The Association of Children’s Museums https://childrensmuseums.org/

Playful Learning Landscapes https://playfullearninglandscapes.com/

Kathy Hirsh-Pasek’s work https://kathyhirshpasek.com/play/

Kimberly Nesbitt’s work https://www.education.nh.gov/sites/g/files/ehbemt326/files/inline-documents/2020/nesbitt-play-based-k.pdf

Angie: Hi, and welcome to the Data Diaries with Dexibit, I’m Angie, and today I’m sitting down with Veronika Gower, who is our Product Director and Veronika has got a really fascinating history, started off life as a child psychologist. Have I got this right?
Veronika: Yes. A behavior therapist.
Angie: My goodness. And then launched into the world of technology and software. And actually before Dexibit worked for a company called Vista with their business unit Movio who do analytics for movie theatres, and now is in the world of visitor attractions, which isn’t all that dissimilar really. Thank you for joining me and welcome.

So the work of product teams has come a long way in the past few years from sort of silo days where business analysts would write requirements away and hand them to a developer who then ships code eventually into test. Why is it so important that we don’t work like that in that fashion anymore, when we are in the business where technology is our product?
Veronika: I think it comes down to the fact that you have different people in different roles. So you’ve got product, you’ve got design, you’ve got engineering and all of these people are keys to you making a product and you need all three in the same room talking about the same problem, approaching it from different perspectives in order to come up with a really good solution that’s viable, feasible, and desirable. So me as a product person, I cannot sit there on my own and come up with a solution, come up with the idea, test the idea with a customer, and then just hand it off to engineering and then ask them to build it because I don’t really know the underlying structure of the code, how complex something is, but also I don’t have an engineering perspective that would guide me and challenge my thinking. And that engineering perspective from a different view… because I come from product and I’m conditioned to think in a certain way, reading the product books that I read. And that’s the whole beauty of having people from different departments, with different roles coming together and using their different perspectives to talk about a problem and idea together.
Angie: So, this is sort of the idea of product trio, is it?
Veronika: Correct. I’ve actually never worked in the way where you only had a product or business analyst defining requirements, and then just passing it off to engineering. I came through the new way of working, which is you have this holy trio, triangle. You have a designer, you have product and you have an engineering tech lead with you at all times. And that’s exactly what we do here at Dexibit. Just to give you an example, we had a customer request to add filters to our visualization so that customers will be able to save these filters of different things they want to do, so they wouldn’t have to add different attributes, they can just save it as a filter and then they just click on that filter and they add it again and they don’t have to keep selecting all the 10 different things they want. Very simple, and then I started chatting to engineering about this. I’m like, “Hey guys, we’re thinking of doing this” and straight away, they were like, “By the way that filters are very complex for our ticketing system because of X, Y, Z. And the underlying architecture that we have from a legacy system in relation to ticketing is complex and blah, blah, blah, blah, blah.” So this work that I thought would be, you know, so very simple for this one data source was very, very complex.
Angie: So you’re kind of solutioning on the fly as you’re understanding the discovery, at the same time.
Veronika: Yeah exactly. So the feasibility of your thinking of what you want to do, impacts what you will do and what you can do. Because you don’t want to be in a situation where design or products have spent months thinking about a problem, if it’s a really big problem, chatting to customers about it, and then only at the very end coming to engineering to understand that, “Oh, this is not even possible. This technology doesn’t even exist for us.” So that’s why you have engineering from the very beginning of problem design.
Angie: What were those things that you talked about? Feasible, desirable, viable?
Veronika: Yeah. So viable in terms of the business perspective, is this something that we want to be building? Is it aligned with our strategy? Where do we want to go as a company? Is it desirable by our customers? Will it add value for our customers? Is it solving some of their key problems that they have? And then always feasible. Is it technically possible for us to do this, given the technologies that we have, or the technologies that are available to us? So you’re constantly addressing these three things, desirability, feasibility, and viability.
Angie: Making decisions around an iterative movement through those things as well, rather than just one big lump sum sort of move as a product at the end?
Veronika: Yeah. It’s sort of trade offs and evaluations, depending on things. So you could have something that’s technically feasible, but very difficult, but it adds such great desirability and value to our customers that, you know, we still want to spend the time doing it. It’s still worth it to go down that route.
Angie: Like that automation for us.
Veronika: Exactly. Very big project, technically challenging. In terms of feasibility, but the value that it will add to our customers, but also the future of our product and where it could go is enormous. And so it’s definitely worth us investing in that.
Angie: So the three of you, product, design and engineering are kind of all making decisions individually together as a team at the same time, by understanding each other’s words and sort of moving through the problem space and solutioning.
Veronika: That’s right. Yeah. And I think to me, that’s the definition of collaboration. And so I would absolutely hate and caution, anyone else working in siloed on their own and not talking and getting those different perspectives.
Angie: Unfortunately, I do have memories of working in a waterfall basis that was what I used to do as a business analyst back 15 years ago. I worked for Hewlett Packard and that’s how IT was done back then. It was sort of before this emergence of, you know, product thinking and, and really sort of product practice. And we did do all of those things. We would spend three months writing requirements with a business without talking to anybody from a technical pathway only to get to the end and find out how hard and big and long these things were. And we would end up sort of with these huge phase approaches that would span multiple years and it would be forever before we shipped anything out. It was crazy.
Veronika: Oh no, that sounds like my personal hell to be honest.
Angie: It’s the way things are done back then, I suppose. So what does that sort of cross functional team look like here?Given the different skills that we need in Dexibit, particularly with data engineering and data science being involved in that picture as well, when we’re delivering?
Veronika: Because we are foremost data company not everybody will have data analysts, data science or data engineers. And depending on the team that we have, so generally you have, you know, backend engineer, frontend engineer, design product. But for us, depending on the team, for example, one of our teams is insights, which is tasked with looking after an area of the product or anything related to the product that delivers visualizations, deep insights, forecasting for our customers. Not so much the experience inside the product, such as you know, how you send an email, how you do reporting, that we have a separate team that looks after that…
Angie: Obsessing over the calendar….
Veronika: … Obsessing over the calendar functionality, the filter functionality. So we actually have data scientists who also feed into that depending on the project that we’re doing. So if we are looking at how to improve our forecast or what we want to do with our forecast, we absolutely have a data scientist who come in on that team and helps us work through the problems and solutions that are possible.
Angie: I think it’s one of the exciting things about here is that at Dexibit being a data product, there are these sort of unique things that come with that land that you do not run into in your general sort of software as a service kind of ecosystem, in other companies. There are very specific things that we encounter that there is not the way things are done already coming out of Silicon Valley or out of the SaaS or tech industry generally, where you can pick up and say, this is how that’s done. You kind of have to work it out as you go along in sort of incorporating data science into a cross functional team or data analysis into a cross functional team is kind of part and parcel of that piece, isn’t it?
Veronika: That’s right. It’s new territory. And you know, we run into issues in terms of how is the best way to structure that, to work with data science and which projects, you know, do we involve them? So it’s definitely an evolving space for us. It’s a learning for us, and there’s just no material out there. And I’ve talked to other data scientists in other companies as well. And they come up with the same problem to be like, there’s no blueprint. It’s a new area of having, you know, data science in product.
Angie: Inventing the way of working as we are.
Veronika: Yeah. Which is an exciting opportunity.
Angie: So that kind of brings us quite nicely into understanding how sort of the research horizons of data science, which when you’re thinking about not for academic pursuit, because we are a commercial company, but when you’re sort of thinking about sort of general research for innovation and progressing that bar forward, how that blends with the roadmap horizons that we think about in product management. How do you kind of make those two worlds sing together?
Veronika: It’s something that we are working on and trying to figure out a better way of working together. But what we want to try and what we’re implementing is, like a three phase approach. There are, if you think of data scientists, they have to do operational things. They have to upkeep our forecasting and the project. And then other project they’re working right now is update dating our machine learning pipelines, a big project.
Angie: This is the Data Bricks thing.
Veronika: Yeah. Data Bricks is so huge, but you know, all these things need to be done, operational things that data science are responsible for and need to do. Then you have data science contributing directly to product outcomes like short term or medium term where they’re working on customer problems. That are, short term horizons, I would say not green field thinking, not that deep research where you don’t know what’s possible, what’s not possible.
As a product company, if you want to focus on those green fields, you probably only wanna dedicate like 10% of your time in that space, because you do have to deliver results and value to the company and your customers. So for us, yeah, we have a roadmap of the things they should be working on in terms of product. I think being very close to product is really important. Right now, there’s nothing that they’re working on for us in terms of very short horizon, but they are working on a medium term horizon and that’s to have a unified industry insight for us. So for us, we have all these lovely customers around the world from different venues within their traction sector. And so we are able to get that data and if we can learn from that data of what how visitation impact like works for that specific, sector within our attraction industry. So if we can figure out how all these art galleries function from, you know, within New York or within certain area of America, and then they can benchmark themselves for a specific gallery. How amazing would that be? So then they can compare and say, “okay, well, everybody else is here. Their visitation is 20% around this time, but we’re actually below that mark, what does that mean for us? Why is everybody else 20% above us? What’s happening for them and what’s not happening for us.” And that actually was inspired from our customer feedback. So a lot of our customers want to benchmark and understand what is happening in the industry, around their space and globally too. That’s a very big problem for them, and they’re not able to solve it themselves because they don’t have access to their data, but we do. And so it’s a very exciting project for us.
