DAM Deep Dive: Orange Logic

Misti Vogt: 00:00

I think surprises are great, but not in software.

Jim Cavedo: 00:03

The fundamental truth is AI can't be considered a feature. It has to be considered a core aspect, almost at the same level as things like storage.

Chris Lacinak: 00:13

People don't want complexity. People want sophistication, right? But along with sophistication comes complexity.

Misti Vogt: 00:18

Your DAM should adapt to your users and train based on your users' workflows rather than having to train your users on your DAM workflows.

Brad Pearson: 00:32

We're focused on problems, not solutions first. So we don't want to put AI and say how can AI apply. We want to say, what are the major problems that exist and where can AI fill in those gaps?

Chris Lacinak: 00:42

Welcome back to the DAM Right Podcast and another episode in our DAM Deep Dive series. I'm Chris Lacinak, your host and CEO of the best DAM consulting company in the business, AVP. In this episode, we turn our attention to Orange Logic, a long-standing player in the DAM space that has seen significant growth over the past several years. You'll hear my conversations with Misti Vogt, Chief of Staff and Head of Customer Success, Jim Cavedo, Vice President of Solutions, and Brad Pearson, Senior Vice President of Product. Three interesting and insightful leaders who bring unique perspectives on Orange Logic's history, technology, culture, and direction. And remember, DAM right, because it's too important to get wrong. **Entrance to the DAMosphere** Misti Vogt Chief of Staff Head of Customer Success

Misti Vogt: 01:30

So I don't know if my entry was traditional. I was a military intelligence analyst actually in the US Army for a while, I know. Humble beginnings, we'll say.

Chris Lacinak: 01:43

Well, thanks for your service.

Misti Vogt: 01:46

Thank you, thank you. And then I went. and did my undergrad in applied statistics and machine learning business intelligence before anybody was talking about it so how the winds have changed. That's serving me pretty well right now, needless to say. And then I was trying to get a job as a data scientist, and I was doing some side jobs in data science, and I wound up landing at a production resource management platform. And I was there for a couple of years and then I went client-side. So I was already in the MAM space, really. So media asset management. I've been in the NAB fold for quite some time, the MACH Alliance, things like that. And then client-side for a little while, helping them implement an ERP platform, enterprise resource management platform. And then I helped them to manage their dev teams because they had to build a homegrown front end that was integrated into the ERP platform. And then once that was deployed, there wasn't anywhere else I could really go there. Great company. They were a components trader, not a software company. So I had kind of done what I could do there. Orange Logic kind of found me by the grace of God, we'll say, and scooped me up just in time. And I feel very privileged. And I've been now with Orange Logic for the last six years. I started as a senior project manager. And in my interview with Karl, he said, well, where do you see yourself growing? Like typical interview question. And I said, I want to be a CEO. And he said, that's a really bold thing to say to a CEO in an interview who basically wants to take their job. And I said, I'm at a point in my career where I feel like it's important for me to be transparent. I don't need to move right now. I'm at a great company. And I want to make sure my next move is what's best for me and what's best for the organization that I'm going into. So I want to be fully transparent. And that worked out for me.

Chris Lacinak: 04:00

Brad Pearson, Senior Vice President of Product.

Brad Pearson: 04:04

Well, I've spent the last about fifteen years in tech SaaS companies of various sizes and sorts across a few different industries, including quite a bit of time in MarTech, but never in DAM before my stand at Orange Logic. So about eight months ago is when I joined Orange Logic, and that's really, before I had integrated with DAMS, but was never very deep into DAM. And so I've been getting a crash course through my time here at Orange Logic, and it's been a lot of fun. really enjoying it. But throughout my entire career, it's been really focused on product, product development, how to build great solutions for clients that are web-based. I've had an interest in the space from before, but no, there was an outreach. We kind of have our secret weapon here at Orange Logic, which is our recruitment team, who are just incredible. And they've They reached out, Omed and team, and I was able to connect with Karl, our founder, and Raph and Brian. I really just got to respect what an incredible product and company they've built. And it got me excited about joining the company and then looked a little bit more into DAM, and there's just so many possibilities and a lot of, I feel like right now is kind of a timely point in history to be interested in DAM just because there's a lot of explosion of capabilities in the space.

Chris Lacinak: 05:26

Now you had what a lot of folks might think of as a challenging entry in the sense that the founder of the company was essentially the product owner, right? So I would think that would be intimidating to come in. Founder-led company, product owner, to have to come in and take that role over.

Brad Pearson: 05:43

I've actually in my career, I've always worked with founding sort of product led individuals. Which has been a lot of fun, always comes with a lot of learning and a lot of challenges at the same time. Karl has been amazing. So he's built a wonderful company. But was excited to see different aspects of his role kind of transition to the broader group that's in play. And so he's actually not only empowered me in a lot of ways to take over aspects of the vision, strategy, but enabled me with a lot of good details. So, obviously, there's big shoes to fill and a lot of work to do, but can't say I respect him anymore, or couldn't respect him anymore for what he's done.

Chris Lacinak: 06:31

Jim Cavedo, Vice President of Solutions.

Jim Cavedo: 06:35

Been here since September of 2024. Ten years before that, I served in a similar role leading pre-sales, consulting, solutioneering types of services for a competitor. But really entered the MarTech space in general early nineties. And in the mid nineties, I worked for a company that some people have heard of, but a lot of people haven't heard of anymore called Iterated Systems. And Iterated Systems was an early pioneer in using fractal technologies to do image compression to send digital formatted content across the internet. And as you can think about that time frame, digital content and space across the internet was extremely precious. And so creating high fidelity compression of that technology was critical to success in the early companies really moving toward the Internet. They were heavy B2C play, so they were selling to companies who had who were selling B2C. The problem was there was a cost to this technology. And there was a burden to the consumer to download the technology, or the decoders to be able to view the content. We love to coin the phrase back then, we were at the tip of a zero billion dollar industry. Because we got killed by everybody that was free out there: MP3, MP4, JPEG, that were all new, but they were all free coming directly on the operating system. So the company made a pivot. And more B2B. And leveraging that same technology, it became more of how do we store and manage this content locally for content reuse and content utilization within the organization. That ended up becoming Media Bin, which was the first commercially viable DAM back in the mid-90s. So that was really the first foray into that space specifically. And then since then, served in consulting roles, but also practitioner roles where I was a user of these systems, including content management and content operations prior to my last stint where I led consumer marketing for a large sports brand, leveraging the technologies we're talking about today. So I've been around the space for a long time, but really that first Mid-90s, first commercially viable DAM, I get to say that I was part of that process.

Chris Lacinak: 08:58

**Company History and Overview**

Misti Vogt: 09:01

We've been around now for 26 years. So long standing company, even though we're kind of just now making our big break into the market so to speak from a marketing angle. But been around for a long time and we kind of started as a passion project For our founder and former CEO now, Karl. And he was in medical school and doing photography for like high-fashion magazines. And he actually just saw that there was a missing link, and that was the ability for photographers to share their content with the agencies and magazines that they were working with. So in true Karl fashion, we'll say, he went and taught himself how to develop and created the first version of Orange Logic. And when we first started, we really just supported stock photo agencies. Many of those customers are still with us today. So Magnum Photo being one of them. A very well known, very high-end stock photography, and then supported that business for quite some time and then slowly evolved, kind of starting to move into the corporate archives and galleries, archives, libraries, museum space. And then that kind of grew into some media with BBC has been with us for a really long time now and And then around 2016, we made the official pivot into DAM and started signing some pretty large enterprise clients that supported that growth. And then I joined the company in 2019. So that kind of like fast forwards us up into 2019. And that was really where I started to see some growth into the large enterprise space. And I have just been fortunate to be a part of that growth ever since. It's really neat to see the evolution of the space, though, and how starting as a digital rights management platform for licensing has served us very well in where we are today because digital rights management, as you know, and content provenance and authenticity is still very much relevant. And that foundation has really set us up for success.

Chris Lacinak: 11:33

Where did the name Orange Logic come from?

