Alter Everything Podcast

MaddieJ · ‎10-26-2020

What is the data landscape at a food bank? How about an air medical organization servicing the Australian outback? We sat down with Foodbank Australia and Royal Flying Doctors Service and learned why data is critical to their work, and how Alteryx helps take their data analysis to the next level.

Both of these non-profits participated in an Alteryx for Good data challenge in March 2020, where Australian university students used Alteryx to provide analytic insights to organizations. To hear the student journeys, check out episode 59: Reporting from Australia: an Alteryx for Good Data Challenge Adventure

Panelists

Maddie Johannsen - @MaddieJ, LinkedIn, Twitter
Pritish Sharma - LinkedIn, Royal Flying Doctor Service Twitter
Sarah Pennell - LinkedIn, Foodbank Australia Twitter

Topics

Copy of LinkedIn resize OTP -4.png

Transcript

Episode Transcription

MADDIE: 00:02	Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Maddie Johannsen, and I'll be your host. Back in March, we hosted an Alteryx for Good Data Challenge, co-sponsored by our partner RXP. The data challenge was kicked off at Inspire Sydney, where students from Australian universities teamed up with Australian not-for-profits to provide analytic insights using Alteryx. Now, I'm sure to a lot of our listeners this sounds familiar, and it is because we did an episode earlier this year that featured firsthand accounts of the students learning Alteryx and working with those non-profits. And by the way, if you want to go back and listen to it, it's episode 59. But in this episode, we wanted to hear the non-profit perspective. And I had a chat with two of the organizations who participated in the data challenge. Foodbank Australia, represented by Sarah Pennell.
SARAH: 00:55	Yes. Hi, I'm Sarah Pennell. I'm a general manager at Foodbank Australia, which is the largest food relief organisation in Australia, and I'm responsible for research and all things statistics at the organisation.
MADDIE: 01:13	And Royal Flying Doctor Service represented by Pritish Sharma.
PRITISH: 01:17	Hi everyone. My name is Pritish Sharma, and I work as the head of data and analytics at the Royal Flying Doctor Service. I live and breathe data and work across the different divisions of the company, especially centred more around the research and the operational side of things.
MADDIE: 01:34	Let's get started. To kick things off, I want to give you a little bit more background on the non-profits because they're seriously cool. Let's start with Partish from Royal Flying Doctor Service or RFDS for short.
PRITISH: 01:52	The RFDS provides extensive primary health care services throughout Australia, including, although not limited to, primary care, nursing, and oral health clinics. The types of services differ in response to the configuration of other local health services in specific operating regions. We also operate a 24-hour, 7 days a week, aeromedical retrieval service supported by a 24/7 telehealth system to people who live, work, or travel in rural and remote regions of Australia. And if you look at that, we pretty much take care of the people in rural and very remote parts of Australia and take care of their health care needs and pretty much fill in the void, which is created in rural Australia.
MADDIE: 02:36	That's amazing. I'm so inspired just listening to that. We have a couple of services like that in the States, probably more than a couple, as I'm sure that everybody around the globe does as well. And I just think that those kinds of services are so important, but also really, really impressive too. The idea of sending doctors and nurses out into those rural areas to service those communities is such a cool, cool thing.
PRITISH: 03:04	And you'd be surprised that we're a 91-year-old organisation.
MADDIE: 03:08	Oh, really?
PRITISH: 03:10	Yeah. And the first flight took off way, way, way earlier where the founder of our company chartered an aircraft and then flew into the rural community to start servicing their needs and this is just phenomenal. And more than that it's very motivating to work for this organisation more so. You're working for a cause. And at the same time, you're making a very direct impact into people's lives.
MADDIE: 03:36	Similar to RFDS, Sarah at Foodbank Australia is also passionate about serving the community and enjoys it, even more, when she can put the data behind it.
SARAH: 03:45	Well, before Foodbank became involved in really delving into and finding out more about food insecurity in Australia very little was known. And we're now considered to be the go-to organisation to provide information and insights into the situation of food insecurity in Australia. So there really was a dearth of understanding. In fact, in Australia, there was a belief that food insecurity didn't exist. We would talk about people going hungry in Australia, and fellow Australians would look at us in shock and disbelief. So in the first instance, we actually had to pin down what the issue in Australia actually is and how many people are going without meals and suffering anxiety because they're finding it difficult to put food on the table for themselves and their families. So that was our first job was to simply help or educate Australia on the fact that there is an issue at all. And what we're doing now is really delving into it. Understanding it. Understanding how people become food insecure. What that condition is like for them. So what the lived experience is. And where they are and how we can help them and how we can address the issue. So we're really exploring every aspect of the issue.
MADDIE: 05:22	Yeah. That's so important. And I'm curious, what has been the most surprising thing for you when it comes to understanding the data that you've seen come in as you're working on this research and really trying to like you said, pin down the full picture of what's happening with food insecurity in Australia.
