WEBVTT 1 00:00:04.960 --> 00:00:41.439 Belarus has arrested a problem. For several years, casey AA has been marketing 2 00:00:41.439 --> 00:00:46.960 the Youngevity brand of nutritional and personal care products. Our experience with Youngevity has 3 00:00:46.960 --> 00:00:52.159 been one positive, so we are pleased to recommend them to you. Regarding 4 00:00:52.200 --> 00:00:57.520 nutritional supplements, we recommend pollen Burst in the berry flavor and tangy Tangerine two 5 00:00:57.560 --> 00:01:02.479 point zero in the tablet form. For regularity issues, we recommend three day 6 00:01:02.520 --> 00:01:07.799 cleans and for personal care, we recommend morning hydration cream. You can shop 7 00:01:07.799 --> 00:01:12.799 online for Youngevity at www dot KCAA team dot com, or you can order 8 00:01:12.799 --> 00:01:17.560 by phone by calling eight hundred nine eight two three one nine seven and tell 9 00:01:17.599 --> 00:01:22.760 customer support that you are part of the KCAA Team. 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When the values stole 18 00:02:02.000 --> 00:02:08.879 up up and the prices go down, down, down, Robert All. 19 00:02:09.080 --> 00:02:17.280 This season will show you the fees and low overhead overhead and from this time 20 00:02:17.319 --> 00:02:22.159 in nineteen sixty seven. So far it's been a great year for Neil Diamond. 21 00:02:22.479 --> 00:02:27.159 Last year nineteen sixty sixty debuted with Solitary Man and Cherry Cherry, Thank 22 00:02:27.199 --> 00:02:30.879 the Lord for the Nighttime just finished its pop chart run. But earlier here 23 00:02:30.919 --> 00:02:35.080 in nineteen sixty seven, Neil Diamond had a terrific hit with Girl You'll Be 24 00:02:35.120 --> 00:02:49.840 a Woman Soon Down, No, Girl You'll be Soon three. Come take 25 00:02:50.039 --> 00:03:08.560 my solo with Moore at Mad from yesterday dot Com. The mortgage voice is 26 00:03:08.639 --> 00:03:14.439 Jeff Barton, your mortgage advocate here on casey AA. Jeff informs you of 27 00:03:14.479 --> 00:03:19.199 the ever changing mortgage industry. Mortgage loans can be confusing and overwhelming, but 28 00:03:19.319 --> 00:03:23.199 Jeff and his guests will help you understand the difference in various loans and help 29 00:03:23.240 --> 00:03:25.520 you own or keep your call. Trust is the major issue here right. 30 00:03:25.560 --> 00:03:30.639 If someone doesn't trust you with their most intimate financial details and secrets, it's 31 00:03:30.639 --> 00:03:32.120 going to be very hard for them to do a lot. Tune into the 32 00:03:32.159 --> 00:03:38.080 Mortgage Voice every Saturday afternoon at three and Sunday at noon here on casey A 33 00:03:38.280 --> 00:03:43.439 eight ten fifty AM and one oh six point five FM. Bob Vila here 34 00:03:43.479 --> 00:03:46.840 with my home improvement tip of the day. Medium density fiber board MDF for 35 00:03:46.919 --> 00:03:51.960 short, can be a cheaper, more stable alternative to plywood if used in 36 00:03:52.000 --> 00:03:54.680 the right way. MDF is made from wood scraps that are broken down into 37 00:03:54.719 --> 00:04:00.400 fine fibers, mixed with binders such as glue, then formed into sheets high 38 00:04:00.400 --> 00:04:03.520 temperature and pressure. Most home centers carry four by eight sheets, usually half 39 00:04:03.639 --> 00:04:08.960 or three quarters inch thick. MDF is often a bit less expensive than plywood. 40 00:04:09.240 --> 00:04:12.319 It holds its shape and you can use it for shelving, cabinets, 41 00:04:12.560 --> 00:04:16.120 trim and moldings. It's best for interior project since it doesn't like moisture. 42 00:04:16.439 --> 00:04:21.879 One important caveat though, MDF contains from aldehyde, a suspected carcinogen, so 43 00:04:23.120 --> 00:04:27.000 you'll need to wear a respirator when cutting it and until it's properly sealed with 44 00:04:27.040 --> 00:04:30.439 paint or urethane, it continues to emit toxic fumes. That being said, 45 00:04:30.600 --> 00:04:34.199 if you take proper precautions when working with it, MDF can save you money 46 00:04:34.360 --> 00:04:39.360 and reward you with good results. Get more into at bob Vila dot com 47 00:04:39.399 --> 00:04:45.399 and right here at home with me Bob Vila. Hi, y'all merl here 48 00:04:45.639 --> 00:04:48.360 good news for once. My neighbors is jealous of me. You want to 49 00:04:48.399 --> 00:04:53.439 know why, because my grass is growing and looking green and I can set 50 00:04:53.480 --> 00:04:57.120 on my sofa out in front yard and I don't even have to overwater it 51 00:04:57.160 --> 00:05:00.160 anymore. You know how I did it. I listened to damn water boys 52 00:05:00.199 --> 00:05:04.600 on the waters on every Thursday night on case CIA. Well, it got 53 00:05:04.720 --> 00:05:09.720 me a smart controller and now it waters at night and my already looks darn 54 00:05:09.879 --> 00:05:13.800 tooting. No more sneaking around and hooking up my horse to my neighbor's spiggot 55 00:05:14.000 --> 00:05:15.600 in the middle of the night, and his dog won't bite me anymore. 