Blog Post

An interview with Hope Nestor on data-driven community services and inclusion

By: Marco Campana
August 11, 2020
TiHS-Episode-20-Hope-Nestor

Be data driven. Make your decisions based on data. We've all heard the platitudes. And data is something that the immigrant and refugee-serving sector has huge amounts of, and does very little with. In 2017, the Toronto East Quadrant Local Immigration Partnership started looking into changing that.

In this episode I interview Hope Nestor, Research Partnership Lead on their Scarborough Newcomer Needs and Trends Report project. According to the 2016 Census newcomers made up 57 per cent of Scarborough’s population. Agencies collect data on clients and communities to ensure newcomers have the support systems they need in place. The project works with these organizations to surface, pool, and aggregate their collective data to identify newcomer service trends and needs.

As you'll hear, it's a work in progress. An important work in progress that can teach all immigrant and refugee-serving agencies more about how they can better use data to improve services, build welcoming communities, and enhance inclusion in our cities.

Some themes from our conversation:

  • Building a collaborative process and project is essential for success - "what we developed is a the idea to build a data pooling platform, so to build really a database where organizations could share data together in a really supportive and neutral space. So without fear of competition without fear of privacy and security issues, where they could come together and share information in a very neutral space."
  • Legacy systems are cumbersome and agencies need support and guidance to either get the most out of them or switch to more user-friendly systems - "This project allowed us to say to people, what are you experiencing with your data? What do you know about your data? What do you know about data analytics? What do you know about management? And have them come together and share in an open way the trouble that they're experiencing, and what they're doing. Because they're doing a lot of things really right. And so many of them are collecting the right information to make really great data driven decisions at their organization. They just need first and foremost, somebody who has the time and the resource to, to do some of that analytics work."
  • Building cross-sectoral capacity will be essential, investments are needed - "I think we're going to need some top down approach where funders are focused on pulling the sector into that next phase. Because organizations can't do it on their own. They need the resources and the funding and they need funders who appreciate that they can't necessarily compete in a data driven world with these large agencies who or or as you mentioned, we have private sector agencies coming in, or come organizations coming in. So we're going to need support for those groups for sure."

Additional resources:

Machine-Generated Transcript

What follows is an AI-generated transcript using Otter.ai. The transcript may contain errors and odd sentence breaks and is not a substitute for listening to the audio.

0:00
Welcome to Episode 20 of the technology and Human Services podcast. be data driven, make your decisions based on data. We've all heard the platitudes, and data is something that the immigrant and refugee serving sector in Canada has huge amounts of and does very little with. In 2017, the Toronto East quadrant local immigration partnership started looking into changing that. In this episode, I interview hope Nestor research partnership lead on their Scarborough newcomer needs and trends report project. According to the 2016 census, newcomers made up 57% of Scarborough's population. Agencies collect data on clients and communities to ensure newcomers have the support systems they need in place. The project works with these organizations to surface pool and aggregate their collective data to identify newcomer service trends and needs. As you'll hear, it's a work in progress and important work in progress that can teach all immigrant and refugee serving agencies more about how they can better use data to improve services, build welcoming communities and enhance inclusion in our cities. I hope you

1:00
find it useful.

1:02
My name is hope Nestor and I am a research partnership lead with the Toronto East quadrant local immigration Partnership,

1:11
which for those who don't know, it's an ircc funded program that develops local partnerships and community based planning around the needs of newcomers. So we do anything from holding action groups for

1:28
people who serve employment sector and the or those who serve newcomers in the form of health services. And then we host larger events like forums and the bridges forum, which is a popular collaborative

1:43
activity that people do in February. So that's our one of our largest activities. And I have been working at the lift for almost two years. Excellent. Welcome. Thank you so much for joining me on on the podcast and lips. I find they're a fairly new

2:00
phenomenon in the sector but do really interesting convening work and almost have created like a collaborative neutral persona in the sector. And I know that in in in your area, you've been doing some interesting recent work through some ircc funding service delivery Improvement Grant around that kind of collaborative, convenient. Can you tell me a little bit about that and where you're at in the project? Yeah, absolutely. So actually, our project is called the Scarborough newcomer needs and trends report project, which is a long name.