SARAH: 05:45	I think the most surprising thing is that food insecurity impacts a wide variety of people. If you had asked me before doing this work, "Who is food insecure in Australia?" I would have immediately said, "Oh, homeless people. Unemployed people. Maybe old people that live on their own and don't have resources or assistance." And that is all true but in fact the largest group of food-insecure people, the working poor. And I had no idea that there were people in Australia who have jobs. So there's someone in the household who has a job, but they still can't make ends meet. And their job is possibly casual or intermittent, part-time, or just simply lowly paid, and that means that they can't-- they can't care for their family. And they might be able to manage for some of the time or even most of the time, but all they need is one piece of bad luck, such as an illness in the family or the car finally giving up the ghost or something like very expensive utility bills in the winter when you're trying to heat your home. That can suddenly mean that food becomes a discretionary item. So eking out a very meagre pantry is how they get by. And that was a big surprise to me.
MADDIE: 07:24	Yeah. It's crazy how everything is so interconnected and as you said it's just fragile. And I think if you don't have that research and that data behind it then as you said it's hard to prove to your peers and it's hard to start having these conversations and start assisting in an impactful way, so.
SARAH: 07:47	Absolutely right. Absolutely right. And the data tells the story and that's helped us to get the attention of policymakers, politicians, and just the general public to understand the situation.
MADDIE: 08:03	Totally. Yeah. And I want to-- that's actually a good segue into another topic that I wanted to get into. Because we published another podcast episode where we followed the students who participated in that data challenge that I mentioned earlier. And just for our audience, each student team was paired with a non-profit. So the students from the Data FrChallenge that supported Foodbank delivered a project that helped identify and visualize food deserts. And I think obviously that's such a cool opportunity for students to learn Alteryx and analytics. It's a unique opportunity and a unique learning experience to really get your hands dirty and really practice in a tangible way. But also, it was a cool opportunity for the non-profits to really capitalize on having volunteers. So I'm curious, how did your teamwork with the students in order to, I guess, help them help you? And a follow-up question, what advice do you have for other non-profits for them to make the most of that volunteer help if it ever comes their way?
SARAH: 09:15	We briefed the students. So we provided them with a broad understanding of the issue and what it is we do on a day-to-day basis and what our challenges are and what we need to achieve. And then we provided them with a number of data sets. So, we have a lot of data. We actually collect information through our inventory system on what food we're getting in, what food we're sending out, who we're sending it to. The volumes and the nature of the food. We also do surveys with the charities that we provide the food too. So we have a lot of data. Our challenge is having the time and the resources to be able to make the most of that data. To actually analyse it and get insights out of it. So what we did was we shared that data with the students and told them that a challenge for us was food deserts, as you've already mentioned. And basically, what they are is places in Australia, where from one data set, we know there are food insecure people but from other data, we can work out that our food relief doesn't go there. And that's because there aren't charities in that area that help people in need and therefore, we're not supplying food to those charities and so there's-- there's no help in that area. And what we wanted to do was better understand where the food relief deserts are so that we can work with our charity network to deliver food to those areas. Or if not the charity network, then we need to find other ways to deliver food. It might be via local councils or schools or basically other existing networks in those communities. But what we wanted to do was, using our two data sets, discover where those deserts are. Be able to know which are the worst areas. So where there are the most people who don't have access to help. And then map that so that we can work on addressing that issue.
MADDIE: 11:34	I also asked Pritish about their experience working with the student participants in the data challenge. Here's what he said.
PRITISH: 11:40	And I was very thrilled when Alteryx and the partners reached out to us for a potential challenge. And just a bit of the background. So we've had this relationship with Alteryx for more than a couple of years now where we're using the product and immensely benefiting from the spatial analytics capabilities. And then when you guys reached out to us, I was extremely thrilled. And getting clearance from leadership was a cakewalk for us. Everyone really wanted us to explore the capabilities. And, yeah, so we started discussing the challenge and we immediately went to the whiteboard and discussion of, what is a key area where we really want someone to kind of blow a torch under the bonnet and see if there's anything we can do better? And I think around the same time early this year there was a big-- I think a drought wave across the country. And it was so severe that we haven't kind of experienced such a drought in years. And especially, there are a lot of farming communities out there. So then we started thinking that there's definitely a need for mental health services.
PRITISH: 12:57	And it's been quite well aggregated across that one in five Australians would require some intervention at some stage of their life. And then we anyways do service the mental health services. So then we started thinking about, how does drought impact the need for mental health services in the bush where there's hardly any coverage or any medical services provided? So then we started drafting the challenge, and that's where it all kick-started this wonderful journey. And I'm extremely pleased with the results we have. And yeah, we're actually discussing the results of the wonderful work the uni students have done. And another thing that really surprised me was that how people from uni who have never worked on or work with Alteryx in their lives could actually drill through numerous data sources, which runs into terabytes at times and are then now able to master the product and get out insights, which would have taken us months to get. And they all did it within two weeks or within weeks. Not two weeks. Sorry. But I think in a couple of months they had the entire product really. And it just shows that, A, how easy it is to work on the tool, how easy it is to master Alteryx and see the benefits are immediately accessible and you can start working on them.
