The Data Catalyst Network: Building Capability in the NoT-for-profit Sector

CONVERSATION WITH Barry sandison, DR Kristen moeller-saxone AND DR TOM VERHELST - 32 minutes 21 seconds

Adoption of AI has doubled since 2022, with almost one in four not-for-profit organisations making use of generative AI tools such as ChatGPT.

Findings from Infoxchange’s latest 2023 Digital Technology in the Not-for-Profit Sector Report reveal the usage of generative AI tools has doubled since their last report in 2022, with almost one in four organisations making use of tools such as ChatGPT.  The report also sheds light on the pressing need for enhanced data capabilities within the sector to disrupt the persistent cycles of disadvantage. With over 1,000 organisations participating in the survey this year, we explore challenges and transformative potential in the sector including the increased use of generative AI tools. Tune in for a thought provoking discussion of how data-driven strategies can reshape the sector and how initiatives such as the Data Catalyst Network, a collaboration between Infoxchange and the Paul Ramsay Foundation, unite stakeholders and leverage data for positive change in the non-profit landscape. 

Rhetta Chappell (host): Hi and welcome to Show Me the Data, a podcast where we discuss the many ways in which our lives and the decisions we make are impacted and depend on data. I’m Rhetta your host for today, and I’m a Data Scientist & Partnerships Lead at Griffith University.

Hello and welcome to season three of Show Me the Data. It’s a delight to be back in studio recording with my co-host, Dr. Tom Verhelst. We wouldn’t be here, of course, if it wasn’t for you, our listeners. So thank you so much for your continued support. Tom is the director of the Relational Insights Data Lab and the Griffith Data Trust, which is also where I happen to work. Today, we have two leaders joining us, both of whom are hugely influential and passionate about using data to inform and improve the human lived experience and deliver sustainable outcomes.

First, we have Dr. Barry Sandison. Barry leads a career dedicated to the better use of data to respond to key social issues and is currently a Paul Ramsay Fellow at the Australian National University. Second, we have the pleasure of introducing you to Dr. Kristen Moeller-Saxone. Kristen is a social innovator specialising in data science and strategy. She has worked across welfare, academic and government sectors using co-design methods to solve problems that require collaborative approaches.

Talking to our guests about their careers and experiences would make for a fascinating conversation all on its own. However, today we’re going to talk about something a little bit different, but equally as interesting, the Data Catalyst Network. And we’re going to focus on their new report called Digital Technology in the not for profit sector. I know Tom and I are super curious to hear about some of the report’s key findings, but more so to learn what Barry and Kristen think we can practically do to improve things. I will also just mention that Barry was recording remotely, so at times the sound quality can be a little bit iffy, but I’m sure you’ll agree his wisdom and insights into the not-for-profit sector and to the health and wellbeing space make the few moments well worth it. Thank you so much for joining us. Now let’s get started.

Hello and welcome to season three of Show Me the Data. It’s a delight to be back in studio recording with my co-host, Dr. Tom Verhelst. We wouldn’t be here, of course, if it wasn’t for you, our listeners. So thank you so much for your continued support. Tom is the director of the Relational Insights Data Lab and the Griffith Data Trust. And we have two leaders joining us today, both of whom are hugely influential and passionate about using data to inform and improve the human lived experience and deliver sustainable outcomes. First, we have Dr. Barry Sandison. Barry leads a career dedicated to the better use of data to respond to key social issues, and he is currently a Paul Ramsay Fellow at the Australian National University. Second, I have the pleasure of introducing you to Dr. Kristen Moeller-Saxone. Kristen is a social innovator specializing in data science and strategy. She has worked across welfare, academic and government sectors using co-design methodologies to solve problems that require collaborative approaches. Talking to our guests about their careers and experiences would make for a fascinating conversation all on its own. However, today we’re going to talk about something a little bit different, but equally as interesting, the Data Catalyst Network and we’re going to focus on there Hot off the press, soon to be released report called Digital Technology in the not for Profit Sector. I know Tom and I are super curious to hear about some of the report’s key insights, but more so to learn about what Barry and Kristen think we can do to improve things. So without further ado, let’s get started.

Show Me the Data acknowledges the Jagera peoples who are the traditional custodians of the land on which we are recording today. And we pay respect to the elder’s past, present and emerging.