Misti Vogt: 11:36

I'll tell you my version of the story, but there are a few out there. When Karl had built the original product and he had a few customers on it. We'll probably say at this point, like less than five. He got a call from a big potential client, and they were interested in the product. They had seen it in the market. At the end of their brief conversation, they said, so what's the name of this company? And he happened to be drinking an orange soda And he, of course, looked at it and saw and said orange. And then logic just kind of fell into place. And ever since then, we've been Orange Logic.

Chris Lacinak: 12:28

In 2023, PE firm Bregal Sagemount invested in OrangeLogic. I have to well, from an outsider's perspective, looking in, it seemed to be a kind of a moment in which the trajectory changed for Orange Logic, although it had been heating up for quite some time, I think, at that point. But I'm wondering if you can tell us a little bit about that and how being PE back has impacted the running of the operation and company.

Misti Vogt: 13:01

Yeah, it was a moment for sure, but it was a moment that came with a lot of thought. And intentional work by the leadership team, myself included, in terms of the due diligence on both sides. Of course, PE firms go through a significant amount of due diligence to make sure that their investment is a sound investment. We did as well on our side. We wanted to make sure that we were partnering with a private equity company that aligned with our vision for the future. and really understood our culture and was willing to kind of come in and foster that culture and accelerate us to growth. We were also a no debt investment. So we didn't take any debt in exchange. It was it was just a straight like ownership share distribution, I guess would be the way of framing that. So we've been profitable every year since inception. We've never had a down year. And that was really important for us going into that investment. They have been really instrumental in our go-to-market engine specifically, because we've always been engineering focused. We hired engineers kind of across the board. So we can still continue to focus on what we do best, which is build best of breed product as well as make sure the market knows that our product exists. And that is making sure that the analysts understand what we offer and that our customers are given the space to communicate with each other and that we're able to offer our product to the market really openly and in a strategic way.

Chris Lacinak: 14:54

**Customer Overview**

Jim Cavedo: 14:56

It really ranges. I would say mostly medium size to large global companies. So we're not really mid-market. It's going to be more on the larger enterprise, the larger call it national companies up to large global enterprises. Industries like media, retail, financial services, and manufacturing. But also due to some unique capabilities that we have in things like archive management, multi-format management, content security, and things like that, we also have a great success supporting NGOs, galleries, libraries, museums, universities, because they have some very specific needs, even though they may tend to be smaller than the large global enterprises, they have some very specific needs that we're able to uniquely solve for within the platform. So we get to serve a wide variety of size companies and industries. And probably like everybody else, we're typically working with the CMOs or C-suite or digital transformation leads. IT transformation leads, creative directors, and then again, because some of these other areas, archivists, gallery managers, people like that. I would say that typically customers come to Orange Logic after they've tried one or two other DAMS. They realize that those systems aren't necessarily flexible enough to solve that their unique use, use cases as they start to grow and adapt. And I think one of the things that I really love about Orange Logic is this unique gift in solving really complex problems for clients. We're rarely stepping in doing the basics. It's almost, you may start in the basics, but it's almost always a phase zero of a really complex set of second and third tier problems that they know that's what they really need to solve for. And again, they typically have had experience with one or two other DAMS, and they know that they're not going to be able to scale that to solve whatever their problems are. So they come to us because we do have experience solving those really complex problems. One of the big areas where customers will come to us after their first or second DAM is either, again, adaptability. And what I mean by that is, they're trying to grow from their core initial use case into department two or region two or region ten or department three. And the reality is what they've discovered in the DAM that they put in place is that it's really good at solving a very specific use case, but then when you want it to solve something else, or solve it in a different way, the system can't really adapt to that. Or it requires professional services to come in and do some work that is complex. And then the other area that clients will come to us is they've hit a scale factor where they can't grow. They can't add in enough content. They can't create enough workflows. Cost of storage is getting out of hand, and they need to be able to figure out how to manage storage more effectively. We've got customers with petabytes of content, not terabytes. We're into the petabyte land. And especially companies who have storage requirements either related to country of residence, data residency storage requirements or they want hybrid cloud environments or built-in cold storage and things like that. As you want to adapt the system or drive larger adoption of a system that necessitates having the ability to scale it more effectively and larger. And so the reality is, you have to be able to adapt the system to drive adoption. And as you drive adoption, you have to be able to scale affordably so that the company isn't getting frustrated with that part of the core digital asset management capability. So I think, again, that's a unique area for Orange Logic to be able to both scale and adapt to meet the different requirements.

Chris Lacinak: 18:52

If you need to anonymize, please feel free. But is there a customer case study that you just the one you love talking about? I'm sure you have many, but is there one that you just really love sharing?

Misti Vogt: 19:03

There's a large healthcare organization that kind of comes to mind in terms of they got it from the beginning. So they had the right executives at the table. They had IT buy-in. It's not just a point solution for the marketing team. They saw it as an opportunity to really bring the community of content creators and distributors together across the board. We started with just replacing their current solution and then it's just expanded over time to the point where now we're doing really incredible things with users that are physicians that are not even your traditional users of the DAM. And I think we're starting to see that model now replicated across other organizations that aren't even in healthcare. So, in financial technology and in pharmacy and pharmtech. And in retail, and that is the concept that this is a community space for content creators, distributors, marketers, creatives, end users, anybody who's involved with really any content across the organization, which who isn't? We're all dealing with content every single day. So creating a framework at the beginning to allow those different departments and different user personas to have a space where they can collaborate and innovate and ultimately distribute to service their own customers has been really incredible.

Chris Lacinak: 20:48

What are the biggest current pain points that you hear from people that are in the market for a DAM solution these days?

Jim Cavedo: 20:55

I would say there are a few that are pretty typical that any vendor in the DAM space probably hears and then there's a few that I think are unique to what Orange Logic hears. Almost always gets customers who are having difficulty managing finding assetsa across sprawling, disconnected systems. And again, that may be companies who've implemented one or multiple DAMs to solve unique problems, but now they've created these silos of content that they want to solve for that. Inefficiencies in creative workflows or creative operational processes, distributed approval systems. Not every DAM has built-in approval capabilities so now all of a sudden you're connecting the DAM to workflow tool X and agency workflow tool Y. So that becomes a problem they're trying to solve for. Compliance and governance is also a huge issue. We've got clients who will shout from the mountaintops about the ability to manage things like digital rights that has massive financial impacts on their business and things we're able to do in that space. I think the other the couple of things that I think are unique that we hear, and again, I come from the industry, so this isn't meant to be a bash of any other DAMS or technologies out there. But I think that a lot of organizations are trying to sell and win the day versus win the business. And what I mean by that is they're coming in, they're coming in really simple, they're able to do a very unique set of capabilities for this client based on the procurement cycle. And that's all they're talking about. And so, what happens is, as soon as the client gets into that next round of what they're trying to do, they realize they can't do it. And so, we get a lot of clients who are, frankly, frustrated by DAM. And they're like, hey, we need to solve a problem here. Can you guys do anything about this? And so that's unique, because I don't know that every DAM is able to be that second or third or fourth generation DAM for a client. Because clients tend to want easy. And I'd like to talk about that a little bit in the procurement process, but clients tend to want easy. And the reality is, yeah, you want it to be easy on day one, but you have to understand complex because your business is complex. And so I think we get to solve a lot of those problems for clients. I also think we get a lot of clients. Again, it's amazing the sheer size. I was talking to a client last night, and they have something like 150 million assets. And they're like what, can you guys manage this? And it's a global brand. And it's great to be able to say, yeah, we've got clients, again, with 30 petabytes of content under storage. And again, a lot of DAMS, especially SaaS DAMS, can't talk about that kind of scale very effectively. So the unique things are, hey, we need a DAM that will grow with us because we can't do this process again. And we have clients who have very complex scaling of content, size of content, type of content. So we're able to do some unique things there because of our hybrid storage capabilities. So I think that those tend to be the biggest pain points we're trying to solve for clients.

Chris Lacinak: 24:05

**Customer Success** What do your most successful customers have in common? Are they doing something differently than other customers? What are the kind of trends or themes that you see there when folks are, you know, off into the races and just going gangbusters.