MADDIE: 14:34	I agree. Yeah. I'm always constantly blown away by the ease of use and how quickly even I can learn things with Alteryx. And I think a lot of that is also due to our community where anybody can join and start learning. Start taking the interactive lessons and maybe even working towards a free certification. And I'll also give a quick shout out to our new ADAPT program as well where you can get a free license if you're affected by COVID. So if you lost your job or were furloughed or anything like that and you want to make a career shift or learn Alteryx, that license is available to them. And we'll be sure to link to these programs in the show notes as well, but one thing that you mentioned too was the results that the students provided and the data that they were working with. And you mentioned, there's so many data sources that you provided them with or gave them access too. And I'm curious if you can talk a little bit about just, in general, the data landscape that the organization deals with that RFDS works with all the time? Because different organizations are always going to have a different data story and they're always-- some people are going to have tons of data and some people aren't going to have that much. And so what does the landscape look like for you?
PRITISH: 15:47	Yeah. So it's immensely vast. And Australia is a continent in itself and it's just so massive. And with a population of around 25 million, it's pretty much we've got people everywhere. And then at times, there are communities of around 10 people in a very remote area. So, to start with, we always look at the latest results of the Australian Bureau of Statistics, which give us population demographics and pretty much how many people are living in a community and we get the geocoding done for pretty much all locations across the country. And then we map it to the existing health services. So be it a general practice nurse working in the community or a hospital or clinic or something. And then we try to join the two to then find out which areas don't have coverage, say within a driving distance of about 90 minutes. And you'd be surprised that there are a lot of such places. And once we've identified those, we then kind of go through each and every location, which is, as we call it within the Flying Doctors, as grey areas where there's no coverage. Then we started looking at, how many people are there, what's the demographic, and what were traditionally the core diagnosis or the diseases that they're suffering from.
PRITISH: 17:21	And then once we've identified those grey areas, we then start plotting which is the nearest airstrip. And we've got a fleet of around 80 aircrafts and most of our planes can just land on a dirt strip. So we look out and identify patches where our aircraft can safely land. At times and especially in the night, it's so dark. And then there's no weather system or you don't understand what's actually the condition of the airstrip. And people actually hold torches on the runway to guide our pilots to land safely there. So once we've identified those airstrips, we then start identifying that these places are easily accessible by air. Some places are accessible by road. And once we've done all that groundwork, we then start looking into our own data, which is running into years, where we say we identify the diseases or the conditions the patients suffer from. And then once we've identified, we then go into the planning session, where typically our planners work for about months and then they work very closely with the health networks within the region to then identify core areas of need and that's when we start flying in. So at times our doctors and nurses they fly into a region and then they stay there for about a couple of days and then they fly back or sometimes it's just a day in day out kind of a clinic. So that's pretty much the landscape of data that we work with.
MADDIE: 19:06	Okay. So essentially what he just said is that data really serves as a backbone for their planning, and strategy and ultimately analytics drives their decision-making.
PRITISH: 19:16	Yes. And a lot of data is-- we get it from external sources or our partners. Healthdirect, they give us a list of all medical services available across the country. We get a lot of other data from different primary health networks. And then you'd be surprised that a lot of data is intuition-based as well. People who've been in that community and serviced that for years. Maybe 30, 40, 50 years as well. They know the place in and out. And pretty much at times, the data could be pointing that there is a need but sometimes those people they know that there is another service available in that area on a Wednesday or a Thursday and therefore there's no need for us to go on those days. So sometimes there are those gaps in data, and that's where the experience of people working there, they kind of come in and plug that gap for us.
MADDIE: 20:15	Let's check back in with Sarah, who also gave insight about data at Foodbank and the people who are working with data in order to make decisions.
SARAH: 20:22	I am very happy to say we now actually have an analyst for the first time ever.
MADDIE: 20:28	That's amazing.
SARAH: 20:29	So data has always been my bag and IT guru also has a great appetite for data. So he and I have been kind of the carriers of the flame when it comes to data at Foodbank. But now in our current circumstances, we have taken on an analyst because with everything that's happening during COVID both with regard to what we need to do to support people but also the corporations and government who are assisting us so we have received a lot of support - funding support and so on - in order to do our job, we know that we need to be able to analyse and investigate what's been happening. We need to report back comprehensively. Those who are providing us with funds, etc., want to know exactly what's happening to that money and how-- and the impact that it's having. And so we knew we needed more help in order to be able to satisfy those needs and to achieve the right level of reporting. And the way we're looking at it at the moment with everything that's changed during COVID, both in terms of the need how we operate, what the government is doing in terms of support for the community and so on, we're seeing COVID as the ultimate experiment.
