Burke: Awesome. I do want to shout out that Jen will actually be back in a little while for a later episode to share the results, some of the takeaways from The State of Data as a Product in the Real Word Survey. So if you are interested in that I know we will have some interesting insights to share.
And thanks so much for being here with me today, Jen.
[00:31:17] Jen Tedrow: Thanks so much for having me, Lauren. This was great.
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