1 00:00:00,120 --> 00:00:03,960 Speaker 1: This is Bloomberg Business Week with Carol Messer and Tim 2 00:00:04,000 --> 00:00:06,280 Speaker 1: Steneveek on Bloomberg Radio. 3 00:00:06,600 --> 00:00:09,360 Speaker 2: Our next guest is a Bloomberg New Economy Catalyst Class 4 00:00:09,360 --> 00:00:12,040 Speaker 2: of twenty twenty two. Now, just a reminder, Catalysts are 5 00:00:12,080 --> 00:00:15,760 Speaker 2: people whose innovations, efforts and objectives have a genuine shot 6 00:00:15,800 --> 00:00:18,360 Speaker 2: at changing the world for the better. And we are 7 00:00:18,360 --> 00:00:20,800 Speaker 2: so delighted to have back with us Anastagia Volkova. She's 8 00:00:20,840 --> 00:00:24,079 Speaker 2: the co founder and CEO of the regenerative ad company Regrow. 9 00:00:24,160 --> 00:00:25,800 Speaker 2: We got to talk about some of the accolades, tam. 10 00:00:26,079 --> 00:00:28,120 Speaker 1: Yeah, well let's just start with just a couple of them. Okay, 11 00:00:28,160 --> 00:00:29,600 Speaker 1: but we got it. We can't say I'm all or else. 12 00:00:29,640 --> 00:00:31,040 Speaker 1: We're not going to get any time for an interview. 13 00:00:31,080 --> 00:00:32,839 Speaker 1: Let's just go with this one. Time is named Regrow 14 00:00:32,880 --> 00:00:35,320 Speaker 1: is one of the one hundred most Influential companies in 15 00:00:35,360 --> 00:00:37,960 Speaker 1: twenty twenty three. Fast Company has named it one of 16 00:00:38,000 --> 00:00:40,800 Speaker 1: the most innovative companies of the year. In Anastasia was 17 00:00:40,840 --> 00:00:42,880 Speaker 1: named to the Time one hundred list of the next 18 00:00:42,960 --> 00:00:45,200 Speaker 1: one hundred most influential people in the world. 19 00:00:45,280 --> 00:00:47,200 Speaker 3: Can I say, aren't you happy? You called it first? 20 00:00:47,240 --> 00:00:48,199 Speaker 3: With the catalysts. 21 00:00:49,360 --> 00:00:51,880 Speaker 2: Yes, yes, yes, yes, you also have a PhD in 22 00:00:51,960 --> 00:00:53,880 Speaker 2: visual drone navigation, which I always think is so cool 23 00:00:53,920 --> 00:00:56,280 Speaker 2: and I think we talked about it last time. Good 24 00:00:56,280 --> 00:00:57,960 Speaker 2: to have you back with us. I know you're in 25 00:00:58,000 --> 00:01:00,360 Speaker 2: for all these quas accolades. I know now, but we 26 00:01:00,360 --> 00:01:03,040 Speaker 2: don't have time. We want to talk to our So 27 00:01:03,360 --> 00:01:06,800 Speaker 2: talk to us about what's going on this week and 28 00:01:06,840 --> 00:01:09,760 Speaker 2: what's going on since we last talked to you in April. 29 00:01:09,880 --> 00:01:11,240 Speaker 3: Yeah, if i'd be loves to be back. Thank you 30 00:01:11,280 --> 00:01:14,160 Speaker 3: so much for having me. Absolutely, it's wonderful to also 31 00:01:14,200 --> 00:01:17,720 Speaker 3: see all the momentum in food and agriculture space and 32 00:01:17,880 --> 00:01:20,759 Speaker 3: the industry leaders generally, we believe that it's an industry 33 00:01:20,800 --> 00:01:23,400 Speaker 3: that can decarbonize as soon as are things. 34 00:01:23,120 --> 00:01:26,240 Speaker 2: Really changing and things are moving? What is to me? 35 00:01:26,600 --> 00:01:28,240 Speaker 3: What does it look like? Okay, let's look at the 36 00:01:28,240 --> 00:01:32,800 Speaker 3: most recent pieces. So to California builds a passing legislature 37 00:01:33,120 --> 00:01:37,000 Speaker 3: and they are going to mandate climate disclosures for companies 38 00:01:37,080 --> 00:01:40,720 Speaker 3: over one billion dollars in revenue trading in California. There's 39 00:01:40,760 --> 00:01:43,520 Speaker 3: also a segment for half a billion dollar revenue company. 