SARAH: 22:05	So we are able now to look at things that are being done in the community, both that we're doing and the government and others are doing and look at what impact they have had and we can-- we've got something that we can look at here that we would never of had without COVID. Now, I'm not saying I want-- I'm pleased that COVIDs come along, but gee never let a crisis go to waste. And there's all sorts of things that we can look at right now and better understand what impact the government and we and the general public can have on something like food insecurity. So from a data point of view, from an analysis point of view, it's actually extremely exciting times. And we believe that the world will not go back to the way it was before. So much has changed during COVID and we want to be able to nail that down, explain it, and retain the good stuff. Retain the improvements that we've been able to make, the insights that we've been able to gain and have a better-- have a better future rather than the same.
MADDIE: 23:26	I think then that's going to be crucial for us to continue to solve these problems because this isn't-- this is obviously a huge deal but there are more things that are going to keep happening, you know what I mean, so there's always going to be challenges. And the better camaraderie that we can build now I think is going to be for the better.
SARAH: 23:45	And there has been amazing innovation during this time. So we at Foodbank have changed our model and pivoted and responded to the new needs in some incredibly creative ways and we don't want to lose that. We want to pin that down, understand what happened, what it achieved, what the impact was, and how we can use those new experiences, new approaches post-COVID. So analysis helps you to achieve that.
MADDIE: 24:23	Let's check in with Pritish. Yeah. It sounds like you guys are getting really creative with everything. I would imagine as well since you're pulling data from all these different sources and as you said you live and breathe data in your role, does everybody at your organisation think as a data person? Are they all data thinkers? Do you guys have dedicated analysts? Or yeah, how do you kind of make sure that everybody on your team and everybody at your org is thinking analytically?
PRITISH: 24:55	Yeah. Data is a journey. And initially, it was all intuition-based, I think, many years ago. And then, Excel came in and we started creating different kinds of reports and people started using the data to make informed decisions. And then we started on the BI journey. We introduced tools, such as Alteryx, yourselves, and then that's where we started getting analytics around the data. We started understanding patterns and so on. So, yes, it is definitely a journey where initially from being an intuitive organisation, you're becoming more aware and take more informed decisions. And yes, to answer the second part of your question, we've got data analysts everywhere, in all the states and the territories in the country, and they kind of work with different teams, be it-- being a charity, we rely a lot on fundraising. So some analysts would be involved with the fundraising side of things, some would be looking more at the operational side of thing, and some would be more inclined towards the finance side of things.
PRITISH: 26:08	And certainly over the years, we've started absorbing more and more data. And it was data which was not available to us earlier. So we can now identify how many hours it takes us for a flight to reach a location. How much fuel do we consume on that flight? What's the crew on that flight? Is it a doctor or is it a nurse? How many patients were there on a flight? And what was the criticality, what was the severity, of the patient? And we can then kind if look through at a case-by-case basis or we can aggregate and summarise and see what are response times. How readily are we available to service our patients and our community. So all of this data was not available for us, and if you were to do it manually it used to take us months. But what we've done and achieved over the past couple of years is leveraging Alteryx we've been able to bring together all of this data which is in different systems. You'd be surprised. We've got about 100, 100-plus systems, and we've brought in data from all of these systems, aggregated it together, and brought in uniformity. And then we've started consuming this data. And it's just such an-- it's just brought our operations and the way we operate altogether a different level. [music]
MADDIE: 27:31	Thanks for tuning in to Alter Everything. For more on the programs and organisations heard on today's episode, check out or show notes at community.alteryx.com/podcast, where you can also chat with us by leaving a comment. We'll also have a link to a blog article by our data science journalist Susan Currie Sivek where she shares resources on how you can use your analytic skills to help organisations like Foodbank and RFDS. And you can join us on social media using the #AlterEverythingPodcast and be sure to subscribe on your favourite podcast listening app to make sure you don't miss any episodes. Catch you next time. [music] So before I hit stop recording, I did want to [laughter]-- I thought it'd be funny to ask you this at the end. But earlier, you said the car giving up the ghost? Did you say that [laughter]?
SARAH: 28:35	I did. Yes. [laughter] Is that not a saying--?
MADDIE: 28:38	I've never--
SARAH: 28:40	Is that not a saying you've heard before?
MADDIE: 28:42	First time, actually. [laughter] What does that mean?
SARAH: 28:47	If something breaks down or dies, it gives up the ghost.
MADDIE: 28:53	That is so funny. Yeah. I love that. [laughter] And I was like, "I better write that down, so I can ask her later at the end." [laughter] So cool.
SARAH: 29:06	You're lucky I didn't put in lots of other Australianisms. Because I have a lot of American colleagues in the Global FoodBanking Network and they're often pulling me up and going, "What was that you said?" [laughter]
MADDIE: 29:20	I know. There are so many that I heard when I was in Australia for Inspire, and I can't think of them off the top of my head. Maybe I'll put them in the-- maybe I'll list them in the show notes later.
SARAH: 29:30	I think that's a good idea, yeah. [laughter]
MADDIE: 29:33	Awesome.