2:33
But we have been working on this project, really, the project came into planning

2:40
and 2017. We had as part of our strategic planning at the lip, we had organizations who came to us and said, We want to do more with the data that we collect from our clients and the data that we collect when we're doing service delivery, and so as the lip and when the STI

3:00
Funding came up, they proposed a collaborative project with the University of Toronto, and with Catholic cross cultural services as the lead agency on the project, where they would bring these organizations who wanted to collaborate on data who wanted to do more with their data to make better use of their data, bring them together to collaborate on that. So what we developed is a the idea to build a data pooling platform, so to build really a database where organizations could share data together in a really supportive and neutral space. So without fear of competition without fear of privacy and security issues, where they could come together and share information on a very neutral plane. And so that's sort of where the university came in and has such a large role is they actually host and how's the data manage the data at the end

4:00
Diversity. So not even at the late, not even at our lead agency is data hosted, it's really supposed to be a very neutral space, which is why the university is such a good fit for us. And so we built this platform, this database from scratch with university. We have Co Op students who've been working with us for two years to develop this. And they're managed by faculty and also staff at the university. And we work really, really closely with them to build to build this platform. And then we work really, really closely with the organizations in our community of Scarborough, those who are serving newcomers, to figure out what kind of data they're collecting first and foremost, what do they want from that data? So what type of research do they want? What do they want to know about how to improve their services? What do they need to know about their clients to provide better services

4:59
and we talked about

5:00
them a little bit about the technology that they're using to host their own data to collect their own data to manage their own data. So that we could create this platform that would, that would encompass all of their needs, and then also be adaptable enough to collect data from each one of the organizations.

5:22
So we have been at this as I mentioned, for two years, we've collected data twice now we actually just finished our second data collection yesterday. So we're very happy. And it's a lot of work. So we're quite pleased. And we collected twice the first time we collected from eight organizations. And the second time we collected from nine organizations, and they were organization to serve newcomers in respect to mental health, employment settlement, language training. We have a micro loan organization who's participated with us

6:00
And those are just the organizations who we've actually collected data from that doesn't include the organizations who helped us to create the platform and helped us to understand the data that's being collected and managed within the sector.

6:16
So it's like a really interesting project. There's a ton I want to kind of unpack there. But I, let's start kind of at the reason for something like this, like what are some of the data challenges, opportunities for in these agencies, especially around they collect a ton of information about clients, but the sector is really well known for not being great at mining that data or using it effectively or even using it for outcomes measurement. It's mostly they've they've been conditioned to do outputs, reporting up to the funder. What's the hope with with kind of taking this kind of community data

6:51
moving forward, but also what has what have agencies have themselves learned around capacity to do data management's do data analysis and things like that.

7:00
As part of this project,

7:02
right, so just to answer sort of your earlier part of that question where this came from, as I mentioned, these organizations wanted more from their data. Because currently what we see is, as you mentioned, we see the data being primarily used for reporting to funders. That means that the data that's being collected is completely based. What's being collected is completely based on what the funder is looking for. An organization could potentially have one organization we spoke to had five different funders, and each funder had a different type of reporting tool that they were requiring that means different data to collect. So more questions to be asked of the clients. The same questions in different ways even in some cases.

7:52
And then not only just a ton of information being collected from the clients, but also all these different

8:00
technologies that are being used to move that data from the organization to the funder. So some organizations, I spoke to managers who at times of busier times of the year, were spending two weeks of the month just on reporting alone. That's an enormous amount of resource and some of that resource was going towards copy and pasting into different Excel documents. So really, the the hope from this project was that not only would we be able to take this data and take this data and make better use of it, but also streamline and identify different opportunities to streamline some of those technologies and to develop technology for funders or to promote technologies to funders, where they are streamlining that process.

9:00
where people are able to

9:03
are able to not only use their the tools that they have more effectively, which is something that organizations aren't always doing. Some of these data management tools that are being used, aren't fully understood. They were created out of necessity in a lot of instances. And so you'll see these really clunky and inefficient systems. You'll see these really many of these systems, you can see the process that organizations took to get there. You can watch as you're looking at the system and you're diving into it. You can see okay, funders in year one of the system, were asking for the following five things. in year two, they were asking for those same five things, but they wanted it in a different format. So now we have it in this way. Now, funders are looking for certain data analytics that organizations had to do so they end up necessary

10:00
It built this particular tool to do that particular analytics. So what you see are these systems that are, they're just cumbersome, that's the word cumbersome. And so we wanted to give shed light on that a little bit as well in this project. So by doing sort of this environmental scan that we started the project off with, where we were trying to come up with ideas of what the platform would look like and what the database would look like. We also created space for people to talk about these systems and space for people to talk about the challenges they were experiencing. And for us to go in and look at some of these systems and make recommendations and make suggestions to organizations on how to streamline some of their

10:47
stuff, how to streamline or improve the validity of some of their data collection practices.