56 00:05:16.000 --> 00:05:18.920 And you can do it too, listening. It is easier than ever. 57 00:05:19.319 --> 00:05:28.759 KCA is now screaming online. It's streaming what it's streaming. You don't well, 58 00:05:29.120 --> 00:05:31.920 I don't know much about streaming, but they're doing it apparently at KSEA 59 00:05:32.040 --> 00:05:36.480 radio dot com. So AnyWho listen to the Water's one and fix your yard 60 00:05:36.519 --> 00:05:42.199 up right right here at CASEAA, the station that leaves no listener behind. 61 00:05:42.319 --> 00:06:00.800 What six point five FM man to KCAA ten to fifty am was one minute 62 00:06:00.800 --> 00:06:06.759 at the multi format network. The information economy as a rod. The world 63 00:06:06.920 --> 00:06:12.759 is teeming with innovation as new business models. We invent every industry industry. 64 00:06:12.839 --> 00:06:17.160 Inside Analysis is your source of information and insight about how to make the most 65 00:06:17.199 --> 00:06:23.839 of this exciting new era. Learn more and Inside Analysis dot Comside Analysis dot 66 00:06:23.839 --> 00:06:34.399 Com. And now here's your host, Eric Kavanaugh. All right, folks, 67 00:06:34.439 --> 00:06:39.839 welcome to the future. Indeed, George Julie Eric Kavanaugh here on Inside 68 00:06:39.879 --> 00:06:44.319 Analysis, the only coast to coast radio show all about the information economy and 69 00:06:44.399 --> 00:06:46.279 folks, so I get to go on a trip down memory lane today with 70 00:06:46.319 --> 00:06:50.319 our guests. Who knows a lot about a technology that East throw years ago. 71 00:06:50.959 --> 00:06:56.199 Master data management, Master data manager? What is that stuff? Master 72 00:06:56.360 --> 00:07:00.759 data is very important because it allows you to virtually reconcile information system so you 73 00:07:00.800 --> 00:07:05.199 have your customer database, your product database, your ARP, your data warehouse, 74 00:07:05.240 --> 00:07:09.920 et cetera. All these different systems while many of them are using the 75 00:07:10.000 --> 00:07:12.839 same data or should use the same data, but a lot of times it's 76 00:07:12.879 --> 00:07:16.720 not aligned well. And so for years we went through this whole rigamarole of 77 00:07:16.759 --> 00:07:21.959 trying to do top down master data management initiatives to be able to reconcile all 78 00:07:23.000 --> 00:07:27.040 these different systems so you can see the big picture. That's really what it 79 00:07:27.079 --> 00:07:30.519 really boils down to is being able to see the big picture to understand how 80 00:07:30.560 --> 00:07:33.519 do all these component parts come together to make the business that we're trying to 81 00:07:33.639 --> 00:07:38.399 run here. And obviously you can imagine that's very useful stuff where it's done 82 00:07:38.399 --> 00:07:42.720 correctly, but the top down approach always had a very very difficult time because 83 00:07:42.759 --> 00:07:46.519 you need people to adhere to very strict behavioral standards. How many people know 84 00:07:46.600 --> 00:07:50.040 people who would like to adhere to strict behavioral standards? Not too many. 85 00:07:50.079 --> 00:07:54.920 It's just not a very human thing to do. But people will align if 86 00:07:54.959 --> 00:07:59.160 they see the vision of something and understand the value. Where our guest today, 87 00:07:59.199 --> 00:08:01.360 Brett Hansen, is CMO for a company called so Mark, and they 88 00:08:01.399 --> 00:08:05.959 do some pretty clever stuff with bottom up MDM, and so we're going to 89 00:08:05.079 --> 00:08:09.600 kind of tie that into the whole go to market theme today about how things 90 00:08:09.600 --> 00:08:11.759 are changing and how you have to change your go to market strategy to get 91 00:08:11.759 --> 00:08:16.040 to the right people. Certainly, if you're in the software world, that's 92 00:08:16.040 --> 00:08:18.120 a much different world now than it was five years ago, ten years ago. 93 00:08:18.600 --> 00:08:22.800 You know, product led growth stuff like that. We didn't have product 94 00:08:22.839 --> 00:08:24.399 led growth ten years ago. Now it's a huge thing. A lot of 95 00:08:24.399 --> 00:08:30.120 companies do so without further