MADDIE: 00:02 Welcome to Alter Everything, a podcast about data science and analytics culture. I'm Maddie Johannsen, and I'll be your host. Back in March, we hosted an Alteryx for Good Data Challenge, co-sponsored by our partner RXP. The data challenge was kicked off at Inspire Sydney, where students from Australian universities teamed up with Australian not-for-profits to provide analytic insights using Alteryx. Now, I'm sure to a lot of our listeners this sounds familiar, and it is because we did an episode earlier this year that featured firsthand accounts of the students learning Alteryx and working with those non-profits. And by the way, if you want to go back and listen to it, it's episode 59. But in this episode, we wanted to hear the non-profit perspective. And I had a chat with two of the organizations who participated in the data challenge. Foodbank Australia, represented by Sarah Pennell. SARAH: 00:55 Yes. Hi, I'm Sarah Pennell. I'm a general manager at Foodbank Australia, which is the largest food relief organisation in Australia, and I'm responsible for research and all things statistics at the organisation. MADDIE: 01:13 And Royal Flying Doctor Service represented by Pritish Sharma. PRITISH: 01:17 Hi everyone. My name is Pritish Sharma, and I work as the head of data and analytics at the Royal Flying Doctor Service. I live and breathe data and work across the different divisions of the company, especially centred more around the research and the operational side of things. MADDIE: 01:34 Let's get started. To kick things off, I want to give you a little bit more background on the non-profits because they're seriously cool. Let's start with Partish from Royal Flying Doctor Service or RFDS for short. PRITISH: 01:52 The RFDS provides extensive primary health care services throughout Australia, including, although not limited to, primary care, nursing, and oral health clinics. The types of services differ in response to the configuration of other local health services in specific operating regions. We also operate a 24-hour, 7 days a week, aeromedical retrieval service supported by a 24/7 telehealth system to people who live, work, or travel in rural and remote regions of Australia. And if you look at that, we pretty much take care of the people in rural and very remote parts of Australia and take care of their health care needs and pretty much fill in the void, which is created in rural Australia. MADDIE: 02:36 That's amazing. I'm so inspired just listening to that. We have a couple of services like that in the States, probably more than a couple, as I'm sure that everybody around the globe does as well. And I just think that those kinds of services are so important, but also really, really impressive too. The idea of sending doctors and nurses out into those rural areas to service those communities is such a cool, cool thing. PRITISH: 03:04 And you'd be surprised that we're a 91-year-old organisation. MADDIE: 03:08 Oh, really? PRITISH: 03:10 Yeah. And the first flight took off way, way, way earlier where the founder of our company chartered an aircraft and then flew into the rural community to start servicing their needs and this is just phenomenal. And more than that it's very motivating to work for this organisation more so. You're working for a cause. And at the same time, you're making a very direct impact into people's lives. MADDIE: 03:36 Similar to RFDS, Sarah at Foodbank Australia is also passionate about serving the community and enjoys it, even more, when she can put the data behind it. SARAH: 03:45 Well, before Foodbank became involved in really delving into and finding out more about food insecurity in Australia very little was known. And we're now considered to be the go-to organisation to provide information and insights into the situation of food insecurity in Australia. So there really was a dearth of understanding. In fact, in Australia, there was a belief that food insecurity didn't exist. We would talk about people going hungry in Australia, and fellow Australians would look at us in shock and disbelief. So in the first instance, we actually had to pin down what the issue in Australia actually is and how many people are going without meals and suffering anxiety because they're finding it difficult to put food on the table for themselves and their families. So that was our first job was to simply help or educate Australia on the fact that there is an issue at all. And what we're doing now is really delving into it. Understanding it. Understanding how people become food insecure. What that condition is like for them. So what the lived experience is. And where they are and how we can help them and how we can address the issue. So we're really exploring every aspect of the issue. MADDIE: 05:22 Yeah. That's so important. And I'm curious, what has been the most surprising thing for you when it comes to understanding the data that you've seen come in as you're working on this research and really trying to like you said, pin down the full picture of what's happening with food insecurity in Australia. SARAH: 05:45 I think the most surprising thing is that food insecurity impacts a wide variety of people. If you had asked me before doing this work, "Who is food insecure in Australia?" I would have immediately said, "Oh, homeless people. Unemployed people. Maybe old people that live on their own and don't have resources or assistance." And that is all true but in fact the largest group of food-insecure people, the working poor. And I had no idea that there were people in Australia who have jobs. So there's someone in the household who has a job, but they still can't make ends meet. And their job is possibly casual or intermittent, part-time, or just simply lowly paid, and that means that they can't-- they can't care for their family. And they might be able to manage for some of the time or even most of the time, but all they need is one piece of bad luck, such as an illness in the family or the car finally giving up the ghost or something like very expensive utility bills in the winter when you're trying to heat your home. That can suddenly mean that food becomes a discretionary item. So eking out a very meagre pantry is how they get by. And that was a big surprise to me. MADDIE: 07:24 Yeah. It's crazy how everything is so interconnected and as you said it's just fragile. And