By using data and behavioural insights to design effective nudges, organisations and governments can promote positive social outcomes and improve people’s lives. Learn how the BUSY Group, one of Australia’s largest for-purpose employment, education and training organisations is harnessing the power of data insights to provide accessible and relevant opportunities to the people and communities they work with. Join us as we discuss the influence behavioural insights can have when implemented ethically and transparently and the potential it unlocks when especially when working with cohorts facing multiple barriers.
Rhetta Chappell (host): Hi, and welcome to Show Me the Data, a podcast where we discuss evidence based decision making and the ways in which our lives interact with and create data. I’m Rhetta. Your host for today and I’m a Data Scientist at Griffith University. Show Me the Data acknowledges the Jagera peoples who are the traditional custodians of the land on which we are recording today. And we pay respect to the elder’s past, present and emerging.
Hello, hello, and welcome to another episode of Show Me the Data, today in studio we have a very special guest and RIDL collaborator, Paul Miles. Paul Miles is the managing director for one of Australia largest for-purpose education, training and employment services organisations called the BUSY group. Paul is a passionate thought leader and change maker, and is a data and behavioural insights junky, so much so, he even has his own podcast on the topic called Budge, with his friend and co-host, Dr. Darren Coppin, which you should definitely check out and I am going to link in the show notes. I hope you find this conversation as interesting as I did. Let’s get started.
Hi Paul, thank you for joining me today.
Paul Miles: Pleasure to be here.
Rhetta: I thought we could just start off by well, if you could just briefly explain what the BUSY group is and what you guys do and kind of where you’re headed as an organisation.
Paul: Yes, so the BUSY group is an organisation that wants to make a difference through education, training and employment. We’re originally a small, local not for profit on the Gold Coast back in the 70s. BUSY stands for Backing Unemployed Southport/Surfers Youth, and over the years we’ve grown now to we’ve got about 103 offices and sites and schools around Australia, where we deliver a whole range of education, apprenticeship programmes, training organisations. We have schools that just basically help people move forward in their lives, change their lives by engaging with education, training, employment.
Rhetta: Yeah, perfect and I love that you kind of take that holistic approach, having been a collaborator with you guys a little bit in some aspects, I understand that you really do want to understand the communities that these people are coming from, and really help them in a meaningful and lasting way. And I was wondering if you could provide me with some examples of how BUSY works with data, maybe already, or maybe ways that you’re kind of looking to start moving into the future? And how they kind of, how you’re using those data and insights to inform your programme delivery and impact.
Paul: Yeah, I mean, obviously, there’s the work we do with Griffith University, which I’ll probably expand on in a minute. But the bit that comes straight to mind is on the apprenticeship side, so BUSY, has been signing up apprentices on behalf of the federal state government, here in Queensland, in Western Australia for, you know, 25-30 years. So, we’re the people that make sure there’s legal, that you’re complying, and they get all the money that you can get from the various funding authorities.
So, we took about 350,000 apprentices’ information, and we looked at what they did, on the basis of training contracts, which is the legal side of it, and we try to work out the biggest issue in apprenticeships. Which is the fact of non completion, you know, we see the same thing, you know, in higher education, further education. But in apprenticeships, only about half the people that start an apprenticeship will actually finish. And this is a huge industry for the sector, is a huge industry for government, because, you know, we’re putting so much money into, into both, you know, the two policy agendas, which are, you know, developing young people have dealt with developing specific cohorts of people into employment. But also, of course, there’s the skill shortage agenda, which is a huge issue now.
So, we, we took all that data, and we just wanted to see if there’s any correlation between the people, that complete and the people that don’t complete, through the information. And of course, it sounds very obvious what we came up with, which I will tell you in a minute. But when we point to non completion of apprenticeships, we actually always point to things like, you know, I hate my boss, wages, wages, wages, wages, it’s always about, you know, how much we’re getting paid. The training organisation, these sort of things, we point to all these different things. But what we found through this very specific data was the fact that it’s as simple as how far someone lives from their place of employment, you know the distance from their employer has such a profound impact on whether or not someone completes an apprenticeship. And of course, what you can then do with that information is, is, you know, we have mentoring support for our apprentices. And you know, we’ll probably come on to behavioural science side of this later on. But with that information, you can then say, right, what are the interventions I need to help somebody ensure they can stay? It’s easy for them to get to work? Or, you know, can they you know, work from home in some circumstances?
