Jacqueline Musabende: Hello, everyone! My name is Jacqueline Musabende. I'm professor at Mount Royal University, and I'm a member of Federal non-profit Data Coalition coordinating committee. So my pleasure to welcome everyone to this conversation. We're so happy to have you joining for this important conversation about the nonprofit sector data ecosystem Jacqueline Musabende: before we go deep into our conversation. We would like you to start by taking this moment to acknowledge the physical spa
ces in the lands Jacqueline Musabende: that we're joining in from I'm joining from Calgary and I will. Jacqueline Musabende: Give this land acknowledgement Jacqueline Musabende: in the spirit of respect, reciprosity, and the truth Jacqueline Musabende: we honor and acknowledge we honour and acknowledge Moh’kinsstis, and the traditional Treaty 7 territory and oral practices of the Blackfoot confederacy: Jacqueline Musabende: Siksika (sigsiga, Kainai (ghaana), Jacqueline Musabende: Piikani, as wel
l as the (stoney) Nakoda and Tsuut’ina nations. Jacqueline Musabende: We acknowledge that this territory is home to the Otipemisiwak Métis Government of the Métis Nation within Alberta District 6. Finally, we acknowledge all nations Indigenous, and the non-Indigenous who live, walk and play on this land. Jacqueline Musabende: and we honor and celebrate this territory. Jacqueline Musabende: I will now give you some details on how we're going to run this conversation Jacqueline Musabende: today w
e have a lot of ground to cover. So we're not going to have a questions and answer during this session. We just wanted to inform you that we will continue to have many conversations that we will host, and we will invite everyone to give us your ideas questions so we can use them to prepare the future conversations. Jacqueline Musabende: This meeting is being recorded, and you will receive recording within few weeks. Jacqueline Musabende: along with related resources. Jacqueline Musabende: Post t
he captioning is being used. Jacqueline Musabende: and if you have any accessibility questions, please let us know in the chat. Jacqueline Musabende: I will give you now the context of this conversation, this session, this webinar, is organized by the Federal nonprofit data coalition. This group focuses on advancing in nonprofit sector priorities in terms of data collected and shared by the Federal Government. Jacqueline Musabende: The group now includes representatives of more than 40 organisat
ions and institutions. Jacqueline Musabende: If you are interested in learning more about this Federal nonprofit data coalition or joining us, please get in touch at the publicpolicy@imaginecanada.ca. Jacqueline Musabende: today, the purpose of this webinar series is to build the sector's awareness of sector data, and it's a capacity to use it to further our missions. Jacqueline Musabende: Thank you very much. Now I will ask our panelists to introduce themselves, please. Jacqueline Musabende: We
will start with Paloma Raggo, then Matthew Russell, and then Alissa Simon. Thank you very much. Paloma Raggo: Thank you, Jacqueline. My name is Paloma Raggo. I'm an associate professor at the school of public policy and administration, and I have the privilege of being the director of the Charity Insights Canada Project, which is a project that seeks to collect weekly information about the charities and their work. So I can give you just a brief 1 min. Paloma Raggo: of who I am. So I've been te
aching and doing research at Carleton for the past decade now, so time flies by and we have the honor and privilege of hosting the only graduate program of its kind of nonprofit leadership and philanthropy in in Canada. So I can see from the attendees a couple of our alumni. So thank you for having me today. Matthew Russell: I'm Matt Russell. From Policysise for Children and Families. Our mission is to inform, and on the well being of children, youth and families at Policywise. I'm a senior rese
arch and policy associate. I was also did my postdoctoral fellowship in administrate and big data with the University of Calgary. Matthew Russell: The the project that's most relevant that I'm really representing here as part of this conversation is I'm the lead of the Alberta Not For Profit Data Strategy, who is seeking to to build the capacity of the Alberta not for profit sector and provide data to to support their needs as they're moving forward. Matthew Russell: Another role that that is re
levant to today that I won't talk about more is, I'm also the lead of a big project where we're building a roadmap to use data to prevent youth homelessness across Canada working with administrative data in frontline organizations. All that stuff. Matthew Russell: A really cool project that you might be interested if you're you're thinking about, building the capacity of the sector or the people you're working with there. Youth womelessness is an issue that crosses sectors, and it it has a lot o
f commonalities for other things that we've heard even from your surveys Paloma. Thank you. Alisa Simon: And Hi, everybody. My name is Alisa Simon. I'm the executive Vice president for E-mental health transformation, which is a long title here at Kids Help Phone and I am really joining because I wanted to talk a lot about, how does an individual charity whose main mission is serving young people? Alisa Simon: How do we need and use data in order to make sure we're doing the best work we can in o
rder to learn. How do we improve? How do we iterate? How do we innovate? And then what is the power of the kind of data that individual charities collect for us to be thinking about bigger impact across Canada and and globally, and so really wanted to share sort of the journey Alisa Simon: that we've been on at kids help phone of not seeing data as just something that yes, we collect because it's part of our work, but actually seeing it as critical Alisa Simon: to our service provision critical
to improvements, and also to thought leadership and positioning and ensuring that Alisa Simon: what we know because young people come to us and trust us is also known by others. And so that's kind of the the position that I'm going to be bringing. I've been at Kid's Help Phone for about 12 years. And so I've really been able to see our journey in understanding and using data grow so, looking forward to the conversation. Jacqueline Musabende: Thank you very much for the introduction. I just liste
ning to what you've done, what you're working on. I think we could never have dreamed of better panelists today. So we just go in and start asking you questions. My first question is for Matt. Jacqueline Musabende: Can you briefly describe what we mean when we say the sector's data ecosystem when we say nonprofit sector's data ecosystem. Matthew Russell: Could you throw up my slide? Thank you, Emily. Matthew Russell: Yeah. So Matthew Russell: when we talk about what is the sectors data ecosystem
