077 – Productizing Analytics for Performing Arts Organizations with AMS Analytics CPO Jordan Gross Richmond

Experiencing Data with Brian O'Neill (Designing for Analytics)
Experiencing Data with Brian T. O'Neill
077 - Productizing Analytics for Performing Arts Organizations with AMS Analytics CPO Jordan Gross Richmond

Jordan Gross Richmond

Episode Description

Even in the performing arts world, data and analytics is serving a purpose. Jordan Gross Richmond is the Chief Product Officer at AMS Analytics, where they provide benchmarking and performance reporting to performing arts organizations. As many of you know, I’m also a musician who tours and performs in the performing arts market and so I was curious to hear how data plays a role “off the stage” within these organizations. In particular, I wanted to know how Jordan designed the interfaces for AMS Analytics’s product, and what’s unique (or not!) about using data to manage arts organizations.

Jordan also talks about the beginnings of AMS and their relationship with leaders in the performing arts industry and the “birth of benchmarking” in this space. From an almost manual process in the beginning, AMS now has a SaaS platform that allows performing arts centers to see the data that helps drive their organizations. Given that many performing arts centers are non-profit organizations, I also asked Jordan about how these organizations balance their artistic mission against the colder, harder facts of data such as ticket sales, revenue, and “the competition.”

In this episode, we also cover:

  • How the AMS platform helps leaders manage their performing arts centers and the evolution of the AMS business model. (01:10)
  • Benchmarking as a measure of success in the performing arts industry and the “two buckets of context” AMS focuses on. (06:00)
  • Strategies for measuring intangible success and how performing arts data is about more than just the number of seats filled at concerts and shows. (15:48)
  • The relationships between AMS and its customers, their organizational structure, and how AMS has shaped it into a useful SaaS product. (26:27)
  • The role of users in designing the solution and soliciting feedback and what Jordan means when he says he “focuses on the problems, and not the solutions” in his role as Chief Product Officer. (35:38)

Quotes from Today’s Episode

  • “I think [AMS] is a one-of-a-kind thing, and what it does now is it provides what I consider to be a steering wheel for these leaders. It’s not the kind of thing that’s going to help anybody figure out what to do tomorrow; it’s more about what’s going on in a year from now and in five years from now. And I think the need for this particular vision comes from the evolution in the business model in general of the performing arts and the cultural arts in America.”- Jordan Gross Richmond (@the1jordangross) (03:07)
  • “No one metric can solve everything. It’s a one-to-one relationship in terms of data model to analytical point. So, we have to be really careful that we don't think that just because there's a lot of charts on the screen, we must be able to answer all of our [customers'] questions.”- Jordan Gross Richmond (@the1jordangross) (18:18)
  • “We are absolutely a product-led organization, which essentially means that the solutions are built into the product, and the relationship with the clients and the relationship with future clients is actually all engineered into the product itself. And so I never want to create anything in a black box. Nobody benefits from a feature that nobody cares about.”- Jordan Gross Richmond (@the1jordangross) (29:16)
  • “This is an evolution that's driven not by the technology itself, but [...] by the key stakeholders amongst this community. And we found that to be really successful. In terms of product line growth, when you listen to your users and they feel heard, the sky's the limit. Because at that point, they have buy-in, so you have a real relationship. ”- Jordan Gross Richmond (@the1jordangross) (31:11)
  • “Successful product leaders don't focus on the solutions. We focus on the problems. And that's where I like to stay, because sometimes we kind of get into lots of proposals. My role in these meetings is often to help identify the problem and make sure we're all solving the same problem because we can get off pretty easily on a solution that sounds sexy [or] interesting, but if we're not careful, we might be solving a problem that doesn't even exist.”- Jordan Gross Richmond (@the1jordangross) (35:09)
  • “It’s about starting with the customer’s problems and working backwards from that. I think that you have to start with the problem space that they're in, and then you do the best job you can with the data that's available. [...] So, I love the fact that you're having these working groups. Sometimes we call these design partners in the design world, and I think that kind of regular interaction and exposure, especially early and as frequently as possible, is a great habit.”- Brian T. O’Neill (@rhythmspice) (40:26)




Brian: Welcome back to Experiencing Data. This is Brian T. O’Neill. Today, I have Jordan Gross Richmond on the line who is the Chief Product Officer of an analytics product that has been designed and catered specifically to the performing arts market, which—so this is a little one of those selfish shows. I think I mentioned in episode one that occasionally I’m going to drop some music-related stuff in here because it is my show, and when I find a music and analytics type of thing, I’m always interested to talk to those people. So, we’re going to jump into some product ideas here with Jordan. Jordan, welcome to the show.