ado. Brett Hanson from Samark, Welcome to Inside 96 00:08:30.160 --> 00:08:33.480 Analysis. Tell us a bit about your company and the cool things you're doing 97 00:08:33.519 --> 00:08:37.879 to help companies get value from their data. Thanks Eric, I think you 98 00:08:37.960 --> 00:08:45.240 said it really well that there has been this ongoing effort and it applies that 99 00:08:45.360 --> 00:08:48.440 just to MBM. It's really the data space in general. We're surely didn't 100 00:08:48.519 --> 00:08:52.799 very tops down it is. We're going to have centralized organizations. We're going 101 00:08:52.840 --> 00:08:54.360 to control data, we're going to govern it, we're going to first out 102 00:08:54.360 --> 00:08:58.960 how we get into different groups. And the fact the matter is, despite 103 00:08:58.519 --> 00:09:03.960 billion and billions and billions of investment, most companies would say, we're still 104 00:09:05.000 --> 00:09:09.600 not a data driven organization, right, We're still not making decisions at a 105 00:09:09.720 --> 00:09:15.320 practitioner level that are data driven. Maybe at the top level they're getting the 106 00:09:15.360 --> 00:09:18.600 data they need, but in terms of line level workers, are they able 107 00:09:18.639 --> 00:09:26.039 to access data utilize that data to make decisions to improve customer outcomes, improve 108 00:09:26.120 --> 00:09:30.240 patient outcomes, improve efficiencies and all those things that we want to achieve with 109 00:09:30.240 --> 00:09:33.639 all the data collection. And a big reason why is because we're still taking 110 00:09:33.679 --> 00:09:39.080 this top down approach. Our philosophy is the other direction, as you called 111 00:09:39.080 --> 00:09:48.120 out, how do we deliver a data product that is specifically designed and delivered 112 00:09:48.519 --> 00:09:54.120 for a business requirement and how does that data product then evolve and grow as 113 00:09:54.200 --> 00:10:00.919 business requirements change? And that's the samark the approach. Let's get into the 114 00:10:00.960 --> 00:10:05.279 hands of business practitioners the tools they need to be successful, versus try to 115 00:10:05.320 --> 00:10:11.039 force them down a symplatize highly regiment approach that has been proven not to work 116 00:10:11.080 --> 00:10:15.840 now for decades. Yeah, I mean, that's such an excellent point, 117 00:10:16.000 --> 00:10:18.720 and I think you guys are really onto something here, especially the data product 118 00:10:18.840 --> 00:10:22.919 concept, So that is really taking off now. And it's interesting because you've 119 00:10:22.919 --> 00:10:26.679 been around as long as I have, I think, or maybe almost or 120 00:10:26.720 --> 00:10:30.440 just about so you've seen some of these trends kind and go big, big, 121 00:10:30.519 --> 00:10:33.679 data, the no sequel movement, and we're going to forget about sequel, 122 00:10:33.720 --> 00:10:37.480 like really are you? And then snowfully turns along with the biggest IPO 123 00:10:37.519 --> 00:10:41.480 in history, saying, yeah, actually, sequel still matters. Actually a 124 00:10:41.480 --> 00:10:43.519 matter of fact, maybe you want to focus on that a little bit, 125 00:10:43.080 --> 00:10:48.399 but getting because here's the thing. The data warehouse, of course, is 126 00:10:48.039 --> 00:10:52.200 this large construct that was designed to build a pull data out of all these 127 00:10:52.240 --> 00:10:58.919 different operational systems, put it into a manageable space that we can run analyzes 128 00:10:58.960 --> 00:11:01.039 on and kind of understand and trends and things. Because we figured out you 129 00:11:01.080 --> 00:11:05.000 can't do analytics on an RP. It just wasn't designed to do that. 130 00:11:05.080 --> 00:11:09.240 It's designed to do the business, to run the business. So that's where 131 00:11:09.240 --> 00:11:13.320 this whole thing came from. And then trying to sort of build this next 132 00:11:13.320 --> 00:11:16.159 generation of apps, if you're trying to do it again from this sort of 133 00:11:16.200 --> 00:11:20.600 top down perspective, you're nowhere near close enough the ground level where this thing 134 00:11:20.679 --> 00:11:24.519 is going to be used and so and even thinking of the traditional way of 135 00:11:24.600 --> 00:11:30.600 building apps and just connecting it to a database like you know IBM or Microsoft 136 00:11:30.639 --> 00:11:35.360 Access or whatever. A sequel server like that has so many limitations in terms 137 00:11:35.399 --> 00:11:41.559 of the flow of data and how performance it can be, how malleable it 138 00:11:41.639 --> 00:11:45.879 is to be able to do interesting analyzes. Whereas if you take the approach 139 00:11:45.919 --> 00:11:48.120 that you folks are taking that some market is taking, and you ask the 140 00:11:48.120 --> 00:11:52.320 business, look, what do you need, then we're going to help you 141 00:11:52.720 --> 00:11:56.840 build out an application that will pull whatever data it needs. And by the 142 00:11:56.879 --> 00:12:01.240 way, as we're doing that, we're going to be increment to leave fashioning 143 00:12:01.360 --> 00:12:05.120 your reference architecture, which is basically what MDM is designed to do. Right. 