? And and we're talking about potentially different types of things. Matthew Russell: So for example. Could we go into slideshow mode? Matthew Russell: Yeah. Thank you. We could be talking about different types of data and all those things. So often, we're talking about the needs of the sector and things going forward. We're talking about sector-level data, so things that that go across different types of not-for-profits, different types of sectors, sub-sectors. Matthew Russell: and it talks abo
ut the the impact the different things that are happening in in the sector. Matthew Russell: Of course. When we talked about the sector's data, that's that's always the vision it came to when I came into this role as a lead is, it's about the sector. What are the big needs? All that stuff? The reality is organizations may see these things a little bit differently in terms of the sector's data ecosystem. So it may not be that system level picture. It may actually be things that are more related t
o Matthew Russell: the needs of those individual organizations, and that's how they see it. So each organization has a different sub-sector. You may be a homeless serving agency. You may be a person in a food bank. You might be a group that's a sports and recreation group. Those are all different things. So often these types of data, this, even the system level can get to those breakdowns in different sorts of ways. Matthew Russell: But the sector might prefer data that's more closely connected
to to their own system in their own types of services. So I threw up this slide. So we'll share this with you. There's there's one edit that I'll fix later. Matthew Russell: But it gives you a sort of an overview of some of those system level data sources that that I've worked with, and also imagine Canada does wonderful work with, Matthew Russell: as well as a couple just simple ones that are examples of of how those other types of data sources could link to you as an organization that that I o
ften bring up as I'm talking to to agencies. Matthew Russell: so first of all, the one that you may or not be familiar with that, I think a lot of people think about when they're talking about the system level sort of impact big level numbers we talk about the Satellite Account for Not for Profits and Volunteering that number one there. Matthew Russell: So this is an update through statistics. Canada. It was. It was closed down for a while. And now we're actually going to a sort of yearly updat
e thing. This has really been, I think, a thanks to a lot of you here who said, this is really useful data, we wanna hear it, and then they started to do that they actually listen to. As we got that repeated, we were talking to their assistant chief statisticians. And they, they said, we need to have this data. Matthew Russell: So every year in the spring. So in about May, I think, is the next update, we'll get the data from about 2 years back. 2 years back is about the the quickest it can be be
cause this is derived based on on actual data and reporting from it from agencies and organizations across Canada Matthew Russell: And it gets estimates of things like revenue. The GDP of the Sector workforce numbers in terms of number of people being employed. It's broken down by the provinces. Which is kind of cool, so you can see, is there differences? How was it looking in those different groups? Matthew Russell: And then it has these other sort of breakdown. So as things like volunteering v
alue data. It's not up to date. We actually did a bit of an analysis in the dashboard below that has the newer numbers. Matthew Russell: If you're interested in those. So what's the dollar value of those those volunteering numbers for the not for profit sector? And then there's also something that they call the human resources module where they've they've linked it to people's demographic information. And then they said, here's how many women are in this sector, and and we know it's a very big n
umber. Matthew Russell: Here are some of those minorities, other groups. And how are they showing up in the the sector? How are they being paid? Matthew Russell: So you have all that. The data itself is is kinda in raw form in tables. So one thing we've provided is the dashboard. It was originally for Alberta. But I was like, why don't we do this for all the provinces? So we just made a a slicer that goes in and you can actually see those main impact numbers across these different data sources.
Matthew Russell: With like a slide. It has breakdowns for different sub sectors. All those things in this dashboard. So if you're interested in using this data or working with it, go ahead. Use our dashboard it's reuse, tt's there, and it's meant for you all. Matthew Russell: The second one I would talk about just briefly, is the Canadian Survey and business conditions. So this one is a survey where they they actually go out. And statistics. Canada not every 5 years, but quarterly sorry. I think
they just released the last quarter and they have numbers and questions that they they pose to community not for profits, and then some comparison with sectors like the private sector. Matthew Russell: What they do is, it's a very short survey. Some standardized like repeated questions, some new questions, all that stuff. And they say, here's some of the needs. Here's the business conditions related to the sector. I found that the right now things haven't changed that much with the surveys. So
I'd like to say, you'll probably you're gonna hear more about Paloma, about her survey. It's sort of like a version of her survey with different sort of things that are more around those business conditions. Although some of those questions might be similar as well. Matthew Russell: The third one. So if you're interested in volunteering. So the General Social Statistics survey they actually have some a survey every 5 years where they go in, and they ask people about volunteering and donating in
different types of conditions. So they actually go out, they call a lot of people and based on that they make some estimates of the amount of hours of volunteering and all that stuff. Matthew Russell: So actually based on those numbers, we went into that data. And we said, this is the estimated value of those numbers. So you can see that in the non for profit dashboard, if you're you're interested. But it's every 5 years the next one just ran. Matthew Russell: So that means I, Matthew Russell:
next year or late this year, we're we're talking about the next sort of cycle will have that release for that data. So if you're interested in volunteering, that's one of those great sources, it's not perfect. It's a survey all that stuff. So it's an estimate. Matthew Russell: So it's not meant to be compared years to year, because methodologies change. Matthew Russell: The third the fourth big one that we often talk about is actually registered charity data. So this is, sometimes we call it the
T3010 data. And you know, these fancy numbers and letters, and how we put that altogether. But this is actually the reported numbers. What people non for profits, or in this case registered charities specifically report to the government in terms of this is our income, and then there's a few items on staff numbers and and all that stuff. Matthew Russell: So based on this, it actually it has really cool things you can do with it if you're a a data person. It does have like the rough things like