Jordan: Thanks so much for having me. Great.

Brian: Yeah, yeah.

Jordan: Glad to be here.

Brian: I assumed that this happened, so you know, I… I know the [performing 00:01:10] arts market more from the stage side and the artist side of things, but when I’m playing, especially in a larger concert hall or performing arts center, I just assume at this point with operations and stuff, there must be data, not just ticket sale data, but there’s probably data making some decisions these days, even in this space. So, that’s what—I kind of wanted to just pull the veils back on that. How is data being used? What was the birth of your product like? How did you fall into this space? So, maybe you could just give us an introduction to what is AMS Analytics, who specifically is it for, and how is it used? Like, how does it help performing arts organizations?

Jordan: Sure. So, AMS Analytics was birthed as a project inside of a consultancy. Sometime in yesteryear, there had been a series of meetings, somewhat casually I think, put together on some kind of regular basis with the leadership from the largest performing arts centers in the country. And these are the leaders who would share lessons and learnings, and they came to a point where they were interested to understand each other from a more analytical perspective. They asked AMS Planning & Research if that was something they could help out with.

And that was the birth of benchmarking in this space. It was very manual and it was early stage. It’s evolved tremendously, and so zoom forward; we’re now sitting on a SaaS platform, it’s a Software as a Service platform subscription model where users are able to log in and see analytics and information that’s going to help them drive decision-making from a strategic perspective. And I took over the project just about six years ago, now. We rebuilt the platform into what it is today, and we’re really proud of what we’ve got.

I think it’s a one-of-a-kind thing, and what it does now is provides what I consider to be a steering wheel for these leaders. It’s not the kind of thing that’s going to help anybody figure out what to do tomorrow; it’s more about what’s going on in a year from now and in five years from now. And I think the need for this particular vision comes from the evolution in the business model in general of the performing arts and the cultural arts in general in America. In AMS, we talk a lot about those evolutionary steps, and it used to be that, go back 100 years, we were sort of mimicking the commonwealth model, where the arts and cultural space were largely supported by donations and large funders. And that’s moved more and more and more into the earned revenue bucket, to today where the largest organizations are primarily earned revenue.

And so essentially, you have these cultural arts institutions, which on the face, look like they might be, kind of, quasi-governmental, they’re certainly nonprofits, but I think a lot of people mistake them as supported institutions, and in fact, they’re actually small-to mid-to sometimes very large-scale businesses. And so they’ve needed to evolve like all business has. And so the tools that we provide enable the leaders of these organizations to make strategic decisions that are really, really critical for their evolution, and to help them track the trends that they and their peers are making throughout their own evolutions. And so, we work very closely with the leadership to understand sort of where their heads are at, and what’s important to them, and where their thinking is, and work to enable them to kind of see the forest through the trees. And we do that with lots of things that probably your listeners have heard lots of about: KPIs, and OKRs, and lots of metrics.

But the idea is that these are businesses. These are businesses, they’re business entities, and they’re run as such, now. And so when you look at the landscape of the leadership today in the arts and culture space, that’s largely who you see. And so they’re looking for tools like this. So, it’s a pleasure to work with them, we’re really thrilled to be able to have these deep relationships.

And the platform is constantly evolving. Right now, there’s a benchmarking aspect to it that looks at operation over annualized periods of time, there’s a compensation tool in there, and there’s a tour history tool in there. So, there’s a lot of tools to help these leaders make strategic decisions and look at their organizations from a broad perspective and get a sense for who the organization really is, what it’s really doing, and where things are headed.

Brian: So, you mentioned benchmarking here, and I think one of the important things, when I’m looking with talking to clients about products and stuff, is a lot of times when they’re spewing data onto the screens, they’re not providing useful comparisons for that information. So, this—Tufte loves to say, “As compared to what?” And it’s one of my favorite questions to ask with analytics when we’re going to present information. It’s only meaningful in some comparison capacity, to some baseline that matters. So, you talked about this benchmark; maybe you can unpack why does the performing arts industry care so much about what the benchmark is for the industry when they’re not actually in competition?

At least I don’t think of, like, Lincoln Center in New York is in competition with the Arsht Center in Florida. They both have multiple venues, they do multiple lines of programming. They’re not really in competition with each other, so I’m interested in this idea that I need to care what’s happening with salaries or, you know, ticket sales, or tour history. Unpack that for me. I assume this is a CXO is the person that’s primarily using your product. Why do they care what’s going on in another state and a similarly-sized performing arts venue when they’re not really competing with them?