Hi and welcome Barry and Kristen, thank you both so much for being here today and taking the time to speak with us. This is the first episode of season three for Show Me the Data. So we’re super excited that you’re here with us. I thought I’d start with a little bit of scene setting and ask you, Barry, how did the Data Catalyst Network come into fruition? How did it all start?

Dr Barry Sandison: Thanks very much for having me here today. The network came out of the Ramsay Fellowship work that I was fortunate enough to be involved with and engaging with a not for profit sector to try and build our data capability and how the capability of the sector could be enhanced. Through that, I was able to set up a group of people who were really interested in being engaged around it. And we got going over a period of four or five months. And then in discussions with the Infoxchange, we talked with Ramsay about the long term sustainability of a network and the idea of a more formal proof of concept. So to give it a bit of a sustainable permanency feel to it, and that’s when James and Kristen, the team got involved and I was able to step aside a little bit and watch from the sidelines as they’ve let it really push ahead.

Dr Tom Verhelst: Could you tell us a bit more about what the Data Catalyst Network is supposed to enable within the sector? Because the service sector in particular has, you know, these massive giants and then has very small organisations where the data maturity and the digital maturity sort of from nascent to very professional. Could you just elaborate a bit on what the interest would be of the sector in the Data Catalyst network? And what is it trying to facilitate or what is it trying to make happen?

Barry: You’re so right. The number of organisations and the variation in capability is immense, and the starting point was to try and engage with some organisations that had a permanent person involved in data or research or building the evidence base, because then we had a starting conversation where it was part of their job rather than how do I fit it in with the view that if we got that going, the capability and the interaction and the sharing, that would go on in a very collaborative sector, then I mean, right down to smaller organisations that could perhaps get the benefit but didn’t have the reasonable space. That was the sort of starting premise. And maybe, Kristen, you’re the one making it happen now.

Dr Kristen Moeller-SaxoneYeah. Thanks, Barry. And I think it’s a great point that you make that what we wanted to do is work with organisations who were already on that journey of data maturity. And we’ve already seen, I think, that, for example, Mission Australia are a real flagship in this area where they’ve devoted a lot of resources to setting up the organisation around having data capability and have shown that when you do that, you can be running things like predictive analysis that that then can generate insights around, for example, the sort of dose of intervention that’s needed to generate in their case its, its homelessness outcomes. So I think that what’s been great about working with organisations who have some capability is that we could show what’s possible. And I think that’s a real key for the sector to be able to see how it’s worth investing in data capability to say these are the sorts of insights we can generate which will lead to the changes in the sector that we need.

Rhetta: I know that the Data Catalyst Network has been involved with this report that’s about to come out. The digital technology and the not for profit sector. And I was wondering, you’re both leaders in the government, academic and not for profit sectors. How would you describe the current levels of data, maturity and digital capability? You spoke of sort of like an exemplar. The Mission Australia. Could you kind of talk to what it’s like? What what are more, more organisations kind of going through? And specifically, how does this level of data capacity within the sector affect their ability to kind of drive the meaningful, impactful change that they’re all set up there to do?

Kristen: Infoxchange We do a yearly survey of technology capability in the sector and our results are about to be released and really show that the sector needs support to develop its capability. We know that only % of organisations can easily get the information that they need to inform their planning improvement and reporting. You know, so it’s only a third of organisations have got that.

I think just a couple of other, you know, important sort of indicators are that one in three organisations agree that their data is easy to understand and use, and it’s that ease of use that’s really critical If you’ve got lots of barriers to being able to access your own data, the data that you’re generating, then it’s not going to just flow into decision making in the way we need it to.

And even fewer. It’s only one in five agree that their systems enable them to understand the impact of their services and outcomes. So you could see here that there’s enormous, enormous room for us to support the sector to improve their capability. Barry, I think you’ve got some thoughts on this too.

Barry: To take it up at a high level. One of the critical things that tends to get forgotten is the huge dollar value of the services provided by the sector, and not a lot of it on behalf of government and the level of accessibility of government data. It useful isn’t great. So I think we need to look at the totality of the capable body of the sector.

But it’s also how much are they allowed to be capable of access to? Sometimes the very data that they give to government agencies under contract and whether they can get it back again in usable format. And then there is the general availability of data that would allow them from governance to me to better understand what they’re doing. And it would in turn support government agendas at state and federal level, such as a wellbeing framework and the measurement of wellbeing. Who better than the sector that is out there doing it to help with that measurement?