40 00:01:43,520 --> 00:01:45,319 Speaker 2: Which does that mean? What do they have to show it? 41 00:01:45,400 --> 00:01:48,400 Speaker 3: Literally? Means that they need to go and calculate how 42 00:01:48,480 --> 00:01:51,480 Speaker 3: they are impacting climate in their own emissions as well 43 00:01:51,520 --> 00:01:53,800 Speaker 3: as their purchase goods and services. So if you are, 44 00:01:53,920 --> 00:01:56,560 Speaker 3: for example, a food company making food that ends up 45 00:01:56,600 --> 00:01:58,680 Speaker 3: on the shelf or on the plate, you literally need 46 00:01:58,720 --> 00:02:00,760 Speaker 3: to be thinking about what is the emission on farm 47 00:02:00,800 --> 00:02:03,520 Speaker 3: because this is where the largest portion of those emissions sits. 48 00:02:03,800 --> 00:02:06,040 Speaker 3: And by twenty twenty seven you will have to declare it, 49 00:02:06,080 --> 00:02:08,720 Speaker 3: which effectively means that if you start measuring it, you'll 50 00:02:08,760 --> 00:02:12,320 Speaker 3: start managing it. And all of the data that someone 51 00:02:12,440 --> 00:02:15,360 Speaker 3: like Regro works on where one of the primary sources 52 00:02:15,360 --> 00:02:17,800 Speaker 3: of the data that they can start understanding their supply 53 00:02:17,840 --> 00:02:22,080 Speaker 3: shoes with and investing in it powers their decision making 54 00:02:22,160 --> 00:02:25,480 Speaker 3: they can tangibly progress towards their net zero and emission 55 00:02:25,480 --> 00:02:28,120 Speaker 3: reduction goals, which as you know, there are plenty. 56 00:02:28,639 --> 00:02:30,519 Speaker 1: When you say that this is one of the industries 57 00:02:30,560 --> 00:02:35,400 Speaker 1: that can decarbonize the quickest, are you including animals in 58 00:02:35,440 --> 00:02:36,160 Speaker 1: this as well? 59 00:02:36,280 --> 00:02:36,400 Speaker 4: Like? 60 00:02:36,919 --> 00:02:39,960 Speaker 1: Are you including cattle farming? 61 00:02:39,040 --> 00:02:42,040 Speaker 3: That's right, agriculture, How. 62 00:02:42,280 --> 00:02:43,839 Speaker 1: I mean this is like one of the worst things 63 00:02:43,840 --> 00:02:44,520 Speaker 1: for the environment. 64 00:02:45,840 --> 00:02:49,400 Speaker 3: It's very subjective, right, So when you start thinking about 65 00:02:49,639 --> 00:02:52,000 Speaker 3: what are the animals supposed to do versus what we 66 00:02:52,200 --> 00:02:55,200 Speaker 3: got them to do, how we disaggregated agriculture. Whilst in 67 00:02:55,200 --> 00:02:58,360 Speaker 3: an integrated system, they're actually all very helpful. It's a 68 00:02:58,440 --> 00:03:01,959 Speaker 3: more circular system. You can feed them better. Crops with 69 00:03:02,240 --> 00:03:04,519 Speaker 3: a lot of emissions in the animal system are still 70 00:03:04,520 --> 00:03:06,520 Speaker 3: in the crops. We produce most of the crops to 71 00:03:06,560 --> 00:03:09,359 Speaker 3: feed animals, not to feed ourselves, so that's where the 72 00:03:09,400 --> 00:03:10,840 Speaker 3: majority of the impact will come. 73 00:03:11,160 --> 00:03:12,280 Speaker 1: First use the complication. 