Angie: So that unified model sort of both helps us increase the accuracy for individual venues and predict things that we wouldn’t otherwise be able to predict if they were new or novel for that venue. and delivers benchmarking value across the industry, like we’re seeing for Recovery Index.
Veronika: Yeah, exactly for Recovery Index, but you can then take it onto so many other levels, not just visitation, you can do anything.
Angie: And one of the interesting things I think about that, those data science horizons as well is that you’ve got also this sort of data, operations of data science, which from a product perspective in SaaS, you kind of don’t really have that anywhere else. Right? Like in SaaS, you build product, you ship it and then you support it, but you don’t sort of ‘operate’ it. And with machine learning, you, can’t kind of just build a machine learning model, set it free into the wild and never look at it again. Every week you need to continuously improve forecast accuracy and integrity and validity, particularly in a time like post COVID, where things are changing so much. And there might be like new features that pop up or things that change or need to adjust the scope of that data and constantly experiment with that. So that’s kind of a new horizon of more like… current and present, in addition to your medium and long, and sort of research horizons as well.
Veronika: That’s right. And that’s only relevant for a company that does use data and has data. So many other software products. I have to think about this. But it is an area that constantly has to be looked at and thought of for example, recently, we saw another forecast falling, not recently, but you know, a few months back. And then the data science team were like, what could we do to make it better? And they looked at different factors and, you know, they tried COVID as being one of the variables and that was actually a great variable to use. And now we’ve implemented that into our machine learning. COVID a factor that helps our models predict better. Again, if you’re not constantly looking and innovating, that specific area, then very quickly it can go down. It’s like a little baby that’s constantly growing and looking after.
Angie: And so what about the topology of product teams? So what goes into the decisions around how you sort of structure your product teams here?
Veronika: I think there’s many ways you could go in that area, theoretically. What we’ve done is we’ve just looked at our product areas. You know, given the size of where we are at right now, what’s happening with the product, and we’ll just cut it up into three teams in terms of product teams. So, as I mentioned before, I think so we have the Experience team that looks after the overall experience of our customers entering the product, doing certain functions, like sending emails, how they’re using the studio, like their overall experience, how can we make it easy for them? How can we make the product more intuitive for them? How can we save them time with our product? And then we have another team that’s Insights team, and that’s focused on answering their key questions that they have of the data. How can we make data inspired. How can we help them visualize their data in a way that makes them have insights and brings value to them? And then comes on the experience to be like both very easy and intuitive and everything else, and yeah answering those other questions. So, you know, to be for a marketing team, what metrics do you need to know? What metrics should you be tracking, or what should you be measuring in that space to be successful? So that’s the insights team. And then we have our team of Automation, and that looks after our ingestion pipelines and everything that happens within like a data product, you know, how data comes in, how it’s integrated, how it’s transformed. So that’s a huge, huge piece for us, a crucial piece.
Angie: So it’s sort of building a new data automation platform underneath all of the app that everybody sort of interacts with as users.
Veronika: Correct. That’s a project that that team is working on right now. You’re building an entire data processing system.
Angie: So you wrote an article recently on our blog about our ways of working in product at Dexibit and you made a mention in there of all of these sorts of things around not working in silos and having your product trio and your cross functional teams and blending the research horizons for data science and finding out the right topology and all these sorts of things. And you connected all of that, that ways of working in products to our team satisfaction. And you had some really interesting findings there. What was that all about? Where does that idea come from of, of that connection?
Veronika: So when I first joined Dexibit I noticed that there was some inefficiencies and a lot of chaos in this space. Obviously Dexibit didn’t have a product owner before I joined. So a lot of the teams were unsure of the overall roadmap or of why they were doing something. The work wasn’t broken down enough for projects. So then the teams could not give a realistic estimate to the business of how long something would take. So then if they would say, “oh, it’s a small project,” because it wasn’t broken down enough when you start digging, it turned out into very large projects, which then the business, you know, didn’t think it would be as large and then potentially wouldn’t have made that decision to work on that specific feature had the business really known how big it was versus what the value that it would deliver for us. And so then there’s frustrations between the business and the engineers and people feeling a bit stressed, like, “Oh goodness, I can’t deliver on this now.” And feeling under the pump, because they’ve said that they could do it. And so I think that’s kind of the key of coming in, putting all these processes in place, best practice, to just ensure that there is that clarity and that process. And it’s well managed and expectations are well managed and we de-risk projects so that we do know what we’re doing, why we’re doing it, how we going to do it? Again, bringing engineers. You know, and solution architect in earlier on to help us design that solution before going ahead and just building it.
Angie: And there’s been a huge uptick in our team satisfaction as a result.
Veronika: Yeah, so we do these surveys within the company. And so it was amazing to see people like, you know, saying, you know, how clear are you on the outcomes or just team sentiment? Like their happiness and yeah, it was just amazing to see.
Angie: You’ve implemented this sort of dual track, agile product development process, and that’s all connected to this idea of pulling in people earlier into planning and doing that discovery and delivery, often simultaneously. What’s the sort of TL;DR… Too long, didn’t read story on how that all works and mechanisms of that?
Veronika: So in practical terms, that means we are actually building features and we’re planning for features that we’re going to build next at the same time.
Angie: So you’re holding both in your hands.
Veronika: You’re holding both in your hands. And there’s just different stages at which you involve which engineers. So we have the trio that does all the initial planning. And then you have the rest of your team engineers who are building the product, the feature that they’ve already broken down, we’ve sized this all up. We have the solution design for it. That’s fine. That’s happening. And then when we are ready, when the trio is ready, we bring in the engineering team that will be working on the next feature and we ask them to take a look at it, to think, to elaborate it, to start breaking it down. So then they’re building something and breaking something down so that by the time they’ve finished one feature, we have the next one really broken down, greater understanding of it. And that way they see what’s coming up, they’re aware of the work. And then we as a business, understand the complexity of that work. So then we can provide better clarity to the rest of the stakeholders of what that entails what’s possible. Which really helps our roadmap and communication with customers.
Angie: One of the things I’ve noticed in the last year or two since you’ve been implementing all these changes and particularly under your leadership and Daniel’s has been this introduction of continuous discovery and a huge amount, more investment in the energy that we spend in discovery before we embark upon delivery. And I saw a really cute quote on that on Twitter or something over the weekend around the fact that as a company, you do that discovery, and you either do it consciously at the start before you start delivering, or you do it subconsciously during delivery, which costs you a huge amount more, or you do it after you ship a product and no, but you have to do it at some point, right? I think that that’s been one of the biggest changes that I’ve noticed is really the amount earlier that we are doing that discovery and really testing out our, our ideas before we start developing. And that has meant that everything we’ve shipped has been beautifully designed, beautifully validated and tested out and has great features that immediately has a lot of uptake for adoption and usage that we see immediately, as opposed to prior where we sort of, almost tested out quite a lot of ideas in live product which probably had a lot more investment in them. And then we ended up with kind of a scramble of things that we had to unpack afterwards, because there was a lot of unproven ideas in there.
Veronika: Yeah, that happens really often for a lot of companies that I have had that experience myself as well, if things are not planned out. And I think one of the core things that causes that is rushing or just not having somebody to manage expectations or these products or the sizing of them. You have to have that space. And as you’ve mentioned, Angie that practice to be like, “no, no, no, before we build a single line of code we are going to do the research upfront about it. We’re going to think about this problem. We’re going to understand this problem. And then if at the end of it, we decide we’re not gonna do it, then we’re not gonna do it.” But yeah, no single line of code should be written before we’ve had that discussion.
Angie: Yeah cause we’ve always like capacity is a great example of this. Capacity is something that we tackled pre COVID because we have customers that deal with capacity problems that are long standing, you know, that just have more visitors than they can fit in their venues. Then we encountered capacity again, through COVID, particularly at the height of the pandemic where everybody was capacity controlled by government decree. And then we’ve sort of got the life life after COVID capacity controls for people who are retaining that, or maybe have special interests for particular exhibitions or events or whatever it might be. So we’ve kind of had three bites at the apple of pulling off capacity. And if I look at the discovery experiences of all three, they are really different in terms of the work we’ve done and the product that is resulting, or the solution concept that results from that is far superior now to, you know, that first thing that we put out in the market, which to be honest, I don’t think anybody used versus now something that’s, you know, quite ingrained with the operations of many different attractions. But it is really cool to see, but an awful example, if you like, of, of things that we’ve had to throw out because of, we didn’t invest enough in, in our discovery
Veronika: And look, I don’t think you can always build products and always get it right?

Angie: Yeah. That’s so true.