revenues and expenses, and they match up pretty well with that satellite account. But you could do other breakdowns and just stuff like that if you have time to work with it. Very rich possibilities. But it's it's not perfect data. We know from this data that it has some issues with cleaning where where it has issues. I remember one group, Matthew Russell: I'm not gonna say their name because I wanna embarrass anyone, but they're off by a thousand, and I was like, oh, that's a big agency. I'm pr
etty sure they're in the millions, and they were saying there are like $100,000. And that happens in this data. So literally, what I would do is I would look at it over like 5 years. And then we we try to find these trends. So thank you. David Lasby, he's he's a a magic man with this data. So if you wanna know more about that, he's a great person to talk about it. There's other people as well that work with it. Matthew Russell: Also, I would say, like the satellite account. The reason with with
that one that we actually wait a couple of years is because this is tax reported data. So that means it's a year later already. But then all of the groups have their own fiscal year. So it's more like about 2 years back is where you're pretty complete for that data. Matthew Russell: So you're not going to have exact to-the-minute data. But it is very rich data. If you want to learn about sector impacts and how how groups are using their money. Matthew Russell: Finally, in these big sort of syste
m-level sort of data sets the charitable donors stats is another group that's from Statistics Canada so people get their reporting like how much they actually gave to charities Matthew Russell: in terms of donations. And that comes through actual tax file data. And they put this into a file that's linked to some people's demographics. So you can see some of those splits and all that stuff so like how much was given by men, women, all of that stuff in terms of numbers. Unfortunately, I think ther
e's less donors right now is one pattern we're seeing although the dollars are going up a little bit over time. Matthew Russell: And then the last 2 is like I was saying is - I know these system level things are not the thing for everyone here on this call - is things like the census data, and like some people are like, it's the census. It's not that interesting. So I actually think the census data is a really cool sort of Matthew Russell: nice tool for organizations that are actually serving in
dividuals because it gives you things on people's demographics. It can be split by fine level geographics. I don't think I include the source, but there's actually a group where you can you can clump those geographies together and get a sense of like, what are those demographics in that area? So you know, what are your clients? What are those people, are we successful in serving those people in my area? And we know this from so much data is Matthew Russell: if you're in one area. Matthew Russell
: that's where more of the access is going to be so. Those are the type of people that you'd be expecting to come to your services. So census is cool cause it has all of that. It has a lot of breakdowns for different types of individuals. All that stuff I've done cool things on on socio economic status with this data just using their raw files. Pretty cool stuff. Matthew Russell: sometimes it's hard to use. So there's lots of Stats Canada training and all that stuff. We also have training alread
y online. So if you just want to go through the whole training series, we have it on our website here. Click through. It's there. It's free it was made for the not for profit sector. We even we changed it so it'd be a little bit more accessible. Matthew Russell: So yeah, click there, click on our website. Look through. Matthew Russell: The other thing is, you might have other sorts of data sources. So I just gave one example, the Community Health Survey. So I know a lot of groups work with indiv
iduals with mental health needs or or well-being needs. So this is a yearly survey on of sort of rougher scale to see how communities integrate scale are sort of doing over time. There's other sort of things like I call it CIHI, data that has more healthcare data. Matthew Russell: And there's other sorts of data sources. But they're out there, that's the main thing I wanted to say there. And these could be all tools, as you're thinking about things that are talking about the individuals you serv
e that help you with your goals. They could also be great narratives as you talk about funding. This is how things are going in terms of the sector. Matthew Russell: So last, I just say, like, if you you're interested, all this stuff, these are all great data sources. You could also drop by on our website. We have a few segments if you're interested in training learning to use data, more learning to use the the Stats Canada website. More, we have a bunch of just webinars up there. Matthew Russel
l: That's under capacity building. If you're interested in some analyses specifically about Alberta, go to the Alberta tab. Matthew Russell: And then, if you're interested in other resources, including like finding Paloma's resources and other sorts of groups, we have all the links and the other resources have meant to be like great things and great tools that we've seen out there that are examples of things that could help you in the non for profit sector. So feel free, jump by and I just say,
Matthew Russell: what is the sector data? Sometimes it's system data, sometimes it's it's around the neighborhoods you serve, and sometimes it's around the health you serve. Those are some examples, and it may just be your data Matthew Russell: And and that's a different thing, too. So thanks. Jacqueline Musabende: Thank you very much, Matt, this is amazing. Jacqueline Musabende: Ask about the ecosystem, and they say that we have the data everywhere for everything. Jacqueline Musabende: It's jus
t probably about what I see to know where we find this information and how we can use it for to improve or to support Jacqueline Musabende: our activities in and non profit. Thank you very much for providing us with overview of ecosystem data for non profit ecosystem and also for sharing data and the source where we can find the information. Thank you very much. Jacqueline Musabende: I will go to the next question. This is, gonna be for Alissa, I wanted to ask, How does collecting data help adva
nce your mission at the kids Help Phone Jacqueline Musabende: and what are some of the challenges that nonprofits face when collecting and using their own data? Alisa Simon: Yeah, it's such an important question, because the reality is as most charities are, nonprofits, we are committed to our mission and our mission is serving people in one way or another. Right? So at Kids Help Hhone, we are there for young people in every moment of need. Alisa Simon: And Alisa Simon: that's what we focus on.