144 00:12:05.159 --> 00:12:09.840 It's designed to give you a hard and fast reference architecture. But reference 145 00:12:09.960 --> 00:12:13.960 architecture is never hard and fast, right. That's the problem is that they're 146 00:12:13.039 --> 00:12:16.000 kind of lucy, you see, but you get them just enough to get 147 00:12:16.039 --> 00:12:18.919 their data products. So you've solved the business need first of all. That's 148 00:12:18.919 --> 00:12:22.799 the important thing. Now the business people are happy and they're actually using data, 149 00:12:22.879 --> 00:12:26.480 and it's data that is governed and trusted. Right, So you've kind 150 00:12:26.519 --> 00:12:28.159 of, I'm a football fan, you kind of pulled an end around on 151 00:12:28.200 --> 00:12:31.279 this whole thing. Right, You're just going straight to the users and saying, 152 00:12:31.279 --> 00:12:33.879 hey, what do you guys need, Let's build that for you. 153 00:12:35.320 --> 00:12:39.120 And in that process. On that journey, you're going to be building out 154 00:12:39.159 --> 00:12:43.120 what is essentially your MDM architecture. Is that about right? That's very record 155 00:12:43.679 --> 00:12:46.320 and I love the football reference. Not too long before we get to get 156 00:12:46.320 --> 00:12:52.200 back into the season, and it's still done with the data analysts and experts, 157 00:12:52.240 --> 00:12:52.759 right, So I don't want to I don't want to suggest that we're 158 00:12:52.879 --> 00:12:56.279 they're not an important part of this, right, But like you said, 159 00:12:56.360 --> 00:13:03.039 it's all about understand what the business objectives are, right, Do I need 160 00:13:03.080 --> 00:13:05.960 a customer three sixty view? Do I need an inventory view? To I 161 00:13:05.960 --> 00:13:09.440 need a location perspective? And of course that's the only the top of You're 162 00:13:09.440 --> 00:13:15.399 going to get much more detailed. And no two companies are exactly alike, 163 00:13:15.759 --> 00:13:20.120 and no two data projects are exactly alike. And so being able to start 164 00:13:20.159 --> 00:13:28.320 with a set of reasonable business objectives defining what those business outcomes are, and 165 00:13:28.360 --> 00:13:33.440 then we have a tool for lack of a better term, that generates the 166 00:13:33.480 --> 00:13:35.720 code on your behalf. So we're not writing code, this is cogeneration. 167 00:13:37.559 --> 00:13:46.799 We can provide typically a first usable solution in less than twelve weeks, so 168 00:13:46.919 --> 00:13:50.639 in less than a quarter we can have something that the business user can get 169 00:13:50.679 --> 00:13:56.039 their hands on, start to play with They're going to have positive reactions, 170 00:13:56.039 --> 00:14:00.080 they're going to have adverse reactions. But when they have those adverse reactions, 171 00:14:00.120 --> 00:14:03.840 they have additional requirements. Perfect we put that in back into the tool, 172 00:14:05.279 --> 00:14:09.399 build that out, and start to resolve those as we're building out. Interesting 173 00:14:09.399 --> 00:14:13.320 and so rather than trying to go a very tops down, year long approaches, 174 00:14:13.480 --> 00:14:15.600 Hey, let's get something in the hands of business, you're in their 175 00:14:15.720 --> 00:14:20.879 quarter, and then grow evolved with them because we know the business isn't standing 176 00:14:20.960 --> 00:14:24.559 still during the time that we're doing this implementation. Yeah. The other interesting 177 00:14:24.600 --> 00:14:30.200 thing too is that by starting at this ground level and of course working with 178 00:14:30.240 --> 00:14:35.399 the data people, I appreciate that you are number one, you're on the 179 00:14:35.440 --> 00:14:39.000 street, right, so you're out there where something needs to happen. Right. 