Misti Vogt: 24:21

Yes, there are a few things. We're big on checklists over here at the Customer Success t eam. Checklist to help them prepare for launch and help them prepare for expansion. And then also internal checklists to make sure that we're setting up our customers for success. And there's a few different facets to that. One, we want to make sure they're getting value out of the platform. The easiest way to do that is through tracking KPIs. So it is kind of the gold standard. Let's make sure we have the KPIs clearly documented and we have ways of tracking those KPIs and we're monitoring those KPIs on a regular basis. And then also we want to make sure that we're multithreaded. So just like the customer shouldn't have one person, the customer success person isn't the only contact that they have at Orange Logic, and vice versa. Because you know, things change. People change jobs, people change positions. There's a lot of volatility in the market in general right now and you never want to be multithreaded in terms of a large enterprise deployment enterprise solution. So that's really important for us. It's important for the customers to see that our executives are plugged in. So they have an executive contact. They'll have their CSM. If there's any projects, they'll have their project resources that are plugged in. We make sure that anytime there's a handoff, the handoff is handled with a lot of care. And we're never just kind of leaving a customer with nobody that they feel like they contact if they don't know who to contact, if that makes sense. Like, there's always somebody that they know they can reach out to if they don't know who to reach out to. So, there's the support umbrella, there's the success umbrella, the project umbrella, and the executive engagement umbrella.

Chris Lacinak: 26:19

That gives us some great insight into what customer success looks like in Orange Logic. I'm wondering, can you tell us a little bit about when you look at a customer and maybe this is let's say in spite of the great work that you do in customer success, there will be some customers that are more successful than others. Are there things are there characteristics of an organization that you see that's adopting and onboarding and using Orange DAM, that you think these are the characteristics that you just know that they're going to do great and be off into the races with the system.

Misti Vogt: 26:55

One, making sure that the value is really clear and we're driving to their objectives, and that that is clear and transparent to their executive stakeholders. Two, that we have multiple points of contact. Three, that we're not a point solution. So we're happy to be a point solution. We are a point solution for lots of customers that are just kind of preparing for like they see the future of an enterprise deployment and they're prepping for that, but we come in as a point solution. But the most successful customers, we see they have IT engagement from the beginning. And that's because we're not a standalone solution at the end of the day. Like your content should never be siloed in any way, shape, or form, especially now. So there's lots of integrations and there's a multi system ecosystem that's really important now for the success of our customers. So if I see a lot of integrations, if I see IT engagement from the very beginning, where an organization has like an IT services branch, and we're owned by that IT services. So Orange Logic is defined as the content platform for the enterprise. And it's set up in such a way that other the departments can go to IT and say, hey, I've got a problem. We're using X, Y and Z products and our content is siloed. And we need a better way to collaborate and to distribute our content. And the IT organization says, oh, well, we've got an enterprise DAM, and that enterprise DAM is Orange Logic. So having that set up in a framework to enable the IT of organizations to then communicate when it's right for those different departments to onboard into the DAM has proven very successful.

Jim Cavedo: 28:57

So the clients who are most successful with Orange Logic are customers, again, not to mention any customer names, a major fashion retailer who has 5 unique brands, 17 teams across 40 countries. They all have very individual requirements. And being able to create a single source of record, if you will, to use that terminology that each one can use, but it looks completely different and interacts completely different across the organization. Another example, a leading e commerce supply company specializing in home goods and furniture replaced seven independent applications with Orange Logic. They have six commercial groups leveraging the system completely independently of each other across thirteen teams. Petabytes of content. So that adaptability is thing that is, if you look at all of our clients, it's they all have very unique use cases as they go across their businesses and or across their business. And the fact that they are able to have the single system that is able to mold itself to meet those different requirements, that's where we see the most success. These are companies who, as I mentioned, they're driving millions of dollars in savings from things like faster go-to-market, digital rights, savings on digital rights violations, or things like that. Being able to consolidate technology systems into one technology system. So that's probably the thing that is, as I look across our clients who are the most wildly successful. It's they have lots of teams using the system that have independent needs. They're not trying to force each team to use the DAM in the same way. They're saying, hey, let's create a system that looks right for you, but it's the same system. One set of administration capabilities. You know, one bill on throat to choke from a vendor standpoint, that has huge impact on that business.

Chris Lacinak: 30:47

How do your customers engage with you and engage with each other? Are there some mechanisms that are in place? Does it just happen organically? What's that look like?

Misti Vogt: 30:55

A little bit of everything. So it happens organically, fortunately, because we have an amazing community. We have a Slack channel that's a customer-run Slack channel, and we're just kind of fortunate to to be included in that community. And because we're users of our own DAM. So that's been a real privilege for us. And then we also have alliance groups. So we have an AI alliance group that meets quarterly, and we're able to plug in some really incredible brands across the board for some thought leadership. And then we also have industry-specific or use case-specific events that'll be kind of like a fireside chat where we get like a we'll have a GLAM fireside chat and we'll usually connect with a partner in order to facilitate that, a partner that kind of specializes in the space, like AVP. Where we can say, hey, let's get together, let's get a bunch of our customers together, let's get a bunch of your customers together and people that are looking for solutions and just kind of brainstorm where we feel like the industry is going and how we feel like we can help them. So, lots of opportunities for community engagement.

Jim Cavedo: 32:12

One of the things we're working on is trying to and this is challenging, but we want to pull that collaboration into the sales process, not just post sales. Like, how do we create that mutual action plan as a part of the RFP process and the close plan to win the business, because again, you want to have a clear set of marching orders with that client. Once you go live, where are we going with this? Versus, all right now we've stood up the system. What else do we want to do? Well, you may have stood the system up wrong based on those decision points. One of the things I love about Orange Logic is that we're pulling more of those conversations earlier in the sales process that might lengthen a sales cycle a little bit, but it's making it a richer sales cycle or more healthy sales cycle versus it trying to become a transactional sales cycle, get the deal closed, and then you get into post sales optimization that maybe you're not set up to be very successful with. So I love that about how we're really trying to pull that forward in the process versus wait a year down the road to get into that mutual action planning. So I think that's a unique thing that we're focused on. And I think we just have some fortunate situations here that allow us to say, hey, I'm less worried about closing the deal today than I am worried about doing the right thing for the client in the long run. I find it amazing how passionate the Orange Logic customers are about Orange Logic. And it's because we're solving some really complex problems and doing some great things for them. But we had something like twenty unique customers, probably forty individuals from those customers come meet us, sit on the couch, sitting on panels, doing presentations. doing dinners with other customers and that this connectivity that we have amongst and between our customers. Sometimes we're involved in, sometimes we're not. It's just amazing. And it's really fun to see that kind of passion from a customer base.

Chris Lacinak: 34:09

If you're enjoying these conversations, take a moment to follow or subscribe to DAM Right on YouTube or your podcast platform of choice. It helps other people who care about DAM find the show, and it lets you know when new episodes are released. And if there's someone in your network who'd appreciate this discussion, please share it with them. Word of mouth makes a huge difference. And if you're in the market for a DAM, whether you're just starting to explore or you're deep into vendor comparisons, we put together a free masterclass on everything you need to know about choosing a DAM and making sure you get it right. It's based on twenty years of experience helping organizations choose and implement DAM platforms. You can find it at bit.ly/yourdamchoice That's bit.ly/yourdamchoice All lowercase, no hyphens, no spaces, no periods. Now, back to the episode **Strengths and Key Differentiators**

Misti Vogt: 35:02

One is innovation. Like we are quick to adapt. And we've built the platform to be incredibly agile and adaptive, as well as our teams, because we all know it's not just the technology, it's the change management side of it. And we continue to foster that culture. And I think that allows us to develop at the speed that we've been developing. And in this market, that's more critical than ever now. I think there's I mean, there's new asset types that are being created, but now with the age of AI, I call it the AI revolution. You have to be agile. And I think that's really core to the culture that we've had since the beginning. And that started with Karl. AI we've had for I think since twenty seventeen was when we first released AI into the market. At the time, it was very trendy, like many other things, but we knew that it wasn't going to be just a trend. So we started to build that foundation, and that's allowed us to move very quickly into the AI market today.