Veronika: Yeah, absolutely. There’s no such thing as perfection. But what we aim to do, and especially a passion of mine is just to reduce the risk for the business. So then if I know we’re following the best processes that I’ve seen work, and many of my other teammates have seen work, you know, if we do our due diligence and we do the best that we can, then we just de-risk that issue and, you know, deliver real value for our customers. And if we don’t get it right, sometimes that’s okay. We can see where did it go wrong? Well, why is this not a value? That’s very powerful.
Angie: And what does that customer discovery look like? Particularly, I know again, if we come back to Dexibit being a data product, and Daniel talked a little bit about the sort of recent industry presentation that he did, where it’s really hard to test out for a data product, whether somebody is actually having that light bulb moment of going, “Hey, I understand that I took away insight. I’ve gained value. That’s gonna help me make a decision in a different way. That’s been informed by this.” How easy is it for them to get to that from a data product? How difficult is it for us to test that that’s happening with a user as opposed to your standard old SaaS product? That feels like it’s, it’s a real complex world in there.
Veronika: Yeah, absolutely. Especially when you take the fact that so even if they understood the insight and gained value from it, there’s no way that we can measure they acted on that insight because they’re acting and those operational strategic decision making happen outside of our product, you know, because of our data. Did they change how many people they scheduled on for the month of June? Yeah. We have no way of tracking that. So that makes it difficult. But we do have monthly business reviews with our customers. So through those conversations, our customer success is able to probe and ask and have those conversations to help us out in that space. And also in terms of just testing new ideas and prototypes, we ran into this problem. I didn’t realize how much, how difficult it is to test new concepts when it comes to data stories with customers. And so what we learned is that we have to have the right customer for that data story. So for example, we have data visualizations for revenue. If we have new insights about revenue, we wanna share with those customers and get their feedback. There is no point showing that to a person who’s not interested in revenue, doesn’t work with revenue. But we must get the person from the finance team to take a look at that insight and see if it is valuable for them. Did it give them something new to walk away with? Can they make a decision based on this information? So absolutely getting the right person to look at that data and also giving them time and space to look at it. It is something that doesn’t happen within a second. They do need time. And so we came out with the concept of the experiment module. We will input these new visualizations and insights and data stories. Let the right customer know, “Hey, this is available for you. Please take a look.” And then later we follow up with questions so that they could take a look at it on their own. Without us there because ultimately…
Angie: Pressure to understand something in the moment. Isn’t it? When everybody’s watching your reaction?
Veronika: Yeah, exactly. And plus I, I’m not going to be there holding their hand when they’re using the product. None of us are going to be there. So we want to design a product that can stand on its own so that we have the right experience, the right health documentation, the right visualizations. That customers can get the value themselves without us.
Angie: So it’s kind of a, a live data prototype. If you like to test out this feasible, viable, desirable type side of things, to make sure that we can, using their real data, show them something that’s an insight of value, as opposed to kind of the traditional way of testing discovery, where you show somebody a mock up. It’s very different, isn’t it?
Veronika: That’s right. Yes. So the key, I didn’t mention here that it has to be their live data too. The nuances of that customer’s business rules need to be taken into consideration to see what was happening with their live data when we input this in whether with other products that have worked on, or like, you know, you think about an email editor An email editor is the same for any customer makes no difference. What data you have, what data you don’t have. It’s a simple function, the same, everywhere. But when you’re talking about revenue, they have different business rules. They, you know, some want to see very granular business line like item line, you know, chips versus somebody who wants to see just cafe data. Two very different concepts.
Angie: Yeah. It’s one of those, again, those sort of unique circumstances of data products that there’s not the playbook for how to do this. So this is one of the things that you all have discovered is important.
Veronika: Right. And I’m just so fortunate we have Daniel who just guides that process and helps us.
Angie: And so take me through what’s next for the product culture here at Dexibit.
Veronika: I think we want to continue down the route of best practice and then bringing everybody onto that journey, especially as we have new staff members joining and growing not everybody comes from the same experience, knowledge, skill set in terms of how to build data products. So I think it’s important that, yeah, we align everybody and explain to everybody of why we’re doing something, how we’re doing it, how we’re building products at Dexibit, you know, what kind of practices we want to implement, why we have the dual track of delivery and discovery, why we have the product trio, why we talk to our customers, why we take a customer approach and we don’t just product designing something that they thought up without talking to a customer or an engineer just going away and doing something without talking to product or a customer.
Angie: So you’ve sort of got this people integration challenge when newbies join of first of all, inducting them into these practices of product and then sort of adding on the data products layer of our thesis, of how those practices apply in a, in a world of data products where these challenges like live data prototypes. And then you’ve gotta layer over the fact that we’re doing that in an enterprise market. So we do that in different ways when we’re working with our customers,
Veronika: Correct, yeah. It is quite different. Again, you know, if you’re working for a product that’s not enterprise or what, you know, $5 a month. Yeah. Very different. Processes that you would have and the scale at which you would sell, everything’s just different, the business model’s different, how you develop, how you can test, very different.
Angie: Well, I’m so excited about where things are at at the moment. The product, but also the product culture here has come so far in the last, you know, year alone. And you know, when I think about where it’s gonna be and another year from here, it’s very exciting to look into the future and see all these ideas of what a post modernization ,post modern, if I can use those words in an app podcast looks like for us.
Veronika: Absolutely. Absolutely. I just, yeah, I think we just have a great team. Everybody here is so engaged. So it makes my work really easy. And yeah, just everybody understands and is willing to listen, willing to change, you know, I just love that.
Angie: Very cool. Thank you for joining me for a cap of hot lemon on this cold winters morning.
Veronika: Thank you, Angie.

Angie: Over in the past few years, the world of data and visitor attractions has come a very long way. So joining me today for our next episode of the Data Diaries is one of its leaders of data analytics doing that work on the ground in one of the world’s biggest cultural institutions I have with me, Baku Hosoe, the head of data analytics at The Metropolitan Museum of Art in New York. Welcome Baku!
Baku: Thank you for having me.
Angie: Baku, you came into the museum field from a consulting background. How does analytics and visitor attractions compare to what you’ve seen in industries like finance, telco and pharma?
Baku: Yes. It was a very different from what I was accustomed to. In many ways it is much more difficult to think about analytics in visitor attractions perhaps because when we think about people’s decision to visit a museum, it is not a transactional thing, it is something that’s deeply emotional and many of our visitors come with high expectations, leave with great satisfactions and often repeat. And so it is even more important than ever, and in a way, very difficult to understand the rich and nuanced experience of each of our visitors and derive insights on how we can improve.
Angie: And it’s always sat pretty close to the executive, the data function at the Met – and from memory at your board level as well. What was some of the origins and the drivers that were behind the data initiative?
Baku: It has certainly been a multi-year effort. There has always been strong interest from all around both internal leaders, as well as board members and even some of the donors have also pinged the institution about what we’re doing with data and how we’re improving the use of data. They all felt the need to invest in this area, which actually helped create my position as well.

It can be seen as a bit of a reflection to go along with the changes in board structure as well. One of the key changes they have made in recent years was to form a revenue committee, which is really aiming at improving the visitor experience all around. And that goes hand in hand with the creation of the data team to have visibility across all the data silos and business unit silos and provide the best in class experience across all the aspects of the interaction with the Met to our visitors, because ultimately whether they show up at the stores or visit the Museum or go to the concert or go on to become members and participate in different live events, they’re all the same people. And it is really important to have a holistic view about each and every one of them. 
Angie: And it’s such a wonderful thing to see, data championed at such a high level. I think it’s one of the key factors for success that we’ve seen in visitor attractions is that it really does need to come from the C level, if not even higher, and so fabulous that the whole board, is on board so to speak, at that level at the Met.
How has your role  evolved over the course of the last few years?
Baku: For one thing to state the obvious, COVID has thrown a wrench into our plan for sure. I have a stepped away from data to work on COVID related project management around the closure and reopening. But putting that aside I would say that my overarching responsibility has remained the same, which is to be the change agent and in a way, an evangelist for the use of data to derive the insights and to inform decisions and actions throughout the museum. But tactically speaking for the first year, I’d say much of my activities or around building things, creating reports, doing things for people. And compared to that, lately things shifted more to influencing or enabling people throughout the organization. That is definitely a one noticeable change that has happened.
And at the same time I think some of the key priorities or focus area have widened. It hasn’t shifted, but just widened, in that for the beginning, it was really important to show visible and measurable ROI through the pure focus on the revenue and audience. But now there are much more efforts around how to improve the operations internally through the use of data, how best to utilize the rich collections data that we have and how to establish the governance structure and a community mentality fostering  the data culture throughout the Met.

