Alter Everything Podcast

MaddieJ · ‎09-14-2020

How can spatial analysis unlock insights for your local food bank? We sat down with Chris Williams, CTO at Precision Analytics Group, to learn more about the current state of food banks amidst the pandemic, how all volunteers collect and contribute to non-profit data collection, and how the Alteryx spatial tools can be an “ace in the hole” for food bank data analysis that delivers real impact to those in need.

Panelists

Maddie Johannsen - @MaddieJ, LinkedIn, Twitter
Chris Williams - @chriswilliams41, LinkedIn, Precision Analytics Group

Topics

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Transcript

Episode Transcription

CHRIS: 00:00	So when you're looking at numbers and you're looking at trends, I mean, 80 billion pounds of food is thrown away each year in the US, not spoiled food, just regular food. I mean, food that's not used in restaurants. Food that's not used in stores. What we try to do is try to monitor how many of those pounds can actually get donated back to a local food bank, so they can use it, and they could distribute it. I mentioned 80 billion pounds. That's 40% of the US food supply. That's 219 pounds per person.
MADDIE: 00:39	Wow.
CHRIS: 00:40	$1,600 per family. If you don't have analytics, you don't have those numbers. [music]
MADDIE: 00:50	Welcome to Alter Everything, a podcast about data science and analytics culture. I'm your host Maddie Johannsen. And in this episode, you'll hear a conversation I had with Chris Williams, chief technical officer for Precision Analytics Group from Portland, Oregon.
CHRIS: 01:06	And I am proud to say that Precision Analytics Group is a minority-owned business entity.
MADDIE: 01:13	Chris is super passionate about giving back using his analytic skills. And he shared some ways in which data and Alteryx can help unlock solutions to solving hunger in local communities.
CHRIS: 01:24	I never forget where I came from, so I always want to try and help out whenever I can. The stars just aligned to be able to turn analytics into something like this which is a huge problem right now and bring some to light to it.
MADDIE: 01:40	Let's get started. It's funny because we met at Inspire 2019 which, I guess, is a little over a year now, ago, and in Nashville. And it was so much fun, and I just really miss that Inspire vibe, but I'm glad to have you back here on the podcast. Because I remember after our conversation in Nashville where you recorded a mini-interview episode with me, which we'll link to in the show notes, I think we both had the feeling that we needed to book a longer full episode to chat more. So finally, we found the time to record, and here we are.
CHRIS: 02:18	Here we are, and it's a real honor to be here. I'm real excited to dive into the topics that we have. And this conversation that we're going to have will really shed some light on an issue that's really permeating the country and actually the world, but we'll focus on the country. And so I'm ready to dive in headfirst.
MADDIE: 02:38	Perfect. Yeah. Thinking about food banks and how important they are to communities, I just want to know from your perspective personally, why food banks as this passion project of yours.
CHRIS: 02:52	Well, I've always been fascinated by hunger, and hunger is a worldwide problem. But as far as the US is concerned, more than 37 million people struggle with hunger in the US, including more than 11 million children. More than 56%, more than half food-insecure households participated in at least one of the major food assistance programs: SNAP, also known as Supplemental Nutrition Assistance Program, people may know them as food stamps; the National School Lunch Program; and the Special Supplemental Nutrition Program for Women Infants and Children, also called WIC. All of these organizations, all of these initiatives are focused on trying to deal with hunger. So when we fast forward to the present time, now we're dealing with the coronavirus pandemic, the aforementioned numbers actually become even more inflated. Many families are without stable employment. And it's anticipated that more than 54 million people, including 80 million children, may experience some food insecurity in 2020.
CHRIS: 04:00	So I mentioned that term. What is food insecurity exactly? A household that is food insecure has limited or uncertain access to enough food to support healthy life. Children deal with this more than any other group because they are reliant upon adults to get them fed. So why do I care? I've always really cared about it. I volunteer here, in the Portland area, with the Oregon Food Bank. It's been something that I've actually dealt with in my younger life when I was growing up. I've had times of hunger when my parents and I were growing up together, obviously. And I never forget where I came from. So I always want to try and help out whenever I can. The stars just aligned to be able to turn analytics into something like this, which is a huge problem right now, and bring some light to it. And when you bring light to something more people pay attention. And this is all about awareness and trying to deal with the problem.
MADDIE: 05:01	Absolutely. Yeah. That's fantastic that you volunteered. This is just really close to your heart, and thank you for sharing that story. Because I think, as you pointed out, it's something that is definitely more common than anybody knows, and it is incredibly important. And yeah, I appreciate all of the background and all of the statistics for people because I'm sure other countries too, outside of the states, also experience this in staggering rates. And I think analytics can really be a huge tool in fighting this and answering these really tough human challenges. And I want to know, when you work with nonprofits and food banks, what are some data trends that you see or maybe some pain points that they struggle with?
CHRIS: 05:50	As people lose their jobs, people are becoming more and more reliant on food banks and nonprofits for their meals. I mean, take Texas, for example, the San Antonio Food Bank. There are people driving in from miles. There are lines carrying around corners, down streets. They just want to be able to get food. When you're not working-- and as the coronavirus pandemic has basically sidelined a lot of people that cannot work right now. So not only are they trying to figure out what their rent situation is going to be, they're trying to figure out what they're going to eat in the next meal. Not to be overdramatic, but that's the reality of a lot of people right now. So when you're looking at numbers and you're looking at trends, I mean, 80 billion pounds of food is thrown away each year in the US, not spoiled food, just regular food. I mean, food that's not used in restaurants. Food that's used in stores.
CHRIS: 06:56	What we try to do is try to monitor how many of those pounds can actually get donated back to a local food bank, so they can use it. And they could distribute it. I mentioned 80 billion pounds. That's 40% of the US food supply. That's 219 pounds per person, $1,600 per family. [music] If you don't have analytics, you don't have those numbers. And it takes a dedicated team of people to compile these numbers and try to figure out how to whittle that down. So you have these high-level numbers. Right? And so at each community level, it's a slice of those numbers. How are we going to address that? What can we do to address that? Well, one way is donor information. Keeping an idea of how many donors do you have right now? How much are they donating? Maybe you can have an initiative to encourage more donations, and maybe you hit that different-- maybe you have a restaurant that donates a lot. Maybe you want to go have a campaign that actually targets more restaurants in your area because this is clearly something that restaurants deal with. Why not get that food? It's donated. It's free. You get that information; someone will eat that night.
CHRIS: 08:25	I mean, there are times in which I've-- growing up, I mentioned that I dealt with hunger. There are times where I've grown up, and it was a decision whether or not I was going to have something or my mother was going to have something. So these are decisions that parents have to make. And we have enough food that we shouldn't have to be forced to make those kinds of decisions. So let's try to cut in the gap. And so this is why analytics are important. And people shouldn't be intimidated by the mounds and mounds of data that are coming in. So just attack a piece, get one part of the story, get as much data as you can about that particular topic, that subtopic within the hunger, and address that. And then another topic comes up, supplements that. Then as you can see the domino effect will follow. You get information and more information that enables a person to make objective decisions on what should happen next: changing strategy when it needs to be changed, keeping things going when things are working, that kind of thing.