10:53
What was the second part of your question? Second part was around what you're leading to actually which is the capacity within the organization. So

11:00
Know that you've taken them through this kind of a process, and they've had actually that kind of time. And I find that that's a big issue for agencies to have the time to figure out what the right system is. Where are they at around capacity to do something more to do something different? And where has the project help take the I guess, the group, even as a community forward with data?

11:22
Right. So what the other thing that we found is that the systems that they were using, really are only a system and the data that you collect is only as good as the resource and the time that you have to put into it. And by resource, I mean, not only time, but funding as well. We see that organizations are that the systems that they're using our systems, they're not like in private sector, right. In private sector, you would see giant amounts for subscriptions to systems where people could manage their clients, and do tons of data analytics work.

12:00
And it would be really user friendly. But what we're finding is these clunky systems, but then on top of that, organizations don't have the capacity to train their staff fully. That's a big problem is stuff. One, one organization, for example, we came in and we said, Oh, I'm curious why you're running your reports in this particular way. And they said, Well, that's the only way we know how, and what what, what ended up we ended up discovering was that there was one person on that staff who had transitioned out of that role, and they held some of the biggest permissions of the subscription. And so what you found was that they were just missing the permission. And we were able to come in and say, Well, we know this system, and we know that you probably were 90% sure you have access to this permission, and it saves them a ton of time and money.

13:00
month just because we were sharing information about the system, we had learned that from another organization, it wasn't some information that we came in with. It was just information sharing between organizations. So the amazing thing about the settling sector is that and something that I learned very quickly is that the people in the sector are so adaptable and flexible and open to collaboration. It's amazing. It truly is amazing. And then, but they need the tools they need to be provided with funding to train people. They need to be provided with the information in order to share that information. They need to be given the opportunity to collaborate. And that's what this project really did. It opened up an opportunity for people to discuss something that they're unsure of. So data is new to this sector. Maybe data itself isn't new, but the concept of using it to its full effect

14:00
If something that people are only saying is necessary now funders and putting the pressure on, okay, you need to, you need to be more data driven. And so now people are saying, okay, we need to play catch up.

14:18
And so this project allowed us to say to people, what are you experiencing with your data? What do you know about your data? What do you know about data analytics? What do you know about management, and have them come together and share in an open way? What they're the trouble that they're experiencing, and what they're doing, right, because they're doing a lot of things really, right. And they're collecting, you know, so many of them are collecting the right measurables to make really great data driven decisions at their organization. They just need first and foremost, somebody who has the time and the resource to, to do some of that analytics work and

15:00
They need, you know, the support of one another and the collaborative spirit that that already exists within the sector to sort of shine through as it relates to data. So a lot of agencies don't have that capacity, even through funding. I mean, and some people talk about it as a separate role even or part of somebody's job, but so much of this stuff is sort of they say on this done on the side of someone's desk. So I wonder if the the model of a lip being this collaborator, this this sort of playing the central role of helping to massage the data is something that that your project has looked at as potentially a model and moving forward? Or is it something that really you're looking at each agency needs that kind of capacity? It doesn't have to be an either or, but I'm curious.

15:45
Where do you Where do you go from here, for example, you've created a structure, but it's a pilot project. It's a short term funding kind of project and you may get more down the line but what what what does this look like as a future for the sector, you know, a community collaboration

16:00
on data or individual capacity in agencies.

16:05
So absolutely, if both, and a big pillar of our project was not only to build this platform and provide this resource, but also to build organization's own capacity within their within the build capacity within their own organizations, because we want to provide them with the tools to do we want them to have the tools and the training to do on a smaller scale, what we are hoping to provide them on a larger scale. And so I think moving forward our hope and our goal is to create a model where absolutely lips and the university would be

16:45
put in a position to provide the resources, the larger scale resources like an opportunity to collaborate. So an opportunity to have access to data from other organizations because not only do you need

17:00
data from your own organization that's really important. You need to know what's going on in your community, especially in the settlement sector. This is such a people as they're settling need a holistic

17:12
need holistic services, they need employment, housing, it all needs to fit health, it all needs to fit together to create that settlement experience. And so we need to share data amongst organizations in order to create that collaboration that that holistic or improve that a holistic service circle.