Jordan: It’s a great question. So, that’s one of the central questions, I think, right?

Brian: Keeping up with the Joneses a little bit? [laugh]. No one knows what it should be, so we can only compare to everybody else’s at one—and I’m not—I’m kind of being—I’m joking, but I’m only half-joking. I have seen this. It’s like, “Well, we don’t know what ‘good’ is, so let’s look at what everyone else is doing and we’ll just decide that’s our benchmark,” but it’s a very non-innovative way to approach it, in my opinion, because it’s saying, “I need to just keep up with everyone else, or slightly beat them,” but we’re not really competing with them, so I’m really fascinated by this idea of benchmarks.

Jordan: So, I come at this question from a couple different angles. And maybe I’ll just—I’ll bucket these in maybe two different ways. So, the first is that when it comes to looking at comparatives—and you’re totally right, without the context, you’re just floating numbers. So, the two big buckets of context that we talk about, and we present, and we remind people to keep in mind, are: you versus the sector. So that’s, sort of like, the traditional benchmarking that you’re talking about.

But the other one that’s really, really important, and arguably could be even more important is you versus yourself because there’s a directionality to things and we want to make sure that we understand the context of where we’re at today—I should say where we’re at today in context with where we’ve come—and hopefully with a intentionality behind where we’re going.

And this leads to this second bucket of thinking that I tend to present frequently, which is, I kind of think of this with an analogy—this is something we talk about frequently with clients and with the participants here—you know, part of the notion of benchmarking is going back to first principles. And the analogy I go to here is in, like, health care. We’ve decided as a collective society that there’s certain key metrics that we care about in order to determine someone’s critical health. We call those things ‘vitals.’ So, it’s your blood pressure, it’s your heart rate, it’s your oxygenation, stuff like that.

So, we kind of take that for granted, I think today, that we measure blood pressure, but at some point that was actually a new idea; that was an epiphany to somebody. So, the first step is first to kind of just arrive at what the heck matters to measure? What’s worth measuring? It’s not always obvious. Sometimes we’ve discovered that organizations aren’t e—they’re not even sure how many people walked through the door that year.

I mean, that doesn’t happen so frequently anymore, but there’s just this—there’s this notion of what’s the baseline? So, we have to first determine what are we measuring? And there’s a discussion there; why would that be important? And we have this old adage, “You get what you measure,” so you want to be careful where you land on that. But once we’ve decided what to measure, then the second step becomes, “Well, we have to figure out where we land on that.”

So, it’s kind of like blood pressure is important to measure. Great. What’s my blood pressure? And it’s like, you get—you know, you’re 120 over 80, or you’re 130 over 90. And it’s like—to your point—if I have no context, I don’t really know what that means. Is that good? Is that not good?

I actually tend to drift away from the notion of good and bad in analytics, it’s more about understanding, kind of going into things with eyes wide open and really understanding what is real as opposed to living according to what we know we do and that sort of what I call tribal wisdom, you know, “This is how we do it and it just works.” So, there’s that first step of, get the measurement. And now I have to figure out what does it mean in context, so I need more information. And then the third step is going to be, where do I want to be? If I get the 130 over 90, given a body of data, I’m going to actually know that 120 over 80 is probably where I want to head, and then I can start to think strategically about how I want to adjust my lifestyle, how I want to adjust my eating decisions, whatever, in order to get myself to those numbers.

So, the same exact trajectory happens here in the strategic planning world where the organization is going to have a selection of what’s important for them to measure. And I think that’s really the first thing that we do is we offer kind of a menu: these are things that we’ve discovered are interesting and important to these organizations to measure. And we’ve all collectively, eventually—now, this is an evolution—we released an actual manual on this through the International Association of Venue Managers a couple years ago that is a first step toward delineating what we think is a definitive set of KPIs. I always talk strongly about people in these organizations, the leadership, it’s really important to adapt these things to the organization and to their mission. So, far be it for me to tell you what’s important, but generally speaking, this is a menu of things that the sector finds salient.