180 00:14:39.279 --> 00:14:41.759 One of my favorite analysts years ago said something I thought that was kind 181 00:14:41.759 --> 00:14:45.799 of profound, almost tautological. He said, Look, if something needs to 182 00:14:45.840 --> 00:14:48.840 happen in a large organization, it is happening. You just may not know 183 00:14:48.879 --> 00:14:52.960 how, but I promise you it's happening. It could be a flappy drive 184 00:14:52.080 --> 00:14:56.240 carried across the hall or something. You never know what the workarounds are but 185 00:14:56.799 --> 00:15:00.840 so first of all, to focus on the business value, that tangible business 186 00:15:00.919 --> 00:15:03.440 value on the front line, wherever that is. Maybe it's in marketing, 187 00:15:03.440 --> 00:15:07.320 maybe it's in finance, whatever, but you will learn things as you pull 188 00:15:07.440 --> 00:15:09.799 data together from different systems. You'll learn about this system, we learn about 189 00:15:09.799 --> 00:15:13.639 that system where it is. With the top down approach, you're kind of 190 00:15:13.679 --> 00:15:16.320 presuming that it's all going to work, and of course you find in the 191 00:15:16.360 --> 00:15:22.000 process that it doesn't always work. But those hiccups wind up being two three 192 00:15:22.080 --> 00:15:26.480 four weeks or two three four months that they cause disruption, whereas in your 193 00:15:26.519 --> 00:15:30.600 world it's a faster path to finishing something. And by the way, learning 194 00:15:30.639 --> 00:15:35.240 a lot about these different component systems along the way, right absolutely, And 195 00:15:35.000 --> 00:15:39.399 you know, think of this almost like an agile development approach, right, 196 00:15:39.440 --> 00:15:45.080 so we deploy, we engage, we learn, we adapt, we deploy 197 00:15:45.200 --> 00:15:48.919 in and again, because it's a cogeneration tool, because we're not I'm not 198 00:15:50.120 --> 00:15:54.759 tearing up templates and starting, you know, hiring developers on hand, we 199 00:15:54.840 --> 00:15:58.679 can innovate very quickly. That's interesting and I think you know the challenge that 200 00:15:58.720 --> 00:16:03.360 somebody companies have is they've they've run through an MBM project it's not like, 201 00:16:03.000 --> 00:16:06.720 you know, we have customers companies like I've never ever heard of MBM. 202 00:16:06.840 --> 00:16:10.240 Now that's very few. Most of them have used MBM, like yourself. 203 00:16:10.279 --> 00:16:15.799 It's been around for more than a decade or so. But it was highly 204 00:16:15.840 --> 00:16:21.480 templatized, as in highly structured, as in tops down, and it might 205 00:16:21.519 --> 00:16:25.159 have worked for their initial engagement. It might have been what they needed at 206 00:16:25.159 --> 00:16:27.120 that time. But think of what's happened over the last decade, right, 207 00:16:27.200 --> 00:16:33.279 we have much more data and more locations and more silos. The expectations are 208 00:16:33.440 --> 00:16:38.960 higher, all those storylines that we hear and over again, and so an 209 00:16:40.000 --> 00:16:42.960 approach that might have been effective a decade or more ago is no longer affective 210 00:16:42.960 --> 00:16:48.799 in today's world. And I would argue that it probably never really achieved the 211 00:16:48.840 --> 00:16:52.320 outcomes at that company's desired because it was based around, again, a top 212 00:16:52.360 --> 00:16:56.440 side approach. You know what I find interesting is, you know, we 213 00:16:56.519 --> 00:17:00.200 all in the technology industry come back to the technology, right, I got 214 00:17:00.279 --> 00:17:04.480 something better, faster? And if you look at data, you know, 215 00:17:04.640 --> 00:17:10.920 why have companies struggled with really achieving the data desired outcomes that they have? 216 00:17:11.480 --> 00:17:15.519 It's cultural, right, you know, there's lots of studies out there that 217 00:17:15.599 --> 00:17:21.359 you know, can point to the fact that culture and adoption at the individual 218 00:17:21.440 --> 00:17:23.759 level or the biggest ahead of the inhibitors. Right, and so again that's 219 00:17:23.759 --> 00:17:27.200 what we're trying to get overcome, which is, hey, business leader, 220 00:17:27.720 --> 00:17:33.960 with your data architect, your data team, let's put together your dream application, 221 00:17:36.079 --> 00:17:38.839 and let's put it together and deliver in the way that you can innovate 222 00:17:40.119 --> 00:17:42.759 and be a part of this versus you know, you sent over a couple 223 00:17:42.759 --> 00:17:45.960 of requirements, you close your eyes. A year later, something big and 224 00:17:47.480 --> 00:17:55.079 unwieldy and completely unflexible comes back at you. That's right, right. No, 225 00:17:55.240 --> 00:17:57.720 I love that you've got this data products folks and focus. And frankly, 226 00:17:57.839 --> 00:18:00.519 I think you're a bit ahead of the of the curve on that one 227 00:18:02.000 --> 00:18:04.519 because just now companies are starting to figure out what do you mean a data 228 00:18:04.559 --> 00:18:10.160 product? Right? It's it's interesting because we have this old mindset of application 229 00:18:10.480 --> 00:18:14.200 and database. Application and database. Okay, well, which database we're going 230 00:18:14.240 --> 00:18:17.960 to choose for this application? It's like exactly okay, Like you know, 231 00:18:18.079 --> 00:18:22.599 databases have their own schema, they have their own performance components, they have 232 00:18:22.680 --> 00:18:26.039 their own way of working with them. They're you know, they're different in 233 00:18:26.079 --> 00:18:29.559 many different ways, depending about what you want to do with them. But 234 00:18:29.759 --> 00:18:33.160 now, of course I'll lets talk about data fabric and some other interesting things 235 00:18:33.160 --> 00:18:37.119 going on. Data mash came along and captured the imagination, even though no 236 00:18:37.119 --> 00:18:41.240 one was able to really identify exactly what it is, Like, what exactly 237 00:18:41.240 --> 00:18:44.559 are you talking about? So like, all these things are happening, but 238 00:18:44.799 --> 00:18:48.640 what people really want is a data fueled product. They want an application they 239 00:18:48.680 --> 00:18:53.119 can use to do their job, whatever it is. So it's like really 240 00:18:53.200 --> 00:18:59.160 stripping away some of the component parts in our own mental map to understand this 241 00:18:59.240 --> 00:19:03.640 is a new general ration of functionality. We don't need to think in this 242 00:19:03.839 --> 00:19:08.359 linear point to point app database mindset anymore. You can think about data products, 243 00:19:08.799 --> 00:19:11.079 and as people work with them more and more, they figure out, 244 00:19:11.119 --> 00:19:17.519 oh, I understand now I don't need to have eighty seven columns and forty 245 00:19:17.559 --> 00:19:21.960 eight million rows in the thing that drives this particular product. It only needs 246 00:19:22.000 --> 00:19:26.559 ten columns and two hundred fifty thousand rows or whatever. Where I'm kind of 247 00:19:26.599 --> 00:19:30.960 going with this is we have to change the mindset about how applications are built 248 00:19:30.960 --> 00:19:36.200 and designed and how the sort of totality of data has to be appreciated but 249 00:19:36.319 --> 00:19:38.960 not consumed at once. What do you think? Right, Yeah, and 250 00:19:40.039 --> 00:19:41.799 that's that's an evolution again. It goes back to people, right, And 251 00:19:42.079 --> 00:19:47.759 you're only going to achieve that if you're getting them the tools that they need 252 00:19:48.039 --> 00:19:55.599 versus attempting to subjugate them to some larger approach. Well, you know, 253 00:19:55.640 --> 00:20:00.559 I think back, let's do a fun trot down memory lane back even in 254 00:20:00.640 --> 00:20:03.279 two thousand and oh gosh, I guess this is like two thousand and eight 255 00:20:03.839 --> 00:20:07.119 for a big media company in New York. They were actually my first partner 256 00:20:07.160 --> 00:20:11.319 for DM Radio way back then when we launched that, and they were using 257 00:20:11.319 --> 00:20:14.880 a new cr at relatively new CRM solution, and it was an absolute nightmare, 258 00:20:15.240 --> 00:20:18.240 right, So basically almost no one used it. A few people would 259 00:20:18.319 --> 00:20:21.599 use it, and the people who used it put tremendous amounts of information in 260 00:20:21.640 --> 00:20:23.799 there. So every call they would put in like thirty paragraphs of stuff, 261 00:20:23.960 --> 00:20:27.119 whereas most people would just put a couple things in. And what did you 262 00:20:27.160 --> 00:20:30.480 have? You had all of these hard and fast rules like no, you 263 00:20:30.599 --> 00:20:33.640 must enter the notes field, you must enter this field, you cannot skip 264 00:20:33.680 --> 00:20:37.480 that field, and all this stuff. So what happens is people just stop 265 00:20:37.599 --> 00:20:40.480 using it. And then it was slow as molasses. I mean it was 266 00:20:40.640 --> 00:20:42.039 brutal, like you'd log in and just sit there and wait for it to 267 00:20:42.119 --> 00:20:45.400 load for like, you know, thirty seconds, forty seconds, Like, 268 00:20:45.440 --> 00:20:48.119 who can do that anymore? You can't do that. You have to be 269 00:20:48.160 --> 