MADDIE: 09:33	Totally. Yeah. You shared a really cool use case on the community that looks at food distribution centers. And I'd love for you to just maybe give us an overview of what that use case was.
CHRIS: 09:45	Sure. The use case that I actually submitted focused around the San Francisco and Marin County Food Bank. We were doing some prospective work for them, and they've turned into a client. And the use case that we wanted to address there were, how many of their open food banks were located in areas that had a high amount of high-poverty households and elderly-populated households? So when I say open food banks, these are food banks-- they've had to close a lot of food banks because of a variety of reasons whether it be short on staff, whether it be just not able to be kept open for financial reasons. We just wanted to make sure that we had all of the open food banks placed on a map so people could see what areas they're able to support. So this was to set the stage for what we have for this particular use case that you can see on the community. And this really helped the organization make some decisions on what areas were being neglected, and what areas needed to be addressed by either food deliveries or mobile food banks. And mobile food banks are probably the quickest fix right now. This is one of the reasons why Spatial analysis is so important because you through a Spatial influence into all the other pieces of data. So we have a whole bunch of demographic data. Obviously, we have the location data for the food banks for this San Francisco area. You throw that together in a map, and it tells a complete story or at least tells part of the story where you might want to address. Because maps and points actually is the quickest way to visually represent what you're doing and how effective it's doing it.
MADDIE: 11:33	Yeah. And I definitely want to get into the Spatial stuff as well. And I think, to take a quick step back, you had given a training, an Alteryx training, for food bank professionals. And I saw somebody introduce themselves in the chat as being on a data team at a food bank which I loved. I thought that was so cool that they had a team for people to think about these problems from that data and analytics mindset. And I wonder how common this is for food banks to have dedicated data workers as resources on staff. Because as you mentioned, food banks are closing, and they don't have enough staff too, just from an operational level. So I think from a analytics level and from a perspective of somebody trying to work with the data, I would imagine that that potentially is a novelty. But it sounds like it's absolutely vital.
CHRIS: 12:34	It's more common than you think because the abundance of data that comes in daily to food banks is really astronomical. They may not necessarily be identified as data custodians per se, but they're responsible for bringing in data whether there have been data from volunteering numbers from a event that may have taken place throughout the week, meals provided to hungry families, how many pounds of food get donated to food banks as a whole. Everybody who works there is basically a data source. They are responsible for interacting with the public whether it be from a donation perspective or basically as a distributor on what kind of food or how much food gets donated to a certain area. All of that has to be tracked in order for the results to actually hit correctly in a certain area. So let me cycle back to the use case. We use Spatial analytics to identify the census tract areas that had high amounts of elderly populated and high amounts of populate poverty areas within the San Francisco area. Every community has to do this. The more demographics that you introduce to an analysis, the more complete your data will be, and the more objective decisions you can make as a result of that. Because the maps will tell you the story because you're combining it with a whole bunch of different aspects.
CHRIS: 14:09	So let me go back. So we have identified where are high-populated areas of elderly people and high-poverty areas. So when we look at high poverty, we look at people making less than $10,000 a year, elderly 65 years and older. So we wanted to identify it because it's going to be harder for them to actually get anywhere to get food dealing with the COVID pandemic right now. Vehicles-- they may not have vehicles anyway, but public transportation may not be as readily available. So if you're in town and you're basically looking at on-foot, you're basically walking to and from. So this is where the Spatial came into play for me. Because not only did I want to plot where the open food banks were, I gave them a Trade Area of quarter of a mile to support those individuals who may be on foot. Quarter of a mile is basically how much I would-- we took a guess at trying to figure out what made sense, and how far people would walk for food, and how far people would walk back with a bunch of food that would be safe for them.
CHRIS: 15:12	And so plotting that on a map and overlaying it on those areas of demographics that we discussed allowed the San Francisco and Marin Food Bank to say, "Okay. This is what this food bank is supporting right now. This is located in these areas. But wait a minute, we have these areas over here where we don't have a food bank." And we put it into a nice workflow in Alteryx, and then it output it into a PDF report which really hit home for a lot of our clients who are seeing this and it definitely hit home for the training. Because it is something that's tangible that you can hand over to a higher-up group that makes more financial assistance to say, "Here, this is what this workflow is telling you. This is what your data is telling you. And this is how it looks on the map. Please use this in your decision-making process on where money is going to go and where the next piece of strategy is going to take place." [music] So you mentioned the training. I'm happy to say that we have started a new discussion group, the Alteryx Food Bank Discussion Group, within the Alteryx for Good Community. And we had our initial training on Thursday. It was wonderful. We're going to build, and we're going to raise awareness. And we're going to make an area where other food banks around the country can feel confident that they can, A, get their answers from this area and, B, share their stories. The more collaboration that we can do, the better everybody around gets.
MADDIE: 16:56	Yeah. It's so inspiring to see the conversations happening on the community and even just during that training in the chat. Because I think one of the things that really stood out to me in your explanation there, was just how important it is to remember that the people on the front lines - the people who are working at the food banks - every person there knows the backstory. And they know the statistics for their community, and they know the people in their community. And I think being able to add that color and have that personal on-the-ground experience kind of is almost more important than knowing how to draw a Polygon in Alteryx. Right? I mean, it's definitely important. But I think that those are the skills that you can learn, whereas the on-the-ground experience and the on-the-ground knowledge is so-- you can't just learn that. Right? I mean that's something that you really have to be a part of. And even collecting donor information or just how you explain to everybody that works at a food bank or a nonprofit touches data in some way, can be really empowering to recognize. Because I think that some people can be a little intimidated when it comes to, "Okay. I need to put together this analysis. I need to tell a story with my data, and there's high stakes because this could affect different aspects of the organization if I don't get it right." And so I think it's important to call that out, and I'm really glad that you did. It's something that is doable, and it's a skill that can be learned. And data literacy is really important, but it's definitely attainable for anybody out there who wants to try.
CHRIS: 18:43	Indeed, and being a part of your community, I mean, there's a sense of ownership. I mean, part of the reason why I volunteer at the Oregon Food Bank is because this is my community; this is where I live. I've lived in Portland for eight years, and I see hunger permeate downtown Portland. I see it throughout the state. And being able to volunteer on Saturdays and being able to pack boxes or collect vegetables and fruits for hungry people that are going to be directly affected by the work that I'm doing, and doing with a bunch of people that day, is very fulfilling. Being a part of that data that's being collected is very fulfilling. You don't have to be a data wiz to do this. You don't have to be a Spatial wiz to do this. You are contributing to the story, the data story, that's being told that will help influence what happens next in that community.