Looking at that menu, you can decide, hey, based on where we are geographically, based on our mission, based on how we’re integrated in our community, et cetera, these are things that we’re going to actually, kind of like—we’re going to put a pin in these things, and we’re going to start to look at them and we’re going to start to actually try to understand where we’re at with these things, whether that be use days in a venue, or just total revenues over time, or average ticket prices, wherever the metric might look like, whatever it might be, they decide, these are the things that are important to us. And they start to look at it over time, and understanding where they land over time against themselves and then where they land against their peers over time, enables them to make intelligent decisions and have intelligent conversations with stakeholders. And that’s really—I think this is finally getting around to the answer to your first question, which is that, “Why do they care? They’re not in competition with each other.” So, I think it’s really twofold.

Sometimes they are because they actually do compete for talent and so they want to make sure that they’re competing on that level, so there’s the compensation piece. But there’s also this notion that there’s a way to run an organization, and there’s a way to run an organization. And there’s such a thing as best practices. And as different as the organization’s may be one to the next—which for sure they are—but anytime you see benchmarking in practice—which benchmarking comes out of the Navy, actually, and it’s been used in every industry that I can tell—no two businesses are identical, but the benchmarking still works because there’s key principles that are comparable over company to company. And so that the truth is—or, that is the truth here as well, and so, if an organization sees that it’s an outlier, it doesn’t mean that it’s good or bad.

It’s an interesting piece of information to explore and to try to understand the reason behind. And I think that’s where having actual data is so critical, so that it’s no longer about anecdotal evidence. “Well, I was on the golf course with my buddy,” or, “I had lunch at a conference, and they do things this way and we do things this way, but it seems to be working for us, and we should just keep going.” That’s very different than saying, “Listen, their earned revenue per patron is x and ours is x minus 12. I wonder why that is?” and digging into those things.

And you might—they could very well end up understanding where that’s coming from and doubling down on it. “We’re in a place geographically where the earnings are going to be different, and we actually—that’s in line with our mission, and it’s actually fundamentally critical now that we communicate it that way. I want to make sure my board chair understands that’s what’s going on here, and I want to make sure that all my civic leaders understand that we’re fulfilling a critical role in our community, and this is a metric that’s actually revealing that.” As opposed to, “We’re just as good as everybody else.” So, it’s not, “We want to sell more rolls of toilet paper and we got to figure out how to get the lines to move more efficiently.” It’s a different outcome, but I think it’s a very similar process in terms of how the comparisons work, how it’s important to select the metrics, and then what it looks like, to kind of process the analysis.

Brian: I hear what you’re saying. And I purposely asked you this question because I know you have an arts background as well, and some of measuring the performing arts is a difficult thing when we can’t even define, like, what is jazz? We can’t define things as easily and we can’t measure everything about the arts. Obviously, operational aspects, you probably have an HR [laugh] department somewhere, you have salaried employees, there’s definitely aspects of the operational side that can be. I’m very interested in how the yin and the yang of, say, the people on the programming side and the artistic side of an organization and the people running the operations and quote, “The business side,” or the operational piece, how that’s working, especially over time because I could see how—you mentioned this toilet paper analogy; we’re not here to drive more rolls of toilet paper, but I wonder if now that we have access to all this data, is there ever a risk that it changes the mission or the culture of the organization to focus on moving the charts up into the right, [laugh] so to speak, when you may have feedback like, “Hey, yeah, we had an underwater jazz group that played plays John Coltrane’s Love Supreme album on electronic instruments in the water. And no, it did not sell well, but we got 400 handwritten letters sent to us that are not tracked by any analytics whatsoever.”

And it brought in a more diverse audience that we’d never had before, and we don’t track people’s race when they buy a ticket, so none of that comes up in the data. So, the operations people or the CXOs, maybe see one thing, the programming person’s like, “This was a total home run even though we didn’t sell the house out.” So, this—I’m just throwing out a hypothetical example of where the non-measurable parts of the arts thing could collide with this. And I’m curious, have you seen any change? Does this—is there anything negative, or maybe not negative, but that leaders need to understand that we can’t manage just to the analytics and the KPIs because we would be missing something integral to our organization if we only looked at what is actually measurable and what has clean data.

Qualitative data, people writing in letters, you know, you can’t do that stuff, unless you’re talking about sentiment analysis at scale with digital information and all this stuff. You can’t measure those kinds of things. So, has that changed anything? Have you seen any change about this? Is this something they talk about? Or maybe I’m just making this up and it’s a non-issue? I don’t know. It’s just conjecture? Like.

Jordan: That’s a great question. I really love that question because it gets to those intangibles. So, a couple things here. No one metric can solve everything. And there’s only one sort of—it’s a one-to-one relationship, generally, from my perspective, in terms of data model to analytical point, so we have to be really careful that we don’t think that just because there’s a lot of charts on the screen, we must be able to answer all of our questions.