That's what we get funded to do. That's what we're writing proposals for funding to do. But the reality is that behind that is a huge amount of data. So when I came to Kids Help Phone, you know, we were really focused in any given day, how are we gonna answer every call? How are we gonna answer text, how are we gonna create new services? And all of that is really important. Alisa Simon: But then, if you're able to take a moment and step back, you start realizing what an unbelievable asset you ha
ve in all the data that is being collected or could be being collected based on what your mission is. And so at Kids Help Phone, we started going, "Wait a second, Alisa Simon: you know, since the beginning of Covid, we've supported young people almost 19 million times. Alisa Simon: Through those 19 million times, we have over 40 million data points on youth mental health, including transcripts of conversations that young people have had with us, what the front line person has filled out about wh
at the conversation was about, or any information we have about the user. We have surveys that the young people fill out about what their experience was, what the impact of the conversation was." Alisa Simon: So the first thing is, we had to look and go, "Okay, what? What data is out there?" Cause we've been having our front line fill out these forms for years, Alisa Simon: but we never really saw it as data with power. We saw it as something that we would look at every once in a while to kind o
f get an understanding of our service. Alisa Simon: So we really took a step back. And we said, where all of the pieces of data that we have as a charity. Alisa Simon: we also have a list of every service and support that's available to young people across Canada. We have a group of librarians, and they collect over 30,000 services supports from food banks to 2SLGBTQ support groups. That's another data source. So we looked at them all. And we said, Okay, how do we bring all of them together, bec
ause the reality is when they're all separate. Alisa Simon: It's really hard to truly understand what's happening within your ecosystem, let alone to maybe leverage it to help others understand what's happening with the population you serve. Alisa Simon: So the last few years we've spent a lot of time building up a data hub Alisa Simon: which is bringing together all these discrete and unique data sets into one place so that we can actually compare and look at what's happening for Kids Help Phon
e and the young people that we serve. Alisa Simon: A few things you gotta think about: First of all, what is the data? And there's always more data than you actually think. If you're able to take a step back and really think about Alisa Simon: what does data mean to me as a charity to the people that I serve to our mission? Alisa Simon: How are we collecting it? Are we collecting it and saving it in ethical ways? Is it kept in Canada? Is it scrubbed of PII, all of that kind of stuff that makes s
ure that if you're keeping data that you are adhering to whatever rules, regulations, that are best practices or laws? And then starting to go, Okay, what can we do with this data? Alisa Simon: And how are we gonna leverage it? And so within that process at Kids Help Phone, there's been a few different things that we've thought about. First of all, when you start getting into millions of data points, Alisa Simon: you start being able to think about, what could AI or machine learning do for us? H
ow could we build products? Alisa Simon: Because we now have huge numbers of transcripts with the real words of young people. So we've built out a model that is using our data to review transcripts. And we're at about a 90% accuracy rate of being able to help our frontline know exactly what the conversation is about, Alisa Simon: so that they're better able to find the best resources, the best tips that they could give on that issue. Alisa Simon: So there's all sorts of cool things you can do li
ke that. But there's also things like, how do we share that data back? Alisa Simon: How do we let Alisa Simon: governments. organizations, advocacy organizations, know what's happening with young people and different topics by population? So you know, one of the big things when you start thinking about data is specifically around equity deserving populations. So at Kids Help Phone, about 10% of our users identify as Indigenous. Alisa Simon: So we have to follow OCAP principles. And that means th
at our data that we collect around Indigenous young people, we share back with communities. We share back with Indigenous organizations because they own that data. Alisa Simon: But it also means we have tremendous understanding around what could we do to improve our services. What do Indigenous young people need? And is it different from Métis versus First Nations versus Inuit? Alisa Simon: And so that data has allowed us to also build new services and programs. For example, Indigenous young peo
ple said to us, when we connect with you, we'd really like to often connect with someone from our background. Alisa Simon: And so we learned that from our data, Alisa Simon: we then built a matching program where young people can text us with the keyword, First Nation, Inuit or Metis, and whenever possible you try and connect them with a frontline person from that same background. Alisa Simon: That came from the data. Alisa Simon: The data also lets us know about impact. What's the difference in
a young person's life if they text us versus call us versus use our peer-to-peer community. Alisa Simon: so service improvements, quality, product development. What are the new kinds of things that we want to build that allow young people to connect and have support in new ways. Alisa Simon: And then those thought leadership. What is it that we're learning about different populations that actually, Canada needs to know? Because the reality is, you know, we talk about data. There is a huge gap,
Alisa Simon: I think it's about 17 years, between research and us actioning that research. Alisa Simon: So charities Alisa Simon: are today seeing people that we know, have real concrete needs. Alisa Simon: If we can get that data out quickly in real time, Alisa Simon: we have tremendous power to not wait 17 years for changes in policies and programs and funding. Alisa Simon: So that's the power. The the other part of your question, Jacqueline, I think, was sort of what are the limitations, and
what are the challenges? And one of the big challenges is, there's not very many charities that are funded Alisa Simon: to be able to leverage our data. We are funded to provide services, and we are asked, how many services did you provide? Who did you provide it? To all of those really important questions, Alisa Simon: It is very hard, particularly at a small charity, to find the time, energy, and expertise, even to understand what kind of data do you have? And how can you use it? And so I wan