I think if you don't have that research and that data behind it then as you said it's hard to prove to your peers and it's hard to start having these conversations and start assisting in an impactful way, so. SARAH: 07:47 Absolutely right. Absolutely right. And the data tells the story and that's helped us to get the attention of policymakers, politicians, and just the general public to understand the situation. MADDIE: 08:03 Totally. Yeah. And I want to-- that's actually a good segue into another topic that I wanted to get into. Because we published another podcast episode where we followed the students who participated in that data challenge that I mentioned earlier. And just for our audience, each student team was paired with a non-profit. So the students from the Data FrChallenge that supported Foodbank delivered a project that helped identify and visualize food deserts. And I think obviously that's such a cool opportunity for students to learn Alteryx and analytics. It's a unique opportunity and a unique learning experience to really get your hands dirty and really practice in a tangible way. But also, it was a cool opportunity for the non-profits to really capitalize on having volunteers. So I'm curious, how did your teamwork with the students in order to, I guess, help them help you? And a follow-up question, what advice do you have for other non-profits for them to make the most of that volunteer help if it ever comes their way? SARAH: 09:15 We briefed the students. So we provided them with a broad understanding of the issue and what it is we do on a day-to-day basis and what our challenges are and what we need to achieve. And then we provided them with a number of data sets. So, we have a lot of data. We actually collect information through our inventory system on what food we're getting in, what food we're sending out, who we're sending it to. The volumes and the nature of the food. We also do surveys with the charities that we provide the food too. So we have a lot of data. Our challenge is having the time and the resources to be able to make the most of that data. To actually analyse it and get insights out of it. So what we did was we shared that data with the students and told them that a challenge for us was food deserts, as you've already mentioned. And basically, what they are is places in Australia, where from one data set, we know there are food insecure people but from other data, we can work out that our food relief doesn't go there. And that's because there aren't charities in that area that help people in need and therefore, we're not supplying food to those charities and so there's-- there's no help in that area. And what we wanted to do was better understand where the food relief deserts are so that we can work with our charity network to deliver food to those areas. Or if not the charity network, then we need to find other ways to deliver food. It might be via local councils or schools or basically other existing networks in those communities. But what we wanted to do was, using our two data sets, discover where those deserts are. Be able to know which are the worst areas. So where there are the most people who don't have access to help. And then map that so that we can work on addressing that issue. MADDIE: 11:34 I also asked Pritish about their experience working with the student participants in the data challenge. Here's what he said. PRITISH: 11:40 And I was very thrilled when Alteryx and the partners reached out to us for a potential challenge. And just a bit of the background. So we've had this relationship with Alteryx for more than a couple of years now where we're using the product and immensely benefiting from the spatial analytics capabilities. And then when you guys reached out to us, I was extremely thrilled. And getting clearance from leadership was a cakewalk for us. Everyone really wanted us to explore the capabilities. And, yeah, so we started discussing the challenge and we immediately went to the whiteboard and discussion of, what is a key area where we really want someone to kind of blow a torch under the bonnet and see if there's anything we can do better? And I think around the same time early this year there was a big-- I think a drought wave across the country. And it was so severe that we haven't kind of experienced such a drought in years. And especially, there are a lot of farming communities out there. So then we started thinking that there's definitely a need for mental health services. PRITISH: 12:57 And it's been quite well aggregated across that one in five Australians would require some intervention at some stage of their life. And then we anyways do service the mental health services. So then we started thinking about, how does drought impact the need for mental health services in the bush where there's hardly any coverage or any medical services provided? So then we started drafting the challenge, and that's where it all kick-started this wonderful journey. And I'm extremely pleased with the results we have. And yeah, we're actually discussing the results of the wonderful work the uni students have done. And another thing that really surprised me was that how people from uni who have never worked on or work with Alteryx in their lives could actually drill through numerous data sources, which runs into terabytes at times and are then now able to master the product and get out insights, which would have taken us months to get. And they all did it within two weeks or within weeks. Not two weeks. Sorry. But I think in a couple of months they had the entire product really. And it just shows that, A, how easy it is to work on the tool, how easy it is to master Alteryx and see the benefits are immediately accessible and you can start working on them. MADDIE: 14:34 I agree. Yeah. I'm always constantly blown away by the ease of use and how quickly even I can learn things with Alteryx. And I think a lot of that is also due to our community where anybody can join and start learning. Start taking the interactive lessons and maybe even working towards a free certification. And I'll also give a quick shout out to our new ADAPT program as well where you can get a free license if you're affected by COVID. So if you lost your job or were furloughed or anything like that and you want to make a career shift or learn Alteryx, that license is available to