CHRIS: 19:45	So you had mentioned about Spatial and how people aren't Spatial wiz, wizzes around, and it's really difficult and can seem very intimidating. I am one of these people. I was terrified of Spatial. I wanted no part of it. I looked at these green icons in the Alteryx Designer, and I'm seeing Find Nearest. I'm seeing Create Point. I'm seeing PolyBuild. I'm just like, "Oh my goodness. What am I doing here? I am a fish out of water, and I am lost." And honestly, I have to give a lot of credit to a really good colleague and a really good friend of mine, Nicole Johnson. She's an Alteryx ace. She actually came to the Portland Alteryx user group and gave a really phenomenal Spatial presentation.
MADDIE: 20:34	Of course she did.
CHRIS: 20:35	There--
MADDIE: 20:35	She's awesome.
CHRIS: 20:36	Yes. She is. She is awesome. And she really encouraged me to go outside my box and learn Spatial. And this is about a year ago. So what I did is I actually started off with the Grand Prix Weekly Challenge - I think it was challenged 129 - and she said, "Try it." And so I took the challenge. I challenged myself and really put my mind to it, took Spatial classes at the last Inspire Nashville, and really, really challenged myself to come up with different use cases that would require me to know some Spatial and enter the food banks. And this was just the perfect storm of being able to test things, and now I am not intimidated at all. The one thing I would probably tell you and tell anybody else who is starting off where I started off as being intimidated by Spatial, what I would say is that just don't, just dive right in. You use Spatial to do pretty much anything that you do in life anyway. You use Spatial analytics to find out which grocery store is going to be the closest one and the best one for you to go to. You're just not putting a fancy title on it. That's analytics. That's Spatial. Being able to do this within Alteryx, having the community to help you, guide you along the way to try to embark on this journey, you're in a safe zone within this Alteryx Community. All we want you to do is succeed.
MADDIE: 22:15	That's really encouraging. And I know that we're talking to everybody listening out there, but I mean, I feel like you were just talking to me directly because I am definitely scared to start out with learning the Spatial Tools. And I think I was definitely intimidated to start learning Alteryx in general. But then once you just get started and you try, you realize like, "Okay. Yeah. I can do this, and this isn't that bad." And so I'm sure the same will happen with Spatial. It's just like that first initial step, for some reason, is always so difficult.
CHRIS: 22:44	For sure. Whenever you learn something new, it's not going to be easy. And so the thing that kept me going is that once I learn it, things will become much easier. So yes, I'm going to go through some growing pains. We all do. Whenever we learn anything new, we go through growing pains. But being a business intelligence developer and working with databases and understanding how Alteryx can help me get better and actually do analysis rather than doing data prep for analysis, it gives me time back to my day. [music] And this is the thing that I always push to my clients and anybody else who is very curious about what Alteryx is. I'll say Alteryx is a phenomenal tool. It actually gives you time back in your day. It allows you to analyze rather than prepare to analyze.
MADDIE: 23:51	Yeah. And I think this is a good time to plug our Alteryx for Good program which provides Alteryx licenses for nonprofits and students out there. So we'll be sure to link to that in the show notes, so people out there can learn more about that. If you work at a nonprofit and you're interested in getting that time back in your day, as you said, it helps you analyze instead of preparing to analyze. I think that's so important. And for people who do get an AFG license, what is a piece of advice that you have for them? You mentioned just dive in and try. But I think also, how you and your use case used that census data, how do you know to do those things? And how do you know how to enrich your data and provide an analysis? Or even how do you tell a great story with your data? How do you get started with that?
CHRIS: 24:49	Well, even though I've only been in Alteryx for about 3 and a half years, I've been in analytics for about 24. So one thing that's always helped me is that I don't always focus on the primary question, and when I'm gathering data, I just gather data. I get every piece of data that I can get my hands on. It may not answer a primary question that was proposed, but it's surely going to formulate something down the road. So when I look at the primary question, I look at the data for the primary question. But you also have to think two or three moves ahead. You have to ask that secondary question or that tertiary question which will inevitably expose something brand new that you haven't even thought of before and that only goes through just talking something out. It's like-- not to use a pun here. So it's literally a workflow. Get every piece of data that you possibly could get. You can't create something that's not there, but you can always hold something in the back for when you possibly need it. Data is your friend. It's when you don't have data is when you cannot make decisions, and you cannot make objective decisions. Because when you don't have data, your decisions become subjective, not objective. And you want the objective piece to win.
MADDIE: 26:17	I love that advice. And jumping forward then to actually working with the data. If you have any sort of secret weapon in your back pocket when it comes to using the Spatial Tools in Alteryx, I want to know what that might be. And this might be a little hard to explain over audio, but we'll be sure, for our listeners, to link to any of the concepts that Chris talks about here in the show notes. But for example, we had emails about multilayered Maps and Polygons and Trade Areas and like all those things. So if you want to introduce any concepts to our audience about those things that would be awesome.
CHRIS: 26:52	Sure. I'll actually take you through the thought process of how I came up with the multilayered Map for this instance. So I was given an Excel spreadsheet of all of the open locations, all the open food banks within the San Francisco, Marin County supporting area. And what we wanted to do is try to create a Spatial use case that would make sense. So what I wanted to do first is that I didn't want to join the data. So I wanted to create a point on the Map with all of the open food banks. But I also wanted to analyze the demographic information that we got from our Business Insights package. So I wanted to take the household data and create a Polygon so that those Polygons would be able to be evenly distributed amongst the city, and this could be any city. I did it for San Francisco in this case. I also did it for the Houston Food Bank. And I sent it through the training. But I wanted to create a Polygon so that the Polygon would be able to be color coded based on the volume of households within that demographic. And so normally, what you would do is, you may want to join those two pieces of data together to figure out where exactly they meet as far as the matching is concerned. I didn't want to do that. I wanted to do a simple overlay because the overlay will tell you more of a story of where you need to go.
CHRIS: 28:24	So I just had the addresses. So I use the Geocoder to create the Lat/Long. Then I created my Spatial points. And then after I did my Spatial info, I created a Trade Area using the Trade Area icon and tool. And so since we're dealing with San Francisco which is a really small peninsula, we wanted to make sure we had a Trade Area that actually made sense. So we decided upon 0.25, quarter of a mile, to symbolize the walking distance. So after I created that point and created the Trade Area, now I have the first part of what I wanted to do on this map. Right? So I wanted to be able to create the point and create a little circle around that point to promote which areas, the radius, in which that food bank would support.