t to just be clear that it requires investment Alisa Simon: from government, from funders, that we actually say we understand that the services and supports that charities and nonprofits are offering are critical. That's why we invest in them, Alisa Simon: the data potential of what they have, what they know Alisa Simon: is equally as important, because nobody knows more about what homeless people are facing than the homeless shelter who is serving them right now. Alisa Simon: But if we don't fi
nd ways to leverage that data, Alisa Simon: then we're relying on surveys that often don't reach that population. We're relying on experts and talking heads who know a lot, and and we have all the right heart, Alisa Simon: but that's different than the people that we actually serve. And so you know again, when I think about Kids Help Phone. The power of what we've really been talking about is Alisa Simon: we have a kid's cell phone, the words of young people, we have the transcripts of the conve
rsations they've had. No one else can describe what they're going through better than they can. Alisa Simon: But the only way that we unlock that power is the funding. the the people power and the understanding of what we can do with that data. So it's not enough just to say, yeah, use your data. It's really important, we have to be able to build infrastructure within our non profits that allow us Alisa Simon: through partnership and funding and all of the other things to leverage that data. Bec
ause it's got huge power. And I don't think we often understand the power of the data that we're sitting on. I can tell you, Alisa Simon: social media understands the power of the data they're sitting on, right? Companies, for-profit organizations - for many of them, they provide things for "free"because they're getting your data. Alisa Simon: And so what I would say as people that work in the nonprofit sector is time for us to really understand the power of the data that we have, and understand
how we can leverage it in order to really be able to move Canada forward and better serve all of the people that we are here to serve. Jacqueline Musabende: Thank you very much, Alisa. Thank you very much. This is really amazing. So I see that Jacqueline Musabende: the key is how to leverage data, because we all have a data or sector has of data, but not all people are going to understand it. The powerful data we have, we need also to be able to leverage it. Again as we talk about the ecosystem
, funding from Government to help a nonprofit to leverage their data. Thank you so much. And I can read the example of Jacqueline Musabende: this model you were able to build, his is going to help front desk to understand. You know, when they have a conversation with younger people they are helping, but also helping you to come up with new services to improve on services. You have to understand the geography. This is really what we needed to know or to understand. So we can understand the way th
e power of that, how we have so thank you so much for sharing this knowledge with us. Jacqueline Musabende: I'm going to go to the next question which is going to be for Paloma. I wanted to tell more about Paloma. When I joined the ANSER, the Association of Non-profit and Social Economy Research, Paloma was there, and I was so happy and blessed to know you, I learned a lot from you. Thank you so much for always being willing to share, and mentor younger people who are joining. So I'm going to as
k my question to you. Jacqueline Musabende: This is the question: in your opinion, what do you see as the gaps in the data we have in our sector? How does the Charity insights Canada Project help address some of these gaps? Jacqueline Musabende: Thank you, Paroma. Paloma Raggo: Thank you, Jacqueline, and you know thank you for having me. I, Carlton, is located on the Paloma Raggo: unceded territories of the Algonquin people, so I just wanted to acknowledge that as well. I wanted to also thank Ma
tthew and Alisa for really highlighting the breadth and the depth of the conversation that we have. And Paloma Raggo: Alisa, a lot of what you said actually resonated a lot with Paloma Raggo: the impetus of the Charity Insights Canada Project. As an academic and as one who Paloma Raggo: likes research methods, I like to teach about that, though I wish that the the audience was sometimes warmer, but you know it is what it is. One of the things I noticed in academia, and I don't know if it's the s
ame for organizations like yours, Alisa. But Paloma Raggo: the academic endeavor is a very extractive endeavor. We ask a lot of information from organization. We take a lot of the knowledge. Paloma Raggo: but one of the big gaps is really linking back and feeding back, you know, what we found in a timely fashion. And so when Covid hit we saw this more than ever. We have pressing needs, Paloma Raggo: the needs change on a 2 week cycle, you know. And on what do we base our information? We need Pal
oma Raggo: real on the ground data that's representing people that are hard to reach. Paloma Raggo: We wanna make sure that we cover a lot of people. And so Paloma Raggo: and Paloma Raggo: a consortium of foundations, led by the Muttart Foundation, but including Paloma Raggo: The Vancouver Foundation, Lawson Foundation and McCall Foundation launched this call saying, How can we make this happen was a a real question. Saying, Okay, how we have a lot of data Paloma Raggo: as as you've seen with th
e 2 first presentations, Paloma Raggo: we have a lot of information. I think we have to change this narrative of, we need more data. What we need is perhaps better data, more integrated data, but collecting more of the same, Paloma Raggo: I don't think we'll solve the fundamental issue that we have here is to make sure that we are representing the voice Paloma Raggo: of the people working on the ground, representing and capturing the needs and the wants. And so to do that, that's where the big
challenge is and our approach to that - which is one approach, and it's not Paloma Raggo: the approach that will answer all data questions in Canada, because the data questions are complex Paloma Raggo: and they require different solutions. But one of the solution we had was Paloma Raggo: to be able to capture perception based data. So the perceptions, the opinions, the needs, the challenges. Paloma Raggo: so that they're complementary with the administrative data that we have. We don't seek to
replicate cause there is good data out there. It might be in a form that's not always accessible, and that's a big Paloma Raggo: challenge that we're facing. There are Paloma Raggo: technical Paloma Raggo: skills needed to be able to really extract something meaningful for practitioners on the ground Paloma Raggo: that you know is not accessible to all. And that is something that we have to as as a sector work Paloma Raggo: towards facilitating access to data, not necessarily only pushing for in