them. And we'll be sure to link to these programs in the show notes as well, but one thing that you mentioned too was the results that the students provided and the data that they were working with. And you mentioned, there's so many data sources that you provided them with or gave them access too. And I'm curious if you can talk a little bit about just, in general, the data landscape that the organization deals with that RFDS works with all the time? Because different organizations are always going to have a different data story and they're always-- some people are going to have tons of data and some people aren't going to have that much. And so what does the landscape look like for you? PRITISH: 15:47 Yeah. So it's immensely vast. And Australia is a continent in itself and it's just so massive. And with a population of around 25 million, it's pretty much we've got people everywhere. And then at times, there are communities of around 10 people in a very remote area. So, to start with, we always look at the latest results of the Australian Bureau of Statistics, which give us population demographics and pretty much how many people are living in a community and we get the geocoding done for pretty much all locations across the country. And then we map it to the existing health services. So be it a general practice nurse working in the community or a hospital or clinic or something. And then we try to join the two to then find out which areas don't have coverage, say within a driving distance of about 90 minutes. And you'd be surprised that there are a lot of such places. And once we've identified those, we then kind of go through each and every location, which is, as we call it within the Flying Doctors, as grey areas where there's no coverage. Then we started looking at, how many people are there, what's the demographic, and what were traditionally the core diagnosis or the diseases that they're suffering from. PRITISH: 17:21 And then once we've identified those grey areas, we then start plotting which is the nearest airstrip. And we've got a fleet of around 80 aircrafts and most of our planes can just land on a dirt strip. So we look out and identify patches where our aircraft can safely land. At times and especially in the night, it's so dark. And then there's no weather system or you don't understand what's actually the condition of the airstrip. And people actually hold torches on the runway to guide our pilots to land safely there. So once we've identified those airstrips, we then start identifying that these places are easily accessible by air. Some places are accessible by road. And once we've done all that groundwork, we then start looking into our own data, which is running into years, where we say we identify the diseases or the conditions the patients suffer from. And then once we've identified, we then go into the planning session, where typically our planners work for about months and then they work very closely with the health networks within the region to then identify core areas of need and that's when we start flying in. So at times our doctors and nurses they fly into a region and then they stay there for about a couple of days and then they fly back or sometimes it's just a day in day out kind of a clinic. So that's pretty much the landscape of data that we work with. MADDIE: 19:06 Okay. So essentially what he just said is that data really serves as a backbone for their planning, and strategy and ultimately analytics drives their decision-making. PRITISH: 19:16 Yes. And a lot of data is-- we get it from external sources or our partners. Healthdirect, they give us a list of all medical services available across the country. We get a lot of other data from different primary health networks. And then you'd be surprised that a lot of data is intuition-based as well. People who've been in that community and serviced that for years. Maybe 30, 40, 50 years as well. They know the place in and out. And pretty much at times, the data could be pointing that there is a need but sometimes those people they know that there is another service available in that area on a Wednesday or a Thursday and therefore there's no need for us to go on those days. So sometimes there are those gaps in data, and that's where the experience of people working there, they kind of come in and plug that gap for us. MADDIE: 20:15 Let's check back in with Sarah, who also gave insight about data at Foodbank and the people who are working with data in order to make decisions. SARAH: 20:22 I am very happy to say we now actually have an analyst for the first time ever. MADDIE: 20:28 That's amazing. SARAH: 20:29 So data has always been my bag and IT guru also has a great appetite for data. So he and I have been kind of the carriers of the flame when it comes to data at Foodbank. But now in our current circumstances, we have taken on an analyst because with everything that's happening during COVID both with regard to what we need to do to support people but also the corporations and government who are assisting us so we have received a lot of support - funding support and so on - in order to do our job, we know that we need to be able to analyse and investigate what's been happening. We need to report back comprehensively. Those who are providing us with funds, etc., want to know exactly what's happening to that money and how-- and the impact that it's having. And so we knew we needed more help in order to be able to satisfy those needs and to achieve the right level of reporting. And the way we're looking at it at the moment with everything that's changed during COVID, both in terms of the need how we operate, what the government is doing in terms of support for the community and so on, we're seeing COVID as the ultimate experiment. SARAH: 22:05 So we are able now to look at things that are being done in the community, both that we're doing and the government and others are doing and look at what impact they have had and we can-- we've got something that we can look at here that we would never of had without COVID. Now, I'm not saying I want-- I'm pleased that COVIDs come along, but gee never let a crisis go to waste. And there's all sorts of things that we can look at right now and better understand what impact the government and we and the general public can have on something like food insecurity. So from a data point