Okay, good morning folks. This is the morning meeting of the House Appropriations Committee on Friday, April 9th. And as happens after we complete our budget work, and if we don't have any bills that urgently need our attention, we take this opportunity to learn. And sometimes we look at aspects of state government or sometimes we look at other sorts of topics and I invited Joyce Manchester with the joint fiscal office into have a presentation. I'm sorry about the dog on basic income and I'm going to stop talking so I can mute the dog and I'll turn it over to unmute myself, not the dog. Joyce, thank you for joining us. Thank you very much. Good morning everyone for the record I'm Joyce Manchester from the joint fiscal office. On Wednesday I was asked to prepare some notes about the program that's known as universal basic income. Sometimes it's called guaranteed minimum income, and we'll talk about maybe a semantic difference there. The basic idea is that a universal basic income program would provide monthly payments to households or individuals with no strings attached, and it's meant to cover some basic necessities. But it does not require work it does not require a certain income level. It's simply meant as a payment to help folks do better in their daily lives. Your opponents see it as a way to alleviate poverty, reduce inequality, or provide a more robust safety net to workers and rapidly changing labor markets. So the idea is that you get this money and that frees up some time and some energy so that you can decide what it is that you need to do to to have a better life. The problem is that there have not yet been enough experiments out in the real world to know exactly how people would respond to receiving this monthly payment to use however they please. So, there have been some interesting experiments in in some recent years and we'll be talking about those in just a minute. First I want to address the term guaranteed minimum income because that is a term that you often hear. And I've, I've sort of decided that some people use it one way and some people use it another way. So quite often people use the term guaranteed minimum income. When they're thinking about a program that says every person or every household should have an income of at least x, and maybe x is 40,000 or maybe it's 20,000 or maybe it's 10,000. But if you're already working and you already have that amount of income coming into your home, then you don't receive this guaranteed minimum income. And every household should have at least some amount. And if you've already got that amount coming in then you don't qualify. On the other hand, the universal basic income program would say every household gets a payment regardless of what other activity is going on in the household you could be working you could be getting a pension you could be who knows having independent source of income, but every every household could get this income. So I'm using the term universal basic income today to talk about a program in which all households would get a certain amount of income per month. Okay, so why are we hearing now about universal basic income. Well, I've got a little bit of history here just because I thought it was so interesting. And it turns out that people have been talking about universal basic income, since the early 16th century in Europe, and Thomas Payne our very own American Thomas Payne promoted it in the late 18th century here in America, specifically for young adults, he felt that this was a good way to help young young adults get established in the new world. So it's sort of hung around for a while. And then in the 1960s, a letter was signed by about 1200 economists calling for guaranteed income for every American and there was quite a lot of discussion at that time about such a program, and it helped lead to a minimum income payment by the Social Security Retirement Program, and also in the Social Security Disability Insurance Program. So now there is a minimum amount that every Social Security recipient would get if they work a minimum number of years at some wage level. So in 2016, there was a lot of discussion in Switzerland and there was a referendum which ultimately rejected a basic income program but again it did spur a lot of conversation around the issue. And you may remember that presidential candidate Andrew Yang proposed $1,000 per month to every American with no requirements. So that's a huge universal basic income program that did not come to fruition but it was certainly out there in the policy discussion. So now we come to the present day and we've seen that COVID-19 has hit a lot of people very hard. And so lots of countries, many, many countries have been discussing basic income and cash transfers. And as you know, the United States provided these cash payments $1,400 per individual to many, many people there was an upper income limit, but lots and lots and lots of people received that payment. And also we've had a reduction in the employment requirement as you know, currently if you are unemployed you do not have to be actively searching for work in order to receive unemployment insurance benefits. So that's a big change and it makes the unemployment payment more like universal basic income because it does not require that you be actively looking for work. And you should feel free to interrupt as I'm going through this. There's lots of interesting stuff going on here. So then we get to some recent universal basic income pilot projects that have been taking place. And some of these have been evaluated so we can actually think about what the results have