So, you make a great point. Have I seen this sort of drive to, kind of… meet the metric? I don’t know that I’ve really detected that in the sector. I think what I’ve discovered instead is a use of language and an awareness and an intentionality around how the leadership are thinking about these things differently. You know, when you have access to information, you just—it tends to shape your thinking.

That said, these organizations are clearly mission-driven and nothing’s stopping that. I want to give an example of where the rubber hits the road in terms of the intangible stuff. One of the things that’s always been really important to us is to measure total impact. Now, to your point, there are always going to be things that are more challenging to quantify than others. In your example, the letters, you’re right, there’s no benchmark for, like, sentiment analysis or something like that, or letter writing, or things like that.

There’s other tools, actually, for those kinds of things. There’s intrinsic impact, kind of, other tools that do specific work like that. But what we’ve done is something entirely different than how we initially were approaching the data model. And that is, if you go back 40 years and you asked a forward-thinking cultural arts leader, “How do you measure impact?” You know, “Tell me about how impactful your organization is?”

They might have told you how many patrons sat in the venue on an annual basis, and said, “Well, look. We have all these people.” You know, “[We just have 00:20:23] have 800,000 people over the course of one year.” And they might even have demographic information, and they might even know sort of how things work in terms of how the discipline buckets are allocated. So, we had 20% of our attendees were children. They might know things like that.

Today, it has to go beyond that because these organizations are more entrenched in their communities than ever before, and so we had to work with the leadership to understand, first of all, what does that mean, and how do we measure that? So, we did two things. The first thing is we had to recognize that there is activity going on in more than just fixed seated venue halls. There’s stuff happening everywhere: there’s stuff happening outside on the front lawn, in the plaza, in the hallway between buildings, there’s pre-show talks, there’s after-show talks.

And so we wanted to be able to capture that information in a way that we could wrap our heads around and our arms around a bigger picture of that level of activity. And so we do that now. We have venue-centric activity and non-venue-centric activity. The second thing we did is we realized that there’s an incredible amount of activity that happens that’s got nothing to do with a ticketed purchase. And that’s also different.

Go back 30, 40 years, the reason to be on the campus of a performing arts center was that you were a ticket holder. And so wherever you went, you were gatekept with a ticket and that’s what they counted. The drop count is what matters. That’s how we know what we did tonight. Today, it’s not the case.

Today, there are events, there are experiences, there are a variability of ways to interact with these organizations, only some of which involve a ticket. And so, if all you’re doing is measuring tickets and dollars and drop counts, you’re totally missing half the picture. So, we went and we first had to understand, well how are you tracking this stuff? Because they do; they want to know for themselves. And we worked with the leadership to understand how we can all work together to make sure that we’re tracking it as a community, as a sector.

So, those two big buckets—the non-ticketed activity and the non-venue-based activity—I think, are some concrete points that get to your question around the intrinsic value and the intangibles. The other thing that we do—and I kind of talk about this in terms of on-screen, off-screen—is that we always ask for notes. There’s just going to be information that is either—it’s a one-off—COVID happens. That’s a one-off. Hopefully.

You know, The Lion King blows through town. That could be a one-off. You know, we talk about the Hamilton effect, right? And so we always want to have a narrative in mind when we’re looking at data so that we can introduce that transparency, that layer while we’re trying to interpret. And so if we see something that looks out, relative to previous years, or we see something that looks out relative to other organizations, we try to be really conscientious about that and work to help explain it and help to understand where it’s coming from. And so those additional narratives, I think, make a big difference.

Brian: Are those actually in the tool? I mean, that you actually bring up a great—and if I—I’m going to try to bring our conversation down into the product domain; we’re at the strategic domain right now—but even things like these annotations about either—whether the user puts them in or they’re sourced from outside, this is something I think is really powerful that’s often missing when we went when we take engineering-driven approaches to building analytical tools, which is just the quant data. But it’s like, you talked about the Hamilton effect, and I think what you’re referring to here is a large Broadway production that’s very popular comes through town; it draws all these patrons in, which may be your patrons that normally would attend a series—a subscription concert show or whatever, maybe a smaller artist, and instead they go see Hamilton, and so all of a sudden the ticket numbers drop and you see the chart goes down and there’s no explanation for it. Is that something—is being able to make these annotations something that’s in the product? Have you ever thought about that?