of view, from an analysis point of view, it's actually extremely exciting times. And we believe that the world will not go back to the way it was before. So much has changed during COVID and we want to be able to nail that down, explain it, and retain the good stuff. Retain the improvements that we've been able to make, the insights that we've been able to gain and have a better-- have a better future rather than the same. MADDIE: 23:26 I think then that's going to be crucial for us to continue to solve these problems because this isn't-- this is obviously a huge deal but there are more things that are going to keep happening, you know what I mean, so there's always going to be challenges. And the better camaraderie that we can build now I think is going to be for the better. SARAH: 23:45 And there has been amazing innovation during this time. So we at Foodbank have changed our model and pivoted and responded to the new needs in some incredibly creative ways and we don't want to lose that. We want to pin that down, understand what happened, what it achieved, what the impact was, and how we can use those new experiences, new approaches post-COVID. So analysis helps you to achieve that. MADDIE: 24:23 Let's check in with Pritish. Yeah. It sounds like you guys are getting really creative with everything. I would imagine as well since you're pulling data from all these different sources and as you said you live and breathe data in your role, does everybody at your organisation think as a data person? Are they all data thinkers? Do you guys have dedicated analysts? Or yeah, how do you kind of make sure that everybody on your team and everybody at your org is thinking analytically? PRITISH: 24:55 Yeah. Data is a journey. And initially, it was all intuition-based, I think, many years ago. And then, Excel came in and we started creating different kinds of reports and people started using the data to make informed decisions. And then we started on the BI journey. We introduced tools, such as Alteryx, yourselves, and then that's where we started getting analytics around the data. We started understanding patterns and so on. So, yes, it is definitely a journey where initially from being an intuitive organisation, you're becoming more aware and take more informed decisions. And yes, to answer the second part of your question, we've got data analysts everywhere, in all the states and the territories in the country, and they kind of work with different teams, be it-- being a charity, we rely a lot on fundraising. So some analysts would be involved with the fundraising side of things, some would be looking more at the operational side of thing, and some would be more inclined towards the finance side of things. PRITISH: 26:08 And certainly over the years, we've started absorbing more and more data. And it was data which was not available to us earlier. So we can now identify how many hours it takes us for a flight to reach a location. How much fuel do we consume on that flight? What's the crew on that flight? Is it a doctor or is it a nurse? How many patients were there on a flight? And what was the criticality, what was the severity, of the patient? And we can then kind if look through at a case-by-case basis or we can aggregate and summarise and see what are response times. How readily are we available to service our patients and our community. So all of this data was not available for us, and if you were to do it manually it used to take us months. But what we've done and achieved over the past couple of years is leveraging Alteryx we've been able to bring together all of this data which is in different systems. You'd be surprised. We've got about 100, 100-plus systems, and we've brought in data from all of these systems, aggregated it together, and brought in uniformity. And then we've started consuming this data. And it's just such an-- it's just brought our operations and the way we operate altogether a different level. [music] MADDIE: 27:31 Thanks for tuning in to Alter Everything. For more on the programs and organisations heard on today's episode, check out or show notes at community.alteryx.com/podcast, where you can also chat with us by leaving a comment. We'll also have a link to a blog article by our data science journalist Susan Currie Sivek where she shares resources on how you can use your analytic skills to help organisations like Foodbank and RFDS. And you can join us on social media using the #AlterEverythingPodcast and be sure to subscribe on your favourite podcast listening app to make sure you don't miss any episodes. Catch you next time. [music] So before I hit stop recording, I did want to [laughter]-- I thought it'd be funny to ask you this at the end. But earlier, you said the car giving up the ghost? Did you say that [laughter]? SARAH: 28:35 I did. Yes. [laughter] Is that not a saying--? MADDIE: 28:38 I've never-- SARAH: 28:40 Is that not a saying you've heard before? MADDIE: 28:42 First time, actually. [laughter] What does that mean? SARAH: 28:47 If something breaks down or dies, it gives up the ghost. MADDIE: 28:53 That is so funny. Yeah. I love that. [laughter] And I was like, "I better write that down, so I can ask her later at the end." [laughter] So cool. SARAH: 29:06 You're lucky I didn't put in lots of other Australianisms. Because I have a lot of American colleagues in the Global FoodBanking Network and they're often pulling me up and going, "What was that you said?" [laughter] MADDIE: 29:20 I know. There are so many that I heard when I was in Australia for Inspire, and I can't think of them off the top of my head. Maybe I'll put them in the-- maybe I'll list them in the show notes later. SARAH: 29:30 I think that's a good idea, yeah. [laughter] MADDIE: 29:33 Awesome.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

Alter Everything Podcast

Podcast Guide

73: Insights in action: Using Alteryx to serve Australian communities

Panelists

Topics

Transcript

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

Alter Everything Podcast

Podcast Guide

73: Insights in action: Using Alteryx to serve Australian communities

Panelists

Topics

Transcript

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.

This episode of Alter Everything was produced by Maddie Johannsen (@MaddieJ).
Special thanks to @andyuttley for the theme music track, and @jeho for our album artwork.