Brad Pearson: 36:15

What we've focused on is how good is DAM adoption? And I think this is something that Orange Logic thinks about differently than maybe our competition and the space more generally. Is we're very focused on how much of an enterprise adopts the DAM. Historically, maybe there are marketing teams there. In certain cases, there'll be production teams, product teams that can involve creative teams to some degree. But only as a final sort of state solution. But content is everywhere. Content is the lifeblood of a lot of organizations. And every almost every team is using different forms of content. And there's a need to consolidate and make that experience better. And so what we do, I think, more than anybody else is really focus on how can we drive adoption deep into enterprises across even teams that you wouldn't expect, even across use cases you wouldn't expect, because that's really you're getting the ROI out of this investment. And so we're we think we think of it as bringing back sort of the initial promise of DAM, which is to break down the silos of all the different places that you're keeping your content and data and trying to make it easily accessible and discoverable and usable. I think one fundamental thing about Orange Logic is the is the adaptability bit. So I think there's that's actually back in our DNA. So getting to the point of different use cases have different solutions. It's fundamentally how we've been built from the ground up. And I think that's it's an interesting take, and I think it's an important one. It distinguishes us in the market, and some folks are very this is one size fits all, and that can work for smaller organizations and then other organizations you really need to figure out how you're driving that adoption. One of the strategies that we've taken, and I think in general, you kind of need to take if you're trying to drive adoption into new areas, is you need to meet users where they are versus trying to force them to do something. entirely different Now you can change how users interact, but that requires a level of change management and a level of buy-in internally and training and materials to get that to happen. And there's sometimes in the technology space, we sort of forget that people and process is still part of the equation. We think technology can solve everything, and it can't, right? It has to be paired appropriately with the right steps. So, one of the, how does this relate to Orange Logic? We really think about how our technology can mold to not just the organizations, but the teams and the individuals that are using the system. The way that a creative production team focusing on photography shoots for retail interacts with DAM content and their workflows are just going to look drastically different from like a social marketing team? And how can the DAM and maybe even more broadly, how can their content sort of ecosystem mirror their needs and their focus in that area? And so that's that's something that we focused on a lot. So, as we go into these new solution categories, we are looking at how we can solve a problem without forcing folks to completely change how they operate.

Misti Vogt: 39:32

Your DAM should adapt to your users and train based on your users' workflows rather than having to train your users on your DAM workflows. With the expansion of DAM across the enterprise It's not even just a nice to have. It's actually it's a requirement. And there are some users that should interact with the DAM without even knowing that they're interacting with the DAM. And that's kind of your creative team. So a lot of your creatives are used to working with on-prem storage and saving locally and kind of sharing those files, and they kind of have their own workflow. Finished assets going to the DAM. Not always the case, but one of the use cases. And then you meet with a creative and you say, Oh, hey, we've got a DAM, and now you have to go and find your assets on the DAM, and then you have to download them locally, and then you have to work on them, and then you have to upload those versions so everybody knows that you're working on it and everybody can see all the different versions you prepare them. So and that's a lot. We don't want to create friction in an already really complicated workflow. We want to do the opposite. We want to simplify it. So when we're talking about creatives, we now have a new tool called File on Demand, which is basically just a mounted storage drive. And the way that The reason we did that is because that's what they're used to. It's very familiar and comfortable for those creatives. So we're meeting them where they're at. And then we're able to organize that file system based on the assets that they need to have access to and should have access to. Thereby, even more simplifying their process. So, if they're working on a campaign, and this is the raw footage from the production team that they're able to work with in order to do their post-production, here's the campaign brief. We can control all that. So, they're not seeing every campaign they've ever worked on. They're seeing the campaign that's relevant to them in that moment. So, we've now simplified their workflow while still meeting them where they're at.

Brad Pearson: 41:51

We kind of have two big product pillars that we're continuing to build on, but are already built quite a bit into the system. So the two that we have is making the system more autonomous, so it requires less resourcing in order to do day-to-day activities and just get the results out of the DAM that you wanted to begin with. And the other side is the adaptability, which we've spent quite a bit of time talking about, which is how do we get the DAM to work well for all of the end users, where they enjoy their experience, they're able to get what they need out of it simply. And that requires a level of configurability and understanding of the individual teams and users and use cases, and there's some features specific to them. On the other side is sort of the how do we begin to speed up common things like metadata management. It's been there since the dawn of time when it comes to DAMS. But how do we make metadata management less resource intensive? How do we change how we're accepting metadata, the quality controls we have on top of it, the production of it? And ultimately, why are we doing all this? Is for discoverability of the content, for reuse of the content, for sharing the content out with other sources, and in some cases, running workflows like on top of digital rights management. So those are kind of I guess those aren't features, but those are pillars that we build around ultimately. So in the like autonomous space, there's there's a lot that we're doing and we talk about AI and a lot of folks kind of talking about AI in this case. But it's more than AI. It's how do you deal with inheritance effectively? How do you make it easier to run sort of bulk processing on top of the DAM? How do you run automations and workflows that where you can take something that you're doing on a day-to-day basis and now make it run without human intervention or with some human intervention in the future.

Chris Lacinak: 43:39

You talked a bit about what I took away from what you talked about earlier related to Orange Logic and you talked about it being well positioned to be able to evolve with an organization. That's what I took away from what you talked about. So you said not every DAM can be The second, third, fourth DAM. I guess I'm curious. You know, we talked about adaptability and scalability. I assume that those comments play into that. But are there other things about the system that you think make it a system that sticks with an organization through that through the evolution of the organization's needs more so than other solutions.

Jim Cavedo: 44:15

Self-service I think is the other aspect that is important. What I probably mean most by self service is that as a DAM administrator, again, if we can sort of think about where this is all going, AI is going to free up the DAM administrators to become much more strategic, leading the charge about what should our content governance look like, what should our content utilization strategy look like. In order to do that, they have to be able to not just have a system that can adapt, but have the ability to do that adaptation themselves or build whatever that looks like. I think that historically, most DAMS have created models that don't really give those tools very effectively to the admins to make those changes. Requires coding, potentially deep, complex admin screens to make changes, to create new workspaces, to create new workflows, to add users, change your permission structures, create new content proxies that may be necessary. Those are complex. And I think that most other systems are heavily focused on the end user, which you should be, but they're not focused at all on the admins. One of the other things that we're getting ready to release here in the next couple of weeks in our next release cycle is a concept of it's called Team Spaces. And the idea is that a team, on their own, even without an admin doing it, will be able to create their own unique experience. Maybe it's a view of the content, maybe it's a structure of the asset galleries, maybe it's the facets and the filters and the browser structure. But instead of having that all be at an admin level, let's let the admin control start to get disseminated out to others who own it.

Chris Lacinak: 46:04

I imagine a scenario in which maybe you're sitting at a bar with another product owner at another DAM platform or something. And I'm curious, you know, is there something maybe it's the product team, maybe it's a feature you have, maybe it's an approach you've taken or a technology you've used, you know, something that's sitting next to another product owner, you might brag about and they might, you know, really be jealous and think, ah, you got me on this one sort of thing. Is there is there anything in that ballpark that comes up when I raise the question in that way?

Brad Pearson: 46:32

The first thing I think about is our technical architecture. This is something that, you know, I've just been able to inherit our CTO, Raph, along with Karl for 20 years, have spent a lot of time Rethinking and rebuilding sort of the fundamentals of Orange Logic to the point where it's pretty impressive, the types of things that it can handle. So the way I would talk about it is we sort of have a full object management model under the hood, where assets and folders and products and anything that you want to build. The relationships between them, the metadata, is all completely abstracted. Now, I'd never say that to a client because this is getting into the technical weeds, and all of a sudden it sounds complex. It's not complex, but it is, it's very flexible so that we can solve things. If say there's a media and entertainment client that needs to track not just the assets, but franchises, brands, series and particular episodes, and have those represented as their own sort of objects and structures and relationships on the DAM, they could do that. Same with on the retail side if they have you know, products and pack shots and categories and markets. Those can be their own first-level objects within the DAM. Same with rights management. And so there's a the applications are really endless. When you pair that with a workflow engine that can function on top of any of that, it's almost like you could build any system you really wanted to on top of it. And we've continued to build in a particular direction. But that just gives so much opportunity for us on the product team to go into new directions, but also for clients if they want to structure their DAM in a particular way.