00:20:52.119 able to move at the speed of your thought, at the speed of emails 270 00:20:52.160 --> 00:20:55.240 coming in and people ring in your phone to tell yourself that has to get 271 00:20:55.279 --> 00:20:57.519 done. That's the speed you have to move at. And so that's where 272 00:20:57.559 --> 00:21:03.759 these data products come into play, as opposed to the old monolithic application design, 273 00:21:03.960 --> 00:21:06.680 which is what we all live through until the last you know, ten 274 00:21:06.799 --> 00:21:11.559 years. Arguably, now that we have these much more federated worlds and we 275 00:21:11.640 --> 00:21:15.599 understand that we can leverage that kind of stuff to build these applications, that's 276 00:21:15.640 --> 00:21:18.720 a whole new ball game in terms of how you go about designing a data 277 00:21:18.759 --> 00:21:22.400 product, how you go about conceiving one of these things, and then of 278 00:21:22.440 --> 00:21:26.039 course you're using it, and that's squarely where you're focused right now, right 279 00:21:26.960 --> 00:21:34.000 absolutely, And that's what how we measure ourselves is are we finding our customers 280 00:21:34.039 --> 00:21:41.599 are successful in their data initiatives? So you know, one is certainly we 281 00:21:41.680 --> 00:21:52.559 strive to have functional MBM solutions up and running in twelve weeks. Sometimes it 282 00:21:52.559 --> 00:21:56.799 goes a little longer, sometimes it goes a little shorter, but that's our 283 00:21:56.799 --> 00:21:59.640 goal, right. And you know, we have a contractor that we actually 284 00:21:59.640 --> 00:22:03.880 built what we call our our blueprints, which provide, you know, step 285 00:22:03.920 --> 00:22:08.000 by step this is this is our recommendation based off of literally hundreds of successful 286 00:22:08.039 --> 00:22:15.240 MBM projects, how we would approach this. Once we have that and you 287 00:22:15.279 --> 00:22:18.559 have your first implementation. I'm not saying it's going to be multi demain or 288 00:22:18.640 --> 00:22:22.079 I'm not saying it's going to solve every business challenge. It's going to address 289 00:22:22.160 --> 00:22:25.440 a critical need where you want to get started. Then we can start to 290 00:22:25.480 --> 00:22:27.680 grow and expand, and then we can say, okay, we've solved location 291 00:22:27.720 --> 00:22:33.160 based services, what's next? So you know, I find the greatest satisfaction 292 00:22:33.200 --> 00:22:37.680 when I'm working with customers that you know, not only started with us and 293 00:22:37.799 --> 00:22:41.119 or successful, but we've grown over time. So I think, you know, 294 00:22:41.160 --> 00:22:45.039 one of my favorite stories to talk about is Chapulte, something you know 295 00:22:45.079 --> 00:22:49.359 we all can recognize. Now they started with us with location based services. 296 00:22:49.960 --> 00:22:55.839 Basically they are struggling with Okay, where are all of our franchises. Something 297 00:22:55.880 --> 00:22:57.599 pretty simple, right, not a big deal. We head them up and 298 00:22:57.680 --> 00:23:03.799 running in six weeks, address that project from there. You know, most 299 00:23:03.920 --> 00:23:07.720 chapults have unique menus. We addressed that. Then we said okay for media 300 00:23:07.720 --> 00:23:12.000 and used ingredients for ingredients to compliance, from compliance to supply chain, and 301 00:23:12.039 --> 00:23:17.480 we're able to work with him through this journey and at every stage help them 302 00:23:17.519 --> 00:23:21.440 find success. Not because we had this massive vision at the start of the 303 00:23:21.440 --> 00:23:23.319 project to go and say, hey, we're going to realign all of your 304 00:23:23.359 --> 00:23:27.640 data. It is, let us solve a problem, let us learn from 305 00:23:27.640 --> 00:23:30.640 that solution, and then let's go solve the next role. Again. I 306 00:23:30.640 --> 00:23:34.359 almost go back to agile development. It's like that's the way to go versus 307 00:23:34.680 --> 00:23:37.920 if we had started off and said, okay, we're going to try to 308 00:23:38.000 --> 00:23:44.480 reimagine your entire inventory, menu, management, compliance all at the same time, 309 00:23:44.799 --> 00:23:47.680 we would fail. Never happened. Now, that's that's right, never 310 00:23:47.720 --> 00:23:49.960 happened. That's really fascinating stuff. Well, folks were talking to Brian Hanson 311 00:23:51.079 --> 00:23:55.160 from some Marquis don't touch dot dot. We're talking all about ground up master 312 00:23:55.240 --> 00:23:59.119 data management and data products and how they can help you go to market We'll 313 00:23:59.119 --> 00:24:06.559 be right back your listen to what if you could own a piece of the 314 00:24:06.599 --> 00:24:10.680 future. What if you could build your next castle not on sand, but 315 00:24:10.759 --> 00:24:15.599 on the bedrock of a modern blockchain ecosystem. 