creasing the production of data, but the access of what we have, whether it's at the government, whether it's through initiatives like ours, or facilitating, you know, supporting organizations on the ground that are collecting valuable data, but finding ways to support that endeavor as well. Paloma Raggo: So in terms, you know, in terms of the idea for the project it was kind of simple, and I Paloma Raggo: give that anecdote often, because as we were thinking of Paloma Raggo: presenting the proj
ect, you know, I was procrastinating a bit, trying to write the proposal and thinking and playing on Facebook, answering these little quizzes, you know, Which house of Harry Potter do I belong to? You know what kind? Paloma Raggo: And then it struck me that I get survey requests by my colleagues about the work of an academic, or what's my position on this? It only going to take 10 minutes, Paloma Raggo: 5 minutes, and I don't do it. Paloma Raggo: and I'm here thinking of sending a survey to the
most busy people I know. Paloma Raggo: Oh, it's only going to take you 10 minutes, 15 minutes. Please answer my survey, and you know we are struggling with survey response rates and all these things. How can we make this happen. Paloma Raggo: And it hit me at some point, cause I was thinking, you know these long surveys that we answer. What if we took the box we use normally, which is like this long survey form, Paloma Raggo: and take her box and flip it on the side, so that each week we ask 2 q
uestions, 3 questions, max. Paloma Raggo: It takes less than a minute, a minute and a half to answer. Paloma Raggo: and we ask the same people to answer these questions over a year, Paloma Raggo: because at some point it's kind of fun. They answered the questions on the Wednesday and on the Friday they have the results. So they know what other people thought as well. Paloma Raggo: And so we proposed that. And people are like, it's not going to work. Paloma Raggo: Okay, you know you're victim of
your naiveté. If you don't know, you don't know, but let's try it, and you know we were lucky that we were able to take that risk. And this year we're launching the second year, and we have Paloma Raggo: maintained an 80 plus response rate. So it means that the same people answering week after week the questions are willing Paloma Raggo: to not only in the first year stay, many of them for second year to continue, because they find, Paloma Raggo: and not only answering the questions, helpful in
terms of thinking through certain themes, but Paloma Raggo: most importantly, feeling, "I'm not alone. I can hear other people's concern. I don't agree with other people's concern." And so it it opens this dialogue. So the goal really here is to Paloma Raggo: fill this part of Paloma Raggo: making sure to reduce Paloma Raggo: this lag between, we take the information, so make it really quick, we give it back. And then, based on that. Paloma Raggo: the next challenge that my team has is to make s
ure that we build Paloma Raggo: and help facilitate building narratives? Can you make your case based on data? Can you make? How can you use this to write proposals, write policy briefs, reports. And so that's really kind of an important gap that we felt Paloma Raggo: we were able to to address. Paloma Raggo: We're starting the second year. So it wasn't the perfect year. But we learned a lot and now we're applying some of these learning this year. So, for example, on Wednesday in 2 days. We're l
aunching these dialogues where we're going to literally present what we asked Paloma Raggo: in the past month and ask people to react. And why do you think we're finding this? like we want to hear, Paloma Raggo: Should we have asked this or something else? And get this continual feedback, because we're able to Paloma Raggo: to kind of listen and react and be agile in that sense. The other important gap I think, Paloma Raggo: we often focus our conversation on the need for more data that is so im
portant. That is the new gold rush. Everyone wants it. Everyone needs it. Which yeah, I kind of teach research methods. Right? I agree. But at the same time, I think an important component is data literacy. We don't talk about enough about the importance of data literacy and data access. Paloma Raggo: Because we then focus on the technical parts of data. Paloma Raggo: But that is Paloma Raggo: more than just numbers and we have to be careful. And I say this as someone who loves quantitative meth
ods, we have to be very careful on overly quantifying information, because the hardest things Paloma Raggo: to measure are often sometimes the most impactful things. Progress is not always something we can measure. So we need to have a real substantive discussion on what data actually means, how it's practiced. Paloma Raggo: And so that we push back a bit on the dominant ideas of, you know, data is financial information. Data is this. Paloma Raggo: And and we see from our conversation. This is m
y ringer, because I tried to keep to 10 minutes, but we see from our conversation that the ecosystem is diverse. It's plural. It doesn't necessarily all agree. But what we need to strive for, maybe, and you know, that's. Paloma Raggo: I hope a conversation we can have is a better integration, a better complementarity, and working in supporting each other. Paloma Raggo: so that at the end everyone knows more about the work that is done in the sector. So Paloma Raggo: that's my spiel here. Jacquel
ine Musabende: Well, thank you very much. Paloma. Thank you so much. Jacqueline Musabende: I really, actually. So my background is in Jacqueline Musabende: software development data management and so on. But I like to see people who are really in the field working or using the data. So I think it's probably to use a technical systems and then to find information. But I like it to see when we data is out there in the field and doing things like when you say that we needed it to start to think abo
ut, what do we mean by data? So people don't just see that as a financial or quantifiable or data. We needed to really understand how data Jacqueline Musabende: we can actually use it to benefit everybody. Also when you say that we needed to be able to have to see that as a complimentary, so data shouldn't, doesn't agree all the time. That's really very interesting. And it to see how Jacqueline Musabende: people can use it. Everybody can know what is going on in our sector. So that's really very
, very helpful. And for people who are, for example, myself, who are technical. I want it to be to see data out there, serving the population, also helping out sector to to complete their missions. Jacqueline Musabende: So thank you so much for answering these questions. We have couple of minutes, I think, 5. So wanted to add these questions for Alisa and Matthew. If you can help us to just tell us what you think are Jacqueline Musabende: the gaps you see in this area and untapped potential in,
of course, our data ecosystem. Jacqueline Musabende: So we start, probably with Matt. Matthew Russell: Sure, sure, I'll jump in. I was like, there's a ton of different possibilities in all this stuff. But I think just hearing what people say in all this stuff it's often the gap is the right data. Matthew Russell: And people have lots of data. And this is what we're talking about here. Everyone has it, but often people haven't thought about the data they actually want to use and all that stuff. M
