In this episode we sat down with David Spriggs, CEO of InfoExchange, a not-for-profit social enterprise working to empower the community help the not-for-profit sector have more impact in their work through the use of technology and data.
This is also the first episode of this podcast with video as well as audio. We hope you enjoy it!
Notable Quotes
“full credit to our our founder, Andrew Mahar, who came up with this vision of technology for social justice”
“there’s just so much that the formal education doesn’t teach you and that you need to learn on the ground. I think I think for me, a huge part of that is is how you work in partnership with others.”
“And it is and it is just so critical for our work in the not for profit sector. Because if we if you talk about helping somebody in need, you know, more of most often they’re multifaceted issues that somebody’s dealing with. You know, yes, they might have a need for some emergency relief food, but they may be dealing with mental health issues, they may be dealing with housing issues, maybe dealing with family violence issues and and none of those things, you know, you can solve as an individual or just or just one organisation.”
“at InfoExchange we operate a platform called Ask Izzy and that helps people in need connect with services across the community. So they use they can use their mobile phone, it can pick up their location and they can say, I’m looking for food, or I’m looking for housing, or I’m looking for mental health support as an example. And yeah, and so it’s it’s an incredibly useful tool for somebody to be able to find the support in their area… So heartbreakingly, in the last 12 months, we’ve had over eight and a half million searches for help on the Ask Izzy platform.”
Transcript
Linda McIver (00:03)
Welcome to another episode of Make Me Data Literate. This is our first episode with video as well as audio. So I hope you enjoy it and it gives you another way to listen. I’m excited this time to be delving into the area of not for profit data with my guest David Spriggs. Welcome David.
David Spriggs (00:24)
Thanks so much for having me.
Linda McIver (00:26)
It’s great. I’m really excited about this. where I think we’re going to talk about a lot of things that I get very passionate about. so my first question, who are you and what do you do?
David Spriggs (00:37)
Yeah, thank you. So, yeah, my name’s David Spriggs, and my day job is the CEO of InfoExchange. And we’re a not-for-profit social enterprise, and we’ve been going for a bit over 35 years on a vision of technology for social justice. So we’re all about empowering the community through the use of technology and helping the not-for-profit sector have more impact in their work through the use of technology and data. and so as you can imagine, kind of data and the subject for today kind of permeates all of all of our work, but maybe a bit more of just about about me as well as a as an individual and kind of my my background. So my love of data actually started back when I was in primary school. And my my my dad was working for a corporate at the time and his boss thought, these PCs might one day become something. So I think all of my employees should learn about them.
Linda McIver (01:22)
Wow.
David Spriggs (01:33)
And so he brought home one of the first IBM PCs from work. and I don’t think he used it all that much, but I fell in love with it. And so kind of I taught myself kind of programming in basic and my kind of first real data would have been like Lotus One Two Three, if people can remember that as the early version of kind of spreadsheet applications and producing, you know, data and charts and and all of that. So I I loved that, kind of went through and knew that I wanted to get into tech, you know, did an IT degree.
Linda McIver (01:50)
wow.
David Spriggs (02:03)
but then joined Info Exchange 17 years ago and kind of and this is my love of that intersection of tech and data and community and and bringing it all and bringing it all together. and I’ve got I’ve got two kids. part of my life married with two kids. And guess what? Like all kids, they’re into tech, data and AI, and I kind of look at what they’ve got access to now versus what I had access to with a clunky keyboard and BASIC and Lotus 123. So anyway, that’s that’s a little bit about me.
Linda McIver (02:07)
Wow.
Yeah.
That’s fantastic. I’m I’m to start off with, I am really impressed that InfoExchange is thirty five years old. I had no idea. That’s that’s incredible longevity in the in the not for profit sector, especially.
David Spriggs (02:33)
Mm.
Absolutely.