Chris Lacinak: 48:23

Is there anything that you feel like your product management team or your product development team is knows better than any other product team or product management team out there.

Brad Pearson: 48:32

I think our developers, first of all, are much more in tuned with how the product functions and some of the end use cases that our clients have than a lot of development teams out there. I think that's really important. Sometimes there's this tendency to try to stick developers in the box and make sure that they're not talking to anybody outside of the box. And the problem is they're fantastic problem solvers. So you want to give them as much context as possible and then they can make incredible decisions. And it's a big force multiplier for you. The other side is our product team is in there in the market. We're talking to clients, we're talking to partners constantly. And I think some product teams kind of go back into a corner and they only are are let out to talk to the market every so often. We want to be in front of the market. And so it's sometimes it's analysts, sometimes it's partners. But if we're not in the ecosystem, how are we going to know what's working and what's not? If we're not talking to existing clients and things that they love about the system and things that they prefer we update, how will we know how to evolve the system over time? And so really embedding our product teams into the market deeply, and then giving them sort of broader reins to decide on solution approaches instead of you can have a very prescriptive Command and control style, where you say at an executive level, this is exactly what we're going to do. We just go do it. We find, or at least I find, in building you know, highly empowered product teams that by giving enough context to the right people and giving a boundary of what the vision is, but allowing them to use their skill sets to come up with the best solution based off of all the feedback that they're gathering, you can accelerate efforts and you get better results at the end of the day.

Chris Lacinak: 50:25

That's gotta be take some serious discipline 'cause I imagine, you know, uh having only a fraction of the experience that that someone like yourself has, but that, you know, when you're looking at a backlog of thousands of tickets and Jira, that the instinct is to we just got to knock these out, just keep going, keep going, keep going. And it sounds like what you're saying is like your folks that are doing product development are taking time, which means they're not coding to learn about the use cases, to learn about the marketplace, to learn about the problems that they're really trying to solve.

Brad Pearson: 51:02

One great example is we've enhanced dramatically some of our workflow design tool capabilities in the last couple of releases. And if we were just processing a backlog, there would be maybe 150 different asks related to this thing, but all very specific on needs that they have. And product, we need to be able to take a step back and what's the bigger picture here? And how do we solve not just the problem that's being asked, but the problem that's not being asked, and the problem that's going to be asked in three months from now? And that's how you start to get higher ROI effects, and you get ahead of not just responding to what clients are asking, but anticipating what they're going to need in the future as well.

Chris Lacinak: 51:46

**Roadmap and Technical Foundations**

Brad Pearson: 51:49

I mean, in general, we're looking at as we're looking into adoption, we're looking at the entire life cycle of content and how can Orange Logic play a greater role in orchestrating content from ideation to value, ultimately, at the end of the day, and where our roles that we can fill in clear gaps in the market today. So one of the things that we've been digging in further is we see a lot of fragmentation in the creative operation process. With not a whole lot of great tools to solve the needs. And where there are tools, sort of forcing creatives, creative operations teams, marketing branding managers to sort of adapt to a certain way of running technological updates. So we've been looking a little bit deeper into how can we consolidate a), to an earlier point, all of the content that's out there into sort of one system. And how can we integrate with those workflows to make what is a very manual and difficult process streamlined and simple and automated. There's a lot of particular features in that list that we're interested in, and we'll roll out more over time. But that's one area that we're digging into quite a lot.

Chris Lacinak: 53:09

Is there a different way that Orange Logic is approaching this AI automation or autonomous DAM, content orchestration different from other platforms today?

Brad Pearson: 53:25

I think so. And you know, you you only know so much about your competition, but and I'm best equipped to speak at how we're thinking about it. A couple things, aspects of how we're going about AI. One is we're focused on problems, not solutions first. So we don't want to put AI and say how can AI apply. We want to say what are the major problems that exist and where can AI fill in those gaps. Sometimes that means that something that may not be quite as sexy is actually some of the best applications for AI. So search and discoverability is something that a lot of folks have done over time, not particularly well, even with AI involved. But it's an area that we can fill in. Metadata management doesn't sound very sexy for AI. Generative AI for image and audio and video creation sounds a little bit more interesting. And we're focused on, not that we're not looking into those types of solutions, but we're looking at where's the for our clients, how do they get the highest ROI? The other thing that we're thinking about is there is still maturity happening within enterprises in terms of their adoption of DAM and also their risk tolerance when it comes to DAM. So something like content creation can feel very risky, or in some cases, moves that shared data out into general models, right? They want to hold on to proprietary content within their system. So we're thinking through how can we build solutions that leverage AI but are going to be accepted by the legal, security, Infosec teams that exist at these organizations. So that's the, and may the last bit I'd say for how we're maybe thinking about AI differently is A lot of the effort that goes into the DAM is managing the DAM. And I haven't seen a whole lot of our competition really talk about DAM management from an AI perspective. I hear a lot of end users using it for discoverability. Maybe AI gets involved in personalization and at the edges of distribution, but but just the management of the DAM itself makes all of a sudden everybody's lives a lot easier because not only are you improving the life for the DAM admin, but they're able to do a lot more, which means the DAM's able to be that much more effective and more highly adopted and used. And so we're looking at that. How do we make the management of a DAM that's existed forever. How do we eliminate that as much as possible and turn DAM admins even into evangelists, strategists for the organization on how they use content effectively, and how do we break down silos across the organization?

Chris Lacinak: 56:16

Are you able to talk, bring that picture into a bit clearer focus for us? I mean, are there some specifics you can offer around what does autonomous DAM management look like?

Brad Pearson: 56:27

Sure. Yeah. I mean, there are a couple different layers of that, I think. I mean, so. You could talk about at the infrastructure level when you start thinking about how storage is done from a costing perspective and how can you intelligently make decisions about where content needs to live. So, that a), it's readily available for those that need to use it, but b), is not writing up a large bill for the organization at the end of the day. It's kind of a simple way, and not a very sexy way, but a very important one at the end of the day for DAM management and for businesses. You know, another thing that comes up a lot is when DAM managers are managing large asset loads sometimes there are changes that get rolled through. There was just one the other day where a particular naming convention added like a space and a apostrophe into you know, a certain set of assets across the entire organization. And you can spend a lot of time, downloading CSV files to understand where all of this lives, making your changes, uploading them, even if you have bulk actions and good search and everything else. And one of the ways we see AI helping is when we're talking about search, it's not just search for end users, for DAM admins. I I can come up with a specific set of criteria that I can write in plain English, and it can return result sets and then pre-fill out the editing updates that I need on behalf of DAM admins. Well, we've saved a DAM admin potentially 20, 30 hours of their time that they would spend doing this one thing, which is annoying but absolutely necessary in order to manage the DAM over time. So that's just maybe a couple of examples of things that are behind the scenes, but still very important.

Chris Lacinak: 58:20

I can hear sighs of relief out there with thinking of not having to do that horrible troubleshooting themselves. You touched on one thing around like the kind of what I'll call the metering, the cost aspect of AI. And I feel like I feel like it does and in one sense, it gets a lot of attention. You what you see is kind of these AI tool X has this quality at this cost versus AI tool Y. But what I don't hear talked about much, but I definitely see with our customer bases, like I feel like there is not a great solution from anybody right now. When we tie into a hundred different plugins, tools, platforms, call whatever you want that can do all sorts of great stuff for us. This like management layer around the metering, management and administration of the cost. Am I missing that? Does that exist? Is that on our horizon? Is that something that you all are working on?