Kristen: Just to give you that dollar figure, it was in , what government provided $ billion of funding to the sector for delivery of services and community strengthening. So it is a big sector. There’s a lot at stake here. If people had the right access to data.

Tom: At real in the GDP, we’re actually quite excited about the Data Availability and Transparency Act because ideally it sort of streamlines how we can get access to different set of data that are sort of stored in silos and particularly in the service industry. You know, when you talked about predictive analytics, for example, of homelessness, like there’s so many factors that play into predicting, you know, the increase or decrease of specific service needs.

And it’s it’s really I mean, I can imagine it’s really difficult for the for profit sector to be able to get a grasp of where all that information lives like So some of that is not even within government, but might be commercial datasets like banking, data, banking debt or financial data. Could you speak to the current state of the data sharing and data linkage between non-for-profit sector in Australia and perhaps provide a few examples of case studies highlighting the power and potential of cross-sectoral data sharing? So between government and the non-for-profit sector or between non-for-profit sector and business.

Barry: I’m a half full kind of person, so say you use the word potential. Absolutely. There is huge potential. If it was a question of how does it stand right now, maybe the cup isn’t quite as full. The detective example very much about the Commonwealth sharing data between itself and then the use of universities, Australian universities to actually help with the sharing of data.

And then there’s the review of the Debt Act to the way next. So was really building a foundation. But I think separate to that, it’s a huge amount of collaboration and sharing going on with data all protected and done under the correct, you know, the Privacy Act with confidentiality and so forth. So just to make sure people are aware, it is done incredibly carefully.

You’ve got organisations like the Australian Institute of Health and Welfare and the Australian Bureau of Statistics, among quite a few others, now very skilled at this. But what we’ve got to do is better capability when this sector has the capability to engage with the data professionals to identify what’s needed, how it could be done, how it is going to have an impact and how it fits into increasing the productivity of what they do and impacting on the vulnerable Australians that they’re often supporting.

And I think that’s the loop in a conversation that really is needed around how do we together build the capability jointly and have that data sharing and the accessibility to data done in an appropriate way really does have an impact on research service providers and policy makers. So really we’re really well advanced. A final comment. I would say under COVID.

We probably took ten steps forward. I’d have to say we’ve probably gone X steps back, I guess how many as we’ve got a bit more conservative. Again, I’d be looking to your words back to the opportunity of what can be done, the greater good.

Rhetta: Is there any sort of great examples of organisations that are sharing that maybe you wanted to talk to you kind of what the Data Analyst Network maybe are doing or things you’ve seen in that space?

Kristen: You know, that is the challenge with that is that it’s not for profits have to work with universities. And I understand. I think it’s important to have those constraints and those protections around data. But it does add a layer of challenge to working effectively with data. So what we’re doing, for example, in our Melbourne group, we’re looking at the issues for young people from disadvantaged backgrounds who are really school leavers and looking to see what are the employment opportunities that can be of most benefit to them.

And so what we’re doing there is something really, I think, quite innovative in that way. We have to not for profit organisations who are willing to share some of their data around their employment programs and the outcomes of those employment programs and looking to engage with the university who will help us to get access to the lead dataset.

So that’s the linked employer employee database. And look at those. And what are the sectors really where the best employment opportunities are for young people? Because so often I think, you know, the outcomes are, well, they’ve got a job. Everyone should be grateful and happy about that. But not all jobs are equal as we will know. And by being able to look at what are the jobs that that agencies are getting young people into, which are the ones where there is decent remuneration and there’s decent employment opportunities ahead of them, and then being able to compare to those population level data sets, we can you know, it’s not just about improving the sector, but it’s also about improving the work opportunities. You know, we’re often sort of throwing that emphasis back on what can the sector do better. But it could be that what we need to be doing is out there talking to employers, saying that some of these work opportunities aren’t really, you know, very good jobs. They’re not good, good. They’re not going to get young people a good future.

So that’s a great opportunity that we’re exploring at the moment and we’ll have some outcomes on for next year. But there’s a couple of other contexts that we’re working in as well in terms of place based data, and we’re working in Queensland with a whole collaboration of not for profit organisations. What’s so interesting about place based initiatives is that they fully range across data maturity.