And and full credit to our our founder, Andrew Mahar, who came up with this vision of technology for social justice and so much of what we’re doing today, but was just so far ahead of his time, you know, 35 years ago, you know, that was that was pre mainstream internet and kind of, you know, these days everyone’s talking about platform solutions and data and you know, technology as a solution to some of the social problems we’re trying to solve.
but back then it was really groundbreaking. So yeah, full credit to to Andrew for for developing that vision and starting the organization in those in those early days.
Linda McIver (03:23)
That’s really impressive.
it’s it it’s kind of almost obvious now, but it wouldn’t have been then at all. That’s really cool. so you’ve talked about having an IT degree, but what else did you have to learn to do your work? Was there anything missing from your formal education?
David Spriggs (03:45)
I I think a ton. And I’ve done yes, I’ve done an IT degree. I’ve I’ve also done a certificate in theology. And that’s actually been that’s actually been an incredible complement to for the sort of work that that we do. I’ve been fortunate I got a scholarship to do a creating shared value course at at Harvard and that was all around kind of working in partnerships. I’m on a few other not for profit boards, so I’ve done things like the Australian Institute of Company Directors course.
Linda McIver (03:53)
Wow.
David Spriggs (04:14)
and last year I finished an amazing program called the Williamson Community Leadership Program that’s run by Leadership Victoria. So I’d kind of count all of those as kind of parts of formal education and and all of those have been amazing. but you’re right, there’s just so much that the formal education doesn’t teach you and that you need to learn on the ground. I think I think for me, a huge part of that is is how you work in partnership with others.
And so often people kind of talk about partnerships and partnerships are critical to our work in InfoExchange. We work closely, obviously with other not-for-profits, but we work closely with government, we work closely with technology providers, with corporates, with universities. and kind of the skills to do that I don’t think, you know, really get taught anywhere. I before joining InfoExchange, I was working in the tech sector and I was kind of working in the partnership space.
And in technology in the sector, we often talk about kind of ecosystems and organizations working together. and it’s what I’ve been trying to do at InfoExchange for the last 17 years now is to encourage more collaboration and and working together. But so much of that is just, you know, the soft skills of you know, how do you get people to talk to each other and how do you get people to play nice together and how do you get people to understand other people’s perspectives. So I I think that’s yeah, that’s
one huge piece which is really just for me anyway, it’s been a learning by doing rather than and kind of realizing the im the importance of it. So yeah, I think that’s that’s one of the really big things I’ve had to learn. Okay.
Linda McIver (05:47)
I have
I have so many strong feelings about that. first of all, the term soft skills drives me mad because my my mantra these days is tech is easy, people are hard. Like that’s the tech is tech is in theory at least deterministic. You know, you get put in the same input, you get the same output, but people that people don’t work that way. And we have all of these people in in educational institutions who say, you know, we we have group projects and so we teach people to work in groups.
David Spriggs (05:52)
Yeah.
Absolutely.
Mm-hmm.
Linda McIver (06:19)
Having group projects is not the same as teaching people to work in groups. You can teach people to work in groups. Those are absolutely teachable skills like any other. But we don’t do it. We just go go work in a group, that’ll teach you. That’s
David Spriggs (06:31)
Exactly. You’re you’re you’re exactly right. And it is and it is just so critical for our work in the not for profit sector. Because if we if you talk about helping somebody in need, you know, more of most often they’re multifaceted issues that somebody’s dealing with. You know, yes, they might have a need for some emergency relief food, but they may be dealing with mental health issues, they may be dealing with housing issues, maybe dealing with family violence issues and and none of those things.
you know, you can solve as an individual or just or just one organisation. So it’s yeah, it’s absolutely it’s absolutely critical in our sector. but you’re you’re so right. The the tech the tech is easy or the tech can be easy. It’s the it’s the people that create the challenges in our work.
Linda McIver (07:15)
Yeah. Yeah. there one thing that you wish everybody knew about data, something that would just change everything if if people understood this?