These are all the areas that have become important almost if not more than the revenue from.
Angie: That last piece is so interesting to me, the way that the focus has widened over the years, because in many cultural and institutions that we see, the focus has actually gone the other way recently with COVID, that they had started out a few years ago with a really broad scope with data. And we tend to encourage people to get narrow in the first instance, when they’re starting to work with data, but in sort of the post COVID months that we’re in at the moment, and that has become really hyper-focused on revenue. Which perhaps, for a lot of cultural institutions, isn’t something that they naturally would’ve started out with. So it was really interesting to see that your journey’s almost taken you in another direction at the Met over the past few years.
Baku: Yeah, it is certainly dependent on the institution. And I think what is happening at the Met in particular is that with the COVID and with the macro trends around the labor force, we are all asked to do more with less.
And when we think about that, it is very important to be efficient, effective, and really be able to prioritize and focus on what matters. There are technologies out there that help us do it, but there wasn’t as much impetus on required being required to do so. And COVID has changed the formula. And I think people are much more excited about having a better way to improve the way we work and the way we manage our work through data that is a driving force behind the broadening of the scope, so to speak.
Angie: So there’s an efficiency layer to that as well as there.
Baku: Absolutely.
Angie: And you make a really good point around data governance, right? That is also a piece that we see as being a really, really important part of the sort of best practice equation and cultural institutions. Because a lot of the work of data is finding out where it came from and making sure that the critic business rules are applied and making sure everybody knows what those things are. And then managing for things like privacy and security and the validity of data as well, and its integrity. Is that what that work comprises for you at the time?
Baku: Absolutely. It really is about having a more explicit structure and also a centralized focus on those areas. All the industrial changes, regulatory changes that are happening around us, impact all of us and influence how we think about collecting, storing, using data. And yet in the past, many of the data users within the Museum were operating more in silos. And there were at subscale when it comes to thinking about all the global changes that are happening. So it was all the more important to create a governance structure and committee that actually look at these things and ensure there is the right level of access, for the right reasons. And keeping transparency and above all, staying in compliance with regulatory changes… an environment, that’s constantly in change.
Angie: And one of the things I think is really interesting. You’ve you’ve built your data department up to include a few people and cross-functional roles as well from across the Museum.
I know a lot of other attractions are really busy hiring data roles at the moment, and it might include their first data roles, or somebody like yourself. But, in your view, what sorts of roles are most useful to hire and what order should they hire?
Baku: I personally think there’s no one right answer that fits for everyone. As we think about data as a function, it is still in the early stage of maturity curve, unlike other established business functions like HR, finance or IT. And I think for many of the institutions, the resource limitations, and really the degree of ambition surrounding the data topic, dictate how best to structure.
Angie: So Baku, coming back to this org structure of how you approach data, what are your thoughts on outsourcing versus insourcing for that function? One of the sort of elements that go into that decision?

Baku: Again, I think there’s really no one right answer that fits all in this particular one. One of the things that I needed to do early on as I started my role was to really evaluate our internal capabilities that existed at the time and how data was structured. And what we found for ourselves was that our data resources existed. But they were scattered throughout the organization and the types of tools they used, the level of capabilities when it comes to data topics, were all at different levels. And more importantly, there wasn’t any conversation across that data resources, because they’re all reporting into different organizations. So when thinking about the design overall, the two main questions we asked was: one, whether to centralize or decentralize data capabilities and two, how much to insource versus outsource. And I think the question is applicable to any institutions who are thinking about the design, but the right answer would be very different depending on both the reality of the organization, as well as the resource limitations and ambitions for the data function in the institution. On the questions or centralization versus decentralization, it really comes down to how different are the types of insights that are needed to be effective for particular areas. And what we found was that there is a very significant difference between say, a retail department versus a fundraising department, versus membership department. So the way we’re approaching it is that there is still a component of centralization, through my team sitting at the data analytics office, but we also have very specialized data resources in some of the key departments. And we all work together in the area where the consistency makes sense, but otherwise have developed very focused capabilities on how best to deliver insights for that particular department. And similarly on the questions of insourcing and outsourcing, outsourcing works effectively when there is not enough in sort of in house capabilities to build it from scratch. Whereas insourcing works flexibly when you already have resource who can handle that. So it does really come down to the scale of your organization and the resource availability as well, too, to decide whether to invest in particular area or not. And for us, we are definitely doing the mixture of it. So in some of the areas, we have more than one data analysts who are really going deep into to utilizing AI, machine learning, to deriving insights themselves in an in sourced fashion. In some other areas, we utilize outsource vendor for both the creation and analysis of the data. So there really isn’t one solution fits all, but really dependent on the reality of your organism.
Angie: It’s great to hear that, that such a conscious decision for you, because I think this is such an important question that is often really skipped over in favor of just talking about the solutions, rather than being a strategic one. And one of my favorite pieces of advice that I was given a long time ago on this question was to insource or to build the things that are unique to your organization. And then to outsource, or to buy the things that are common in your industry, so that you sort of concentrate your investment into the areas that make your organization special. And it sounds very much similar to some of the things that you’ve been doing at the Met. Because the total cost of ownership of some of these data solutions can be… when everything is built in house… can become incredibly, incredibly heavy to bear for one organization, when you think about maintaining something, and as, as you’ve mentioned before, going through a roadmap of, of developing something over over a period of time as well.
Baku: I cannot agree more with your statement there. One of the things that we have to realize is that as, as cultural institutions the Met is obviously one of the bigger players in the space, but even we are subscale for many of the things. And when we think about the industry at large, there’s a tremendous value in having an outsource vendor who can scale more effectively for the type of topics that impact and influence everybody as you noted.
Angie: Whereas something like collections data is going to be so unique for each organization. You know, it’s something that differs so broadly between say an art museum versus a history museum versus a science museum. And, you know, at that point there is sort of no productized approach to it is there.

And what about the sort of attributes and skills we should look for in data hires. What do you see as being the best people to get for the job?
Baku: I think, generally speaking, there are two elements to think about. One is about the business skills. And the second one is about technical skills. And really it is a question of, what’s the status with data champions, so to speak, within the organization, in terms of what should be the focus or priority in each. To elaborate further on this, I think I believe strongly that one of the most important thing is to have one data champion within your organization, fairly high up so that, they can have both visibility into what the institutional priorities are, but also to be able to channel and provide the best findings, the most useful findings from data initiatives, to the senior leaders within the institution. And this person’s key role is to really elevate data to insights, and then to tell a story that would then influence decisions and actions at the most important levels. And that really comes from having a robust understanding of the business and being able to talk and engage at the board and the management though.
Angie: That’s such a hard trade-off, isn’t it, that a lot of attractions have to make. If they can only get one hire. Is that sort of an analyst? Do they then bury that in the finance department or marketing department or something similar, ticketing, et cetera? Or is that a leader, that can then show that venue and help connect as you say, the business with the data, to turn data into insights and to really start to prove that right.
Baku: It is certainly a hard decision. But I do again, think that when it comes to to data, the reality is that I think most institutions have very rich data already. And if you look at the market, there are tons and tons of analysts as well as many excellent services and vendors and tools and softwares that allow you to do most anything. But what you need to have is somebody who can help guide prioritization of where to focus and to use these tools in the right way. Otherwise you just drown in the sea of options and choices and resources. So you have to start with the data champion and from the there, you make a more difficult trade off in decisions of the second person you hire, how much focus to put on the technical skills versus business skills.
Angie: Speaking of that champion, a big part of that job, I imagine is really encouraging adoption and usage, rather than sort of simply bringing data to people to give it to them, but rather sort of teaching them how to fish for themselves. For your internal users of data at the Met, how have you gone about that?
Baku: I think it really starts with showing a bit of a proof of concept on what ‘good’ looks like. So, what I try to do is to keep mind of an understanding of who are going to be important stakeholders who will be using data in depth. We can first take on a bite size project and do more of the building process through the centralized data team, but then show, really illustrate the value that we can provide through this. Once there’s a buy-in on this, I think generally speaking, there’s a lot more willingness to learn and adopt and invest in that area from each of those areas. So we would then work with them to focus more on the enablement and training element, as opposed to doing it for them. That’s generally the sequencing of it, but all of this needs to start with being able to show actual values to start out. And that goes back to having a conversation and really good understanding of what the key questions are for each of the areas, what the problems they’re trying to solve, what are the hypothesis they have about the opportunities? And really proving or disproving them through the use of data.
Angie: It’s such sage advice for everybody in this area is  distilling things down into problems and then questions and then hypothesis, or even in some cases, assumptions that people might be making that need to be proven right or wrong.

What about developing data literacy? How have you approached that?
Baku: One of the key things on the data literacy throughout the organization is accessibility and also providing how to read and utilize insights. So to give a tangible example, we’ve created a automated dashboards and reports, which is now actually open, not just to the senior leaders of the organization, if we used to receive such reports, but also to a broader set of people within the institution including mid-level managers and sometimes even all staff. And the key is never to just distribute reports in PDF format and help people take a read, but to accompany with presentation Q and A’s, some sort of sessions to engage them in both describing and having them truly understand the takeaways, but also having them an opportunity to lead to ‘so what’ of findings. That kind of effort takes a lot of time, but it pays dividends in really making people pay more attention to it and having a better understanding and actually having them create more questions and requests that help us make better decisions. So it helps everybody to increase the awareness and understanding and interest curiosity around data.