You know, from small community groups with who are operating very much in a qualitative data context and to much larger ones, and we have government involvement in that context as well. And what we’re aiming to do there is really set up data frameworks for place based initiatives so that they know what are the hoops that they have to get through to get access to those population level insights. And that seems to be the real key, I think, for not for profits to be able to access those population level data inside.

Rhetta: I guess moving on from data sharing and data linkage potentially, and I’m not sure who would like to answer this, but a bit curious and it’s quite a hot topic. I’m sure everyone’s talking about it on every single podcast in the world at the moment, but generative AI and kind of the advancements that have made these tools more accessible and freely available and how it’s kind of like a double edged sword sometimes.

And how are organisations like the Data Catalyst Networks kind of these enablers of helping people make more sense of their data and use their data more intelligently? How are you working with the not for profit sector to kind of use these new tools, these new broad resources to, I guess, level up their digital capabilities of their data capabilities?

Kristen: That’s such a fascinating area. I think in that what we know from our tech report, for example, is that generally usage has doubled over the past year in not for profit contexts. So they’re out there, they’re having a go. I think at the same time, though, there are real challenges associated with that. And interestingly, I think fundamentally the use of any of these things, AI in particular comes back to good data quality that if we’re going to be using AI effectively, we’re going to have to do that based on having really strong data.

Of course, we can’t put our own data into an AI tools. And what we’re seeing, for example, in the network is that II note taking tools are being taken up by partners. And at the same time, there are others who are saying, well, look, you know, what I’m really concerned about is that if I allow access to some of those note taking tools, what’s happening to that data?

Where is it going? And so we’re really, you know, developing resources that partners in the sector can use to think about things like which of the AI note taking tools are storing data in Australia or elsewhere. Are you aware of those issues? Are you comfortable with those issues around where your data is going to? And so it’s real.

I think there’s a range of organisations who are out there trying things, but also others who are going. We’re really very concerned about where that data goes and who it’s being used by. So it’s absolutely a hot topic in the sector. It is where the sector is using JNI tools and is keen to know more.

Tom: Just to build on that, if you don’t mind. So there’s a few of the larger tech companies that are trying to sort of sell this within the tenancy of government, for example. So, you know, we all know the chat chip, which is sort of based on this enormous data corp, is that they’ve sucked up from everything they could, but they’re sort of trying to apply the same models on top of, let’s say, for example, servers, data that they’ve collected within a specific department.

Like do you see any value there and do you see any value there? Particularly because if you work with the not-for-profit sector where all the data is in silos, a lot of the value of these models, especially when you’re sort of providing them to an end customer, it’s like, you know, where can I get this service or, or these are my issues and where can I get help? How do you see that evolving?

Barry: One of the things that we need to cover is the whole issue of data and all its separate things, but very closely aligned things and the role of AI. And what does that mean? And the fact that at the Commonwealth level you’ve got data around within the Department of Finance and the digital side, the digital Transformation agency, both working together, there’s a really big opportunity to look at what are the kinds of policies that could be done to help other sectors.

I think one of the big issues is how does it tie in I quite way of questioning through the productivity Commission and the kind of approach they’re looking at and does the community sector, because this could be a great conversation. It goes all over the place. But back to the community sector, how would it apply to help them deliver their services in a better way and have greater impact?

And I think by making the questions a little bit more pointed allows us to hone in on the art of the possible in relation to the sector. And what they need is both Christiania there to enable and support and it’s actually getting the sector to identify more of what the potential might be. And that’s maybe a long way of getting to the who are the interpreters that understand data digital.

I know enough about the strategic intent and the functions of the service sector to be able to walk the path in between and explain what might be possible. So I think we now have people that know the tech at high level but don’t really know what what’s needed at the other end. And we’ve got people assuming that they need lots of things.

But what we need is some clever people in between to actually bridge that gap and bring them together is a term I think it’s huge possibilities and how it can be done back to the service information, whether it’s data sharing, data linkage or I need to have an understanding of how that kind of data from the services can be better used and that could be collaboratively between organisations or even just internally, but with some of their technology.

Tom: Yeah, I think there’s a lot of talk that what you said before and there’s a lot of work on the data quality because it’s like, you know, if Netflix recommends the wrong series to you, you sort of get annoyed for  minutes and then switch positions. You get pointed at the wrong service provider or you or you miss out on something that you really needed.