Rhetta: Yeah, I love that about data analysis, you sometimes find these hidden gems that are sometimes so obvious, you’re like, oh, my goodness, why did I even think of this? If it’s just too hard for me to get there? I’m probably not going to go there. And yeah, kind of removing all of those kinds of points of friction within the system, which kind of brings me to the next thing I wanted to talk to you about. And maybe we can use that what you just said as an example, which is kind of using data to understand behavioural patterns and kind of incentivize positive behaviour, or the behaviour that you’re wanting to elicit, is kind of the bread and butter of this kind of behavioural economics and science. So, is there any kind of practical examples of how you guys are implementing these sort of behavioural science nudges or other kinds of techniques in terms of trying to get what you want out of these people? Or like how? What are you guys doing about that?
Paul: Yeah, look, this has become a huge passion of mine and it is not something we’ve done some amazing projects, but I think there’s so much more that we can do. And I think you know, if you look at what I said about apprenticeships, and you look at our school students. Our schools are all designed for the kids who are, I think disengaged or at risk of disengaging. So again, you have that issue around will actually finish their education? Will they come to school every day? And then the same thing to all of our employment programmes, we look at the long term unemployed, so we get people into a job. And then can we actually keep them in that job? You know, for the long term. So, we’re always dealing with this issue of completions, sort of retention of people in these cohorts, I think there’s some amazing things can be done with behavioural sciences around nudges, which are predominant around that communications piece. When we communicate, what’s the language we communicate with? How often do we communicate? Prepping the employer, prepping the apprentice before, or the job seeker, before they actually go into employment around the expectations, around the behaviour of other people towards them. And you know I have my own podcast, as you know, Budge, where we talk about this issue where a young man who, you know, we are talk about in groups, a young man who would go downstairs ready for a job interview, you know, he’s in a family, which is has generation unemployment. The father will laugh at him and take the mick out of him, he’ll go down in his new suit all ready to go off to an to an interview, and the father will laugh at him. You take that same situation where the dad’s down the pub, a guy walks in, and he’s all set in his suit to go to his interview, the father won’t take the mick out of him in that sense. And a lot of this has to do with that sort of behaviour, what we need to do is actually prepare that job seeker, that young man for what’s going to happen to him from his in-groups, and sort of the behaviour of all those people around him, and he has to be prepared for that.
So, it’s both in the preparedness of job seekers, but then also those interventions along the way, as once they’re actually into the placement. But what we have done though, is we’ve actually done a massive amount of work around what’s called Stages of Change, Transtheoretical Stages of Change, which is a piece of work that came out of Rhodes University, Rhode Island University in the US, and again, it was with a good friend of mine, Darren Coppin, who will have this Budge podcast with, he actually had a company called Esher House, where he applied this Rhode Island University Transtheoretical Stages of Change concept, he took that from basically people, you know, assessing their willingness to give up smoking, and he applied it to long term unemployed. So what if what he’s able to do is determine whether or not people who were long term unemployed were they were in terms of stages of change, in wanting to work and willing to work. And in fact, there’s four stages of change, but he actually added a fifth one, called an authentic actor, which is actually determining if somebody is genuine about wanting to work. So, by taking his behavioural science around stages of change, what he was actually able to do is determining what interventions there should be for long term unemployed people. And you know, what classically happens you know, that there’s only a certain amount of funding providers like ourselves, they’ll take a group of unemployed people, put them in a room, provide them all with the same interventions to get them into work. When in fact, you know, based on the stages of change, you can be far more clear and precise around what is that intervention that person needs, because you might have somebody who’s, you know, raring to go, wants to get a job. We don’t need to do a lot of work on, let’s just get them into the interviews, preparing for the interviews, we might have another person, the other round, who has such trauma, from a whole range of things, whether it be addiction or abuse or domestic violence, we have to tackle those issues first, you know, before we try and get them into, you know, this is how you get a job. And, of course, then those people in the middle, which are just unauthentic, and just, you know, coming along, so they have to enter compliance regulations of the unemployment. So, we’ve been using that, you know, and that programme, it’s actually the most successful programme in the world when it comes to retaining unemployed people. So that’s been our biggest our biggest area. And then the other side is actually, you know, Darren and I sat down one day said, “Look, how can we apply this to my retention issues and apprenticeships?” We were quite honestly, we were we were drinking and in my unit in Surfers, looking out over Surfers, that thought bubble popped into our heads, which was, you know, can you apply stages of change to apprentices authenticity of wanting an apprenticeship and willing to sustain an apprenticeship? And the answer is, yes, quite frankly. So, we then started applying that to apprentices pre apprenticeship to determine is this person genuine about an apprenticeship? And are they likely to last in that apprenticeship? And again, we’ve seen, you know, we’re talking small numbers here, but we you know, about 5% increase, but that’s profound. When you talk about going from 50 to 55 it has a huge impact on the retention and the money, then that gets saved, and also the resources that need to go into individuals to be far more targeted around the mentoring, the support, or even, should this person even be doing an apprenticeship? Are they actually better off, you know, just getting a job until they figure out what their life should be? Or are they better off going back to college or do something different? And of course, it then identifies a whole range of other areas, interestingly you talk to everyone about those insights, that nugget that we pick up, the nugget that Esher House has picked up by working with us, was the fact that one of the major predictors about somebody not completing apprenticeship was how often they change their phone number. So, if somebody changed their phone number twice, that’s a massive predictor of somebody not finishing an apprenticeship, because it’s obviously an indicator that something’s going on and their liability, absolutely all about stability. And so, you know, those are the sort of things you miss and what you can achieve through behavioural science, but there is also looking at that data that underlies it.