17:35
That works that works.

17:40
Yeah, so I think our goal is really to provide a model for universities and lifts to come together and say we're going to open up this conversation. We are going to provide you with the analytics resources, the technology resources, and the neutral space. That's

18:00
such an important part, this neutral space for you to share information because organizations, rightfully so in the way that our funding structure works is it's competitive.

18:12
And data, especially moving into the future is going to hold all the cards. It's going to we're seeing funding models that are or are now developing things such as report cards for organizations where these report cards are going to be developed. And they're going to be solely based on your financial and your service delivery data. And so we're not moving away from competition. We're moving into a more competitive field when it comes to data as we move forward. And so organizations the idea, especially at the beginning of sharing their data, amongst one another was really challenging for them to get their heads wrapped around because the funding model has not it hasn't opened it up in that way.

19:00
And so we really want to act as a neutral source and especially with the university to give that space to everyone. Well, that makes sense. And I mean, moving forward is a great segue to looking at kind of the future of settlement work in some of these because I think you're right in terms of the data. There's also a lot of newer actors that are moving into this space, whether they're private sector or new nonprofits who are data first. And a lot of ways they've already started from the perspective of you know, using a good CRM, like it's a Salesforce or something really powerful and much easier than these legacy models, for example, they're starting in a in a place where the technology itself has evolved to be easier to even use. And so they're going to be able to do data driven decision making much more quickly, at the same time that the funder has shifted to and in theory anyway, outcomes measurement approach a client centric approach with the core values or principles that they put in the recent call for proposals. For example, what does it What will it take

20:00
For I guess you're you're with eight or nine agencies now and you're seeing them over a few years having to make this shift forward. What do you think it looks like for the sector as a whole, just shift to being more data driven to being more outcomes focused in terms of its measurement, with the resources they have in with the capacity that they have what what kind of a significant shift? Would that look like moving forward?

20:26
And on the size of the agency that you're talking about, and what services they're providing, um, my fear, I guess, is that smaller agencies, and who have less resources both to have subscriptions to larger CRM, or more useful CRM, and also who don't have the capacity within their organization because as you mentioned, somebody's doing the data analytics off the side of their desk, because they've got 100 other things going on. So for those organizations, it's going to really require that funders put

21:00
A lot of emphasis on funding new initiatives for smaller agencies to get to bring themselves forward into this new this new era. And to move away from some of those legacy models, or to improve upon those legacy models where they're meeting a certain standard and data and or meeting a certain percentage of their, their,

21:25
their decision making is done data through data, and that they're able to

21:32
show success by use of data. I think with some of the larger agencies, they're already moving in that direction. Some of the agencies that we worked with are already using Salesforce. We see people are already using ocms, which some people who listen to this podcast may think, well ocms has a lot of work to do, but it does but at the end of the day, it is one of the more

22:00
advanced tools that we're seeing anyway, within the organizations that we're working with. So I think it's really going to the as we move forward into this next phase of data in the sector,

22:13
I think we're going to need some top down approach where funders are focused on pulling the sector into that next phase. Because organizations can't do it on their own. They need the resources and the funding and they need funders who appreciate that they can't necessarily compete in a data driven world with these large agencies who or or as you mentioned, we have private sector agencies coming in, or come organizations coming in. So we're going to need support for those groups for sure. Absolutely. So um, so I guess at the end of the day for your project, you're you're helping to kind of raise some big issues in the sector, but also provide some frameworks and some solution.

23:00
What, what is sort of the final outcome? Or what can people expect from the project that might help them move themselves forward in their agencies? When it comes to data? What can they learn from what you're what you're doing in Scarborough? Sure. Um, well, hopefully lots and lots.