atthew Russell: And it's not about the questions they want. They may collect it for the reporters or reporting where people say, this is what you need to have for these numbers, and it has nothing to do with the needs of your agencies. It's for another reason or a system level thing. The data that you actually need is really important. Matthew Russell: If you're talking about that system level data that I was talking about. The big gap we often see is those volunteer not-for-profits, Matthew Rus
sell: those not-for-profits that don't have staff and are not registered charities. They are not reporting a not for profit form or whatever they're they don't file the same forms, and their data is not coming into the whole thing. Matthew Russell: So and they're a big group, they're they're considered up to 50% of not-for-profits here in Alberta. I'm sure that number is big in other provinces as well, and that gap is a huge thing because we're the volunteer sector, the not for profit sector is
very big. Matthew Russell: There's more, but those are what I'll go for with a couple of minutes. Alisa Simon: Yeah. So I think I would. Say, there's a few gaps that I often think about. And I talked about some of them when I was speaking earlier. But I wanna highlight that so many charities and nonprofits, and even non-registered organizations that are doing good, Alisa Simon: the people that we serve and their stories, and what their life is like is not represented well in the data. Alisa Simo
n: And that is because our surveys often don't reach them when we think about, you know, Stats Can and things like that. And it's because often when we are doing research. Alisa Simon: we're asking really amazing questions. But we might not be getting to the end user. We want to. But also we don't necessarily give their voice the opportunity to come through, because we often have check boxes that we're asking people to fill out and things like that. So to me, when I think about the power of the
data at Kids Help Phone, and then I think about the gaps, it really is the words, the stories, the impact of the end user themselves. And Alisa Simon: that's really hard to gather, right? If you are a face-to-face organization, you might not have transcripts. But are there other ways to collect those kinds of stories? Because Alisa Simon: that, I think, is what we're missing so much. And I'll tell you over the last few years, Alisa Simon: you know, we've been doing more and more of our building
of new services co-designed with young people, and people are doing that all across the sector, which is amazing cause they need to be involved. Alisa Simon: But again, when we choose to do co-design, what we're often doing is we're picking what I call the handraisers, and I don't mean that in a mean way. I was a hand-raiser. It's the young person who goes, Oh, I want to be involved in co-design, I want to help build something. Alisa Simon: How do we make sure the quiet people, the people at the
back of the class, the people who don't volunteer, that their needs and voices are also being heard. And again, at our charities and nonprofits, we're hearing them. They come to us, and so we have to find a way to leverage that data. Alisa Simon: I think the other question is often around, you know, again, if you don't have a lot of resources, how do you even go about this? How do you start even thinking about what data you might have? Almost all of us have paperwork at the very least. Alisa Si
mon: We have our front line filling out forms. So I would start thinking about, is there a way to take that paperwork Alisa Simon: and start organizing it in such a way that it goes from individual paperwork records to data? Alisa Simon: And again, it takes resources. It takes knowledge. But we all have that kind of data, regardless of how big or small we are, regardless of how many staff we have, or if we're volunteer or staff. Alisa Simon: it's really starting to think about, where are those p
laces that we might have information that if we had the support, whether it was funding or partnership to be able to take that information and organize it, Alisa Simon: we would suddenly have data? Alisa Simon: And that's the the piece that I think we need a mindshift change on within this sector to really say, what information do I have that if I had the right process, the right funding, the right partnership, Alisa Simon: that information could be suddenly something that we know as data, Alisa
Simon: and therefore be leveraged in really cool ways? Jacqueline Musabende: Thank you very much. Thank you so much to share this information about needing to have the right data. How do we know even that we have the right or wrong data? To be able to create also this environment where we provide everything you need from funding, support, Jacqueline Musabende: technical skills, to make sure that we provided this environment where nonprofit sector can find access to this data and then be able to
use this data. Jacqueline Musabende: Thank you so much for sharing this information. So I'm going to just to go and ask you around a question, ask everyone of you to give us your advice somehow, as an expert in this field. Jacqueline Musabende: The question is going to be, what is your basic piece of advice for people who are interested in learning more about the data, but are not sure where to start? So we start with Paloma, then Matt then Alisa, thank you so much. Paloma Raggo: Of course I wi
ll say, you know, Paloma Raggo: go back to school, come to the Masters. But no, but jokes aside I think Paloma Raggo: learning more about what you don't know. So, knowing what you don't know is an important initial step. There are so many ways Paloma Raggo: going about what is data? And I think, Paloma Raggo: one of the things we are trying to do. Really, at a basic level through the CICP is we created one of the pillar of the project this called the Community Education Center. And what we're tr
ying to achieve here is really basic Paloma Raggo: intro information about data literacy Paloma Raggo: and basic to the level. What is data, what is a variable, a, and we're not getting into more the the technical parts, because there are great courses out there online at schools, universities. Paloma Raggo: But oftentimes we just need these little pieces to connect the dots ourselves. And so it's really through, I think, allowing people to know what they don't know. Paloma Raggo: and then kind
of assess what what they need, what they can do Paloma Raggo: one of the things you know during the gap question that I didn't necessarily talk about - and Jacqueline, you will know - is that you know, as academics in the field, sometimes it's hard to find support and Paloma Raggo: funding to do research in the field. So it's hard in the field. But as academics, Paloma Raggo: it's hard to make a career studying the nonprofit sector. To be quite honest, and I think our funding agencies need to un