Angie: It’s funny, isn’t it, it’s sort of that moment when you bring data and insight to a group and you walk away with more actions and questions… it’s actually the successful outcome that you aimed for, rather than everybody sort of smiling and nodding and saying, great, let’s move on. So the work has sort of never done, is it?
Baku: Absolutely. That’s the, that’s the blessing and the curse of the role for sure.
Angie: And what sort of changes have you seen in how your team communicate with each other or collaborate over data or how they make decisions or their team culture? What sort of impacts have you seen with this work?
Baku: I think we’re still certainly in the middle of the journey on this one and by no means  we’re done with this sort of transformation. But one thing I do really enjoy seeing is that people often have conversation at the beginning of the project, or a fairly early on in the project, to discuss how to evaluate and how to think about the success. I think so much of what people used to do was around – here’s a great idea. These are all the reasons to do it. Let’s do it and let’s discuss how to do it. But not so much on what, what does success look like? And numbers are not the only thing for sure. There is a qualitative and quantitative aspect to measuring success, but the fact that people are thinking ahead and thinking about that question as they design and come up with wonderful programs within the museum is very encouraging to me.
Angie: Speaking of that qualitative and quantitative view, I know you recently merged the visitor evaluation function at the Met into your data and analytics team. How do you see those worlds of that traditional qualitative world colliding or complimenting the more quantitative space of analytics and conversely, how does the technology of data analytics disrupt some of those more traditional approaches in that field?
Baku: Qualitative data compliments quantitative data in many ways, they go hand in hand, especially to tell a story. As we have previously talked about the importance of that. Numbers are very cold. There isn’t as much of a sense of feeling and emotions behind it. But once you compliment the quantitative analysis with the qualitative backups, you really put the actual human beings behind data.
And this helps both convey what really we’re finding and what are the things that we can do to improve people’s experience. And technologically speaking, there has been a tremendous progress in many areas, just from the way the world has shifted over the last several years. Couple of examples that really come to the top of my mind. First one is email collection. So COVID has really pushed us into approaching online ticket ticketing more fully. So prior to COVID, most of the people coming to the museum, didn’t buy tickets in advance. They just showed up and bought the tickets through the registers or kiosks. Now the majority of people purchase tickets prior to visiting the museum. And this actually allows us to collect contact information the emails, which allows us to conduct a much better post-visit surveys on follow-ups with our visitors. Turning to on site. The fact that there is a higher and more technologies are supporting on-site surveys, like iPad, the multilanguage surveys and just the sheer quick turnarounds of the findings and survey respondents to be able to derive insights quickly. It has been a game changer on speed to insight. And thinking a little bit about the qualitative data, the world of AI with natural language processing, to be able to analyze thousands, tens of thousands of customer feedbacks through the use of AI to categorize them and quantify even the quality of the comments have certainly allowed us to track what people are  thinking, and saying to us in much more efficient ways.
Angie: Natural language processing. It’s such a good example of how the qualitative and quantitative can come together, even if it is just a first pass, isn’t it? Because previously a lot of those comments would have to be manually coded from scratch by the visitor evaluation teams. So they have to go through and say if they positive or negative or what sort of topics and emotions are coming through and to be able to have that first pass where they can still go and confirm those things and, you know, obviously go and do a lot deeper surveys or processing to get their core takeaways of the meaning that people are giving across. But it does, it does help speed up that process of very manual labor. And focus the time of visitor evaluation on interpretation, as opposed to codifying.

Baku, what sort of obstacles have you had to overcome in executing data strategy?
Baku: I’d say, it was not quite an obstacle, but one thing that did come up as necessity is the, is the need to relentlessly prioritize and focus. There are almost too many things that can be done in the world of data and the museum. And it has really been important to create and maintain and update a multi-year roadmap with a clarity around what we’re focusing on this quarter and next quarter, and so on and so forth, as opposed to taking on all tasks and, and failing at all. This comes back to the resource constraints. If I had a team that’s 10 times as big, obviously we can do more in the shorter time. But just like any cultural institutions, we do have resource limitations. And that really requires us too to know what the focus and prioritization should be.

Angie: And what are some of the biggest challenges you see, if we are looking forward to the future, whether it’s at the Met or more broadly in the whole industry for all cultural institutions, can you leave us with your thoughts on where visitor attractions and working with data are headed?
Baku: Yeah, similarly, I think in general, there’s still a lot of uncertainties when it comes to data as a function, especially in the cultural institution or visitor attractions at large, there probably needs to be a little bit more time and cases being built from in this phase that we’re in with the evolution of the data as a function before we have a shared understanding across the industry of what good looks like. And here are the types of people to hire and here are the types of things people work on. And again, technology is already out there to really unlock value from data that exists, but there really isn’t a sufficient amount of, or availability of the talent and resources who can help bridge the gap between the technology and the cultural institutions, and have a holistic vision for data approach at large. So I think that that is the piece that the next several years will be a time for the industry to really develop and cultivate.
Angie: And it is going to be such a challenge, particularly with the tight labor market we’re in, at the moment as well, for the cultural sector to then compete with the commercial one. It’s going to be a very difficult challenge to address.
[Baku: Certainly agree. Looking at the bright side of it, including myself, I think I think of this as, as a truly, truly a big white space and opportunity for the like-minded people. I am reminded every day, how much value I could be delivering by unlocking values through data. And I’m always feeling constant feeling of need to do more and more and more because I know I can help the Museum make better decisions and actions by working on certain things. It’s just that, you know, there’s a limit to how much one can do in one day. But I do think the same applies for anybody within the institution. And the fact that it is still under developed, or still in the developing phase, really gives opportunity for the people to explore what they can do here in this particular industry, and the areas compared to some of the more well-established industries where the use of data is already codified and cleaned up. And there’s not much more exploration to be made.
Angie: It is fascinating, isn’t it? I think over the past, I think… five years, we have seen data go from experimental and sort of the early innovation of research and then into sort of proof of concepts and pilot projects. And now very much into evolving functions where the focus is on return and deriving value. And really seeing that sort of maturity of the industry, if you like in the data world, it’s an exciting phase to be in.

Baku: Absolutely. 

Angie: Baku, thank you so much for joining us today and for all of that fantastic advice for those people who are going to follow in your footsteps of becoming data leaders themselves and, and for the institutions that will follow in the footsteps of the Met in investing in that function and navigating all of the highs and lows you’ve no doubt been on over the past few years, particularly with the pandemic thrown in there. Really appreciate you joining us today and thank you so much for sharing that journey.
Baku: Thank you very much.

Angie: Well, hello and welcome to the Data Diaries. I’m Angie Judge from Dexibit here today with Nancy Proctor, entrepreneur, historian, and thought leader. Welcome Nancy. 

Nancy: Hi, Angie. Thanks for having me. 

Angie: Nancy is the Chief Strategy Officer and Founding Executive Director at The Peale, which is actually the first purpose built museum in the U.S. and now the center for Baltimore stories and a laboratory for cultural innovation too. And Nancy has a fascinating career history. She was previously Deputy Director of Digital Experience and Communications at the Baltimore Museum of Art, before that – Head of Mobile Strategy and Initiatives at the Smithsonian, Head of New Media and Initiatives at the Smithsonian’s American Art Museum, and has a PhD in American Art History, a background in filmmaking curation, feminist theory, and criticism in the arts and lectures and publishers on technology and innovation and museums impressively in French and Italian, as well, as English.

Outside of her cultural and academic work, Nancy and her husband Titus Bicknell co-founded The Gallery Channel in 1998, which was later acquired by Antenna Audio, where Nancy led product and sales for many years, going through the acquisition by discovery, coming into the Travel Channel.

Nancy, that sounds like the world’s most interesting career history to me. Can you take us back through that story of how that all got you to where you are today? This most amazing mix, this very unique blend of entrepreneurship and academia and commercial and cultural industry leadership. 

Nancy: Well I will definitely try to at the risk of perhaps being guilty of, as I say, I’m being asked what time it is and telling you how to build a clock. So I had a lot of different interests in life. I ended up for personal and strategic reasons more than academic ones, attending the North Carolina School of Science and Mathematics.

Even though at that time, I really thought of myself more as a writer or certainly more of a creative humanities person, but it meant that I got to spend some formative years with serious scientists, and technologists. In particular people working with early computer coding and that kind of thing, and developed a huge appreciation for geeks, I guess and subject matter specialists of all sorts who are really passionate about what they do. I’ve tried to always follow my passion in my career and do the things that I found were most interesting to me. And indeed that kind of came through when I was working on programs for conferences like muse web or before that MCN and the Tate conference, when people would say, well, what do you want me to talk about?

I would always say, well, the thing that makes you the most passionate, the thing that you’re most interested in because that’s what’s going to engage others. And similarly, I always said, I will learn any subject matter as long as I have a great teacher. So that’s, I suppose, been the engine behind my journey.