23:19
Bye. But what it would be just so wonderful if what we really want to do is we want to do two main things. We want to encourage collaboration, we as the lift, that's always our focus. We want to open up the conversation about data. We want people to feel more comfortable talking about their data, using their data, sharing their data, and collaborating with one another. And then we also really want to demonstrate the value of data and demonstrate what it can do because something that came up so often we went back to organizations and said, What do you want to know from your data? What what

24:00
challenges do you see regularly that we can answer with your data? And oftentimes organizations because they aren't used to answering questions through data, or it hasn't been around as long as let's say in private sector, organizations were hesitant or

24:21
unsure necessarily. They were. They knew that they know that there's tons of value. And they know that they're, they want to make better use, but we want to show them demonstrate through our own research and demonstrate through our own findings, what data what types of data driven decisions can be made, and what and demonstrate sort of what they can do on a smaller scale at their own agency. So what's there I mean, a lot of the sector talks about anecdotal knowledge right, though I just know this about my clients as it were you able to see a shift in some of these agencies have like the Oh, there's so much that I could learn that I even didn't necessarily

25:00
They know about or check my own assumptions based on the data that you've been able to help them collect and analyze better.

25:07
So, to be very honest, I would say the answer to that is no. I'm only because right now, in the last two years, we have been in a very, it's still the project is still very young. And so we have been what we've been collecting, we're been very cautious of what we're collecting. We're collecting demographic information, service delivery information, but we are treading very lightly as our technology is young. And as we are sort of entering into privacy and confidentiality. The as we're feeling that out, we're trying to be very reserved in what we collect. And so when our first report came out, I think that there were some findings and organizations were happy to have and they're happy to see the collaboration.

26:00
between one another. But really, I think in order to demonstrate that we'll be able to demonstrate that a bit more and report to, as we collected a little more information, people might see a bit more, they might have an opportunity to see something they haven't seen before or that they're they see less of,

26:20
we'll be able to make some bigger insights, I guess. And then but I think what, what really came out of the what learning really came out of the first report was just, I think if you asked our organizations they would say, it was about the collaboration. And it was about the the one on one interaction about their own data, and about their own data practices and getting at a table with one another to talk about challenges and have open and honest conversations about their data. I think they would say that was more the value in the first report. And hopefully in the second report, we can

27:00
do more of that demonstrating for them?

27:03
What bigger value from their from their data? That's that's really the interesting point, I guess there's so much culturally in the sector around around competition and around fear of sharing information that it's baby steps to move forward. And that, that that's a huge leap that collaboration, first of all, I guess, getting that trust getting them around the table, getting them to agree that this is something that's important, and then being able to show perhaps, the value of that data as you progress. I mean, it's a long game and a lot of ways for the sector. It's it's, it's interesting, it just feels like there were the with with the pandemic, things are feel more and more compressed. So in some ways, you're ahead of the game for a lot of agencies because you've gotten that collaboration, you've gotten that trust. So hopefully the next steps might even move a little bit faster towards that kind of data mining.

27:51
Yeah, exactly. Exactly. Excellent. Well, I'm looking forward to the reports. When when do you have you been reporting out to the sector or what's your

28:00
What's your plan or vision for reporting back to the settlement sector more broadly around around the learnings from this.

28:07
So as it stands right now, as it stands with the data and our reports that come out of this project, those reports actually go only to the participating agencies. That was part of that building of trust. We built a lot of trust at the table for nine agencies is really small. You can if you were to dig deep enough, or to think hard enough about some of the findings, I think he would be able the ones at the table might be able to make a pretty good assumption about which agencies fall where, because they're so familiar with one another. And because we're all Scarborough based groups, we've worked together in the past, and so we kept it so the reports are just for the agencies. The agencies

29:00
Then after the report came out, we went to them and said, okay, we want to share knowledge with the community. It's about collaboration on a larger scale as well. And we chose some insights that we chose. I don't know, I think there might have been 12 or 15 insights from the report itself that they were comfortable sharing with the, with the other agency. So that information went out to a broader network of agencies, and then the learnings for the project as far as collaborating and encouraging others to participate. That's an ongoing process. That's a process that we do regularly through presentations of the liquids on we,

29:43
you know, conferences,

29:45
myself just going out and doing it and reach. So we're trying to teach this podcast I guess, as well. We're trying to teach about the learnings as much as possible while still maintaining the

30:00
Privacy data for the organizations who participated. So yeah, no, that makes sense around the data, I guess it's it's it seems like such an opportunity to learn about do just that what you've learned about collaboration, what you've learned about the value of data in the sector, are there any key kind of messages that you would want to give to the sector around those who are whether they're small or large thinking about how they could better harness data, either individually, but also collectively working with other agencies or lips or other partners? What, what what takeaways from from a project like this, do you think would be essential for the sector to understand and the funder? I mean, I think you've, you've said some of them, it requires investment, it requires time. It requires, you know, understanding the systems that you actually already have, and perhaps finding better ones if you can afford them. Are there other things that that sort of leap out as like really big learning for for other folks in the sector who, who might need a starting point to even where to take the first step? Sure. Um, I think

30:55
patience which you know, what?