Brad Pearson: 59:23

Yeah, it's something we're working on. I don't think you missed anything. I think that's a salient point. Particularly our strategy, which is we want to integrate with all of the best solutions out there. So there's no one AI model or one AI company that does great in all categories. And so we want to be integrated with the best in each of the fields and even by vertical or subtype. My favorite example is OCRs that are focused on old school cursive handwriting as an AI model, which are not usually picked up in the Google or AWS sort of OCRs because they're not trained on that type of content. But yeah, especially with the explosion of different AI models and services and vendors out there, understanding how costs accumulate and how to be mindful of cost accumulation over time for all of those AI services is key. We've, some of the way that we do it is we have proactive conversations with customers about it before we roll it out. And we have some tools that are built into the system. But I definitely see a future where some of this can be expressed in advance based off of what your needs and your interests are. So, for instance, if we take like embedding of of vectorized metadata for images. You use that for natural language search. If I want to type in natural language a search, I need to kind of search across embedded data on images. Maybe you need that for the most often searched images, your final with a certain class of visibility that's public and available. But maybe for your deep archive, you don't need to run vectorized embeddings, you're not running big searches across all of that, and the cost benefits not there. Folks just need to be aware of what that trade off is and how could I think that's where AI could service as well. We were talking about AI and chatbots as sort of a management layer on top of different sub AI models, especially if it can come up with here's what the cost assumptions are, and here's my recommendation based off your needs. It's something we're thinking about and I think it's an ongoing problem. But it's you most of the time I see it, it's handled sort of one to one manually with humans in the mix.

Chris Lacinak: 61:36

Pulling on a couple of threads here, one being AI, kind of generative AI, one being this connection into just a huge ecosystem of platforms where we can create content and edit content and consume content. And of course, thinking about content that organizations create and manage in the DAM that end up out in the wild, social media, and file systems and things. Content authenticity is becoming more and more of an important topic and I'm curious if you could speak a little bit about how Orange Logic is addressing the content authenticity and maybe engaging in things like C2PA standards or things like that. Are you all working on that front?

Brad Pearson: 62:27

Yeah, yeah. We last year or earlier last year, we deployed sort of deeper integrations into reading manifest files for C2PA and being able to update it based off of rendition creation. And there's I think it's a great step forward. So your ability as an asset comes in to understand its provenance and understand authenticity, where it came from, whether AI was involved at any stage and to what level it was. The challenge that we're seeing is even with that integration, it's one of those things where technology is only solving so much of the problem. It's how good your process is end to end. So we have some clients that have a very sort of strict perspective. And their idea is if we don't have information about the asset, there's no sort of C2PA manifest file associated with it, then we just assume AI was involved. Anything if we don't have the history, AI was involved, and that's how we're going to treat it from a legal perspective. Others are a little bit more open. But the main challenge we're seeing is not, there's good technology options and built into Orange DAM. The challenge is on process and getting and then this is kind of where we get back to content orchestration and getting into the entire sort of life cycle of content is the earlier that we get involved in the life cycle of content, the more we're able to ensure a certain consistency of use and updating of that content effectively. Like updating the manifest files when changes are made and capturing that across the board. But if DAM is more of a final state system and there's twenty different drives that it goes through before it gets there, the likelihood of getting accurate authenticity data is lower.

Chris Lacinak: 64:24

You need all players in the ecosystem to play nice and not delete your C2PA data

Brad Pearson: 64:30

Exactly. And sometimes it's not even your enterprise. You're sending it to a third party agency and whether they're also making the same updates. And so it's just difficult to enforce, I think, right now.

Chris Lacinak: 64:43

I'm curious to know a little bit more about your internal operations. Can you tell us a little bit about how you as the product owner work with the product development team and what that relationship looks like?

Brad Pearson: 64:54

Yeah, great. We uh so we have uh product managers uh That are high level and focused on initiatives overall. So it's kind of my philosophy of product management is that product management is not really an entry-level job. You have to have enough market understanding, you have to have enough customer understanding, and you have to have wide enough scope in order to make big enough decisions. And so very much go for an empowered product model where you have product managers sort of leading the charge in terms of different initiatives that we're wanting to drive value, partnering with their clients and partners in the system. So their job is to figure out what are the most valuable updates for our clients that meet sort of a business need that we have internally. And those two have to pair together. Sometimes product management gets kind of pushed, can high on strategy or can get pushed into sort of tactics. We keep product managers strategically focused, but able to speak to some of the tactical day to day level. We don't create layers of separation there. On our development side, development's in charge of delivery of what's going on. And overall, is it feasible that we can build this out? Does it make sense? Is it going to work long term? And so on the opposite side, we have a great development team that is able to run sort of a lot of the delivery end to end. You talk to some development teams and delivery is not something they're really good at. They need somebody else to sort of manage them from a delivery aspect. And our CTO has done a wonderful job building a high-performing team that's able to take a project from end-to-end. When we're working with a team, the product and our UX designers to decide on Hey, we're working on this problem set, We've come up with a solution approach, We've validated with the market, We've talked to our users, We've aligned with the needs that we have here, We've come up with designs, We can hand that over to the dev team, and they're able to take that all the way to delivery. Continuedly syncing up with the the product side to make sure that they're still on track. And then we release it. So I mean, that's a there's a lot of details in there, but that's in a nutshell the product development life cycle. Yeah, it works really well for us.

Chris Lacinak: 67:19

**Industry Insights and Future of DAM** What are some early signs that you might see from a customer where you think that are good indicators that they might be struggling or at risk of poor adoption and need some extra help.

Misti Vogt: 67:35

The first thing is KPIs. So leading indicators of adoption. And this one can get a little tricky, too, because sometimes high engagement means everything is going great and sometimes high engagement means people can't find what they're looking for. So you can't just take everything at face value. You kind of have to define those KPIs with the customer and know what to expect. And that's one of the biggest leading indicators is, hey, our KPIs aren't exactly falling where we would expect them to and we want to jump on a call with the customer. I think I have a list of like 50 leading indicators that we like to watch out for. We're probably overly cautious, but some of the other ones are unfortunately right now we're seeing a lot of layoffs and rifts and just kind of organizational structure changes. And we want to make sure that we stay in front of those for multiple reasons. One, it's the people side of it. You know, like these are people that we build relationships with and based on the community that we build and the relationships that we build with individuals, we never like to see that. It puts the account at risk, but also, you know, we want to help that individual if an individual is impacted that we work with regularly as much as possible, and that we lean into the community for that. So, risk indicator, yes, and then also just an opportunity for us to be humans and care about our customers and do whatever we can to help them to find their next role if anybody that we're working with is directly impacted. Also, for any public organizations, we work with a lot of large enterprises, as I mentioned earlier. But we like to just kind of proactively monitor the overall health of a business because that can be a leading indicator that maybe there's some risk there or some opportunity. With every risk, there's an opportunity, right? So, it kind of could go either way.

Chris Lacinak: 69:45

Shifting to the broader DAM industry, what do you think the biggest obstacles to DAM being more pervasive than it is? What are those obstacles? What's holding DAM back as a technology and industry, do you think?

Misti Vogt: 69:57

I think really data integrity is a big piece of it. And I think just the there's a fear of not being ready that I see, where it's, I feel like my data is everywhere. It's almost like it's impossible. It's going to be impossible for me to be in a position where I feel like I'm really ready to adopt a new solution. You just have to do it. DAM, I can only speak for Orange Logic because I haven't been at other DAMS, but we offer a lot of solutions to help you do that data cleansing, deduplication, like the migration effort as part of the DAM program itself. I know you guys offer some services to really help lower that fear. Like, I have to clean up everything before I'm ready to migrate into a new DAM. And then with AI now, it's more important than ever to have a central source of truth that's well governed and protected and structured in a way to continue to drive the brand in a really meaningful, productive way, if that makes sense. So I think you just kind of have to have to do it. Like everybody, every organization at this point needs a DAM. Whether or not you're a large organization and you need an enterprise solution like Orange Logic or a smaller organization and you need a DAM that's really just kind of targeted to that smaller market. Both are really needed and important to allow you to start to take advantage of the new AI opportunities that are available in a very strategic, thoughtful way.

Chris Lacinak: 71:48

Pivoting off of that question, if we think about where the industry is headed in the next three years, what do you think's on the horizon for DAM?