been. The most prominent one has taken place in Stockton, California Stockton is a town that's what east of San Francisco south of Sacramento, not not a very well to do town. The mayor back in 2018 2019 was Michael Tubbs and he really spurred the the universal basic income pilot project in his city. It was called seed the Stockton economic empowerment demonstration. It was funded completely by philanthropic interests. So no tax money was used to to pay for it. Let's see recipients had to be 18 years old. The median income median household income in the city of Stockton was about 46,000 and recipients had to be living in a neighborhood where the median household income was not greater than 46,000 so these were not the folks living in higher income neighborhoods within the city. But if you lived in a neighborhood with median income 46,000 and happened to have higher income, you still could be a recipient of this of this program. So what's interesting to me is that the town, the city of Stockton arranged to have waivers so that there was no reduction in other safety net programs. So if you were receiving food stamps or rental assistance or pensions or other other unemployment insurance, those benefits were not reduced. You simply received an extra payment. And in this case it was $500 a month. And after discussions with community folks they decided to issue it via a prepaid debit card, so that nobody could feel that they were left out of the program because they didn't have a banking account or they didn't have a way to access the money and so forth. So they were mailed a prepaid debit card for $500. Okay, so this was a randomized control trial. And if you're familiar with experiments out there in the world of social policy you know that randomized control trials are the gold standard. But what happens is that you find a lot of similar types of households. You assign some of them to receive the benefit, and you include the others who don't receive the benefit, but they are the control groups so you're looking at how they behave relative to how the recipients of the monthly income would behave. So this program started in 2018 and I'm sorry in February of 2019 it actually got underway. And after February of 2020, a research group was was able to access a lot of data and study the results. So, oh yes, I forgot to mention the entire program cost about $3 million. So that's that's what it costs to get it going. And we now have these results after one year of the program. So here are some of the results that have been found to date. Now this is from the first year of the program and there will be even more research conducted once the program is completed after the two year stint. But this is what they've found so far. We have recipients experience less income volatility over time, and relative to the control group. So, here's an example of why you want to have a control group, maybe that the city of Stockton was on an upswing from February 19 to February of 2020. And maybe everybody was doing better. Okay, so this control group allows you to compare the recipients to the folks who did not get the extra money. Yes, there was less income volatility among the recipients. Secondly, and this is the result that's probably gotten the most attention recipients obtained full time employment at more than twice the rate of non recipients. So, the idea is that if you have extra income, it may mean that you can take a day off from work and look for a better job, or get the certification for the work that you're doing, or enroll in a an evening class, because you can afford a baby center for your kids, it just might offer enough flexibility, so that you can do other things. Should we stop for a question. Yeah, I did, but I'm going to assume you just called on me so thank you, Chair. Joyce, thank you. So I'm reading the footnote regarding the income fluctuation I just want to get a good definition so that I can understand that the footnote states that recipients income fluctuated 46.4% monthly so let's just round it to 50% and I'll give you an example of what I think it means. If your income was just pulling number out of the year $100, it could go down to 50 or up to 150 on a monthly basis is that is that what this, you know what the study is found. Yes, that's right. It's actually the coefficient of variation which means it's the standard deviation divided by the mean, but you don't have to get that statistical if you don't want to. So, okay, so I think I think you're on the right track. Okay, thank you. Okay, so, so now we're talking. Sorry, Joyce, another hand, Jim. Thank you, Mary, we can just call on ourselves if you that's easier. Joyce, it's interesting in looking at this. Stockton example and some of the results from the, you know, study. So, they couldn't pick the worst time with the pandemic starting in 2020 because, you know, kind of begs the question with the world turned upside down.  