Rhetta: Yeah, yeah. That’s so that’s so fascinating. Just out of curiosity, I’m just curious, so, when you’re kind of implementing these sorts of nudges, and maybe if this isn’t something you’ve done, but maybe with your talks with Darren, you’d understand like, do you have to be transparent about your what you’re doing? Like, can you use nudges and people not know, or do you have to explicitly explain?
Paul: Yeah, that’s, that gets into it. Funny enough, we got a podcast coming up on this, it gets in a whole new world of the ethics of behavioural science, you know, and this has been in the media a lot recently, because of the use of the New South Wales Government, around using nudges of course to encourage people to get their COVID vaccine. So we are very transparent about what we’re doing and explaining people to people what we’re doing. I think you have to be you know, that’s the ethics of this, we have to be very transparent.
Rhetta: That’s great Paul, one thing I’d like to ask you are what are the biggest data gaps in your field? So you’re talking about, like, kind of working in these training, education and employment services sector? Do you feel like there’s any data that you would love to have access to? Or do you feel as though kind of, maybe there’s too much data and you just can’t make sense of it? What are your feelings around that?
Paul: I think I think it’s more the latter, the gap is there’s so much data that we’ve talked about this earlier on. I’ve spent 17 years of my life being in a Welshman, trying to say, “da-ta” and I previously said “day-ta”, and as a Canadian, no going “da-ta”, “day-ta” and I don’t know which one is anymore?
Rhetta: I change way too much too, I’m so inconsistent.
Paul: But, yeah, I think the gap is the fact that there is so much information, you know, but I think the gap in my sector is that employment a skills gap, which is perennial problem from a policy perspective. You often have things where, you know, a department will have employment and education for a while, but not skills, but then they’ll pick up skills, but not education, or, you know, an employment skills are separate. And it seems to me, there’d be the similar sort of thing with the data, we have this amazing data around local communities, you know, who are the long term unemployed? You know, what cohorts they come from? you know, what is the socio demographic issues there? And then, of course, you have all the other data, which are the skill shortages, you know, who are the type of employees there? And I think the gap is actually bringing that together and I think historically, from a policy perspective, we tended to work at those in isolation. So, the opportunity, of course, is if you can take this, and this is something of course were trying to do with Griffith University. If you could take those cohorts and understand who those cohorts are and if they had a local community and really understand what are the skills gap? who the employers? Also, what’s the future? Of course, you know, because, you know…
Rhetta: Industry trends.
Paul: Literally, you know and how many of these can we get into cybersecurity, those sorts of things. If you could bring those together, that’s where the gap is, but that’s all where the opportunity isn’t. And I think a lot of the issue in my sector, particularly, is this difference around the fact that government is very, very good at sort of collecting the data, but so much of the service delivery is done by external private providers. So the other gap they’ve got is how do you take the government data develops, but then outsource it to people like us to deliver the services? So how do you bring those two together so we’re actually utilising their data? They make a lot of it available, but I don’t think there’s necessarily a really proactive approach from either side, to bring that data together to put into practical solutions for local communities.