Misti Vogt: 71:58

I'm so excited about this, Chris. I think I think there's a big shift in the way that DAMS are used today. One, in the way that we're tagging content. I don't, we're still going to be tagging content. I'm very much convinced at that, but we're not tagging content so you can find it anymore. We're tagging content in order to train the machines to engage with the users that are going to be interacting with the DAM. And the DAM in itself is going to be, at the risk of saying what everybody else is saying right now, but it's true. The DAM is going to be an agentic platform that's bringing together several agents that interact and understand your content. and will be able to work with you as if it were an assistant of sorts, an assistant that really understands what you're trying to accomplish. And understands what content is available to help deliver on what you're trying to accomplish without you having to go and search for it anymore. So I think the AI, the AI is going to sit with the DAM, and it's going to be a conversational system, and you're going to interact with it as if it were a colleague. And I think that future is actually right around the horizon.

Chris Lacinak: 73:21

One of one theory that I have around this kind of what I'll call a utopian vision where all the walls come down and everybody's in any application and they're able to search and find and use and edit and create and deposit things into the DAM from wherever they sit. Which is a it's an awesome I do I think that we got that is where we're going. But one of my fears that I have, and I'm wondering if you think it's true or not, and if it is, what can technology do to help solve this? Is governance. And this is it's a bit of an unfair question because the technology itself has only small touch points with governance. It is a very human endeavor. So if this is if it's an unfair question, feel free to say so. But I'll throw it out there just to see if you have any thoughts on that.

Brad Pearson: 74:08

Yeah, I mean, I think I mean, certainly governance in general becomes it's a difficult problem, but it becomes maybe a little bit simpler if you have a unified solution across all of these various parts of the ecosystem. Half the issue is in handing off content from one team to another, from one use case to another, how does provenance around the asset come along with it? How are you able to have the metadata, the, you know, in certain cases, rights management use cases that are it's been permitted to follow the asset around? So I think that that's that's one side. I think That becomes a little bit easier with a single solution, but it doesn't necessarily solve the problem at the end of the day. I think there are different governance models depending on where in the funnel we're talking about. I think that's where this kind of meet people where they are. In an ideal world, sort of all content has one massive metadata scheme, we have a master view into how governance functions or digital rights function sort of across the ecosystem. And in reality, that's not the case, and there takes a lot of process and people structure in order to make that work. And so how I'm thinking about it, at least, which I'll leave it there, is is don't try, when you're trying to consolidate all of these teams onto a solution, don't also adapt all their processes at the same time. It's too big of a bandaid to rip off. Find the next most valuable update to make that's going to drive real impact for your business and be agile about it. And that's going to make the difference. By trying to have like one giant mental model for it, it feels like it's like a big physics thesis or something like that. It sounds great, and it's just you'd spend years and decades trying to get there.

Chris Lacinak: 76:09

I kind of take what you just said to one element of it being that this kind of unification and integration of systems does bring sunlight into what have been historically kind of dark silos. And with that, you get some major advantages around governance controls and things that you can do automated and manually. So that gives me some more hope. That puts some light up there for me. I appreciate that.

Brad Pearson: 76:37

Like a correlate for me, I do come from some data engineering in the past. And in data, there's a big emphasis on data lakes, which is just just output all your data into one area so that you at least have it all consolidated. What you eventually do with it will become much easier down the road if you first handle the problem of consolidation. But if instead of you trying to handle consolidation at the same time as building out all of your views into the business. You're trying to solve too many problems all at the same time. Solve the first problem, which is let's consolidate and have it in one area, and then we can figure out sort of the next layers to tack onto it.

Chris Lacinak: 77:15

Thinking about adaptable DAM, I tend to think of and feel free to disagree if you disagree with this, but what we have historically called portals as long as they've been around, which has not been too many years now, but as a key feature of adaptability. Are portals here to stay? Are those changing? What does the future of portals look like? Does that change in some way on the horizon? Or are portals here to stay as we see them today?

Brad Pearson: 77:43

The need for different experiences on top of the DAM is here to stay. But I think portals historically, have been these siloed things that haven't been well integrated with DAM and DAM workflows in all cases. Depends on what portals we're talking about, and there's not like one common definition out there. But a lot of the things I've seen in the market tend to be great. You have a great homepage, maybe you have one search screen, and then the rest is kind of configuration within the one-size-fits-all DAM. So it's kind of a way to get in, but not it lacks some depth to it. And where I think there's, where I think this will break down at some point, there's not everything is portals, right? Everything is just an experience on top of the DAM. And it's not a difference between a hand-built site page versus my DAM search. It's all kind of blended into one, is where I see that going. So I think, and since portals become everything, portals go away in that sense, but it a mix of the two.

Chris Lacinak: 78:46

The feature set exists, but there's no longer the need for the label is what I hear you saying.

Brad Pearson: 78:51

Yeah, I think so. I think that's really just how DAMS should function.

Chris Lacinak: 78:55

As someone who reads articles frequently about the role of AI in coding and stuff, I mean, what does the future of AI and the coding work that happens behind DAM platforms and every other technology that we interact with in our days. What's that look like?

Brad Pearson: 79:12

It's used a lot right now to be honest, like our teams use AI, our development teams use AI in a number of different ways. And we look at actually AI initiatives, internal AI initiatives for the development teams in terms of what percentage increase in outputs can we get by leveraging AI and X, Y, and Z? And some of them make a lot of sense, and some of them will make more sense in the future. And that's kind of the the updates. But there's sort of different AI when you're doing technical vetting at a higher level and you're trying to understand new technology, you're trying to understand third party systems, you're trying to coalesce a range of asks, AI for problem solving and as a gut check for technical vetting is great. On the other side for coding, you have Copilot and others built into a lot of the the IDEs for the coding environments that are allowing you to you know, it used to be just autocomplete. Now it is autocomplete, but it's AI autocomplete, which is it speeds it up even more considerably. The other thing we think about is for QA. So how can as we automated testing has been a big thing for a while, how do we make sure we have quality releases? AI has a big, powerful role that it can play in beginning to ensure quality in the releases and notify the teams before deployment of something going wrong. So we have probably six or seven AI services we just only use in our development teams today. It's a big deal and a big part of how we go about our work.

Chris Lacinak: 80:49

And what do you think has changed in the past, let's say, three to five years with organizations considering DAM, approaching DAM, using DAM, how has that changed on the customer side? What are they doing? What's happened in the past three to five years there?

Jim Cavedo: 81:03

Cloud first. Ten years ago, cloud first was almost a nonstarter. Now it's becoming the expected solution, although we do see customers who, especially with large video situations or large file size situations where some on prem or some hybrid storage is important to them. A heavy, heavy dependency on collaboration between systems. So, your PIM users, CMS users, your DAM users, your Creative Suite users, they all want to be able to collaborate in real time across the system. Heavy scrutiny on ROI. But again, I don't know that's unique to today. That's been around since I first entered. Like, you know, we've got to make sure that we've got good justification. But I think the thing that it's foolish to not say is at the top of the list is going to be AI and how AI is driving automation and efficiencies in the system. AI isn't new to DAM, but the speed of innovation around AI and how AI is driving new thinking and new capabilities and new decisioning over the last two to three years, it's mind-blowing. It's honestly fundamentally shifting the purpose of the DAM beyond just a storage container into something where you're getting new and enhanced value out of your existing content. So, you know, I think the and the work that we've got ahead of us as providers and partners in this space to help customers understand how to get value out of AI, how to do it safely and ethically. How to solve unique problems leveraging AI. It's not just about creating new content, but generating and predicting metadata. About allowing, which allows your admins and your librarians to become more thought leaders around content and content orchestration and content organization than they are worried about tagging content or is the right metadata being applied to assets. I think being able to then have better validation processes. I mean, I remember having conversations with clients a year, 18 months ago, and it was today everybody wants to validate what AI is generating. A year from now? It's just going to be happening. And that's how fast the speed is going. And some clients are completely leaning into that, right? They're there. And others are going to be much more measured in their approach around leveraging AI. But I think that the fundamental truth is AI isn't it can't be considered a feature. It has to be considered a core aspect of almost at the same level as things like storage. Like, how does AI fundamentally change the DAM of the future? And that's really what's shifting.