31:00
Anytime that you take on a new initiative out of an organization, or you try and change an old initiative, which at times is more difficult, really,

31:10
you have you have difficulties, you have challenges. But with data and the capacity that exists within our sector,

31:21
we've really people need patience, people. It's something that migrating to a new idea, new ideas around data and new processes around data. It's complicated, and it takes time and it's tedious. And people are not necessarily always so open. It feels very much like a secondary thing to their jobs. They're there to serve clients, and they're there to do the social work of the of the sector. And the data collection is a nuisance in a lot of instances.

32:00
So trying to build up the understanding within the sector, the importance of data and the importance of moving forward with patients, and instilling

32:17
the at the very base level, those who are collecting the data all the way to leadership, the importance and having a very

32:29
having buy in from every level is really important. Because without buying from every level, we are not going to see change, we're going to see pushback at some level. And whether it be a leadership role or with those who are collecting the data, you need to be on the same page. Because otherwise it's a very frustrating experience. And so moving forward into this new age. I think also it's really important to emphasize the power of data and

33:00
how careful we should be the data in our sector, we found lots of challenges and validity and lots of challenges in the way data was being managed. So we want to ensure and instill the idea that we need to tread very lightly moving forward data can have a really powerful impact. If you read the right stat, it can stick with you your whole life, and our sector is no different. We need to make sure that what you know it's garbage in garbage out. We need to make sure that the validity of the data and the insights that we come up with are going to benefit our clients and are going to be in the right spirit for our clients. And that

33:48
you know, this idea of

33:52
this idea of quantifying everything can be

33:58
cannot always be the answer.

34:00
Answer. So we need to make sure that we although we are moving towards a data driven, just data more data driven system,

34:09
or process within our sector, we also have to remember

34:15
remember to tread lightly to be to make sure that the data is going to represent, as I mentioned,

34:24
represent something positive for the clients and also for people who are working in the in the sector. That's a really important key message. Yeah, thank you for bringing that up. I think that's that's really important. Is there what, what's what's next, I guess, for the project in terms of are you coming to a close or is this something that will continue?

34:44
So we have, as I mentioned, we'll have a second report coming out for the agencies that participated just now after a second data collection will continue to provide capacity building within the sector. So we do workshops. We do one on one

35:00
information with people as they're starting to come into the fold of the project will continue that until right now, we're finding until March 2021. And so the goal is to continue that capacity building and also to do another data collection. For anybody who's interested in participating, please contact me because we are definitely interested in bringing more organizations into the fold and expanding not only the data that we have, but more importantly, expanding the understanding that we have around data in our sector and understanding we have around how to collaborate around data in our sector. Is that an invitation for Scarborough based agencies or anyone in the sector?

35:44
So right now, it's actually Scarborough based. We do hope someday to be to be expanding outside of Scarborough, but for right now we're, we're focused on Scarborough. It's our it's our catchment area, but also we want to

36:00
Make sure we want to do it right. And we want to make sure that our system is ready, and that our understanding of how to collaborate is ready and Scarborough, Scarborough, I noticed a row and Scarborough is just the perfect place to do this. Because the organization's there have such a tight knit group. They trust each other so much. And I came into the lip and the people who were my colleagues who had been on the lip for a long time have cultivated such a wonderful atmosphere of collaboration and trust. So scrubber really is the perfect place for this. So we want to stay true to that until we're ready. Fantastic. Well, thank you so much for taking the time to share information about your project. I'm I'm looking forward to any of the public reporting that comes out for sure. I think there's a lot here that that that's valuable for the sector to know about. And so, hopefully we can help get the word out. I appreciate you taking this time.

37:00
To share all of that and all your insights. Well, thank you so much for having me. It was a pleasure. Thanks so much for listening. I hope you found this episode interesting and useful for you and your work. You can find more podcast episodes wherever you listen to your podcasts are also on my site at Markopolos org. I appreciate you listening in if you have any tips, suggestions, ideas or want to be interviewed or know someone who wants to be interviewed, please drop me a line through my website, or Marco at marcopolis.org. Thanks again.

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