But does it attract people and sometimes there's barriers to picking up and moving across the country, but I would think in a city, you might actually be able to measure that because you've got neighboring communities that wouldn't be that hard to move in, but maybe they put some, you know, barriers to doing that I'm just curious if they measured that at all what's or any change and maybe a year too early to, to knew where it was just a pilot. Participate in the program you had to be a resident of Stockton at the beginning of the program, and they're going to follow the same people over two years so I don't think it's possible to move in midstream and become part of the program. So I wanted the continuity of the same people in the program for two years. Okay, thank you. Sure. All right. Now we're good so we're talking about this employment effect and I will mention that this is a big deal in part because other experiments have not found an employment effect. There's going to be a lot more investigation of exactly why this has happened in the Stockton experiment and not in other experiments. I want to put a little bit more specifics on this. The recipients who are employed full time went from 28% of recipients to 40% after one year. And if you look at the control group, they, they went from 32% up to 37%. So, a 12 percentage point increase for the recipients and just a 5 percentage point increase for the control group. It's true that the second year of this experiment is really going to be influenced by the COVID-19 experience, which is in some sense, very sad, because it's going to put a new wrinkle into all the results. On the other hand, they're able to see how having this basic income will help people during such a big economic downturn. And that could provide some some really good insights. So, about a year from now we will tune in again and see what the results look like. Joyce, we have another question. Bob. Yes, thank you. Just quickly, what would, can you give me an example of what a philanthropic income dollar is? Well, so these are primarily nonprofits that are in the business, well, not in the business. Their goal is to explore different social experiments. So, for example, there's the economic security project who donated a million dollars to this pilot project, and they receive donations from regular people from corporations and so forth. And their goal is to try to test some new ideas and see what works out in the real world. Yes, but in, and I won't, I won't go any further than this one. I kind of thought kind of that, but California's a lot different than Vermont, as far as available. I don't have money's in that respect. Or I certainly would think so, you know. So that may be I, I have not investigated where all the philanthropic dollars came from but I would imagine that some of them are coming from nationwide nonprofits not necessarily just located in California, but we can look into that. Yeah, right. Thank you. So, so we've talked a little bit about the employment effect and how having this basic income may just allow people the freedom to explore more avenues for future employment and, and getting certifications and so forth. And there are some other notable results as well. For example, recipients were less anxious and depressed, both over time and compared to the control group. And of course when you're less anxious and depressed you probably do better on the job, and you probably are more willing to think about what comes next step after your current job. So I saw statistically significant improvements in emotional health, fatigue levels, and overall well being. And again, these are all measured using instruments that are known to people in the, in the world of measuring mental health and emotional well being and so forth the Kessler 10 and the SF 36, which means nothing to me but probably means something to some of you. And so, the researchers also asked, if you had an unexpected expense of $400 this month, how would you pay for it. And at the beginning of the experiment, the recipients 25% of recipients said they could pay for it with cash, and the others would have to borrow money who knows where they would borrow it from but they didn't have $400 in hand to pay for an unexpected expense. But after a year, that number went up to about 50%. So about 52% of people were able to pay with cash for an unexpected monthly expense. Yes, and the researchers did say that that that could be particularly important given the pandemic that hit everybody shortly after the end of the first year of this experiment. The researchers also asked how people spent this basic income, and about 37% of the money was spent on food, about 22% on sales of various kinds merchandise such as home goods clothing and shoes, discount dollar stores, about 11% on utilities 10% on auto costs, and 21% on alcohol and or tobacco. So this has always been a big question, how are people going to spend the money are they just, you know, spending it on frivolous things or are they spending it on necessary things so it's important to, to look at the data on that. So that's where we are on the Stockton pilot project some of you might have heard the NPR story Wednesday morning which spurred some of the conversation that led to this investigation. So, it is getting some attention and I, I expect it will get further attention as time goes on. Okay, so we can move on to a few other examples and I know much less about these other examples, but it's interesting to think about how different experiments were conducted. So Ontario established the basic income pilot project in April 2017. The pilot project was set up with the goal of giving fixed income to people with with lower no income so again, an income threshold. The project was supposed to run for three years. So this experiment, if there was other earnings. So if people had a job, their basic income was reduced 50 cents on the dollar. So if you earned $100 a week, your basic income was reduced by $50 a week. Okay. After about a year, the government in Ontario changed from the Liberals to the Conservatives, and the program was stopped. So instead of three years of data there's about one year and a few months of data. And of course, people felt rather annoyed, upset, and frustrated that the experiment was stopped midstream. So, there were very few employment effects detected in that experiment, but recipients did say that their health self esteem and job prospects were enhanced. That's the Ontario project. Now, this is an interesting one in Finland. 