I think it can be really powerful to just make those COVID vax—you know, like, “COVID restrictions started here,” when you’re looking at it a histogram. All of a sudden you have a lot more context now for what’s going on having these little annotations in here. Is that something that happens or can happen?

Jordan: Yeah, no. It happens. So, there’s general annotations. Actually, it’s been in the roadmap for ’21 since the begin—since January, we’re building—

Brian: Since COVID.

Jordan: Yeah basically—

Brian: [laugh].

Jordan: —right? [laugh]. There’s actually a transparency layer in the tools to see, as you’re describing, kind of like, you know, they’re not histograms, but essentially, this notion of pointing out where these milestones are happening.

Brian: Yeah. Time series charts or something.

Jordan: Yeah, exactly.

Brian: Yeah, that’s what I mean. Sorry.

Jordan: You know, and actually, just to clarify, the Hamilton effect, generally speaking for these organizations, is actually the opposite as you’re describing; it usually means it’s a huge bump in their—

Brian: Oh.

Jordan: —revenues. In their revenues.

Brian: If they’re the one showing Hamilton.

Jordan: Yeah, exactly.

Brian: I thought you were talking about the opposite, which is everyone else drops because it [laugh], you know, it’s drawing in so much audience, you’re seeing a downturn. But I—it makes sense; your organizations probably are the ones hosting a large-scale Broadway production anyways. So.

Jordan: Yeah, that’s right. That’s right. But just to your point about the annotations, [you know 00:26:08], that narrative is not going to be clear in the data always, so it’s really important to find ways to include as much soft data as possible so that you’re constantly creating that additional context.

Brian: So, let’s try to bring our listeners down into this product domain. How did you—I want to hear about, just briefly, is there a routine process you go through for making product? So, how did you decide what shows up when you open the tool and why are there ten reports? Or why is it this way? How did you come to that, and how are customers involved in that?

Are the actual end-users—not the buy—I don’t know if the buyers and the users are the same, and you’re—a lot of times in enterprise, they’re not; the person writing the check is not the end-user who’s going to be looking at this data and making decisions with it or whatever. Maybe you could start there. Is it the same person? And, b) how are they involved in designing this solution such that it will actually be useful, usable, valuable, all of that?

Jordan: So, you know, we’re talking to the senior leadership in an organization when we’re discussing the value, but it’s an interesting product because it actually involves the whole organization on some level. We’re looking at ticketing data, box off data, we’re looking at staff, we’re looking at the financials, so we’re covering the whole operation. And so on some level, I need buy-in from everybody; I need to be able to make the charge that there’s value here for everybody. Which is something we’ve worked really hard to show that. I refer to this concept of democratization of data frequently, that the more people in the organization who have access to the information, the better.

The better off everybody is because that context is not just about making strategic plays at the top level of the organization; it’s also about helping everybody get on the same ship going the same direction. And I have now seen wonderful examples of this in a number of organizations who have done this, where they are pushing the data down deeply into the org, and managers and on every departmental level, are able to see information that’s relevant to them and understand how their wedge of the budget works alongside everybody else’s, and why some of those decisions are made. So, I think it’s an interesting dynamic; it makes for some complexity. Ultimately it’s the CEOs and the CFOs and the CXO suite, that’s, kind of I think, most bought-in and most in tune. I’ve got CFOs who, you know, they’ve got information from the tool is sitting on their desk, like, 365 days a year.

They just, they show me on Zoom. They’re like, “Here it is right here.” [laugh]. So, I think at that level, they might be referring to it more frequently, but it’s sort of a full organization kind of play. In terms of how we think about the development, this is something that I think I take particular pride in how we approach this.

We are absolutely a product-led organization, which essentially means that the solutions are built into the product, and the relationship with the clients and the relationship with future clients is actually all engineered into the product itself. And so I never want to create anything in a black box. Nobody benefits from a feature that nobody cares about. [laugh]. Sounds obvious, but you’d be shocked how frequently stuff like that happens.

And so to that end, we have a number of—it’s actually three; we have three user groups. They’re their advisory boards; that’s how we have constructed them in our organization. Other technology firms do it differently. We collect a lot of information, we do a lot of data, I have a lot of ways to collect information inside the application, but these user groups are really the fundamental touchstone for the evolution of the product. These are the people who are deeply invested in the value that those organizations are receiving from this product and they’ve made themselves available and are willing to share where things need to move in order to be truly valuable.