David Spriggs (07:24)
I I think though it’s a kind it’s broad, but but how you can use data to really look at how do we solve some of our wicked social problems that we’re dealing with, that we’re dealing with as a community. often people gravitate towards more the sort of heartstring stories about, you know, what’s going on and they’re and they’re important. But but the but the use of data, because if you don’t have the data, how do you know the scale of the problem?
that you’re trying to that you’re trying to solve? How do you know what your intervention should maybe be? How do you know whether as a sector, you know, the problems are getting better or worse? and ultimately, you know, how do you know whether the intervention that your organization is working on is actually making a difference or not? And if you can’t, if you can’t understand data and you don’t have effective data, you know, none of none of those things and and maybe a couple of examples to kind of bring that to life. One is
Linda McIver (07:54)
Mm.
David Spriggs (08:21)
at InfoExchange we operate a platform called Ask Izzy and that helps people in need connect with services across the community. So they use they can use their mobile phone, it can pick up their location and they can say, I’m looking for food, or I’m looking for housing, or I’m looking for mental health support as an example. And yeah, and so it’s it’s an incredibly useful tool for somebody to be able to find the support in their area.
Linda McIver (08:40)
that’s amazing.
David Spriggs (08:46)
And an empowering tool because you can do it from your perspective. You can read about services, and then you make the choice whether you want to connect with that service or not. But probably something we didn’t anticipate when we launched Ask Izzy was the value of the anonymous data that comes out of the back end. So heartbreakingly, in the last 12 months, we’ve had over eight and a half million searches for help on the Ask Izzy platform.
Linda McIver (09:10)
god.
David Spriggs (09:12)
And as heartbreaking as that is, it actually provides a picture of what the level of service demand is across the community. And you can look at that by geography, you can look at that by the type of service that was in demand. You can see the trends as to what’s really trending upwards at the moment. Obviously, in cost of living crisis and the fuel crisis we’ve now got, it’s so much around emergency relief and and financial assistance. So so that’s that’s an example of data kind of being able to help, you know, understand the problem. another, yeah.
Linda McIver (09:40)
And is that just
just in Australia, that that eight and a half million yeah that eight and a half million
David Spriggs (09:43)
That yeah, that eight and a half million is just
is just in Australia in the last twelve months, which as I say, we say it’s great, people are aware of it and people are using it, but just yeah, just heartbreaking the scale. So that’s so that’s an example kind of where it helps us understand, you know, the scope of the problem and the service demand. but we also and how thing exactly and how things are changing. And and another for us is we provide client and case management solutions to the not for profit sector.
Linda McIver (09:53)
Mm-hmm.
And how things are changing as well.
David Spriggs (10:13)
there’s a bit over 6,000 organizations use that that platform. And so they’re using that to help manage their client intake and develop case plans. but but over time, that’s that can be an incredibly useful tool to help measure outcomes. And we do that in partnership with government. The Australian Institute of Health and Welfare is one of our partners in the homelessness area, for example. And you can go back and you can now look at over 10 years of data.
And through statistical linkage keys, you can see somebody’s journey in and out of homelessness. And so you can see the effectiveness of either your organization or the kind of homelessness programs as a whole and kind of and the outcomes that that are tracking for people that are experiencing homelessness or or have experienced homelessness. So, you know, that’s that’s an example of kind of where you can track, you know, the effectiveness of of the programs that that you’re delivering.
Linda McIver (10:41)
Wow.
David Spriggs (11:10)
but there there’s a couple of examples, but I just wish that people would take a much more holistic view of the of the potential for data to to help in these areas.
Linda McIver (11:20)
That’s I I love the focus on actually figuring out what works because it’s something that comes up again and again in my work when I’m delivering workshops to teachers or to schools and I say, you know, how many times have you had some new program implemented and it’s all very exciting and everyone’s really into it and then twelve months later you move on to a new program and no one actually implements the first one and everyone, everyone experiences that in education and I don’t think it’s confined
to education. It’s it’s a really broad problem. You know, even government programmes are often not evaluated. They’re released with a lot of fanfare and and shiny brochures and stuff and then they’ve done their job buying votes and they move on.