CHRIS: 29:21	So the next thing I would do is go ahead and create the Polygon layer. And the Polygon, actually, there are a couple ways you could do it. So one way that I did it is that I went through the Allocate Input and chose the census data. And one of the things that you can have as an output is being able to output actual Spatial object field which would be in this case the Polygon. So I satisfied my requirements as far as choosing the high poverty or the elderly population. I think in my training, I actually focused on age 45 to 54 because integrating the census data from the household Pulse survey which was something new that we added - I'll get to that in a second - it actually exposed that the most hungry people, as far as the age group was concerned, was the ages 40 to 54 in a lot of these metropolitan areas. So I switched that a little bit to try to bring that point home and created a PDF report that actually combined all of that data to provide a case for that. This may help, leading into more funding to deal with that particular problem.
CHRIS: 30:33	So getting back to the Spatial here. So I've created my Polygon, and I've created my Spatial point with the Trade Area. I want to overlay those guys. I want to make sure if I overlay these guys, then that actually tells a story on, "Okay. This is where this point is, and this is how it lies within all these polygons." So I created some layers in the map, so I had those two streams flowing in. And then I created a color code. So the color code was based off of the population of the demographic that I'm dealing with so specifically the age range. And what Alteryx does - and it's really awesome that Alteryx is intelligent enough to do this - is that it will take all of the measures generated, the numbers created, and it will create five even fields or even breakdowns of that data. And then you can decide how the color code goes. I like to go from red to blue so the red being the most highly populated and blue being the least, and being able to have those colors be identified.
CHRIS: 31:41	So you have the polygons on the bottom, and then you have the points and the Trade Area on top. And when you layer those guys it comes up to a really nice perfect type of situation where you have all your points without any bounds as far as the drawing is concerned on a map, in front of your face to say, "This is what your data is telling you." So we added another aspect to this. So I have the map, and I have the points on the map. And that's really, really cool. So more is better in some cases. So I wanted to bring that home a little bit more. So the census data actually has some household survey information off of its page that is free to download. So what I did is that we went in there and took that information, downloaded 11 weeks' worth of data, and put that into a repository and included that analysis as well as the map into one report. So we took that and took, I believe it was 2B of-- or 4 actually, of food sufficiency. And we identified the hunger, what age groups were hungry for a particular week. And then we did a rolling 4-week average to get a more stable trend on what was actually happening because sometimes the week-to-week can fluctuate. So the rolling 4-week average was actually the decision maker why I wanted to choose a certain age group to focus the map on. So once you have your layered map, it turns into a reporting exercise.
CHRIS: 33:33	And one thing I wanted to say, is that the Alteryx reporting capabilities are very underrated. It can provide you a very slick and informative business-style report, especially if you don't have a reporting system on the back end to develop this. We were able to create a really comprehensive report with a cover page, with maps, with a line chart just like we did in the training, and so this is what we came up with. And delivering that to a client and having somebody say, "Here, this is what we've come up with, with your one piece of data. We got one piece of data which were the addresses of all the open food banks." And me and my company, we were able to go ahead and take that one spreadsheet and turn it into this. So it's something that everybody else can be confident that you can do as well. And the nonprofit organizations that we have been trying to service and educate about what we've done, this is something that you can definitely do because you have the blueprint now to do it and then expand from there maybe. There's so much data to be had. This census data that we just found, that's free. Anybody can get that. So the business insights becomes important because we were able to create the Polygons off of the demographic data that already existed. So we combined stuff that already existed along with new information, and you can combine even more information into this workflow that could get an even better story. So along with that, "the more data is better theme" that I'd like to make sure gets known, is very applicable.
MADDIE: 35:28	Totally. Yeah. And it's so helpful to hear you kind of break down the concepts. Because if you leave it at a category, if you just say, "Oh, I'm going to try Spatial," I think it can be kind of mystifying. And so breaking it down and saying, "You can do all of these different things with it," and just tackling them one by one, I think, helps to really demystify it. So that was really, really helpful. And also, super cool to hear how you took that spreadsheet, and you turned it into this ridiculously helpful and easy to visualize report. I think that's amazing. So we'll be sure to link to everything that Chris just talked about, as well as just some other resources that are out there on the community, to help people kind of understand and get a better idea and follow along with what you were saying.
CHRIS: 36:12	Wonderful. And the one thing about Alteryx - and this is just a general Alteryx statement I'm about to make - is that it makes data investigation, and data processing, data blending fun. Because, really, you get instantaneous results as soon as you run a workflow.
MADDIE: 36:32	Yeah. That's amazing. And this has all been so inspiring. And for people out there that are looking for maybe skill-based volunteering opportunities, maybe they are an analyst in our community and they can do the same thing that you're doing, how do they approach that? How do they find these opportunities? And maybe for people even who aren't looking for skill base but just in general, where are your favorite places to find these opportunities and get involved?
CHRIS: 37:01	I think, hopefully-- and this is the whole reason. One of the themes behind why I wanted to start this discussion group is to post there - we have a thread; hopefully, we'll turn it into something bigger - and just throw your hat into the ring. Maybe go find a local facility and just ask them, send them an email, give them a call if you want. If you feel comfortable enough, drop by. It's really as simple as that. I mean, you don't have to have an out-of-body experience to contribute. It may be as simple as just asking question one or sending one form of communication to anything local that you can find. I mean, everybody has data that could help you. And hopefully, I've been able to shed a little light on how you could start.
MADDIE: 37:55	Totally.
CHRIS: 37:55	Because Alteryx for Good is fantastic. They know of a lot of opportunities. I mean, yeah, you can feel free to reach out to me. I'd be more than happy to start a discussion with you about opportunities that I've seen. In addition to, I mean, obviously, you've seen the use case, but for that one use case, I've seen probably at least 8 or 10 different requests outside of that. So let's start a conversation and figure out where it goes from there.
MADDIE: 38:23	Love it. Well, thank you so much, Chris, for joining me. I'm so glad that we finally got to make this happen. And it was actually kind of cool, I guess, to do kind of like a one-year follow-up from our last conversation. So yeah, this is great. Thank you so much.
CHRIS: 38:37	[music] And, Maddie, thank you so much. It's really an honor to speak to the community. It's an honor speaking with you, of course. And let's do it again sometime.
MADDIE: 38:44	Totally. Yeah, anytime. Thanks for listening. If you're interested in learning more about our Alteryx for Good program, Chris's Alteryx use case, or anything else discussed on today's episode, check out our show notes at community.alteryx.com/podcast. And while you're there, register for a free community account. You can learn more about Alteryx, join in on the conversation, and connect with over 175,000 users who are passionate about data. Catch you next time.
MADDIE: 39:25	Perfect. You're a professional. So I'll cut it there.
CHRIS: 39:31	This was fun. Was it okay?
MADDIE: 39:33	It was awesome. Honestly, the entire time, I'm like scrambling writing on this piece of paper. I'm like, "Okay. This is a Tweetable quote, Tweetable quote," like everything that you said, I think was just a perfect soundbite. So yeah, I mean it was killer. You nailed it.