2000 unemployed folks were given about $600 a month for two years beginning in 2017 no strings attached. This was the first nationwide basic income experience, but it was not considered a big success in part because employment effects again were minimal, only a very small difference between the study group and the control group in terms of finding work. Again, the recipients did report statistically lower levels of insecurity and stress. This may be that in Finland, of course, many basic needs are taken care of by the government. So you have health insurance, you have childcare, you have lots of things that are quite different from the way the world works in the United States. Joyce, we have a question, Robin. Yeah, thanks. And thanks, Joyce. That actually was going to be my question or comment because as a Scandinavian country, I know they offer much more in the way of support. So I wonder if there's any way to control for that or, you know, look at the data in a different way because maybe it's a success in that it's less needed because there are other supports. I don't know if there's a way to look at that differently because it really isn't comparing. We have much, much more unequal distribution of wealth in our country and they do not. Absolutely. And I think as there are more experiments in different countries will be able to control for those other social factors that will give us a better understanding of what what programs would do in different settings. Okay, so this doesn't surprise me that it would be less of a success and that it would be more in a place like Stockton where the inequality is so much greater. Great. Thanks. I'm going to wrap up. I see I've just about run out of time. There's an experiment going under going on right now in Kenya, with a very high level group of researchers running the show in terms of collecting data and evaluating it. About 15,000 households in almost 300 villages in Kenya were randomly assigned to either no payment or a payment monthly for 12 years. So remember this just started in 2018 and we'll go on for 12 years. Another group will receive payments to cover basic needs for two years. And then a fourth group will get payments to as a lump sum. So just a $1,500 payment. And the experiment, it seems to be really well designed so that they can look at the various outcomes from all of these different groups. They've got a Nobel Prize winner, Abhiji Benerji, who is well known from MIT, who's going to be helping with that evaluation. So let me stop there. I see we're almost out of time. Yeah, thank you, Joyce. That was, to me, very interesting. And I had not realized that so much was happening, nor that the history of this, which I particularly enjoyed. Dave. Are we wrapping up at 930 sharp? I'll try that. Not at sharp. I think. I'm set. And that wasn't my question, but I'll try to be succinct. Joyce, could you imagine some type of hybrid in Vermont? We provide a lot of cash assistance to people. None of it a full therapeutic dose. If you're eligible, we say here's money for food. Maybe cover 30% of your food allowance. If you're eligible, we say, here's money for childcare. Doesn't cover the full cost of childcare. If you're eligible, we say here's money for housing. Section eight, you could argue might cover the full cost of housing. We provide significant amounts of money. If you're eligible for reach up, here's a monthly cash assistance doesn't cover enough to make ends meet. But if you add it all together, it's not insignificant. But today it's very categorical. If you're eligible for reach up, it's not significant enough to meet the needs for which it's it's given. Could you imagine going to the federal government requesting a waiver to pool those dollars, and then not for everybody, it wouldn't be folks, perhaps like us, but for certain income categories, and with financial coaching, etc. I would say to a person and say, with certain parameters, how would you like to use this money, and you might say, you know, I'm going to nail the housing because I want to be stable I want to have a place where I put my head on the pillow and not worry about it. I'm going to get some reliable transportation. Then I can get a job and I'll take care of my food budget, but it's more independent you might feel better about things and it might be more productive. Is there been any pilots or waivers along that line that you're aware of. Thank you. Right. So that's a great question and that's exactly why people are studying the experiments in Kenya so carefully because of course there is that lump sum. And it says here's a lot of money, you can decide how to use it some people might decide this is the time to to invest in education, and I'll skimp on housing and I'll skimp on food and whatever. Other people might decide this is the time to start a business and I'm going to plow the money into a business and so forth. So, yeah, that's the best experiment that I know about that would say, just give people a basic income and let them decide how to allocate it among the various needs that that they have. Absolutely. Yeah. So, um, Dave asked the, the more detailed question that I had had in my mind, and I was just up at the kind of boy we've tried lots of different ways to alleviate poverty, and have spent so much money over the years. In fact, there seems to be more