It was just following my interests, but I’ve been very, very fortunate and not least at birth that although, you know, I don’t come from a terribly wealthy family or anything. I nonetheless was born white and able-bodied, in a country where I had certain safety nets, systems that meant that I could afford to take certain kinds of risks and have more or less gotten away with most of them.

I started out actually studying classics at university and I was paying my own way through college. So I was thinking about the economy and getting value for my money and realized I could get two majors for the price of one. So I was like, well, what would be a good second major to add onto classics?

It’s gotta be easy because classics is hard. And I perhaps naively decided that art history would be a good compliment because it was mainly sitting in a dark room, looking at pretty pictures. Subsequently I found out that there’s a lot more to art history than that, but I think the common denominator there is history and it’s only actually been fairly recently through my work with The Peale that I’ve realized that I really am inherently a historian.

And that’s because history is really stories and in romance languages. In fact, the word for history and story is the same. I just love the way those things came together. Early on I had some fantastic history teachers who taught by simply telling the stories of our past. So that was kind of one piece of the puzzle. I also very early on met the person who became my husband, Titus Bicknell and, and really my partner in, so many things in life. He too, came from a humanities background as a writer, a poet, something of a composer and musician but got very interested in early computing and had a roommate who was a computer science major and a potter.

So there’s this kind of pattern of finding one foot in the sciences and one foot in the arts and humanities. And so through Titus, I learned a little bit about early computing. I ended up doing a master’s degree at the university of Leeds, studying with Griselda Pollock that was feminism and the visual arts, try to apply some of the theory that I was studying to questions of what is a feminist art space, what is a feminist exhibition? What’s a feminist curatorial practice. But of course I was a student and I had no money still paying my way through school. And I didn’t therefore have the means to publish a catalog and Titus suggested, well, how about instead of a printed catalog having a website. and I was kind of like, I’m not really sure I know what a website is, and I certainly don’t know how to build one.

We’re talking about, this would be between 1992 to 1995. I think we built our first website actually in ’95 for an exhibition that I curated. And I liked so many, I had the hope that the internet would, would democratize access to, to art in particular, contemporary art and make it easier for artists to reach collectors and be better known and make money off of their practice without too much mediation. of course we found Out that the power of capitalism meant that that effect was not entirely realized, but it did get me into, technology. For arts and culture and cultural publishing. And that was, really the impetus for our starting initially something we called new art which was kind of an exhibition project that was the first CD rom as well as website of contemporary art in the UK.

I’m still based, I think by this time doing my doctoral, at Leeds university, ironically, perhaps studying 19th century American women’s sculptors, but also doing this technology thing and that led to our founding the gallery channel, whose aim really, again, quite naive.

I wanted to capture the sort of marginal exhibitions and art practices that were typically underfunded, therefore couldn’t again, publish themselves as catalogs or create any kind of lasting record, but that we’re doing really important, radical work on art, on art discourse on, on curatorial practice. And I didn’t want that knowledge to disappear. This is the historian coming in, the archivist. I wanted to preserve that knowledge for others to build on, and so The Gallery Channel was built. We started in 1998 with the idea of documenting exhibitions through virtual exhibitions tours that would be image and text and audio based ways of online walking through real world exhibitions.

Of course the problem, there was the business model and there was also a technology problem. First of all, in 1998, we’re still all operating on dial-up modems. And so not really great bandwidth for downloading lots of images and high file size content. But also the people I really wanted to serve and work with were artists who were too poor to afford a catalog or even hiring a traditional exhibition space.

That’s why they were working on the fringes. So they certainly didn’t have enough money to pay me to, keep this business going. The good news is we learned a few things from that about business. We also learned about how valuable the listings were, just the knowledge of what exhibitions were happening, what artists were involved, what institutions in places were involved, that that had a value.

And so we were able to syndicate that listings content to like Lycos, which older members in your audience might recall was one of the first internet portals and browser systems. However, as the internet bubble burst and that revenue stream started tanking, we transitioned to a new phase, which is our knowledge of technology for cultural publishers. We became valuable to companies like Antenna Audio the audio tour company that – I think they recently closed actually – but they came to be known as Antenna International. In those days they were one of the biggest audio tour companies in the world. They had lots of major clients ranging from the met to the Louvre to the Vatican Museums, Rijksmuseum Museum and lots of smaller ones, but they knew that with the rise of the internet and digital technology, they needed to move beyond the traditional audio tour, which had actually begun as something – gosh, Louis Tallot discovered back in the 1950s as a kind of reel to reel tape and radio broadcast systems, but had in the 1980s really an industry with the Walkman.

Then they transitioned to digital MP3 players and they knew they needed to go beyond that So I was hired and they acquired the gallery channel, as a kind of an arm and an activity of antenna audio back in 2000. My job as head of new product development was to work on everything that was not a traditional audio tour.

So I worked with the first virtual tours. the first downloadable tours podcast, cell phone tours, and audio visual tours. We launched the first multimedia tour on a handheld device, pre iPhone. This would have been 2003 at Tate Modern. and we actually got a BAFTA for that. Which I think partly was because we were put in the same category as Sony and all of the video game companies and I think the judges in that category just couldn’t bring themselves to give an award to the kind of shoot them up. video games were our competitors. So they felt like they were perhaps serving culture better by awarding it to what was really a fairly modest very early audio visual tour. I will also admit we had fantastic collaborators, Jane Burton, who was then the curator of Tate Modern and her husband, who’s one of the principles of Double Negative, who do incredible visual effects and that kind of thing and films. So we were able to tap incredible talent to build that. So that’s what I did with Antenna for a while, until it sold to Discovery Channel, which, have to say, I thought at the time was brilliant because Discovery knew video and then had known audio. And I thought that was the next step for what we were doing with digital was to really get to grips with the visual side of things. Unfortunately it turned out to be in many ways, the beginning of the end of the company, because a big corporations like that and particularly in Discovery’s history, they wanted to list on the stock market. And so there’s a certain profit margin below, which there’s just no point they’re even getting out of bed. Antenna had always been a very slim margin company because we were working with museums and it was as much mission-driven as anything. It wasn’t about getting rich. And so the company just really didn’t thrive under Discovery.

I left, after the company was acquired and went to the Smithsonian and was able to work with the brilliant Mike Edson at the American Art Museum, in terms of new media strategy and initiatives there before a couple of years later moving, actually kind of following Mike in some ways into the office of the CIO and working with other colleagues there on mobile strategy and initiatives.

And that was really a position that was created in response to seeing the rise of mobile as a very important technology for the Smithsonian to be on top of. I don’t know that the institution really understood how to integrate mobile or indeed digital strategy into everything that it did being such a large and sprawling organization that was a complex proposition.

But anyway, it was a fascinating startup moment for me. And I guess at this point it should have started dawning on me that what I really like is the startup. I like being in at the beginning of things precisely because structures and systems are not terribly well defined. And you get to write the rules to a large extent.

 That said, about six years into my time with the Smithsonian, I had another startup opportunity, to move to the Baltimore Museum of Art and help them really professionalize what they did with digital and start their first digital division. I ended up being also in charge of marketing communications and visitor services.

By the time I left a couple of years later, that was a really wonderful opportunity to build digital kind of from the ground up. But what I still didn’t know was how to really build a museum from the ground up. I had gone from working as a consultant to museums, to working in the biggest museum in the world, the Smithsonian in a very specialized role or set of roles.

And I really wanted to understand how the whole museum got put together. And it was very clear to me that it was no longer really effective to talk about mobile or even digital as a standalone separate thing. It was so deeply interwoven by this point, we’re talking 2014, 20 3, digital was integral to absolutely everything that a museum did.

So I wanted to understand the other, the other facets of that and I also was, I felt like there were things that needed to be done in the cultural sector, quite urgently that. Established museums, even a relatively small and nimble museum, like the BMA – we’re just not going to be able to move fast enough to do so. I left the BMA and started an initiative that was in large part inspired by my work with MuseWeb the conference, and a mobile company that we had gotten to know where we’re working through, through those who were willing to sponsor an initiative to collect community stories. And I recommended Baltimore as a wonderful city for that.

It’s one of the oldest cities in America. So it has a lot of stories and has always been an international city because it’s a port city. So it’s always had a large and international audience And therefore very diverse communities. And in fact today is a majority African-American city.

So I just felt like it was a wonderful place to start with saying, okay, what are the parts of the story in the sense of the local and national cultural heritage that haven’t been adequately preserved or shared or amplified? I was able to lead with the help of a lot of people, including the team of the Smithsonian’s Museum on Main Street, an initiative to start this kind of local storytelling program that led me to encounter The Peale and its Board.

As an American art historian, of course I had heard of the Peale family, but like so many people, I associated them with Philadelphia. I didn’t realize that they had actually built a museum in Baltimore as well. And that building was in fact, the first purpose-built museum in the country. So represents a really interesting moment in museum and national history of where Rembrandt Peale and his collaborators had to think. What does a museum look like as a piece of technology, if you will, a physical space with certain affordances, what does it need to enable? What does it feel like? What kinds of experiences does it make easier or not? So I. went to see a wonderful exhibition that had been curated there, by the contemporary, which was a kind of a nomadic contemporary art gallery in Baltimore at the time and fell in love with the building, which is something that building just does to people. It’s magical.