Rhetta: Yeah, we hear that a lot when we go out and work with different partners and clients, there’s that kind of like that insight piece. It’s like, okay, cool, I know what’s happening, but what do I do about this? So what like, how can I fix this? Or how can I make an action based on this and how do I evaluate my action afterwards to see if it was actually effective.
Paul: Sorry but I’m just gonna jump at the other side of that, of course, is the execution piece from for an employer. So as an employer, you know, we often do know what we need to do. Executing strategy is not as simple as you know, I think government understands it to be, you know. We might identify an issue, but actually putting that to ground level is far more challenging. And that doesn’t just apply to my sector, it actually applies to any business, any business plan that ever comes up, everyone can write a business plan, execution is the other challenge. And I think executing with frontline staff, we’re probably very overwhelmed dealing with long term unemployed people, dealing with apprentices, dealing with, you know, people with disability and people who have massive, so you know, social issues. You know, applying that and executing that local level, that is, you know, that’s the other challenge, I think.
Rhetta: And that’s one thing that I think that the BUSY group is really known for doing really well. And one of the things that we were kind of looking at when we had that collaboration with you around using the data to better understand the communities that these long term unemployed people are coming from, was kind of matching, kind of trying to understand the kind of complexities within their own lives and that lived experience and then match that and kind of do some clustering around “Okay, well, this community is like this community, BUSY is doing something really awesome here and that’s working”, what other communities have the same kind of demographic makeup, and could we potentially do something the same in those areas and kind of looking to do that? And like you said, the sky’s the limit, but it’s about what’s actually practical and what can actually make sense?
Paul: Yeah, absolutely. And there is a real opportunity there. You know, government tends to outsource the sorts of things that aren’t, you know, original bases around Australia, and that is absolutely one of the things we look at. You know, is there something in Cairns that applies in Broome or applies in Fremantle, you know, they’re nowhere near each other, but are there related, you know, industry skills and social issues that make strategy similar.
Rhetta: Yeah, yeah, no, that’s great. And I think to kind of bring this to an end, I’d like to ask you our closing question, which is what we ask everybody. And it’s if you could have access to any data set in the world, and we’re kind of putting morals, practicality, ethics, anything business sense aside? What data would you like to have a bit of a play around with and gain instant insights from and why?
Paul: I should have put a lot more thought into this. Car park in Griffith University data, that’s what I would love. I once worked here about 20 years ago, my first day couldn’t park, I didn’t realise you needed coins. And I’ve come back sort of 15-20 years later now didn’t realise you need an app. So, I was late on my first day, and I was late today for this podcast. So, I’d like all the data how much that outsource company makes that I shout out down that intercom thing on trying to get into a car park. No, I think I think for me, it’d be like kidney disease, I have chronic kidney disease, I’m looking at dialysis and transplant down the line. I would love to come up with a solution to avoid that because you know, there are people who have had, you know, kidney disease declining and sort of recovered. I’d love to understand every intervention, every piece of data around the world that’s ever been done into that, to bring us all back. And you know, and that that would actually then have also profound impacts. You know, kidney disease actually is a major thing and anyone that’s listening, my message to everyone is go get them checked. You can get to 10% function without even having any symptoms. But it is something that becoming an increasing problem, you know, particularly as we live, less, less healthy lifestyles. So, I think I’d love that access to all the data in the world on that and to see what can we do to avoid? You know, we have some amazing medical professionals, but you know, that when you bring the data together, we’ll get the insights, we’ll see the things that medical professionals working in isolation can’t necessarily see themselves.
Rhetta: Yeah, perfect. That’s a beautiful and very heartfelt answer. So, thank you for sharing that with us and we’ll also let the car parking authorities know.
Paul: I’ll probably be locked in now, I won’t be able to leave Griffith. Clamped.
Rhetta: Well, thank you, Paul. It’s been an absolute joy, speaking with you, I’d continue to ask lots of questions, but we’ll bring you here to an answer. Thank you.
Paul: Thanks so much for having me. I really appreciate it.
Rhetta: To listen to more episodes of show me the data, head to your favourite podcast provider, or visit our website, ridl.com.au and look for the podcast. We hope that by sharing these conversations about data and evidence-based decision making, we can help to inform a more inclusive, ethical and forward thinking future. Making data matter is what we’re all about. And we’d love to hear why data matters to you. To get in touch. You can tweet us @G_RIDL. Send us an email or if you prefer, just send us a letter by carrier pigeon. Thank you for listening. And that’s it till next time, take care and stay safe.