Like there’s a very different level of risk associated with using AI based on data, especially if that underlying data changes depending on, you know, what the government is paid for or what the flavor of the current politicians are like. There’s so much work there to be done around making sure that if we do start to use AI in these sectors, that the underlying data is of the right quality and of the right content contemporary segment that you’re not looking ten years ago because that’s just completely irrelevant.

Barry: I think it’s a proceed with caution, but there’s huge opportunity and to some extent it’s going to happen. Like all of the stuff with technology, yes, it’s a matter of when and the degree to which it is managed and done carefully.

Rhetta: And I think that kind of paves the way for a next question. When you talked about how there’s got to be so many organisations and so many different people with different skill sets involved in this, how is the data catalyst kind of working as an enabler and a supporter to help foster these collaborations between the not for profit sector and maybe with academia and government?

Are they doing this or there’s other funding bodies to not only, I guess share these data resources, but to also build those data capabilities or even understand what they should be thinking about when potentially adopting these new tools and ways of working.

Kristen: We’re working it sort of three ways. One is just to set up, I guess, like little incubators where we tried them and I was talking about that earlier. We’re in Melbourne where we’re we’re actually I think it’s quite an unusual context where we’ve been able to get not for profit organisations to share some data together to see if we can solve that problem in a context.

And we’re working through that in different ways in different states. Because you’re right, there’s there’s always lots of contextual factors that influence this as well. So for example, we’re working in South Australia with on the issues of successful transitions into school. So it’s that first thousand days for children and what’s the data we need to help them make those transitions.

And we know that in South Australia at the moment there’s just been a royal commission has handed down findings on this particular issue and a lot of those findings are very data related. So there’s a real sense that government understands how important it is to improve data in these contexts. And so the involvement in these processes is really critical as well.

So it’s great to be working in Adelaide and looking at those issues and being able to say to government, okay, these are the sorts of data that not for profits need, but this is also the data that not for profit brings to help solve those problems. So we’re we’re having those incubation contexts, as is one element of the data catalyst network.

The other one is through our webinars and newsletters, sharing information about what’s out there, because a lot of not for profit organisations are so focused on service delivery, doing an incredible job of that. But it really need to be able to access government data. And so we have these regular webinars. And so this way we’re sharing things. For example, the University of Western Australia has an atlas of child and youth wellbeing that’s been available at the state level for some time.

It’s now available at the national level and they’ll be talking at the webinar and showing people how to use these geospatial mapping tools because that in itself, you know, one of the issues is, is what sort of data capability to the not for profits have amongst others. This is not just unique to that sector to be able to interpret the data that comes out of geospatial mapping tools and they are absolutely revolutionary to be able to drill down to a local.

You know, this is like TSA to level to be able to see what are the health and wellbeing markets for children and young people across the country. Amazing data to be able to access. We’re sharing that with them and they really they’ve heard about that amongst other things, the Institute of Health and Welfare. Talk to us about the new data that were developing around domestic violence and family violence.

So being able to share have that sort of cross-sector, you know, across government and sector collaborations around what’s out there, what can you use, how can you be understanding the impact of your services compared to what’s going on at that population level? A Really, the sort of key things that we’re doing, we’re also looking to fund a number of sort of discrete projects where we actually, you know, test some data ideas in inaction.

So these are the sort of three key things that the network is doing. And I think it’s it’s it’s yeah, it’s really very helpful, I think, for all of the agencies involved to be able to have a go to be out there having a go in a context which is which is safe, too, Because I think, you know, going back to those conversations about I, I think risk is something that the sector is really well aware of and not keen to sort of rush headlong into trialing new technologies, knowing full well that the data of the people that they know about is extremely sensitive. So it’s well protected and and held.

Rhetta: I was lucky enough to see an early version of that tool and it looks really beautiful as well, the way they’ve designed the whole user interface and things like that. So I really hope that the organisations can get the most out of that. And I think that kind of leads on to our lasting closing question, which we ask all of our guests.

And it’s more of a thought experiment, and I think I’d love it if both of you could answer, because we do compile the answers from all of our guests and we kind of find it quite interesting to look at them at the end of each season. But basically, if you could give access to any data set to the not for profit sector, we’re not just talking about you as individuals, but back to the sector.