I think one reason is it’s not, It was not built on the model of the Acropolis. It was built on the model of a federal style townhouse. So it has these very human, if not homely proportions. And so it doesn’t intimidate, quite as easily as those neoclassical facades with big classical pillars and lots of steps up to the front door kind of thing.

So I was persuaded by some really smart people including Jackson Gilman for Laney, who’s the city of Baltimore’s historic preservationist, that the stories and the voices that I had been trying to help amplify preserve to some extent would really benefit from having a home in a building of this historical importance that kind of showcase is precisely what so many of them had never been afforded and other more traditional institutions.

And therefore we needed to save this building. At this point, it had been standing empty for 20 years. The roof had started leaking. There was a lot of water damage. Its last run as a museum had gone from 1930 to 1997. It had never, amazingly to me, had an elevator or other accessible features put into it.

So I undertook to be the founding Executive Director for the Peale, which no longer had a collection, a physical collection other than the building itself. And we had to find a purpose for it because you know, buildings are all nice, but what’s it going to do for the community? And so it’s purpose became to be really a home for Baltimore stories, a place where the cities, communities and voices can be preserved and heard and amplified and where they could also be supported with access to the resources, be they financial or technology or expertise to help ensure that those stories get told and get heard as well as at home.

So that is, kind of how I ended up at the Peale. This was now 2017 And I was the only staffer for a while. But we started attracting folks. And I think this goes back to something I first heard when I was at the Smithsonian from Chris Anderson, the editor of Wired magazine. He came to speak at the Smithsonian in an event called Smithsonian 2.0 about re-imagining the Smithsonian. I think this was around 2009 and he told the story of Joy’s law, which was named after the founder of Sun Microsystems, I believe, which is basically something like this: the best person to do any particular job doesn’t work for you. And moreover you can’t find that person, but if you send out the right signals, you can attract them to you.

We had $40,000 for operations when I started at Peale and that was to pay me and everything else that needed to be done. So I certainly didn’t have the money to go out recruiting great talent with great money.

But I realized that what we could do was be a place where people could do things that perhaps they couldn’t do and more established and better funded institutions quite as easily. So we started attracting people who needed a place to realize a dream. and so our team kind of grew and by 2020, with the pandemic on, I needed, frankly, to have more time to teach my kids, so we decided to homeschool in the midst of the pandemic. And I also felt like it was a moment where we could, we had a big enough team that we could start looking at distributed leadership models or a decentralized power in a way I’d always felt like the traditional museum directorship model is fairly feudal in its structure. You know, with this all powerful director at the top. and everybody else kind of jumping when they say jump and asking how high, that was not how I wanted the Peale to grow up. So, I had the opportunity to start collaborating with Christa Green, who took on the role of our Chief Administrative Officer and is my co-director of The Peale and that’s when my title shifted to Chief Strategy Officer. We also worked very closely with Geoffrey Kent, who’s our Chief Curator. And initially David London, who was our Chief Experience Officer and now has another wonderful job with the greater Baltimore Cultural Alliance as their director of innovation.

So, in a sense, the leadership team has shifted to now include a Chief Operations Officer, Robin Marquis, who’s also been with The Peale almost since the beginning, as our Accessibility Manager, and, now as also leading all of our institutional development. So with a really strong focus on being accessible, being inclusive.

And Robin is helping lead us through this process of really rewiring power at the Peale so that we are more of a worker owned organization, which is a little bit of an odd thing to say in a nonprofit, but rather than again, having top down hierarchical, relationship, among the staff and the team and the leadership. Another really important ingredient in all of this is the Peale’s Board who were brought together by a passion wanting to save this important building and do something meaningful with it, for the community, rather than through any kind of. Personal ambitions to network or be seen as having a certain kind of status or role in Baltimore society, so to speak.

And I’ll have to say they have all made this possible by being incredibly supportive of a really quite radical vision. and they had already, before I got into the appeal, decided not to call it a museum to call it the Peale’s Center for Baltimore History and Architecture. Because there was this sense that museums would hold us back in some older and less appropriate models.

I think today we’ve kind of come full circle where we are embracing the term museum with the understanding that we’re reinventing it, that we have an opportunity because this is both a very old institution and a brand new one to draw the best learnings and best practices from the past to build something radically new and very relevant for the present.

And as I’ve learned in my 20 some years in museums, if the board doesn’t get that and doesn’t support that it doesn’t matter who your director is, who your leaders are, or who your team are. They’re not going to be able to make It happen. So it’s really been all of those elements that have come together to make it possible for us to do something that I think is very new and very exciting. 

Angie: It is such a magical story. And speaking of being at the beginning of things and people having their own love story of The Peale, I remember the last time I was, in Baltimore, which I think, was about 2017 when you just picked up the keys to the museum and it had been closed for a while and it was it had that smell and that feel about it.

But there was, I think, an immersive improv theater upstairs who were in full dress rehearsal mode. And you took me down into the basement of the museum and we were going through things that people probably hadn’t touched for decades and finding all sorts of joys down there. And it has been a memory that’s stuck with me for a very long time.

It was quite the treat to be, to be, able to save the museum in those beautiful early days before everything got started. 

Nancy: You bring back fond memories. We call that the basement of Harry Potter because it seemed that, I mean, again, we had no money, right. So we had to kind of beg, borrow and steal. We pieced together everything that we did. And it seemed like anytime we needed something, we just went down in the basement and we would find it.

But that was because being a city, it was still a city owned building. Since it wasn’t being used, it was where all the other city agencies would dump stuff that they didn’t have storage space for. So yes, it was a magical place, and it still is. The stuff is all gone because we’re almost at the end of our renovations, but we are actually, I think when you came to submersive productions, the local immersive theater company was creating a wonderful show in the building about real museums.

And the practice of collecting is HT Darling’s incredible museum, where they used a fictional story to do. Wonderful critique of museums and collecting, but one which you didn’t just have to be a museum person to care about. It was a great story for everybody. And they are actually, in fact, you just got an email from them yesterday about they want to do something in the basement when we reopen.

And I can’t wait to hear their ideas. This is what I’ve found throughout with The Peale, when somebody is attracted to the Peale because it’s the place to do the thing that they most want to do. They’re always right. And they always come with ideas that I could never have thought of. No, even a committee of much more brilliant curators and museum leaders, and myself couldn’t have come up with the best ideas as Joy’s Law says always come from somewhere else. And so the most important thing is structuring yourself to be open in a way that those ideas find you and then supporting them to make them happen 

Angie: Nancy, I remember you said to me once that the Peale doesn’t find people, people find the Peale and you’ve got this very contemporary leadership structure there.

What’s the philosophy behind all of that and this almost inverted curatorial process being very community driven? 

Nancy: Well, if you think of a museum as not just a treasure house, a place where you put the valuable things of culture that somebody said are valuable and therefore should be preserved. If not more so, a production house, a place where culture gets created and enabled, then you really need to be led, not from administrators and subject matter experts in a top down way, but you need to be led by the creators themselves.

And if you value creating an inclusive cultural record of a place, then you need to value all voices as creators. And so that’s where you really do end up needing as I’ve called it, this inverted curatorial process, which starts with a community or a creator from the community saying these are the stories that are important to us in this moment that we want to tell that we want to be heard, that we want to preserve and transmit to future generations.

Then you go, okay, well, as an institution, as the museum What do we need to do to enable that? And in some cases, the creators know exactly what they want to do. Like some of the immersive theater companies or artists or curators we’ve worked with. And we just need to give them the space and perhaps a little bit of support along the way, and in various forms of resources to make it happen. In other cases, you’ve got somebody who has an amazing story that needs to be told. But they’re not in a position… this is not their usual creative practice, and they need much more support with how to go about recording that and how to go about publishing that story, how to go about presenting that in a public context.

And then if you cast your museum, your institution in that role of enabler, then all the other normal stuff that a museum does in terms of marketing or educational programs and outreach follows, but still driven by that community instigator. Again, rather than I know one of the things that I’ve heard all the time throughout my career in museums is, oh, if you just brought, you know, such and such department in sooner, be it marketing or education or it, or whatever, this would have all been a much more joined up process.

When things are driven from the community, you actually avoid a lot of that siloing of activity and information. And most importantly, you have your audience and your relevance baked in because the creator is already coming from a community. And this was one of the early concepts that we led with in the stories project that I started when I left the BMA is that the content creators in a community, the storytellers, if you will, are always already known to that community and respected by them.

So if you can find them and enable them, everything else follows as opposed to treating it as more of a voyage of discovery, à la Columbus, or a mining, digging for and finding diamonds in the rough and then trying to polish them, which is a much more colonizing kind of structure and process.

So we obviously don’t want to go there. We want to, to invert that curatorial process, we want to be community driven. And then that means also at our own staff level, those hierarchies need to be dismantled. And so as soon as we had a kind of a critical mass of staff and I’m very proud of the fact that, and very grateful, I should say that during the pandemic, instead of laying people off, we were able to hire more people.