74 00:03:14,240 --> 00:03:17,160 Speaker 3: I am saying that we need to decarbonize all parts 75 00:03:17,160 --> 00:03:19,600 Speaker 3: of the burger and starting to list what are the 76 00:03:19,639 --> 00:03:22,639 Speaker 3: parts that we should decribonize, But I am definitely saying 77 00:03:22,639 --> 00:03:25,640 Speaker 3: the alternative burger is better for the environment. Yes, but 78 00:03:26,000 --> 00:03:28,400 Speaker 3: there's things about the burger that are also not terrible 79 00:03:28,440 --> 00:03:28,640 Speaker 3: for them. 80 00:03:28,880 --> 00:03:30,440 Speaker 2: And a station when you work with the company, what 81 00:03:30,520 --> 00:03:31,079 Speaker 2: exactly do. 82 00:03:31,040 --> 00:03:34,560 Speaker 3: You do for them? We help them first uncover their 83 00:03:34,639 --> 00:03:37,440 Speaker 3: school three emissions i e. Those that on farm, So 84 00:03:37,560 --> 00:03:40,200 Speaker 3: if they come and pick their supply sheds, they say, 85 00:03:40,200 --> 00:03:42,400 Speaker 3: I source this over there, can you tell me how 86 00:03:42,560 --> 00:03:45,360 Speaker 3: is that impacting the environment? And we actually letter up 87 00:03:45,360 --> 00:03:47,800 Speaker 3: the data from the field level, so we have dynamically 88 00:03:47,880 --> 00:03:51,320 Speaker 3: generated data on a near real time basis that can 89 00:03:51,360 --> 00:03:53,880 Speaker 3: say here's what's happening in the landscape, this is what's 90 00:03:54,120 --> 00:03:57,040 Speaker 3: what's impacting the environment right now. Once they have that snapshot, 91 00:03:57,320 --> 00:04:00,360 Speaker 3: they can also model with the platform that wee them, 92 00:04:00,400 --> 00:04:04,080 Speaker 3: the ag resilience platform, the abatement potential, that is to say, 93 00:04:04,240 --> 00:04:07,240 Speaker 3: what can I change for better? What can I reduce? 94 00:04:07,280 --> 00:04:08,960 Speaker 3: How can I get to my mission production goal? 95 00:04:09,040 --> 00:04:11,800 Speaker 2: So it's not about carbon offsetting, it's actually do so 96 00:04:11,840 --> 00:04:14,040 Speaker 2: you don't create carbon in the first place. 97 00:04:14,560 --> 00:04:19,159 Speaker 3: Yes, it's value chain investments. It's almost call it in setting. 98 00:04:19,200 --> 00:04:22,280 Speaker 3: It's the opposite. So you take action within your value chain. 99 00:04:22,600 --> 00:04:25,599 Speaker 3: You are not you're reducing your own emissions. You're not 100 00:04:25,760 --> 00:04:27,680 Speaker 3: looking to offset them somewhere else. 101 00:04:27,800 --> 00:04:28,480 Speaker 2: I hate offset. 102 00:04:28,520 --> 00:04:31,920 Speaker 3: Sorry no, and European Commission is with you. 103 00:04:31,839 --> 00:04:34,200 Speaker 2: Because you shouldn't be making You've got to reduce the 104 00:04:34,240 --> 00:04:37,400 Speaker 2: carbon footprint. It's not a case. It's not exactly I'm 105 00:04:37,440 --> 00:04:39,320 Speaker 2: not going to all right, so I'm creating a lot 106 00:04:39,320 --> 00:04:40,880 Speaker 2: of carbon, but I'm going to go plant some trees. 107 00:04:40,960 --> 00:04:42,800 Speaker 2: You're still putting the carbon in there, like we've got 108 00:04:42,800 --> 00:04:43,800 Speaker 2: to reduce it overall. 109 00:04:43,800 --> 00:04:45,880 Speaker 4: That's just no. 110 00:04:46,000 --> 00:04:49,240 Speaker 3: Absolutely, we have to find ways of producing food in 111 00:04:49,279 --> 00:04:52,000 Speaker 3: a way that doesn't harm the environment so much, it 112 00:04:52,000 --> 00:04:54,839 Speaker 3: actually renews it and regenerates it. 113 00:04:54,600 --> 00:04:59,720 Speaker 1: Is vertical farming one of those answers. Good question, It's 114 00:04:59,800 --> 00:05:00,680 Speaker 1: very controversial. 