And we listen. We listen. I mean, I re-architected, essentially from the ground up, the compensation tool during COVID, and it was entirely driven on user feedback. We wireframed, we built an MVP, we did—we sort of, at every stage of the process, we’re working alongside this advisory board. And because of that, we had a huge degree of confidence, both from engineering, but also from the rest of the user group because we could then turn around and say, “Hey, this is an evolution that’s driven not by the technology itself, but it’s actually driven by the key stakeholders amongst this community.”

And so we found that to be really successful. And I think just the notion that, in terms of product growth, that when you listen to your users and they feel heard, that the sky’s the limit. Because at that point, they know they have buy-in. I should say, they know you’re bought into them and so you have a real relationship. It’s like, it matters.

Brian: Yeah, yeah. I mean, this is design 101 stuff, in the design world. It’s not 101 stuff, I think a lot of times in the analytics world, where we just assume that data will speak for itself and that customers will understand what to do with it when we put it on the screen. Maybe you spend some time on a little bit of data visualization, but by then it’s like, “If you don’t get it, well, that’s not my problem.” [laugh].

It’s a very different approach, which is ground up. It’s starting with pain, problem, need, challenge, and trying to understand how someone perceives what our work is doing, what our designs are doing, and all of that. So, I’m curious, are these groups, is this something where it’s like, “Hey, here’s the landing page for the new compensation tool.” And you send it to a group of people, or you send it to individuals in a group? Like, you have a CFO group, which has five CFOs of performing arts orgs, and you individually send it to each one, or you have a session with them? Or could you talk a little bit about, like, literally how it works, the interaction with these customers?

Jordan: Yeah, sure. So, it’s a little of both. We call regular meetings. You know, when we’re actively… kind of feature designing, we’ll pull together a regular series of calls with the whole group. The reason I find that to be more useful than getting individual feedback—although the individual feedback has its own place and it’s really important to give people the opportunity to share without influence.

So, in a safe space, they know that their feedback is valuable and they’re not being influenced. On the other hand, there’s no right answer to a lot of this stuff. It’s not like we’re designing a car and if there’s three wheels or four wheels, that can make a huge difference. This is more—like, it’s gray. And we want to find a way to address the problems that’s going to solve it for the most people.

And so, you have—especially when you’re dealing with leadership; I mean, their leadership for a reason, right? They have conviction. And so you can have somebody who’s clearly convicted along a certain line of thinking, and be totally convinced that everybody else is going to work just that same way because they can’t imagine how anybody else could work any other way. But you get a call together and let them express that in front of their peers, and their peers can speak up and say, “You know, I hear what you’re saying. We actually do something completely different.”

Brian: Yeah.

Jordan: And what happens in those conversations, first of all, I learn a ton. I am not a CFO; I’m a product guy. And so I’m learning hey, wow, there’s legitimately more than one way to skin a cat here, in this particular issue where I don’t have subject matter expertise. And then the outcome generally lands us somewhere in the center, where both parties have agreed that the solution addresses each of their needs. And that’s something that we just—I certainly couldn’t do that in a black box, and I clearly couldn’t have done it with just one of them.

And so we need everybody in the room to stack hands and say, hey, this works for everybody and this is how we all want to do it. And that consistency is another key principle to any of this work, that at the end of the day, whatever it is, we all just need to be doing it the same way because then at least is comparable but yeah, so that’s generally how we run these things. And I’ll just say, it’s a touchstone for product leaders, but in product, we like to say that successful product leaders don’t focus on the solutions, we focus on the problems. And so that’s where I like to stay because sometimes we kind of get into lots and lots of proposals, and so my role in these meetings is often to help identify the problem and make sure we’re all solving the same problem. Because we can get off pretty easily on a solution that sounds sexy and sounds interesting, but if we’re not careful, it might be solving a problem that doesn’t even exist.

Brian: Yeah, yeah. I kind of wanted to wrap this up with, maybe, an experience that you’ve seen with the product where you had to make a significant change to something based on user feedback. And I’m particularly interested because I know you had a role as a BI analyst, I think it was the Broward Center in Florida. What’s different about—when you’re talking about—when you’re an analyst and you’re analyzing data, maybe you’re presenting dashboards or some kind of visual solution that ultimately will be used for decision-making, the difference between that and the difference between creating a data product that actually has to drive a business and so it’s not just enough to analyze the data, what’s the difference there as you move, I’m going to say, move up the stack to, now my work has to be so good, someone would pay for it. It’s a different mindset.