If there was one data set that you could give them that would really improve the way that they make their decisions are going to unlock super fruitful insights. And again, we’re kind of parking our kind of cost or privacy concerns that we would normally have to the side. But I’d love to hear what both of your thoughts are in terms of that one data set that would just, I don’t know, give some kind of like shed moments.

Barry: Well, I might go first and I’ll do it in two parts, I think. Right. So the first would be if you look at a data set, I think the world of income support as a longitudinal data set gives incredible insight into what has happened both in place and in cohorts, not about the individual. It’s not about a service response to an individual, but it’s an amalgam of these different income support payments that would allow you to see what is going on.

And if you link it to that data set, you can look at the what is the change as a result of various service interventions and so on. And because it goes back decades, you can then extrapolate. You don’t have to start a project now wait five, six, seven years to say, I wonder what happened to some extent you could go backwards and find out whether a variations, but at a bigger level, it’s not so much a data set, but it’s about by opportune the future and the art of the possible.

The Commonwealth has just put out its digital atlas and released it in June, July. I hope it would be. What if you had a social atlas that had people data using all of that infrastructure, that investment that’s already there and had a social atlas and it shows my age. They used to be hard copies. Social Atlas was some decades ago after a census postcodes.

And so what about if that was available so communities could see what is happening in their communities? That’s good for democracy. It’s good for service providers, policymakers. These see what’s going on. That would be to me, rather than a data set. It’s about making data available so it gets used. Data is no good if it stays hidden away, locked up in big spreadsheets and in holdings.

Rhetta: How about you, Kristen?

Kristen: I’ve been most excited. I think I met up and yeah, the opportunities that it generates for for insights for the not-for-profit sector. And I find it very hard to set aside the policy ethical and privacy concerns. But and I think it is well protected currently. But I think if we could allow more access to edit MADIP.

Rhetta: The data dataset is actually sorry for our listeners, just in case anyone doesn’t bear it.

Kristen: Do you want to explain it in detail? You probably know.

Barry: It’s the multi-agency data integration project run by the Australian Bureau of Statistics. It’s now got a new name, which I can’t remember now, but, but it’s it uses an integration in a secure data lab within the ABS of multiple datasets under very strict controls for access. So it’s a very controlled environment, which is great. It allows you to bring together different datasets to understand what is happening to various cohorts that you might want to study.

So it’s a resource research tool. It’s a fantastic and the learnings of managing it in that very controlled environment, it’s the way next. But already it’s showing that the lot of universities accessing, it’s in that many hundreds of research projects that are being done. So it really does show the the power of data when well-managed.

Kristen: Yeah, I’ve seen it used in a range of contexts. It’s not just about thinking about outcomes for individuals, but also being able to do things like map workforces within the sector, you know, things like the homelessness workforce and the like. We don’t really know enough about those workforces so that we can really plan and assist and be able to shift where the need is greatest. So I think MADIP is one that excites me the most.

Rhetta: That’s a dataset I’ve long yearned to work with. We’ve worked with Blade, which is the business MongoDB to states, and yet it’s fascinating what you can learn and when you apply for the blade data set, you have to look at the magic like all the different options you look, there’s all these things all together. This would just be really fruitful for doing some analysis. Was there anything that either of you would like to say in finishing or like our listeners to know or anything to finish off?

Barry: Look, I would just say that it is about collaboration in learning about data because there is different capability across individuals and organisations. Amid the collaboration, there is the huge opportunity to do things better and most of the services within the sector are clearly all about their clients. And therefore, if there’s a way in which we can improve the outcomes for clients by this work through the network and supported by Ramsay, it’s just such a huge opportunity.

Rhetta: Yeah, I couldn’t agree more. We worked in certain different places with trying to set up different data collaboratives within that community services space, and there is just so much potential, like you said there, and there is a lot of appetite for it. And I think that if we can kind of capitalise that on that like you guys have at the Data Catalyst Network, it’s really exciting what we can do.

Kristen: Yeah, and perhaps I also think that it’s also about us just continuing to grow data literacy in the sector and any effort we can make to assist in in getting that process going, taking the small steps, encouraging people to get access to data and get access to training. I think that anything we can do in that area will help us to really be able to make the most out of this revolution, the intelligence revolution we’re a part of now.

Rhetta:  Well, thank you both so much. I really appreciate you both taking the time to talk to us. And I think that’s it. Yeah. Thank you. Thank you. 

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