115 00:05:00,920 --> 00:05:03,560 Speaker 3: It's very controversial because you have to consider everything from 116 00:05:03,560 --> 00:05:06,080 Speaker 3: the system perspective. Right, So on one hand, you have 117 00:05:06,440 --> 00:05:10,280 Speaker 3: the transportation of say salad from Salinas, California, to New 118 00:05:10,360 --> 00:05:12,839 Speaker 3: York City, and that's absurd, So you probably should consider 119 00:05:12,839 --> 00:05:15,919 Speaker 3: growing it here, if you recycle some of the resources, 120 00:05:16,440 --> 00:05:18,919 Speaker 3: if you're able to provide it with the water it 121 00:05:18,960 --> 00:05:22,880 Speaker 3: needs without drowing more water into that farm over time. Okay, great, 122 00:05:22,920 --> 00:05:25,360 Speaker 3: but you still look in at a system that largely 123 00:05:25,520 --> 00:05:31,520 Speaker 3: requires artificial synthetic input fertilizers, and they sustain the system, 124 00:05:31,600 --> 00:05:34,880 Speaker 3: is opposed to say soil out there that when healthy, 125 00:05:34,880 --> 00:05:39,640 Speaker 3: sequestors carbon and provides water, cleaning, clean air, all of 126 00:05:39,680 --> 00:05:43,200 Speaker 3: those ecosystem services to us living all around on those 127 00:05:43,480 --> 00:05:44,360 Speaker 3: those environments. 128 00:05:44,800 --> 00:05:47,880 Speaker 2: You know, it's interesting. We had Johannes Zuting of Powers 129 00:05:47,920 --> 00:05:51,800 Speaker 2: twenty one on and they basically are making sure that 130 00:05:52,360 --> 00:05:55,200 Speaker 2: you know, or helping developing the developing world, you know, 131 00:05:55,440 --> 00:05:57,960 Speaker 2: create data sets. They don't actually have the data, but 132 00:05:57,960 --> 00:06:00,200 Speaker 2: they're pulling from different sources and making sure it's year. 133 00:06:00,240 --> 00:06:02,560 Speaker 2: But the whole idea is you need to collect and 134 00:06:02,560 --> 00:06:06,120 Speaker 2: track transformative data to help bring about transformative policies and change. 135 00:06:07,080 --> 00:06:09,680 Speaker 2: Talk to us about the importance of that having that 136 00:06:09,800 --> 00:06:12,200 Speaker 2: data that you guys are providing right, the information, but 137 00:06:12,440 --> 00:06:17,840 Speaker 2: also go hand in hand with governments states countries saying 138 00:06:18,040 --> 00:06:19,760 Speaker 2: we've got to do better, and so you need the 139 00:06:19,839 --> 00:06:20,640 Speaker 2: data to kind of meet. 140 00:06:20,960 --> 00:06:24,719 Speaker 3: Absolutely it has to and we have plenty to update 141 00:06:24,920 --> 00:06:28,679 Speaker 3: the listeners on with the IRA money, with the investment, 142 00:06:28,720 --> 00:06:31,920 Speaker 3: with the Inflication and Reduction Act and the Embedded Climate's 143 00:06:31,960 --> 00:06:37,560 Speaker 3: MARGE Commodities program, the Administration is looking to effectively accelerate 144 00:06:37,720 --> 00:06:42,279 Speaker 3: the investment into low carbon commodities and agricultural sector. But 145 00:06:42,400 --> 00:06:47,320 Speaker 3: also they have released recently an initiative specifically focused on 146 00:06:47,360 --> 00:06:50,520 Speaker 3: the data and the MRV the monitoring, reporting and verification 147 00:06:50,600 --> 00:06:54,000 Speaker 3: of emissions and practices, and they completely go hand in hand. 148 00:06:54,040 --> 00:06:56,479 Speaker 3: So if we ever want this to be a truly 149 00:06:56,560 --> 00:07:00,520 Speaker 3: bipartisan issue that is internationally accepted, we need to start 150 00:07:00,560 --> 00:07:02,640 Speaker 3: looking at the data and not wondering where the money 151 00:07:02,680 --> 00:07:04,880 Speaker 3: is going on. Because once you are seeing that the 152 00:07:04,920 --> 00:07:08,080 Speaker 3: money is getting to where it needs to be, why 153 00:07:08,120 --> 00:07:10,280 Speaker 3: wouldn't you invest more in because you are getting that 154 00:07:10,280 --> 00:07:12,400 Speaker 3: return you're looking for. But it's the data that needs 155 00:07:12,480 --> 00:07:13,360 Speaker 3: to tell that story. 