CHRIS: 00:00 So when you're looking at numbers and you're looking at trends, I mean, 80 billion pounds of food is thrown away each year in the US, not spoiled food, just regular food. I mean, food that's not used in restaurants. Food that's not used in stores. What we try to do is try to monitor how many of those pounds can actually get donated back to a local food bank, so they can use it, and they could distribute it. I mentioned 80 billion pounds. That's 40% of the US food supply. That's 219 pounds per person. MADDIE: 00:39 Wow. CHRIS: 00:40 $1,600 per family. If you don't have analytics, you don't have those numbers. [music] MADDIE: 00:50 Welcome to Alter Everything, a podcast about data science and analytics culture. I'm your host Maddie Johannsen. And in this episode, you'll hear a conversation I had with Chris Williams, chief technical officer for Precision Analytics Group from Portland, Oregon. CHRIS: 01:06 And I am proud to say that Precision Analytics Group is a minority-owned business entity. MADDIE: 01:13 Chris is super passionate about giving back using his analytic skills. And he shared some ways in which data and Alteryx can help unlock solutions to solving hunger in local communities. CHRIS: 01:24 I never forget where I came from, so I always want to try and help out whenever I can. The stars just aligned to be able to turn analytics into something like this which is a huge problem right now and bring some to light to it. MADDIE: 01:40 Let's get started. It's funny because we met at Inspire 2019 which, I guess, is a little over a year now, ago, and in Nashville. And it was so much fun, and I just really miss that Inspire vibe, but I'm glad to have you back here on the podcast. Because I remember after our conversation in Nashville where you recorded a mini-interview episode with me, which we'll link to in the show notes, I think we both had the feeling that we needed to book a longer full episode to chat more. So finally, we found the time to record, and here we are. CHRIS: 02:18 Here we are, and it's a real honor to be here. I'm real excited to dive into the topics that we have. And this conversation that we're going to have will really shed some light on an issue that's really permeating the country and actually the world, but we'll focus on the country. And so I'm ready to dive in headfirst. MADDIE: 02:38 Perfect. Yeah. Thinking about food banks and how important they are to communities, I just want to know from your perspective personally, why food banks as this passion project of yours. CHRIS: 02:52 Well, I've always been fascinated by hunger, and hunger is a worldwide problem. But as far as the US is concerned, more than 37 million people struggle with hunger in the US, including more than 11 million children. More than 56%, more than half food-insecure households participated in at least one of the major food assistance programs: SNAP, also known as Supplemental Nutrition Assistance Program, people may know them as food stamps; the National School Lunch Program; and the Special Supplemental Nutrition Program for Women Infants and Children, also called WIC. All of these organizations, all of these initiatives are focused on trying to deal with hunger. So when we fast forward to the present time, now we're dealing with the coronavirus pandemic, the aforementioned numbers actually become even more inflated. Many families are without stable employment. And it's anticipated that more than 54 million people, including 80 million children, may experience some food insecurity in 2020. CHRIS: 04:00 So I mentioned that term. What is food insecurity exactly? A household that is food insecure has limited or uncertain access to enough food to support healthy life. Children deal with this more than any other group because they are reliant upon adults to get them fed. So why do I care? I've always really cared about it. I volunteer here, in the Portland area, with the Oregon Food Bank. It's been something that I've actually dealt with in my younger life when I was growing up. I've had times of hunger when my parents and I were growing up together, obviously. And I never forget where I came from. So I always want to try and help out whenever I can. The stars just aligned to be able to turn analytics into something like this, which is a huge problem right now, and bring some light to it. And when you bring light to something more people pay attention. And this is all about awareness and trying to deal with the problem. MADDIE: 05:01 Absolutely. Yeah. That's fantastic that you volunteered. This is just really close to your heart, and thank you for sharing that story. Because I think, as you pointed out, it's something that is definitely more common than anybody knows, and it is incredibly important. And yeah, I appreciate all of the background and all of the statistics for people because I'm sure other countries too, outside of the states, also experience this in staggering rates. And I think analytics can really be a huge tool in fighting this and answering these really tough human challenges. And I want to know, when you work with nonprofits and food banks, what are some data trends that you see or maybe some pain points that they struggle with? CHRIS: 05:50 As people lose their jobs, people are becoming more and more reliant on food banks and nonprofits for their meals. I mean, take Texas, for example, the San Antonio Food Bank. There are people driving in from miles. There are lines carrying around corners, down streets. They just want to be able to get food. When you're not working-- and as the coronavirus pandemic has basically sidelined a lot of people that cannot work right now. So not only are they trying to figure out what their rent situation is going to be, they're trying to figure out what they're going to eat in the next meal. Not to be overdramatic, but that's the reality of a lot of people right now. So when you're looking at numbers and you're looking at trends, I mean, 80 billion pounds of food is thrown away each year in the US, not spoiled food, just regular food. I mean, food that's not used in restaurants. Food that's used in stores. CHRIS: 06:56 What we try to do is try to monitor how many of those pounds can actually get donated back to a local food bank, so they can use it. And they could distribute it. I mentioned 80 billion pounds. That's 40% of the US food supply. That's 219 pounds per person, $1,600 per family. [music] If you don't have analytics, you don't have those numbers. And it takes a dedicated team of people to compile these numbers and try to figure out how to whittle that down. So you have these high-level numbers. Right? And so at each community level, it's a slice of those numbers. How are we going to address that? What can we do to address that? Well, one way is donor information. Keeping an idea of how many donors do you have right now? How much are they donating? Maybe you can have an initiative to encourage more donations, and maybe you hit that different-- maybe you have a restaurant that donates a lot. Maybe you want to go have a campaign that actually targets more restaurants in your area because this is clearly something that restaurants deal with. Why not get that food? It's donated. It's free. You get that information; someone will eat that night. CHRIS: 08:25 I mean, there are times in which I've-- growing up, I mentioned that I dealt with hunger. There are times where I've grown up, and it was a decision whether or not I was going to have something or my mother was going to have something. So these are decisions that parents have to make. And we have enough food that we shouldn't have to be forced to make those kinds of decisions. So let's try to cut in the gap. And so this is why analytics are important. And people shouldn't be intimidated by the mounds and mounds of data that are coming in. So just attack a piece, get one part of the story, get as much data as you can about that particular topic, that subtopic within the hunger, and address that. And then another topic comes up, supplements that. Then as you can see the domino effect will follow. You get information and more information that enables a person to make objective decisions on what should happen next: changing strategy when it needs to be changed, keeping things going when things are working, that kind of thing. MADDIE: 09:33 Totally. Yeah. You shared a really cool use case on the community that looks at food distribution centers. And I'd love for you to just maybe give us an overview of what that use case was. CHRIS: 09:45 Sure. The use case that I actually submitted focused around the San Francisco and Marin County Food Bank. We were doing some prospective work for them, and they've turned into a client. And the use case that we wanted to