poverty now than at least times in the past we certainly haven't made the progress that I think folks had hoped or thought we would coming out of the 30s and 40s. I'm not proposing that we do something like this but I think this is an interesting question about, can we be rethinking about how, how we support folks who who are trying to climb their way out of difficult circumstances and that would that was some of my thinking behind just asking for a presentation on it not not because there is a proposal coming, but just what we're doing doesn't seem to be working as well as we had would hope, and is there a different way to think about this. I'm not seeing any more hands and I know that we're past 930. And I just let me say, thank you very much, Joyce. And I know that you're planning on turning this into an issue brief when you have a chance and maybe it's something we can continue to use the term of art, noodling on over time. Peter. I know this is interesting. I, I, you know, I enjoyed seeing how people felt about about these, these funds and receiving these funds on a whole different topic. Hopefully, did you see my response email regarding the the pension sheet going forward. In other words what our a deck would be going forward we need to get that updated. And understand the, the, the results of the, the input results of the experience study and how it's going to impact future payments. So we do need to get that that that updated, perhaps made it can contact the the treasurer and ask for that updated sheet or we can ask Joyce Manchester to add to ask Chris Roup to, to get that together or both. Yeah. So, thank you Peter yes I did see your email and, and we will get that information. So, let's say thank you to Joyce and let her get on with her day. Appreciate it again thank you for responding so quickly to our request. Thank you and if folks have other questions just send them along because I do plan to finish up an issue brief in the next week or so, so if you have more questions let me know. Okay, good. Thank you. Bye bye. Folks, we, the floor is now we have, you know, been scheduling things for next week we are not meeting on Monday we will meet on Tuesday. I forget what time. So far it's the afternoon starting at 115. So pay attention to because we're on the floor in the morning. So pay attention to email just to see how the agenda gets updated. Yes, I see any other questions or thoughts Robin. So we're done for the day in this committee. Yeah, yeah. Well, you picked a lovely couple of days for this we appreciate it madam chair we, we need the spring weather and to get restored. I think restoration is in order for all for this committee you guys worked really hard. So my thanks have a terrific beautiful weekend and we'll see everybody on Tuesday.


Hey everyone, happy, happy hour. It's Las Vegas. It's always happy hour here, but it's literally happy hour at Snowflake Summit. Day two of theCUBE's coverage of Snowflake Summit 23 live from Caesar's Forum in Las Vegas. Lisa Martin, Dave Vellante. Dave, what's your summary of all the conversations we've had about data, data strategy, AI, in the last 36 hours? data matters. Yeah, no data. I think the key is people really, to really get to be a digital business, you got to put data at the core. So you have to have a data strategy that gives everybody access to that data, consistency, coherency across the data platforms. Absolutely, data democratization is no joke. We've got a couple of guests here. Amit Rai is here, S.B.P. of Data as a Service from Zoom Info, Andy Reffles, Director, Sales Operations and Strategy at Capital One Commercial Banking. Guys, welcome. Thank you, thanks for having me. I can't wait to connect the dots on this one. Yeah, Amit, let's start with you. Zoom Info at Snowflake Summit. What's, I'm going to do a Jerry Seinfeld. What's the deal with that? Yep, great question. First of all, thank you for having us here. If you think about Zoom Info, Zoom Info has historically been very successful on the sales and marketing side. We are world's largest B2B commercial data provider when it comes to sales and marketing. The reason we are here at Snowflake is because folks like Andy, who are more on the data analytics side, they are actually using Zoom Info, all the company data, contact data that we have gathered over the last two decades. It goes directly inside Snowflake and then they are able to do predictive modeling and that's what acts as a data foundation for the modern go-to-market engine. So when you think about formographics, technographics, intent data, who is currently in the market, all of that data is directly available to the data analytics and data science team such that they are able to do total addressable market analysis, ideal customer profile analysis and they are able to be prescriptive, proactive rather than reactive and old traditional ways. So that's why we are here. Wow, cool stuff. Andy, talk a little bit about your role at CAP 1 and why did you choose to work with Zoom Info and stuff like? Yeah, so at CAP 1 I'm in the commercial bank and I help drive enablement for our sales team. I would call them RMs if I say RM, relationship managers. And so for us, for our commercial bankers, it's a relationship business. They have to know a lot about the company. We want to provide them the right tools to do prospecting work, find who's out there, as Amit said, like what is the universe? And connecting the dots with third-party data with our internal database that we build and grow is imperative. So my job is to bring the information to our sales teams as easy as possible, right? And