156 00:07:13,480 --> 00:07:15,640 Speaker 1: Talk to us more about this because I always wonder 157 00:07:15,680 --> 00:07:17,720 Speaker 1: about incentives here. It's one thing for the state to 158 00:07:17,760 --> 00:07:21,200 Speaker 1: actually require disclosures like California is doing, you know, and 159 00:07:21,200 --> 00:07:22,920 Speaker 1: it's a side point. But my concern is that, Okay, 160 00:07:22,920 --> 00:07:24,560 Speaker 1: all these companies are going to move to Texas, which 161 00:07:24,600 --> 00:07:27,440 Speaker 1: is a state that will not require these types of disclosures. 162 00:07:28,080 --> 00:07:29,880 Speaker 1: Maybe that's a conversation for a different day. 163 00:07:30,040 --> 00:07:31,840 Speaker 2: You really grow in Texas. 164 00:07:31,960 --> 00:07:33,960 Speaker 1: I mean, you could base your company in Texas instead 165 00:07:33,960 --> 00:07:34,520 Speaker 1: of facing it. 166 00:07:34,600 --> 00:07:38,600 Speaker 3: Anyone who trades in Texas, not anyone who's headquartered like 167 00:07:38,680 --> 00:07:40,920 Speaker 3: in California. For the California bill, you just have to 168 00:07:40,960 --> 00:07:43,240 Speaker 3: be trading in California. You are not headquartered in. 169 00:07:43,200 --> 00:07:45,280 Speaker 1: California, so people won't get around it. 170 00:07:45,640 --> 00:07:48,800 Speaker 3: I don't think you can move something to Texas and 171 00:07:48,880 --> 00:07:51,240 Speaker 3: stop trading one of the largest economists in the world 172 00:07:51,240 --> 00:07:52,000 Speaker 3: that is California. 173 00:07:52,080 --> 00:07:55,480 Speaker 1: Yeah, that's very true. Okay, maybe the lawyers will be 174 00:07:55,480 --> 00:07:56,000 Speaker 1: busy trying to. 175 00:07:56,000 --> 00:07:58,760 Speaker 2: Figure out a way maybe hopefully so. 176 00:07:58,800 --> 00:08:02,760 Speaker 1: What's good But estion is really about is really about data, 177 00:08:02,800 --> 00:08:04,760 Speaker 1: and you know where that data comes from and how 178 00:08:04,800 --> 00:08:06,440 Speaker 1: you measure that data in this day and age. 179 00:08:06,680 --> 00:08:09,160 Speaker 3: That's right when you're looking at this type of bill, 180 00:08:09,320 --> 00:08:11,320 Speaker 3: people are getting concerned that this will actually put more 181 00:08:11,320 --> 00:08:13,640 Speaker 3: burden on the suppliers, of which farmers is one of 182 00:08:13,680 --> 00:08:17,280 Speaker 3: the categories in this industry, of course the primary category. 183 00:08:17,640 --> 00:08:21,320 Speaker 3: So this data, you don't need to invent more ways 184 00:08:21,360 --> 00:08:24,280 Speaker 3: to get this data. We already, as Greta Thamberg always says, 185 00:08:24,320 --> 00:08:26,200 Speaker 3: we already have all the solutions. We just need to 186 00:08:26,280 --> 00:08:31,400 Speaker 3: actually implement them. So regrow gets data from fire management system, 187 00:08:31,440 --> 00:08:35,160 Speaker 3: statistical surveys, but importantly satellite imagery, so remote sensing of 188 00:08:35,240 --> 00:08:37,679 Speaker 3: practices tells us a lot about what's happening in the 189 00:08:37,760 --> 00:08:40,760 Speaker 3: land in a non invasive way, in a very scalable 190 00:08:40,760 --> 00:08:43,679 Speaker 3: and cost effective way. Then we pass it through climate models, 191 00:08:43,800 --> 00:08:48,120 Speaker 3: soil carbon crop models to understand what is the impact 192 00:08:48,200 --> 00:08:51,120 Speaker 3: on the environment. So we see the practices from space, 193 00:08:51,320 --> 00:08:54,200 Speaker 3: from local systems, tractor tells us what's going on. We 194 00:08:54,200 --> 00:08:57,160 Speaker 3: don't