address there were, how many of their open food banks were located in areas that had a high amount of high-poverty households and elderly-populated households? So when I say open food banks, these are food banks-- they've had to close a lot of food banks because of a variety of reasons whether it be short on staff, whether it be just not able to be kept open for financial reasons. We just wanted to make sure that we had all of the open food banks placed on a map so people could see what areas they're able to support. So this was to set the stage for what we have for this particular use case that you can see on the community. And this really helped the organization make some decisions on what areas were being neglected, and what areas needed to be addressed by either food deliveries or mobile food banks. And mobile food banks are probably the quickest fix right now. This is one of the reasons why Spatial analysis is so important because you through a Spatial influence into all the other pieces of data. So we have a whole bunch of demographic data. Obviously, we have the location data for the food banks for this San Francisco area. You throw that together in a map, and it tells a complete story or at least tells part of the story where you might want to address. Because maps and points actually is the quickest way to visually represent what you're doing and how effective it's doing it. MADDIE: 11:33 Yeah. And I definitely want to get into the Spatial stuff as well. And I think, to take a quick step back, you had given a training, an Alteryx training, for food bank professionals. And I saw somebody introduce themselves in the chat as being on a data team at a food bank which I loved. I thought that was so cool that they had a team for people to think about these problems from that data and analytics mindset. And I wonder how common this is for food banks to have dedicated data workers as resources on staff. Because as you mentioned, food banks are closing, and they don't have enough staff too, just from an operational level. So I think from a analytics level and from a perspective of somebody trying to work with the data, I would imagine that that potentially is a novelty. But it sounds like it's absolutely vital. CHRIS: 12:34 It's more common than you think because the abundance of data that comes in daily to food banks is really astronomical. They may not necessarily be identified as data custodians per se, but they're responsible for bringing in data whether there have been data from volunteering numbers from a event that may have taken place throughout the week, meals provided to hungry families, how many pounds of food get donated to food banks as a whole. Everybody who works there is basically a data source. They are responsible for interacting with the public whether it be from a donation perspective or basically as a distributor on what kind of food or how much food gets donated to a certain area. All of that has to be tracked in order for the results to actually hit correctly in a certain area. So let me cycle back to the use case. We use Spatial analytics to identify the census tract areas that had high amounts of elderly populated and high amounts of populate poverty areas within the San Francisco area. Every community has to do this. The more demographics that you introduce to an analysis, the more complete your data will be, and the more objective decisions you can make as a result of that. Because the maps will tell you the story because you're combining it with a whole bunch of different aspects. CHRIS: 14:09 So let me go back. So we have identified where are high-populated areas of elderly people and high-poverty areas. So when we look at high poverty, we look at people making less than $10,000 a year, elderly 65 years and older. So we wanted to identify it because it's going to be harder for them to actually get anywhere to get food dealing with the COVID pandemic right now. Vehicles-- they may not have vehicles anyway, but public transportation may not be as readily available. So if you're in town and you're basically looking at on-foot, you're basically walking to and from. So this is where the Spatial came into play for me. Because not only did I want to plot where the open food banks were, I gave them a Trade Area of quarter of a mile to support those individuals who may be on foot. Quarter of a mile is basically how much I would-- we took a guess at trying to figure out what made sense, and how far people would walk for food, and how far people would walk back with a bunch of food that would be safe for them. CHRIS: 15:12 And so plotting that on a map and overlaying it on those areas of demographics that we discussed allowed the San Francisco and Marin Food Bank to say, "Okay. This is what this food bank is supporting right now. This is located in these areas. But wait a minute, we have these areas over here where we don't have a food bank." And we put it into a nice workflow in Alteryx, and then it output it into a PDF report which really hit home for a lot of our clients who are seeing this and it definitely hit home for the training. Because it is something that's tangible that you can hand over to a higher-up group that makes more financial assistance to say, "Here, this is what this workflow is telling you. This is what your data is telling you. And this is how it looks on the map. Please use this in your decision-making process on where money is going to go and where the next piece of strategy is going to take place." [music] So you mentioned the training. I'm happy to say that we have started a new discussion group, the Alteryx Food Bank Discussion Group, within the Alteryx for Good Community. And we had our initial training on Thursday. It was wonderful. We're going to build, and we're going to raise awareness. And we're going to make an area where other food banks around the country can feel confident that they can, A, get their answers from this area and, B, share their stories. The more collaboration that we can do, the better everybody around gets. MADDIE: 16:56 Yeah. It's so inspiring to see the conversations happening on the community and even just during that training in the chat. Because I think one of the things that really stood out to me in your explanation there, was just how important it is to remember that the people on the front lines - the people who are working at the food banks - every person there knows the backstory. And they know the statistics for their community, and they know the people in their community. And I think being able to add that color and have that personal on-the-ground experience kind of is almost more important than knowing how to draw a Polygon in Alteryx. Right? I mean, it's definitely important. But I think that those are the skills that you can learn, whereas the on-the-ground experience and the on-the-ground knowledge is so-- you can't just learn that. Right? I mean that's something that you really have to be a part of. And even collecting donor information or just how you explain to everybody that works at a food bank or a nonprofit touches data in some way, can be really empowering to recognize. Because I think that some people can be a little intimidated when it comes to, "Okay. I need to put together this analysis. I need to tell a story with my data, and there's high stakes because this could affect different aspects of the organization if I don't get it right." And so I think it's important to call that out, and I'm really glad that you did. It's something that is doable, and it's a skill that can be learned. And data literacy is really important, but it's definitely attainable for anybody out there who wants to try. CHRIS: 18:43 Indeed, and being a part of your community, I mean, there's a sense of ownership. I mean, part of the reason why I volunteer at the Oregon Food Bank is because this is my community; this is where I live. I've lived in Portland for eight years, and I see hunger permeate downtown Portland. I see it throughout the state. And being able to volunteer on Saturdays and being able to pack boxes or collect vegetables and fruits for hungry people that are going to be directly affected by the work that I'm doing, and doing with a bunch of people that day, is very fulfilling. Being a part of that data that's being collected is very fulfilling. You don't have to be a data wiz to do this. You don't have to be a Spatial wiz to do this. You are contributing to the story, the data story, that's being told that will help influence what happens next in that community. CHRIS: 19:45 So you had mentioned about Spatial and how people aren't Spatial wiz, wizzes around, and it's really difficult and can seem very intimidating. I am one of these people. I was terrified of Spatial. I wanted