Chris Lacinak: 83:49

What what piece of advice would you give to someone that's in the market to procure a DAM now about how to make sure that they're successful in that procurement process.

Jim Cavedo: 83:58

Let's get executive buy-in. This isn't this shouldn't be something that is done in a silo, in a small pod. It should be that there should have some senior level executive buy-in because, again, that vision of where we're going, I think, is important. As an organization, when that doesn't occur, especially early in a sales process or in a motion that we go through, that's a red flag that, hey, is this really going to get to a finish line that's good for us, but also good for the customer? Very clear goal setting, not wanting to over-customize or overly prescribe how the system should work. Like where we tend to have the most success is an organization who's like, hey, here's the problem I'm trying to solve. Vendor A, show me how you can solve this problem. Vendor B, show me how you can solve this problem. Where it becomes really challenging is here's the problem I have, and here's how I want to solve it. Show me how you're going to do this. And it's like, well, that's not the way our system works. Our system's going to do it this way. And then all of a sudden, it's like, well, you've got a complete disconnect in problem-solution capability. So don't over-complicate it by prescribing exactly how you want the system to work. Let's be more focused on what we are trying to solve for. I think that's critical in this process. And then I think the other side of that is, again, understanding the long-term impact, like what's that roadmap? Where are we going? So that we can make sure that we're buying a solution today that's going to solve whatever those problems are down the road as well.

Chris Lacinak: 85:31

You talked about this, like, people want simplicity and complexity. I usually think people don't want complexity. People want sophistication, right? But along with sophistication comes complexity. But that's so spot on. I'm wondering, and you sound like you had more to say there. So I'd love to hear a little bit more about what are your thoughts around that kind of tension and simultaneous simplicity and sophistication?

Jim Cavedo: 85:56

It's a hard question to answer because I'm in the middle of forty five sales motions right now. And the thread through all of them, most of them is we want the user experience to be really easy. And I believe that to some degree, there's a little bit of fallacy to that because, yes, we want the user experience to be really simple. For what use case? For what group of users? Because that simple user experience for that group of users may be completely horrible for this group of users. And so I think where it becomes challenging when you're going through, especially through a procurement cycle, is that You don't want to overcomplicate the sales process or the buying process because, again, there's deadlines and there's impacts of decisions. You don't want to overcomplicate it, but you need to also have this vision of what the future looks like. And make sure that whatever system you're putting in place, whether it's a DAM or PIM or whatever it is, has that ability to adapt to that. It doesn't mean you have to solve every one of those future use cases day one or make sure that the system can do that specific use case. But it is about making sure that as you are looking at these systems, they are built to mold around the needs of the business versus forcing the business to mold around the needs of the technology.

Chris Lacinak: 87:16

**Personal Touch** Is there a current mantra for the company or some core message or principle that gets repeated around the virtual halls of Orange Logic these days?

Misti Vogt: 87:28

We say be orange.

Chris Lacinak: 87:30

Be orange? Be orange, okay. So, what's that mean?

Misti Vogt: 87:34

Be orange is really our our internal mantra to be agile, to do what's right for the customer, never accept mediocrity, and to do what's right by the customer at the end of the day. So sometimes that includes making the hard decisions, and we don't shy away from the hard decisions, we embrace them.

Chris Lacinak: 87:58

Is there a philosophy or belief that you hold, that's kind of a driving force for you that maybe whether you're at Orange Logic or any other company that you really carry with you and use in your leadership.

Misti Vogt: 88:12

At the end of the day, just do what's right. Like we've even had to, with our 98% retention, we have had to part ways with a couple of customers. But I remember some of those conversations as we're working on getting their assets out and getting everything they need. And the last one I had, which was about, I don't know, a year ago or so, they said, this feels like a really bad breakup now. And like, that's it. Like, we're not here to hold your assets hostage or anything like that. And if it's not working, I think there's a lesson to be learned in that. And we want to help you to grow your business or to deliver on your customers and deliver on your own missions And if we're not doing that, like we're not going to be there to prevent you from potentially doing that somewhere else, you know? So it's just do what's right. And that has really served me personally and professionally. I'm very transparent. Probably some would say too transparent in certain instances, especially from a marketing perspective. Good thing I'm not in marketing. Some would argue that I am in marketing, but just de facto. But yeah, I'm just I'm very transparent, very open and honest. I think surprises are great, but not in software, not in enterprise software. Nobody wants surprises. So I've always just kind of lived by be honest. And if that honesty results in something that isn't beneficial for the business, at the end of the day, it does always come back.

Brad Pearson: 89:54

There's a couple of core tenets, I think, to how I think about product development and building great products for customers. First, and this should be obvious for anybody in product, but focus on problems and not features or solutions. You can get distracted by solutions that are out there in the market. We can take something like AI, which has wonderful applications and a depth of use cases. But if you approach it from the wrong perspective, and you start with AI, kind of like folks started with blockchain. Instead of starting with the problem and looking how it could solve it as a type of solution, I think that that's one problem I see and something that I work against. The other is thinking differently, not being afraid to rethink fundamental propositions that are in the system. Why do we have to do things this way? When we're talking about creative operations, some of the things we're digging into is how do we how does the DAM play a better role? Consolidating all of the various technologies that are there in the space. And DAMS historically haven't really thought about that, right? Google Drive stays Google Drive, Box stays Box, email, local drives, whatever, kind of stay where they are. And it's strange to me, but that's something where we're taking a step back and rethinking it. And I think maybe the last bit is thinking both short-term and long-term at the same time. So we want to be able to move quickly. At the same time we want a vision of where this is going to end up in our final solution and the final product. If you think short term all the time, you end up in a tough spot down the road. If you think long-term all the time, you can't move quickly enough to address needs that show up. And so trying to find the proper balance of understanding and having a long-term vision and placing moves that you're making now into a longer-term roadmap.

Chris Lacinak: 91:43

I do have one final question that I ask all my guests on the DAM Right podcast, which is, what is the last song that you added to your favorites playlist?

Misti Vogt: 91:52

Oh, on my Spotify? Oh gosh. I this is such a good question that I feel like I listen to the saddest music. Like, I'm such a, I listen to a lot of breakup music. The last song I added, and I just literally looked, is Ordinary by Alex Warren. And it's a beautiful song. So I highly recommend you check it out.

Brad Pearson: 92:18

I don't remember what my last song was. I'll say one of my recent songs I've been listening to. I'm a Kendrick Lamar fan, and obviously, it's gotten a lot of press recently. So, I've been listening back through his recent album. So, I've been putting a few more of his records on on the on my playlist. I think Hey Now is the last one that I put online. So that's not maybe not the last one, but near the last one that I added.

Jim Cavedo: 92:46

Recently, I've gotten into Jack Johnson, Dirty Heads, Tropadelic. These are all like sort of beach vibe types of singers, kind of Jimmy Buffett-ish. So I would say probably Jack Johnson is probably the most recent person because I keep adding more and more of his stuff to my playlist.

Chris Lacinak: 93:03

You got a favorite Jack Johnson song at the moment?

Jim Cavedo: 93:06

I wouldn't even remember the names of the songs. I tell you, because this is where the Spotify AI DJ has made me lazy. I don't have to think about it anymore. It just shows up, and I'm like, I like that song.

Chris Lacinak: 93:16

All right, well, we got a Spotify playlist of uh people's songs, so I'll just pick a Jack Johnson song. If you're enjoying these conversations, take a moment to follow or subscribe to DAM Right on YouTube or your podcast platform of choice. It helps other people who care about DAM find the show and it lets you know when new episodes are released. If there's someone in your network who'd appreciate this discussion, please share it with them. It makes a huge difference. And if you're in the market for a DAM, whether you're just starting to explore or you're deep into vendor comparisons, we put together a free masterclass on everything you need to know about choosing a dam and making sure you get it right. It's based on 20 years of experience helping organizations choose and implement DAM platforms. You can find it at bit.ly/yourdamchoice That's bit.ly/yourdamchoice All lowercase, no hyphens, no spaces, no periods.