have to ask the farmer for absolutely everything. We 195 00:08:57,240 --> 00:08:59,760 Speaker 3: have to accept that agriculture has been running on data. 196 00:09:00,000 --> 00:09:02,720 Speaker 3: It's a big business, it's a big industry. It has 197 00:09:02,760 --> 00:09:05,280 Speaker 3: the data. If you provide the incentives and you assure 198 00:09:05,320 --> 00:09:08,679 Speaker 3: the privacy, you will be able to get the system 199 00:09:08,760 --> 00:09:11,680 Speaker 3: to a level of transparency where it can all actually 200 00:09:11,679 --> 00:09:16,360 Speaker 3: flow in a direction of Paris one point five degree trajectory. 201 00:09:16,360 --> 00:09:17,480 Speaker 2: What companies are you working with? 202 00:09:18,000 --> 00:09:23,560 Speaker 4: We're working with General Mills, Kellogg, Cargil, folks across the 203 00:09:23,600 --> 00:09:26,880 Speaker 4: supply chain, from those that provide input to the farmer's 204 00:09:27,040 --> 00:09:29,480 Speaker 4: trade and aggregate and process the commodities all the way 205 00:09:29,480 --> 00:09:31,480 Speaker 4: to those that you pick up their boxes off of 206 00:09:31,559 --> 00:09:35,559 Speaker 4: supermarket shelves and plates or oldly for example, is another cool. 207 00:09:35,360 --> 00:09:37,880 Speaker 2: One US only or is it global? 208 00:09:37,960 --> 00:09:38,960 Speaker 3: Global? Global? 209 00:09:39,080 --> 00:09:41,760 Speaker 2: So everybody's involved in it. So what has changed you 210 00:09:41,760 --> 00:09:43,840 Speaker 2: guys have been around? Is it five six years? 211 00:09:43,920 --> 00:09:45,880 Speaker 3: That's we're going to be twining seven? This no number? 212 00:09:46,080 --> 00:09:48,440 Speaker 2: So what's changed from when you started in just kind 213 00:09:48,440 --> 00:09:49,560 Speaker 2: of about thirty seconds? 214 00:09:49,559 --> 00:09:52,760 Speaker 3: Oh, impact has changed? Right, three years ago, we weren't 215 00:09:52,800 --> 00:09:56,880 Speaker 3: having this conversation. Absolutely every step you take during not 216 00:09:56,920 --> 00:09:59,960 Speaker 3: only Climate Week but generally when you interact with corporate 217 00:10:00,240 --> 00:10:03,880 Speaker 3: and governments, resiliences at the forefront. For us, we of 218 00:10:03,920 --> 00:10:06,640 Speaker 3: course have grown in the response to that interest from 219 00:10:06,720 --> 00:10:08,319 Speaker 3: the market, from the policy and. 220 00:10:08,280 --> 00:10:10,880 Speaker 2: People are changing their practices because of the information they're 221 00:10:10,880 --> 00:10:11,400 Speaker 2: getting from you. 222 00:10:11,559 --> 00:10:15,480 Speaker 3: That's correct. People are establishing more ambitious plans. People are 223 00:10:15,600 --> 00:10:19,000 Speaker 3: able to understand how to invest into the transformation because 224 00:10:19,040 --> 00:10:21,480 Speaker 3: they can clearly see what the return would be. And 225 00:10:21,559 --> 00:10:24,560 Speaker 3: important to Carol share the risk of the farmers upfront. 226 00:10:24,600 --> 00:10:26,600 Speaker 3: You're not telling them to do something without no one 227 00:10:26,720 --> 00:10:27,480 Speaker 3: was going to lead to. 228 00:10:27,679 --> 00:10:30,959 Speaker 2: Can't wait to see her the next six years, seven years, 229 00:10:30,960 --> 00:10:32,679 Speaker 2: hold for you that till twenty thirty. 230 00:10:32,720 --> 00:10:33,320 Speaker 3: You're right on. 231 00:10:33,520 --> 00:10:35,480 Speaker 2: Come back soon. We really appreciate an a stage of 232 00:10:35,480 --> 00:10:38,080 Speaker 2: a Covia. She's co founder and CEO of Regrow here 233 00:10:38,120 --> 00:10:38,600 Speaker 2: in studio