derstand that because Paloma Raggo: I would give the advice, reach out to us, and Paloma Raggo: if we can, we will find a way to partner. I think there is sometimes kind of this notion, of not partnering enough with the academics, and we're always happy and willing to work with organizations. But again, it's always a question of resources. There are very few. The community is small. In Canada we know each other. But I think, it would be Paloma Raggo: great to really get better these collaboratio
ns. And I think that could help Paloma Raggo: in many regards of what can we do ideas, innovation, creativity within the sector around data. Alisa Simon: So go ahead, Alisa, if you're if you're having an issue. Oh, sure and sorry, everybody. My computer has said it's about to shut down, and it doesn't seem to care what I say. So if that happens, I apologize. Alisa Simon: So I think my piece of advice would be Alisa Simon: given that we all get into this because we have heart, and we believe in t
he mission of the organizations, that's why we do this right? That's why we get into the work, whatever the cause. Alisa Simon: If you were able to take a few hours and take a step back and say, if I had a magic wand, that's the question we often ask young people, if I had a magic wand, what would be different Alisa Simon: in better supporting the population that my charity is here to support? Alisa Simon: And if you think of that answer, then think, do I have anything within my service, my orga
nization, my agency, that could help make that happen? Alisa Simon: And then write that into your next funding proposal. Alisa Simon: Write that in as a cost. Alisa Simon: whether it is turning your paperwork into data, whether it is hiring a part-time data person, whether it is partnering with a university, actually make that a part of your next funding proposal Alisa Simon: because we have to be able to dream it. We have to be able to see that our data can change the lives of the people we ser
ve. Alisa Simon: and then we have to be able to make that happen. And so it doesn't have to be hundreds of thousands, millions of dollars. It can be starting with for $20,000, I might be able to get a 10 hours a week data person to come in and help with this. Alisa Simon: And so I'm gonna write that into my next proposal. It might be I can't get any money, but I could partner with a university or with an organization that has data capacity because they might be interested in what that story and
vision is. So I think we have to understand as individual charities and nonprofits the why of our data Alisa Simon: so that we can help tell that story to partners and funders. And so that's the work that I think we can do as leaders within our charities. Is, try and understand, What's the problem we want? Jacqueline Musabende: Yeah, I guess it happened. Okay, Matthew, can you please take over? Matthew Russell: Yeah, yeah. We got most of the comments, and then I would be talking about a lot of t
he common things that she was talking about. So I say, like, the biggest thing I would say is, Matthew Russell: don't don't make it too complicated. And I'm just saying this because I I've worked with a lot of groups. I'm also working on the big roadmap project and Matthew Russell: a lot of people are asked to give and and collect a lot of data and a lot of times doesn't make sense. So one thing in in terms of working with data is going, there might just be like, how do we simplify? How do we ta
lk with those funders and and make it so what we're collecting is less Matthew Russell: rather doing more? What's less? Another thing could be, just in that same thing is like thinking about like the use as she was just talking about this. What's that impactful question about how you're going to use this question. I've always come this. And we've we've had things that were like Matthew Russell: we have all this data. Let's work with it. And all this stuff. And the question wasn't there, Matthew
Russell: and it just wasn't collected there. And if you just had one question around your primary thing that you're trying to solve with each of those programs. And that's probably all you can ask. Or you can do with the clients you're working with. They're stressed out. They're having hard times, all of that stuff. You don't want to ask a ton of things. You want something that's relevant to what they're doing. So it's do less once again. Matthew Russell: It doesn't have to be fancy how you anal
yze it. All that stuff you don't have to be. You don't have to get a PhD, you don't have to go on a post-doc like myself. You don't have to do that. You can do fancy stuff by, just this is a simple question around the needs. And maybe a qualitative thing. Just a question like, How are you doing in terms of this domain that you're serving Matthew Russell: in terms of that same thing as in terms of ease. The other thing is doing it right away. Matthew Russell: So starting early, if you want to hav
e data, and all that more is better. So if you start when you're doing something, you have a new service, say, what's that question we're going to collect like she was just saying before she left is when you have that funding call plan for it upfront. If you do that, you ask for that money. You have it. You're ready to go Matthew Russell: and then, like she was saying. maybe you can do it. You have that capacity in your group. Matthew Russell: You can do it yourself. You can learn it. There are
training courses and all that stuff. But if you can't, you can get help from someone there. There's academics. There's there's groups that do that as well. Or there's lots of contractors. There's other options like for 10 hours a week around some some simple need. But the the thing that will come back to is, do you have that question? Do you have the thing that you're going to need? If you didn't collect it, and it's for your goals, it's not gonna be there and it's not gonna be helpful. So Matth
ew Russell: that's a lot of points, but it's keep it simple. Jacqueline Musabende: Thank you very much. Matt and Alisa and Paloma. Thank you so much for sharing your experience and expertise for data for our sector. Jacqueline Musabende: Just to let you know that we have another webinar coming on March 27. For this one we look into Statistics Canada data on our sector. So we include practical demonstrations on how we can use the Statistics Canada data for things like a fundraising, strategic pl
anning and volunteer management. Jacqueline Musabende: So the registration link, you will find in the chat, and we hope it to see you all there. Thank you very much for attending this webinar, and then we will see on you on a march at twenty-seventh. Paloma Raggo: Thank you for organizing. Matthew Russell: Thank you for organizing, and thank you everyone for attending. This is great.
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