I'm not working with technology, they're not all tech people, so I have to make it simple, get it into delivery method. It has to be something that'll meet them where they are. And so we've had a long journey with Zoom Info and there's a story we'll get to about some specific data that we had and we were working on spreadsheets and people were getting us requests and it was wildly inefficient. And so our journey started with a very simple use case that led us to a much more streamlined and collaborative place we are today. Before we get into that, what's the hot products today that you're marketing? Oh, so again, I'm on the commercial side, so our hot product is money, right? So you want a hundred million dollars. So you're talking loans, right? We're talking loans. What are hot markets? Is it not commercial real estate, I presume? We have commercial real estate part of the business. I'm on the middle market banking side. So again, specialty-driven, middle market companies. So you talked about really important things. TAM, ideal customer profile and intent data, right? So I presume the ICP has changed as interest rates rise, as commercial real estate gets, you know, office vacancies are open, et cetera, things change. And so as we get into it, I'm really interested in how as the market changes, as the TAM expands or shrinks, as the ICP changes, intent data is constantly changing, how you deal with all that. So this is a fascinating case study. Yeah. Okay, so where'd you start? So we'll start with intent. So the part where we started with them was we had specific intent. As you said, Zoom info is a good job of telling you what companies are out there. And that's great for our sales team. But to know who is active in those markets, all right? With our big companies, we can go to firms like, say, Bloomberg, right? And they have big data on transactional information. On our smaller private companies that our team tries to work with, very hard to find out who is active in the market. So we work with the team, with them in the team at Zoom info years back now, building out a way to consume data around UCC file, like liens, the company would file. And it's filed state by state. So what that tells us is data, you can get it. You can go to your local state. Every state gives you information a little differently. And you could say, hey, show me all the companies that are actively with Capital One, right? That will give you an idea of who's active in the market borrowing money, or, you know, having borrowing. But the very manual intensive, very specific state by state. So working with a team on delivering a widespread, a one data file, bringing it into our universe. So now, instead of a hundred different sales teams, RMS, coming to me with a request, we put the data in one place, give them a report, they can get to it themselves. It's in our, it's in our lake. It's in our world. They can access it out. We can, you know, data analysts can pull it out for them. But it becomes more of that self-service model. And we've just made it so much easier for them to interact with this data. And again, it's intent. It's showing them who's active. So your question, David, like, I may not be as active now, given what's going on markets, but I'm going to be active, right? It's like just to scale changes a little bit. I'm always going to be prospecting. And this information lets me know who is there. You're building pipeline. Building pipeline. So what is, what is your ideal customer profile and how is that changing? I mean, that differs, right?  We have some specialties. So again, customer profile can change largely, again, by industry and then the size of that company. You're loaning tens of millions or anywhere from small to large, hundreds of millions? Yeah. Is it, is it, is it big spectrum or is it? You're going up to billions of dollars in certain cases. But what's the low end? Is it, is it? In our business, so yeah, good question. Capital One has a lot of different business segments. We have retail, small business, right? And my, my world, our low end is maybe million dollars, right? So it's, it's nice. So pretty low end then. Can be, can be. Million dollars is a lot of companies out there, even small businesses that can, That's right. Can tap that type of credit line, right? That's right, that's right. So again, you're trying to loan deposits, right? Full treasury management suite, full cash management suite, right? Capital markets, products for those companies. So it is, it's a full commercial. So things are tighter right now. I mean, the Fed's obviously tightening. We're listening to them today. They still sound pretty hawkish. Okay. So you'll build pipeline to, you have existing relationships, obviously. And, okay. So you want to expand those. And then you want to build new, new relationships. And that's where Zoom info comes in, right? That's right. That's right. Maybe to deepen where you already are. And then if you're adding new folks in new areas, that's what we use them for. Yeah.  