no part of it. I looked at these green icons in the Alteryx Designer, and I'm seeing Find Nearest. I'm seeing Create Point. I'm seeing PolyBuild. I'm just like, "Oh my goodness. What am I doing here? I am a fish out of water, and I am lost." And honestly, I have to give a lot of credit to a really good colleague and a really good friend of mine, Nicole Johnson. She's an Alteryx ace. She actually came to the Portland Alteryx user group and gave a really phenomenal Spatial presentation. MADDIE: 20:34 Of course she did. CHRIS: 20:35 There-- MADDIE: 20:35 She's awesome. CHRIS: 20:36 Yes. She is. She is awesome. And she really encouraged me to go outside my box and learn Spatial. And this is about a year ago. So what I did is I actually started off with the Grand Prix Weekly Challenge - I think it was challenged 129 - and she said, "Try it." And so I took the challenge. I challenged myself and really put my mind to it, took Spatial classes at the last Inspire Nashville, and really, really challenged myself to come up with different use cases that would require me to know some Spatial and enter the food banks. And this was just the perfect storm of being able to test things, and now I am not intimidated at all. The one thing I would probably tell you and tell anybody else who is starting off where I started off as being intimidated by Spatial, what I would say is that just don't, just dive right in. You use Spatial to do pretty much anything that you do in life anyway. You use Spatial analytics to find out which grocery store is going to be the closest one and the best one for you to go to. You're just not putting a fancy title on it. That's analytics. That's Spatial. Being able to do this within Alteryx, having the community to help you, guide you along the way to try to embark on this journey, you're in a safe zone within this Alteryx Community. All we want you to do is succeed. MADDIE: 22:15 That's really encouraging. And I know that we're talking to everybody listening out there, but I mean, I feel like you were just talking to me directly because I am definitely scared to start out with learning the Spatial Tools. And I think I was definitely intimidated to start learning Alteryx in general. But then once you just get started and you try, you realize like, "Okay. Yeah. I can do this, and this isn't that bad." And so I'm sure the same will happen with Spatial. It's just like that first initial step, for some reason, is always so difficult. CHRIS: 22:44 For sure. Whenever you learn something new, it's not going to be easy. And so the thing that kept me going is that once I learn it, things will become much easier. So yes, I'm going to go through some growing pains. We all do. Whenever we learn anything new, we go through growing pains. But being a business intelligence developer and working with databases and understanding how Alteryx can help me get better and actually do analysis rather than doing data prep for analysis, it gives me time back to my day. [music] And this is the thing that I always push to my clients and anybody else who is very curious about what Alteryx is. I'll say Alteryx is a phenomenal tool. It actually gives you time back in your day. It allows you to analyze rather than prepare to analyze. MADDIE: 23:51 Yeah. And I think this is a good time to plug our Alteryx for Good program which provides Alteryx licenses for nonprofits and students out there. So we'll be sure to link to that in the show notes, so people out there can learn more about that. If you work at a nonprofit and you're interested in getting that time back in your day, as you said, it helps you analyze instead of preparing to analyze. I think that's so important. And for people who do get an AFG license, what is a piece of advice that you have for them? You mentioned just dive in and try. But I think also, how you and your use case used that census data, how do you know to do those things? And how do you know how to enrich your data and provide an analysis? Or even how do you tell a great story with your data? How do you get started with that? CHRIS: 24:49 Well, even though I've only been in Alteryx for about 3 and a half years, I've been in analytics for about 24. So one thing that's always helped me is that I don't always focus on the primary question, and when I'm gathering data, I just gather data. I get every piece of data that I can get my hands on. It may not answer a primary question that was proposed, but it's surely going to formulate something down the road. So when I look at the primary question, I look at the data for the primary question. But you also have to think two or three moves ahead. You have to ask that secondary question or that tertiary question which will inevitably expose something brand new that you haven't even thought of before and that only goes through just talking something out. It's like-- not to use a pun here. So it's literally a workflow. Get every piece of data that you possibly could get. You can't create something that's not there, but you can always hold something in the back for when you possibly need it. Data is your friend. It's when you don't have data is when you cannot make decisions, and you cannot make objective decisions. Because when you don't have data, your decisions become subjective, not objective. And you want the objective piece to win. MADDIE: 26:17 I love that advice. And jumping forward then to actually working with the data. If you have any sort of secret weapon in your back pocket when it comes to using the Spatial Tools in Alteryx, I want to know what that might be. And this might be a little hard to explain over audio, but we'll be sure, for our listeners, to link to any of the concepts that Chris talks about here in the show notes. But for example, we had emails about multilayered Maps and Polygons and Trade Areas and like all those things. So if you want to introduce any concepts to our audience about those things that would be awesome. CHRIS: 26:52 Sure. I'll actually take you through the thought process of how I came up with the multilayered Map for this instance. So I was given an Excel spreadsheet of all of the open locations, all the open food banks within the San Francisco, Marin County supporting area. And what we wanted to do is try to create a Spatial use case that would make sense. So what I wanted to do first is that I didn't want to join the data. So I wanted to create a point on the Map with all of the open food banks. But I also wanted to analyze the demographic information that we got from our Business Insights package. So I wanted to take the household data and create a Polygon so that those Polygons would be able to be evenly distributed amongst the city, and this could be any city. I did it for San Francisco in this case. I also did it for the Houston Food Bank. And I sent it through the training. But I wanted to create a Polygon so that the Polygon would be able to be color coded based on the volume of households within that demographic. And so normally, what you would do is, you may want to join those two pieces of data together to figure out where exactly they meet as far as the matching is concerned. I didn't want to do that. I wanted to do a simple overlay because the overlay will tell you more of a story of where you need to go. CHRIS: 28:24 So I just had the addresses. So I use the Geocoder to create the Lat/Long. Then I created my Spatial points. And then after I did my Spatial info, I created a Trade Area using the Trade Area icon and tool. And so since we're dealing with San Francisco which is a really small peninsula, we wanted to make sure we had a Trade Area that actually made sense. So we decided upon 0.25, quarter of a mile, to symbolize the walking distance. So after I created that point and created the Trade Area, now I have the first part of what I wanted to do on this map. Right? So I wanted to be able to create the point and create a little circle around that point to promote which areas, the radius, in which that food bank would support. CHRIS: 29:21 So the next thing I would do is go ahead and create the Polygon layer. And the Polygon, actually, there are a couple ways you could do it. So one way that I did it is that I went through the Allocate Input and chose the census data. And one of the things that you can have as an output is being able to output actual Spatial object field which would be in this case the Polygon. So I satisfied my requirements as far as choosing the high poverty or the elderly population. I think in my training, I actually focused on age 45 to 54 because integrating the census data from the household Pulse survey which was something new that we added - I'll get to that in a second - it actually exposed that the most hungry people, as far as the age