David Spriggs (12:05)
Yeah, yeah. That’s
and it and it takes and it takes a great amount of accountability for you know as an individual or an organization to actually look at those things and say, you know, yes, yes this worked or no this this didn’t work. you know, yeah. Yeah. So it takes yeah, it ta it takes courage to stand up and say when something when something hasn’t worked.
Linda McIver (12:20)
Yeah.
Let’s
It does. It does.
To say, you know, this thing that I did that I put so much effort into, it didn’t actually achieve anything. But then you can try something else or you can improve it or, you know, actually continue until you get impact. So that brings us to this the new question that I haven’t asked before, which is, are there things that data shows that you wish more people knew about?
David Spriggs (12:52)
Yeah, and and I think kind of bringing back to that example of ask Izzy that we were just talking about, I I think within the general public, people would be surprised to learn that there’s so many people suffering in our community and that there’s so many people experiencing hardship, you know, which is which is up to now around thirty to forty percent of our population as a as a country, and that growing kind of disparity between the between the haves and have nots. And you know, that’s
That’s that’s sometimes spoken about, but I don’t think people necessarily understand the depth of it. And I don’t think people necessarily understand the data points. And you know, when we talk about eight and a half million searches, can we boil that down into that was eight and a half million, you know, individual issues that people were having that they needed that they needed help with.
and I just yeah, often think that that’s not really well understood in the general public, just the the scale of of hardship that’s that’s being experienced across our communities at at the moment and and unfortunately looking like it’s on a an ever increasing trajectory.
Linda McIver (14:01)
Yeah. We spoke when we met about some data during COVID times that that you had that when the financial relief was increased by the government and then when it was decreased. Can you talk a little about that?
David Spriggs (14:11)
Mm.
Yeah, so it’s and it links very relevantly to a campaign the sector’s been leading and the Australian Council of Social Service in particular has been vocal on this, on kind of raising the rate of, you know, what’s called what’s called Job Seeker, but basically s support, financial support for people in our community doing it tough. so yeah, what we saw during COVID when those rates of Job Seeker were increased and there were programs like JobKeeper in place.
Guess what? The demand on Ask Izzy for things like emergency relief food dramatically fell because people were able to afford to to buy food to put on the table. And so they weren’t needing to access emergency relief food. and I think, you know, that provides us a compelling set of data if if you ever needed one as to as to why kind of increasing that level of financial support.
is not just a good thing to do from a social perspective, but actually demonstrably, you know, reduces then the demand for emergency relief and other sort of not for profit and and government services that that people need to access.
Linda McIver (15:27)
actually tangibly effective. And I like I like your comment, if you ever need it. Like yes, w I it’s it’s astonishing to me that we need to demonstrate that this is a good idea. Like I the
David Spriggs (15:34)
That’s right.
That’s right. I mean
it was kind of like a randomized control trial, you know, before, during and after. But yes.
Linda McIver (15:45)
yeah. Yeah.
yeah. so we have the data and we have the means we demonstrated that we have the means to solve the problem and we’re choosing not to do it and that’s that’s really confronting. what are the worst data mistakes you’ve seen?
David Spriggs (16:08)
So I think I think there’s a lot, but one which has obviously been in the news a lot recently is Robodebt and kind of and and I can I can imagine, you know, before this all went wrong and before the Royal Commission, you know, somebody was probably sitting there at their desk saying, Well, we have all of this data around support that’s being provided to the community.
Linda McIver (16:15)
Mm.
David Spriggs (16:30)
You know, how how can we make sure that that money is being spent fairly from a taxpayer perspective? And if people have been overpaid, what might we be able to do about it? but the way that was implemented through the use of data and automation and the hurt and the pain and the stress that that caused in community at at the acute end, I think, to people even taking their own lives, is just a is just an example of
you know, how not how not to use data and and automation without the right kind of safeguards and controls and thinking through how it’s going to be used, thinking through what the implications might be, thinking through the ramifications, you know, provide in the in that case of providing the level of support to people, monitoring exactly all of those all of those things. And that clearly was a program with data.