Yeah. I think just to double click on that, one of the amazing things about B2B that a lot of folks don't know is that getting basic information for companies, like revenue of a company, you said $1 million, employee-sized location industry. When we started our journey with Capital One, they actually had information for only 15% of their low-end customers, 1.5. That was one of the best case scenario for Capital One. That is actually true, even for all the Fortune 500 companies that I've worked till today. Large companies that sell to smaller businesses, even those basic information for revenue, employee-sized location industry, they have no idea about that. So when they partnered with Zoom Info, the number one value that they got was, now they were able to segment close to 70% of their low-end business, 70, from 15 to 70%. And that resulted into massive ROI. So in the world of big data that we are talking about, one of the biggest challenges that Capital One had was, they were using spreadsheet siloed systems. When Andy and team got together, one of the things that was a pretty big win for them is, now they use Snowflake as a customer 360 repository, where third-party data provided like Zoom Info is able to provide them data for all the 32 million active businesses in the United States, and more than 100 million locations. So now once you have that data, now you can do predictive modeling, now you can do net new acquisition, now you can serve the existing customers. So that was a pretty big value add, which continues to be very, very major challenge for almost all the companies that we have talked with. How are you dealing with the changing waves of PII and privacy, et cetera? Great question. So a lot of folks don't know that a lot of these PII things are not applicable when you are talking about business, because Zoom Info is all about business data. What is the revenue of the company? What is the employee size of the company? What is the industry of the company? So that's part number one. Part number two, we treat businesses as humans, meaning what are the people in those companies that are looking for products for your business, not necessarily like behavioral or personal information? So bottom line is we are able to uncover what are the businesses that are currently in the market for your products? Again, PII information is not relevant because we do not want to get into personal information. That's number two. Number three, when it comes to privacy security, again, like partnership like Snowflake and things like that, our customers' data never leaves their premise, so data share, security, governance, all of those things become applicable when you are using infrastructure like Snowflake. So you've replaced spreadsheets and now people access Snowflake directly or you're developing reports. We brought via Snowflake in through our, some tool, right? We use Salesforce for reports, right? So we're reporting on there, we have Tableau, we have QuickSight, but we're connecting our sales team, they're not going into Snowflake themselves, but we give them access to these tools in one of those fashions to access this data. So it's Snowflake's in the back end and hidden. Go in its thing and I'm representing the guys that they don't know any of that stuff, behind the door, it's closed, they just want to see, I'm typing in, I'm in, where are we? We're in Las Vegas, I need companies of a certain size in a certain industry that are not already in my database. So it connects, now it's not just a spreadsheet that I get from Zoom Info, it's connected to what I already know about. And so I can eliminate things I already have and show me stuff I don't have. So huge transformation, Andy, going from manual spreadsheets that's just kind of like, ow, that hurts, to completely digital backbone, digital transformation, how long did that take and how did you get the cultural and C-suite buy-in to drive such massive change? I told them how angry I was about building spreadsheets all the time. It takes time. It takes time. It takes salty. Some people like their spreadsheets, right? And they're used to them and they're easy, right? They are easy. When you give somebody a spreadsheet, I can follow columns and rows, they're not the ones building those spreadsheets and having to match. So look, I think the idea that, listen, we're giving you good information. We're connecting it now easier than ever to our existing information and I give it to you whenever you want it, right? You don't have to ask me, I get back to you in a couple of days. So I think more real-time access to the data, quicker turnaround, and I can have everybody asking me at the same time via these reports or these tools that are easy to use. So constant feedback back and forth, working with Amit and the team over the years on tweaking it, enhancing the information, it just has created a great experience. So yeah, you don't do it overnight, but the information has been valuable and important to their growth as RMS. What are some of the next steps? What are some of the next business units, functions, et cetera, that you guys are going to be working with Zoom and phone? I think the next step is to really turn on the insight aspect of it, right? It's one thing to say, hey, I don't have this company in my database, I have this company database. The next part is to be some of the stuff that Stoneflake is coming up with and I think the teams are like, okay, I got all this stuff. What do you think you should be looking at? And I just open up something and it tells me some suggestions, right? I think that's the next step of connecting third-party data with our first-person data, first-party data, right? And now our sales team, hey, here's some suggestions. We're not quite there yet. We do that, I do that as a human and my team can do that manually, but I think we can get some more automation to that and make that part be their next big phase. Insights key. On that last question for you, when you're talking with prospective customers like Capwan, what are some of the best practices that you share with them in terms of partnering with third-party data providers? So that they can really