The Board really supported me in converting funds, wherever we could so that we can make sure that people were safe, their incomes were safe. And then once we had a critical mass of people, it started making sense to talk about, now, changing the leadership structure, because it wasn’t just, me and a couple of other people who could all fit in a car and have a nice conversation.

We had to really think about communicating and collaborating on a much more, wider scale. So yeah, that’s something that we’re very much in the middle of, or I should say at the beginning of it in the middle of a strategic planning process and a business redefinition process that will hopefully speak to this need to rewire power, not just at the Peale, but I think throughout the cultural sector.

Angie: And when it comes to that motive, innovation and creativity and empowerment, what lessons have you taken from the history of startups in the sector or from the history of new museums themselves? 

Nancy: You know, I don’t know enough about that yet, Angie and I really, really need to know more – I’m taking the idea that the best way to learn something is to teach it. I have embarked this year on a project to create a course, which will help me write a book, precisely about the history of startups and museums, both, in the U.S. and and around the world. Obviously the Peale is itself a great example. And there are many others. So both historic and contemporary. I really want to do more research into that and learn from those other examples. And I would love to hear from anybody who has great stories along those lines, that might help inform this process and, and to help me help amplify those stories too, in the great Peale tradition. 

Angie: Nancy, there’s a couple of things happening in the cultural sector at the moment. There’s of course the great resignation and the shifting awareness of our roles in society issues like the living wage and career privilege. Then we’ve got this next generation of students coming forth and the way that we interact with the general public is changing around the issues around education, bridging the digital divide and such. How do you think about the museum’s role in those sorts of changes and instigating that next generation force, what is the work ahead for you and the team? 

Nancy: Bridging the digital divide is a really critical issue for The Peale that came to the fore with the pandemic. And we were under stay at home orders and yet our job was to preserve and share and amplify the voices of people who might not normally get recorded and become part of the cultural record. How are we going to reach people who may not have internet access at home who may really be separated from the free tools and services that we make available to culture, keepers and storytellers because of that digital divide and we tried a number of things and I don’t know that any one of the worked hugely. I think together we made a first step towards bridging the digital divide, but there’s so much farther to go. We have a storyteller ambassador, Daisy Brown who would go on walks with her dog and bring her camera and a microphone and see people sitting on their stoops.

Baltimore is famously a city of stoops and a lot of culture happens out on people’s front steps. And she would ask them how they were doing and start recording their stories of what it was like to live in Baltimore and the early pandemic under the stay at home order, et cetera. We partnered with libraries without borders who distributed these backpacks that have internet access to people who didn’t have it in the form of a kind of internet hotspot, 4g drive, and a laptop computer.

And, those devices came loaded with certain software and tools that could be helpful for everything from finding COVID information to recording your own story. So The Peale’s tools were part of that toolkit that was given out, There’s so much more that needs to be done. I was very happy to see our state and our city, appoint people and provide budgets for broadband and digital accessibility. but even there was still so much at the beginning. one thing that was particularly inspiring that I heard this time was, in a panel discussion that we had about bridging the digital divide and the artist Latrice Gaskins, who was born in Baltimore and is now based in Boston was part of that panel discussion.

I asked her, what would it take to really decolonize the tools and the platforms that we’ve come to be so dependent on, we’d been talking about things like ambivalence around platforms, like Facebook and indeed all of these large corporate owned platforms that we use and both love and hate. And she said, and I’m paraphrasing here, she said it much better than I can, ‘we’ll never really decolonize those platforms and those technologies until they are built by the people who have been excluded from those systems of power’. So essentially it’s a riff off of Audre Lorde’s ‘the master’s tools will never dismantle the master’s house’. We need to make sure that the tools are in the hands of the people who have been colonized historically, to enable them to generate platforms that are inherently decolonized. At least that’s the hope. And I found that very inspiring, but of course, translating that into direct action is a much more complex proposition than I confess, I don’t have as much of a plan for, as I would like to. So I think that’s going to continue to be a big challenge at the Peale and beyond. But I, you know, I have great faith in brilliant young minds coming up to help us sort this out. And one of the things that we are at the appeal in addition to being a community museum, and a home for Baltimore stories, we’re also a teaching museum. And so we were able during the pandemic to also start up an apprenticeship program working with young people who really are coming from some of the most disinvested communities in Baltimore. They are folks who squeegee clean windshields as part of their hustle for surviving, and have often experienced homelessness for a large part of their lives.

And just not really had much support from anybody. And our Chief Curator, Geoffrey Kent he himself had come from a pretty challenged background and life story, and he wanted to share what he had learned and what had helped him get to a better place in terms of, personal and financial stability and security with young people who came from similar backgrounds couple of them helped us pilot this concept in the summer of 2020 installing an exhibition that we hosted, by the artist Kim Rice. Importantly, I think Kim is a white woman and her work is all about exploring her white privilege And the systems that have enabled her privilege not just today, but generations back. She discovered a while ago that her ancestors had enslaved hundreds of people. And so she was able to trace the effects of that privilege and exploitation of labor up to where she is today. We had two apprentices that summer, both young black men. Working on installing this exhibition under Jeffrey Kent’s leadership. And that really, I think inspired a lot of people. We were able to get support to expand the program this past year in the fall of 2021 to four apprentices whom we’re currently working with and add in a component that was really the brainchild of Shantay Daniels who’s the executive director of the Baltimore national heritage area here. I met her early on in my time at the Peale. And she said, you know, Nancy, when you finished renovating the Peale, it’d be really neat if you could think about taking what you’ve learned And and helping save so many of the other historic buildings that Baltimore is just rich in that need new purposes and they need to be saved physically as well. And perhaps use that as an opportunity to expand the historic preservation trade. There are very few people entering the historic preservation trades. and it has always been kind of a field dominated by white men and as they’re dying off, so to speak, literally and otherwise it’s an opportunity for other people to come in and learn these skills.

They’re very creative jobs, very well paid, and they don’t necessarily require a college degree or, or any of the kind of intergenerational wealth that often you have to have in order to get a higher degree. And so it’d be a great place for people from disinvested communities to find really meaningful and important and well paid work.

And I loved that idea, but I really thought, I need to wait and we’ll finish the renovation. And then we’ll be able to tackle a project of that scale. But Geoffrey Kent, thank God, is not that patient. And he really pushed us for it. And he absolutely was right. We did. And this year, the apprentices are learning both historic preservation skills with David, who’s a historic preservationist with 40 years experience. We’d met him through a project that we’d been able to be part of from the national trust they did. It’s called the hope crew hands-on preservation experience. And it was aimed precisely at getting people of color to have experience of the historic preservation trades and consider that as a career path.

So for two summers, we got to work with two different groups that David was teaching on that program, and he agreed to come and teach our apprentices as well this past year, and is still working with them down in the Peale’s basement teaching them things that they’re then doing even on the field building. So they’re part of renovating our space and hopefully. Learning skills that they could use both to become a historic preservationist or like Geoffrey Kent know how to install exhibitions and curate them and know something more about the art business and the entrepreneurial activities there. But also these are the ideas that these are transferable skills that can be valuable in all sorts of different career paths that they might take.

I think that’s a really important part of who the Peale is today. That it’s part of our mission to re-imagine what museums can be. And again, it’s not just about what you do, but about who you are and the apprenticeship program, being a teaching museum, being staffed by emerging museum professionals from all sorts of different backgrounds and walks of life is an opportunity for us to really help diversify the entire cultural workforce and make sure that cultural institutions are, are not just, you know, educated, privileged white people like me talking to each other.

Angie: I think that’s the perfect bow to put on this. As you said, it’s not just about what you do, it’s who you are. And I think that when it comes to your own story and then the story that’s coming out about The Peale, that’s what it’s all about. It’s marvellous to see how you’ve weaved those two things together. 

Nancy: Oh, well, thank you. 

Angie: So Nancy, these issues around rewiring power have struck every institution in the sector, acutely. The Peale feels so uniquely placed to have the freedoms to think and act differently. You’ve got the reopening ahead of you the summer that we’ll need to take in with you and see how that unfolds and this post pandemic future will be like? 

Nancy: Yeah, well, I’d love for you to visit us virtually and in person. I guess you may know that we were able during the pandemic to work with the folks at Linden Lab and our friends at Virtual Ability to completely reconstruct the Peale in it’s second life. And it’s a beautiful, amazing virtual building where we’re able to host exhibitions 24/7. So I invite you and anybody listening to come visit there anytime they like. Obviously I’d be thrilled also to welcome you to the Peale museum building, which is a very, very special place in downtown Baltimore. We’ll reopen with our first programs in May. And then we’re really using the idea of a kind of soft reopening to, you know, run through everything, make sure we’ve got the signage right, all our systems and every hour support for visitors and our partners are all working well. And then we’ll do a grand reopening later in the year. So stay tuned for that date, but I’d love for you to participate in any way you can. 

Angie: I can’t wait to get back.