Linda McIver (17:13)
And also monitoring.
David Spriggs (17:23)
you know, front and center of of of what they were of what they were doing. Yeah.
Linda McIver (17:27)
And the the horrifying thing is we don’t seem to have learned from that. We’re doing the same with the NDIS. the disability support, they’re they’ve brought in an algorithm to determine people’s support needs and there’s no intervention, there’s no oversight, there’s no and then where is the accountability, where is the ability to solve a problem? Because there is there is no way to write a a a
a software system that is flawless, that’s not doesn’t exist. And particularly when you’re dealing with these I know, I’m preaching to the converted here, when you’re dealing with these complex social issues, you can’t reduce that to numbers and and precise calculations. That’s not the way it works. So you have to be able to step in and go, in this case, the system has got it wrong. And and they’ve explicitly made the decision not to do that.
David Spriggs (18:22)
Yeah.
Linda McIver (18:26)
And I it How? Why? I can’t it’s it’s bewildering to me.
David Spriggs (18:33)
I don’t know. It is. And I think I think NDIS is again kind of a good example around use of data just in the in the general public and the in the general community talking about NDIS right now. So it is a hot topic of conversation from you know, the financial impact of the NDIS. And yes, the costs are spiraling. And so, you know, yes, government should be looking to address that and what they can do about it. But you often see kind of points of data being
misused in that kind or not provided in a broader context. So, you know, they’re talking about NDIS providers who are, you know, ripping off the scheme. And, you know, I’m sure in a in a program of that scale, you know, of course you are going to see some some of those some of those kinds of behaviors. But but often the way that some of these, yeah, some of these are presented, they’re they’re not presented in the broader context. So whether it’s, you know, people who are seen to be ripping off the scheme as individuals or providers,
or you know, other issues that they’re trying to solve. It’s a massively complex scheme. And so to to try and have a soundbite of a little statistic which supports the the view that whoever’s putting it forward is trying to is trying to convey is often just oversimplistic and kind of misusing misusing some of those data points. Yeah.
Linda McIver (19:36)
Mm.
Well that’s that’s the next question, isn’t it? The about data being deliberately
misused. And and the they seem to be taking the data that some providers are routing the system and using it to reduce services to participants who are not, by and large, the people rorting the system. It and like w we’re not solving the problem. We’re just
David Spriggs (20:14)
Yeah.
Linda McIver (20:20)
making it worse in some sense in that, you know, the punish the participants for things they didn’t do. W again, where is the where is the logic? I don’t
David Spriggs (20:27)
Mm.
Okay. No, no, absolutely. And I think yeah, and as as we’ve said, I think, you know, the NDIS is so complex to try and boil it down to those, you know, individual stories and sound bytes is just, you know, it it often then becomes kind of misleading even with even with even with the best intent. and I guess and I guess that’s what I’d say about the misuse of data more generally is, you know, often and I’m sure I’m guilty of this as well, you know, you’ve you’ve you’ve got a view about something
And you’re looking for data to support it. And and that will and and that will blind you to all of the other data that that might be out there. And you’re looking for individual points of data that will that will support what it is that you’re that you’re trying to say. and even even without you know a degree of you know ill intent there, that’s that’s a trap that all of us can that all of us can fall into.
Linda McIver (21:03)
Mm. Yep.
Yes.
Yeah.
absolutely. And
it you know, confirmation bias is is almost a flaw of of human psychology as much as it is an issue with data. We we love it. It makes us it it’s really satisfying to find some data that that that, you know, confirms our our biases and shows us what we want it to show. and and the the abstract idea that data is
David Spriggs (21:35)
Absolutely.
Yeah.
Linda McIver (21:54)
unbiased and pure and you know, you can’t argue with the data. You absolutely can and you should at all at all you know at at every opportunity. If you haven’t tried to prove your ideas wrong, then you haven’t really looked at it properly.
David Spriggs (22:03)
Yeah.