design a data strategy that's going to help them be successful? Yep, great question. So one of the things that we have seen is, historically, lot of these back data things have resided with IT, CIOs. Increasingly, we are seeing over time that lot of the chief data officer are aligning themselves to revenue outcome. Sales and marketing is actually a bloodline for a company. Like really, that's how the company grows. So in terms of best practices, what we are seeing is, you don't have to roll out a master data management strategy for two years, four years to build your master data for finance and procurement, for sales team to get the benefit out of it. So step number one, companies like Snowflake has enabled democratization of all the data. So let's say you are using Salesforce. You can have a bidirectional sync with Salesforce, your market, your Eloquah, directly data getting pushed to Snowflake. We make our data available directly in Snowflake. Literally within months, the chief data officer is in a position where they can go to the CRO and they can tell them that you guys want to grow 20%, next quarter 30%, 40%, which is what ZoomInfo does, which is what Snowflake is doing, which is what Microsoft is doing, which is what many of our Fortune 500 customers are doing. So not thinking about is an IT infrastructure, but more of a business outcome. That's why modern data for revenue outcomes, that's one of the best practices where you don't have to wait for mastering the data for years, but utilizing tools like Snowflake and utilizing your current system, being prescriptive, doing the TAM analysis, getting a full segmentation view of what is your ideal customer profile, having all the data available in the backend office, now prescribing it to salespeople and giving them lightweight tools that you as a seller are calling and reaching out to these folks all the time rather than figuring out who to call, when to call and things like that. Companies don't have time for that. Guys, this is a fantastic use case.  Now we get it. We appreciate it. We also appreciate hearing the cap one story. Thanks guys. Thank you. All right, our pleasure. For our Gaston for Dave Vellante, I'm Lisa Martin. You're watching theCUBE. You can find all of our Snowflake content and all of our CUBE content at thecube.net. Analysis, editorial, you want it? You got it 24 by seven on siliconangle.com. Up next, we're going to be talking about public sector for Snowflake, which is new. Stick around, you're watching theCUBE, the leader in live tech coverage.


What man has done, he can undo. This is an idea that comes from Master Sri Yukteswar, who explains that the karma that we create in our lives are not destined to cause us ruin, if we are willing to work with that energy and transform it through our effort and willpower. Any energy that we have enacted for evil or selfish purposes can be mitigated by the focus on bringing more attention to the light of our soul and bringing that good energy forth through our words and our actions. It's okay to humble ourselves, it's safe to ask for help. We're all in this together after all. So don't worry, if you've got some things in your past that you're not happy with, things can be made right, it just takes the effort to do so.


The article discusses the use of task shifting as a means to expand access to antiretroviral therapy, ART, in Sub-Saharan Africa, where there are severe shortages of human resources for health, her royal highness. Task shifting involves delegating tasks performed by physicians to staff with lower level qualifications. The article presents the results of a systematic literature review that found 51 studies reporting outcomes related to task shifting in his treatment and care. The most common intervention studied was the delegation of tasks from doctors to nurses and other non-physician clinicians. The study found that task shifting is an effective strategy for addressing her royal highness shortages, offering high quality, cost-effective care to more patients than a physician-centered model. However, challenges to implementation include adequate training, support, and pay for staff in new roles, as well as regulatory compliance. Task shifting should be considered for careful implementation, where her royal highness shortages threaten rollout programs. This article was authored by Ford Nathan, Callahan Mike, and Schneider Helen. We are article.tv, links in the description below.


My name is Ellie. I'm six years old. I want to be a swimmer class teacher. We needed pediatric oncology service, which wasn't available in Bel-Air. So we will transfer it here to University of Maryland. Ellie has the most common type of cancer that we take care of, which is a pre-BALL, so acute lymphoblastic leukemia. She underwent chemotherapy for about two and a half years, which is the standard of treatment for children with leukemia. And it mainly involves chemotherapy, including getting spinal taps in order to give chemotherapy into the spinal fluid itself. I mean, we are very happy with her recovery. She has been in remission now for a little bit over a year, and she's really blossomed over this past year, being off the treatments. It's quite amazing to see, especially the little two-year-olds, three-year-olds come in because they're extraordinarily resilient, and they're usually running around our waiting room, playing and happy, and that's really what's really amazing about my job and what I do every day. She's like a normal, healthy, young girl now, which is just a blessing for us. I like to dance. I like to swim, and I like to ice skate.