group was concerned, was the ages 40 to 54 in a lot of these metropolitan areas. So I switched that a little bit to try to bring that point home and created a PDF report that actually combined all of that data to provide a case for that. This may help, leading into more funding to deal with that particular problem. CHRIS: 30:33 So getting back to the Spatial here. So I've created my Polygon, and I've created my Spatial point with the Trade Area. I want to overlay those guys. I want to make sure if I overlay these guys, then that actually tells a story on, "Okay. This is where this point is, and this is how it lies within all these polygons." So I created some layers in the map, so I had those two streams flowing in. And then I created a color code. So the color code was based off of the population of the demographic that I'm dealing with so specifically the age range. And what Alteryx does - and it's really awesome that Alteryx is intelligent enough to do this - is that it will take all of the measures generated, the numbers created, and it will create five even fields or even breakdowns of that data. And then you can decide how the color code goes. I like to go from red to blue so the red being the most highly populated and blue being the least, and being able to have those colors be identified. CHRIS: 31:41 So you have the polygons on the bottom, and then you have the points and the Trade Area on top. And when you layer those guys it comes up to a really nice perfect type of situation where you have all your points without any bounds as far as the drawing is concerned on a map, in front of your face to say, "This is what your data is telling you." So we added another aspect to this. So I have the map, and I have the points on the map. And that's really, really cool. So more is better in some cases. So I wanted to bring that home a little bit more. So the census data actually has some household survey information off of its page that is free to download. So what I did is that we went in there and took that information, downloaded 11 weeks' worth of data, and put that into a repository and included that analysis as well as the map into one report. So we took that and took, I believe it was 2B of-- or 4 actually, of food sufficiency. And we identified the hunger, what age groups were hungry for a particular week. And then we did a rolling 4-week average to get a more stable trend on what was actually happening because sometimes the week-to-week can fluctuate. So the rolling 4-week average was actually the decision maker why I wanted to choose a certain age group to focus the map on. So once you have your layered map, it turns into a reporting exercise. CHRIS: 33:33 And one thing I wanted to say, is that the Alteryx reporting capabilities are very underrated. It can provide you a very slick and informative business-style report, especially if you don't have a reporting system on the back end to develop this. We were able to create a really comprehensive report with a cover page, with maps, with a line chart just like we did in the training, and so this is what we came up with. And delivering that to a client and having somebody say, "Here, this is what we've come up with, with your one piece of data. We got one piece of data which were the addresses of all the open food banks." And me and my company, we were able to go ahead and take that one spreadsheet and turn it into this. So it's something that everybody else can be confident that you can do as well. And the nonprofit organizations that we have been trying to service and educate about what we've done, this is something that you can definitely do because you have the blueprint now to do it and then expand from there maybe. There's so much data to be had. This census data that we just found, that's free. Anybody can get that. So the business insights becomes important because we were able to create the Polygons off of the demographic data that already existed. So we combined stuff that already existed along with new information, and you can combine even more information into this workflow that could get an even better story. So along with that, "the more data is better theme" that I'd like to make sure gets known, is very applicable. MADDIE: 35:28 Totally. Yeah. And it's so helpful to hear you kind of break down the concepts. Because if you leave it at a category, if you just say, "Oh, I'm going to try Spatial," I think it can be kind of mystifying. And so breaking it down and saying, "You can do all of these different things with it," and just tackling them one by one, I think, helps to really demystify it. So that was really, really helpful. And also, super cool to hear how you took that spreadsheet, and you turned it into this ridiculously helpful and easy to visualize report. I think that's amazing. So we'll be sure to link to everything that Chris just talked about, as well as just some other resources that are out there on the community, to help people kind of understand and get a better idea and follow along with what you were saying. CHRIS: 36:12 Wonderful. And the one thing about Alteryx - and this is just a general Alteryx statement I'm about to make - is that it makes data investigation, and data processing, data blending fun. Because, really, you get instantaneous results as soon as you run a workflow. MADDIE: 36:32 Yeah. That's amazing. And this has all been so inspiring. And for people out there that are looking for maybe skill-based volunteering opportunities, maybe they are an analyst in our community and they can do the same thing that you're doing, how do they approach that? How do they find these opportunities? And maybe for people even who aren't looking for skill base but just in general, where are your favorite places to find these opportunities and get involved? CHRIS: 37:01 I think, hopefully-- and this is the whole reason. One of the themes behind why I wanted to start this discussion group is to post there - we have a thread; hopefully, we'll turn it into something bigger - and just throw your hat into the ring. Maybe go find a local facility and just ask them, send them an email, give them a call if you want. If you feel comfortable enough, drop by. It's really as simple as that. I mean, you don't have to have an out-of-body experience to contribute. It may be as simple as just asking question one or sending one form of communication to anything local that you can find. I mean, everybody has data that could help you. And hopefully, I've been able to shed a little light on how you could start. MADDIE: 37:55 Totally. CHRIS: 37:55 Because Alteryx for Good is fantastic. They know of a lot of opportunities. I mean, yeah, you can feel free to reach out to me. I'd be more than happy to start a discussion with you about opportunities that I've seen. In addition to, I mean, obviously, you've seen the use case, but for that one use case, I've seen probably at least 8 or 10 different requests outside of that. So let's start a conversation and figure out where it goes from there. MADDIE: 38:23 Love it. Well, thank you so much, Chris, for joining me. I'm so glad that we finally got to make this happen. And it was actually kind of cool, I guess, to do kind of like a one-year follow-up from our last conversation. So yeah, this is great. Thank you so much. CHRIS: 38:37 [music] And, Maddie, thank you so much. It's really an honor to speak to the community. It's an honor speaking with you, of course. And let's do it again sometime. MADDIE: 38:44 Totally. Yeah, anytime. Thanks for listening. If you're interested in learning more about our Alteryx for Good program, Chris's Alteryx use case, or anything else discussed on today's episode, check out our show notes at community.alteryx.com/podcast. And while you're there, register for a free community account. You can learn more about Alteryx, join in on the conversation, and connect with over 175,000 users who are passionate about data. Catch you next time. MADDIE: 39:25 Perfect. You're a professional. So I'll cut it there. CHRIS: 39:31 This was fun. Was it okay? MADDIE: 39:33 It was awesome. Honestly, the entire time, I'm like scrambling writing on this piece of paper. I'm like, "Okay. This is a Tweetable quote, Tweetable quote," like everything that you said, I think was just a perfect soundbite. So yeah, I mean it was killer. You nailed it.

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

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70: Mapping solutions: using Alteryx to serve community food banks

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

Alter Everything Podcast

Podcast Guide

70: Mapping solutions: using Alteryx to serve community food banks

Panelists

Topics

Transcript

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