Yeah, I couldn’t agree more. And that and that’s the richness of yeah, truly working with data is is using it as the basis to ask more questions and and un and understand more rather than just taking it as here’s a here’s a table of data. Yeah.
Linda McIver (22:26)
Yes. Yeah.
So what it f for the general public who doesn’t have your level of data skill, how do we spot things like that? You know, you said that the the little sound bites of data about the N DIS are being misused. What do we look for?
David Spriggs (22:43)
Yeah, and I and I think that’s increasingly more complex in this world that we’re now living in with, you know, this and misinformation flying at us flying at us all the time. and so it it used to be and it still is to some extent, you know, look for reliable, trusted sources. and fortunately we do still have reliable and trusted sources out there. We still have a you know a publicly funded media organization in Australia called the ABC. We have, you know, many other
Linda McIver (22:48)
Yeah.
David Spriggs (23:11)
journalists that do amazing investigative journalism. And so kind of we do have those trusted sources out there. And that doesn’t mean we shouldn’t ask questions about it and that we shouldn’t question what’s going on. But there is kind of that sort of reliable and trusted sources. for me, kind of, yeah, we’re never looking at any kind of stats in media or elsewhere. It’s always looking at what’s what’s the source of the data, kind of understanding where it might have come from.
You know, understanding, as you just mentioned before, that confirmation bias that this is this is probably somebody either either the journalist or more likely the story that they’re reporting on from that person’s perspective that they’re interviewing. And this is more than likely going to be data that’s going to be supporting their that’s going to be supporting their position or supporting the line that the that the story is taking. and that and then I love some of the
Linda McIver (23:56)
Ha ha ha.
David Spriggs (24:03)
you know, the amazing fact check organizations that we have that actually that actually go through some of the data points. and and it and and as those organizations often find, it’s not a not necessarily always the clear cut, you know, green or red, this was right or wrong. It’s often grey and somewhere and somewhere in the middle and and open to and open to interpretation.
Linda McIver (24:26)
Yes.
David Spriggs (24:26)
but if
but if anybody can help us solve for that problem, I think it’s one of the biggest challenges we’ve got at the moment with children and young people is to how we can how we can educate them on those sort of trusted and reliable sources. And even within that context, you know, asking the right asking the right questions. Just because you’ve seen it come through in your feed a hundred times doesn’t doesn’t make it true necessarily.
Linda McIver (24:44)
Yeah. Asking
Yeah. There’s a classic X K
C D cartoon that refers to that as citogenesis. So somebody says something and then somebody finds that and and cites it and so suddenly it’s confirmed and then you you know, everyone goes back to that one source. I remember when I first started the Australian Data Science Education Institute, I was doing a lot of talks and interviews and stuff and
And I found I was trying to find out how much data is produced every day on the internet. and I found a stat that was it was a really weird number. It was something like two point five quintillion bytes or something. Which we don’t we don’t talk about quintillion bytes. You know, it’s exabytes or petabytes or gigabytes. What what are quintillion bytes? And everyone was using this number and I tracked it down to one blog on it was on
David Spriggs (25:35)
No.
Linda McIver (25:45)
An IBM website, but it was just a blog and it said, imagine, for example, that we produced 2.5 quintillion bytes. That’s that was it. Like that was the that was the source. And sometime after that I found there’s actually a research discipline called forensic what is it? it’s it’s like research archaeology or something. It’s like actually digging down and trying to find the source of some of these things that we believe with such passionate intensity.
David Spriggs (25:52)
Yeah.
Linda McIver (26:16)
It’s
David Spriggs (26:17)
y and you’d love to be able to visualize what the size of that number really means, other than the number of zeros that sit that sit on the end of it for the data we’re producing.
Linda McIver (26:23)
Yes. Yes. Definitely. I mean
it doesn’t matter whether you’re talking exabytes or quintillions of bytes, no one has any real tangible sense of what that means. It’s it’s just it’s just a number. It’s like talking about billions of dollars. No one no one has a concept of what a billion really is. It makes no sense. so
David Spriggs (26:42)
Listen.