It’s for somebody else. It’s not about, “Well, that’s what the data says. I don’t know, but I’m on to my next project because you told me to analyze the ticket data and I did,” that mentality versus what you’re doing, which is creating a product around it. Is there something there you can share about the change in, maybe, your career or your headspace about how you approach all of this, that you could share with us?

Jordan: Sure. It’s a really interesting question. What comes to mind it’s something—so the Data Science Association, they have a quote I think they use every time they send an email. It’s something along the lines of “Data science is the best job in the world.” And I think what they’re speaking to is this notion that all you want—or when all you need to do when you’re only charge is to find interesting insights, the sky’s the limit and you could just bury yourself forever.

You’re right, I did BI work for Broward for a couple years, and it was sort of the first effort, to my knowledge, at least in that area of the country, and we brought a lot of interesting ideas out into the open not just for our organization but for the art sector in general, in terms of what kind of data is sitting in the box office at all? I think there was a time not that long ago that we kind of didn’t know. Nobody realized how much information we really had that we were sitting on. But you make a really interesting—I mean, it’s a really interesting question, like, what does that transition look like? So, not everything is critical.

Not everything is important. I think there’s really two buckets here, I think on the one hand, I relate to it like a human being. There’s a value in understanding ourselves because the better we understand ourselves, sort of just, the better we’ll operate and function with other human beings. So, I think the same is true for organizations. The better we can understand ourselves as an organization, the better off we are in terms of how we’re going to approach and defend ourselves and grapple with whatever challenges we face.

So, on that level, the more the better and every metric might be really interesting. But when it comes to making decisions, and when it comes to really grappling with critical key components to evolving an organization, it usually comes down to one or two things. I mean, it’s often just one thing. And it’s not the same for every organization. It’s driven by the leader, and how that leader thinks, and what that leaders background and experience looks like.

But my job is to understand today, my job is to understand what are the most critical factors that these leaders care about? And how do I make that clear and front and center for them? You asked earlier, how do we decide what they see when they log in? I take what I call an analytics-first approach or insights-first approach. I don’t want people to have to take five minutes or click fifteen times to get to information that’s relevant to them.

When they log in, they right away are seeing the most relevant, the most up-to-date information that we have for them. And the idea is, this is what we’re here for. And so I think it’s about understanding what’s important to these leaders… working to build those relationships and furnishing them with the most salient, most relevant information that they have—that they can get to make the most important decisions that they need to make. And I think that’s the biggest difference. It usually comes down to one or two things.

And if you’re sitting at a BI desk and your only job is to just find interesting stuff, it’s a completely, completely different world. So, the two, they kind of marry up, but at the end of the day, running an organization is a very different enterprise than sort of [taking 00:40:12] to the data. And I think it’s been a wonderful journey getting to understand, alongside these leaders, what challenges they face and how we can best support them.

Brian: Yeah, I think you said it well. I mean, you—it really becomes about starting with what those problems of the customers are, and working backwards from that because you can’t start from the data, necessarily, at least in my opinion; I think that you have to start with the problem space that they’re in, and then you do the best job you can with the data that’s available. Maybe you go out and source some other data, but at least you have a framing for what they’re trying to do with it, as opposed to, “Here’s all the stuff we got. Do the best you can with it.” Which is a very different mindset, I think, in terms of the approach.

So, I love the fact that you’re having these working groups. Sometimes we call these ‘design partners’ in the design world, but I think that kind of regular interaction, especially early, especially often, as frequently as possible, that constant exposure is a great habit. It’s a great thing to share. And so I’m glad that you guys are doing that over there. Jordan, it’s been a great conversation. Where can people find out about you and AMS?

Jordan: Sure, please go to ams-analytics.com. You can check out, we’ve got a lot of research there right now, we’ve got some reports that we’ve been running that have to do with looking at audience sentiment as it’s been evolving over COVID. My contact information is there. And anybody who’s interested in a demo or would like to see the products can reach me there as well.

Brian: Awesome. You were a music ma—I was a percussion performance major. I saw that you have a music degree, too. What did you play?

Jordan: Clarinet.

Brian: Clarinet. Awesome. Excellent. Do you still play?

Jordan: Not so much.

Brian: Not so much?

Jordan: Actually, I play piano more regularly now.

Brian: Oh, okay. That’s all right. No, no, that’s great. That was—it was fun to—it’s always interesting to find another artist that’s moved into this space. So, thank you so much for coming on and sharing these ideas, and I hope we can stay in touch.

Jordan: Me too. Thanks so much for having me. Really appreciate it.

Brian: Thank you. Cheers.

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