Linda McIver (26:47)
We’ve talked about the first question you ask when you look at stats in the media. What is the first question you ask when you look at graphs in the media?
David Spriggs (26:52)
Mm.
Yeah, I I think I think quite similar kind of what’s the what what’s the source of the data? Where’s it where’s it coming from? You know, how how relevant is it to the to the story that they’re that they’re putting forward? all of those all of those sorts of issues around, you know, confirmation bias and and the rest of it. and often, of course, it’s how the data’s presented when it’s put into a chart as well versus what the raw data might have looked like. So, you know.
We’ve we’ve all done this over time is, you know, you change the scale of the graph on the on the y axis as a as a very basic point to make it look like there’s been a bigger increase than it might be if you actually understand what the raw numbers underneath are are telling you. Yeah.
Linda McIver (27:38)
Yeah.
Yeah, that’s a classic. And I I’m always a amazed when I do that in a teacher workshop. The teachers who who work with data a lot are looking at it going, wow, that’s terrible It we don’t think about it. And it’s it’s one of those things once you start working with it you c you can’t unsee it and so you start looking for it everywhere. But but until you’re really working with it and thinking about it as a as a matter of course, then you you don’t look for it and you’re easily fooled by a graph that you know, where there’s
David Spriggs (27:40)
Okay.
Linda McIver (28:08)
A really big peak. You think, wow, that’s a big change. Then you look, it’s like point zero zero zero one. Maybe it’s not so big. that’s one of the reasons I do what I do, right? To try to make sure that kids learn that and and build that into what they do. Yeah, it’s tricky. this has been great. I I really enjoyed this conversation. and that brings us to the last question, which is what excites you about data?
David Spriggs (28:16)
Absolutely. Okay.
Mm.
Yeah, I I think the the potential for not for profits and and their use of data and in the environment that we’re in today, which as you said, there is so much data out there and there’s so much kind of data infrastructure out there as well, more than there has ever been before, to support not for profits and and the sector with their work. So whether that’s, you know, better understanding what are what are the needs within the community, you know, measuring an organization’s impact. I mean, to me that’s incredibly exciting.
Linda McIver (28:46)
Mm.
David Spriggs (29:05)
And what makes me the most excited is we we do an annual survey of the not for profit sector on the use of technology. And in our last survey, November last year, the number one priority for leaders came out as the use of data for evidence-based decision making in their organizations. and and it’s almost come from nowhere. If you look at previous years, it had always been around the priorities, all around well, we want to improve our fundraising or we want to improve our websites and those sort of things that.
Linda McIver (29:23)
that’s awesome.
Mm.
David Spriggs (29:34)
you know, are obviously important for not for profits and charities that are that are fundraising. But to actually see that kind of suddenly leap to the top, I was incredibly excited about because that shows a real kind of shift in a real shift in attitude and and motivation within the sector. and I think it kind of it implies as well that people are now feeling that that’s possible. You can actually have that aspiration and you can do something about it. So so I find that incredibly exciting. the other in our current environment
You know, we’ve we’ve gone, you know, maybe half an hour in this podcast and we haven’t even mentioned the words artificial intelligence. and so kind of and so to me that is that is exciting. And yes, there are a number of challenges, and people need to be aware of all of the risks and limitations of AI. but for an organization that’s actually done the work on data foundations, which is to me kind of a prerequisite to really make effective use of AI, then the use of AI
Linda McIver (30:10)
Ha ha.
David Spriggs (30:32)
in in helping kind of bring insights out of that data for an organization. I I think is going to be transformational for our sector over the longer term. you know, give given that yes, you need guardrails in place and there are risks and challenges, but ult ultimately I’m an optimist for where for where we can go with some of that. And even even the use of AI as it’s evolving in in helping with cleaning up some of the data and and helping with coding and and those sorts of tasks. So
I’m hoping that’s gonna be an enabler for the sector in terms of making better use of of the data that they’re holding.
Linda McIver (31:07)
Can you talk a little bit more about what you mean by data foundations? You you said you you’ve got to get the foundations right and I completely agree, but many of our listeners won’t won’t know what that means.
David Spriggs (31:15)
Yeah. Yeah.
Yeah. No, so I think there’s a perception, not just for not for profits across all organizations, that AI is going to come in and it’s going to be able to solve all of your problems. And because you can just ask questions in a nice natural language way, it will give you the correct answers. Whereas if you think about it from the practicalities of if you’re running a homelessness service, for example.
You actually need to have your data in order. So you need to be able to understand, you know, who your clients are, what their needs are, you know, what are the outcomes that you’re looking to that you’re looking to measure. And you need to have that information kind of structured appropriately in a system so that you can then, you know, use that data to provide insights, you know, whether it’s whether it’s using AI or not using AI. so that’s what we talk about in in having data foundations actually having yeah, those individual elements.
data is important to your organization, kind of having it having it well organized and and having it accessible.
Linda McIver (32:17)
Think that’s something that might be, you know, if I were to turn the tables and ask the questions of myself, that might be my one thing that I wish people understood about data. Well, actually, I probably have I couldn’t limit it to one. but but that idea that, you know, once you have data, you can just use it to find all kinds of stuff out really misses the the foundations, as you say, that the idea that you have to have it structured and organized and well maintained, and that you can’t just kind of
David Spriggs (32:30)
Yeah.
Linda McIver (32:48)
have data from a whole lot of sources and and throw it at an AI and go do the thing. I remember some years ago I was working at CSIRO and I was talking with scientists about their data use and I was talking with some people who were designing new solar cells. and I was really excited about the idea that, you know, they they could compare the the performance of the new solar cells to the old solar cells. They said we can’t do that because we haven’t
calibrated the machine and we don’t store the data the same way and I was just like
But why? We’re not taught to do that. People don’t have those skills and they’re not obvious. How to how to structure and and organize your data is is it’s another skill that you can teach. But we don’t very often and and it’s it’s really tricky. So you bring in a data scientist once you have the data. That’s too late.
David Spriggs (33:31)
Yeah.
Yes, absolutely. And and it’s challenging for for not for profits who are in resource constrained environments. And so to actually spend the time to do that properly, you know, is a is a significant investment. But you know, from my perspective anyway, something that organizations, you know, can’t afford to ignore anymore.
Linda McIver (33:52)
Mm.
Yeah. Yeah. I love that that that people are suddenly thinking about that. That that the leaders of organizations are suddenly going, we have to get evidence and you know, we have to really evaluate things properly and we have to look at our data. I I I love that. That’s I wonder if
David Spriggs (34:20)
Yeah. And and even more
so, using it for decision making, which ultimately is what you hope all data can can help inform.
Linda McIver (34:29)
Yes, more evidence based decision making would be great. It’s distressingly rare. Thank you so much. This has been a wonderful conversation.
David Spriggs (34:39)
thank you so much for having me. And I think just a a quick little shout out as well, if there’s any not for profits that are that are listening in, one of the things we run at InfoExchange is a data catalyst network. it’s free to join and it’s for organizations who are passionate about making better use of data in their organization. So if you’re keen to learn more about that, just just have a look at the InfoExchange website and you’ll find the you’ll find a link to that. but thank you so much for for having me today. What a wonderful conversation. Yeah, thank you.
Linda McIver (35:06)
It’s
been fabulous. And I second your endorsement of the Data Catalyst Network. I’m in there and it’s great. There are some really good conversations. So highly recommend you jump in and it’ll really help you level up your organization’s data data use, I suppose. Thanks, David. This has been fabulous.
David Spriggs (35:23)
Fantastic.
Thanks so
Linda McIver (35:26)
been listening to Make Me Data Literate, a podcast from the Australian Data Science Education Institute. Check out the rest of our work to build critical thinking, data literacy, and AI literacy at
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