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Indeed, your host Eric having on 365 00:28:19.119 --> 00:28:23.720 here with Grett Hanson from Samarki's we're talking about going to market and the way 366 00:28:23.720 --> 00:28:27.599 you do that is you understand your business better. Quite frankly, that's what 367 00:28:27.599 --> 00:28:30.640 this whole data world is about. It's about understanding your business. And we've 368 00:28:30.640 --> 00:28:36.079 been talking about master data management and ground up versus top down. And the 369 00:28:36.160 --> 00:28:37.799 ground up is great because you learn a lot of things along the way and 370 00:28:37.839 --> 00:28:41.680 then what you learn can help you to design the next data product and the 371 00:28:41.680 --> 00:28:44.759 next data product. But I did want to give the audience some background on 372 00:28:45.079 --> 00:28:48.599 you know, what are the kinds of solutions that you can solve using Master 373 00:28:48.680 --> 00:28:52.039 Data Management. You mentioned a couple in the break three hundred and sixty degree 374 00:28:52.119 --> 00:28:55.000 view of the customer. How long have we've been talking about that? For 375 00:28:55.119 --> 00:28:57.160 like twenty five years, they've been talking about three hundred and sixty three view 376 00:28:57.160 --> 00:29:00.279 of the customer, and really the whole time has been about a thirty six 377 00:29:00.359 --> 00:29:04.720 degree view of the customer and together, you know, the other three hundred 378 00:29:06.160 --> 00:29:11.799 what twenty four are just waiting, but maybe just explain to the audience how 379 00:29:11.839 --> 00:29:15.960 you can enable customer three sixty using this kind of MDM data product approach. 380 00:29:18.640 --> 00:29:22.319 Well, it's obviously a topic that's near and near to my heart as someone 381 00:29:22.359 --> 00:29:26.839 that has marketing as part of their responsibilities. You know, how do I 382 00:29:26.960 --> 00:29:30.559 understand my customers in a holistic way? And like you said, it's you 383 00:29:30.559 --> 00:29:34.359 know right now, it's twenty five or thirty degrees. So, first off, 384 00:29:34.440 --> 00:29:38.799 we have our serum system Salesforce or HubSpot or any of the forty six 385 00:29:38.880 --> 00:29:41.519 other serum systems you use. That's great, that's a great starting point, 386 00:29:41.599 --> 00:29:45.640 right, But that that in itself is a data silo, right, You're 387 00:29:45.640 --> 00:29:51.119 typically going to want to be able to pull in information from whatever system you're 388 00:29:51.200 --> 00:29:53.480 using for finance, you know, so I can understand what are my most 389 00:29:53.519 --> 00:30:00.319 profitable customers. I want to be able to pull in information from my stomer 390 00:30:00.359 --> 00:30:04.200 support, which customers are having good experiences, which customers are struggling right now. 391 00:30:04.680 --> 00:30:08.160 The last he will do is be sending out some sort of promotional content 392 00:30:08.240 --> 00:30:11.759 talking about some exciting new product to a customer who is right now failing to 393 00:30:12.079 --> 00:30:17.680 be successful in the implementation. Right that's going to have a complete opposite experience 394 00:30:17.680 --> 00:30:22.279 that we're trying to have. So what indim allows us to do is starting 395 00:30:22.279 --> 00:30:25.440 to get that what we call golden record. I know it's a cliche, 396 00:30:25.559 --> 00:30:30.599 but I can look and say, Eric Havanaugh, who is he not just 397 00:30:30.079 --> 00:30:36.319 what his address and email is, but his address and email, how much 398 00:30:36.319 --> 00:30:40.880 he's spent with us, what is this customer service experience? What products has 399 00:30:40.920 --> 00:30:45.400 he had? What produces of services is he using actively? And that allows 400 00:30:45.400 --> 00:30:51.119 me to actually drive some really powerful insights into how I approach you versus generic 401 00:30:51.240 --> 00:30:55.720 span email, which of course we know never works or whatever to highly targeted, 402 00:30:55.839 --> 00:31:00.440 thoughtful type communications. We work with a lot of ancial institutions. That's 403 00:31:00.440 --> 00:31:07.519 one of our primary vertical sectors. And what they're looking at is, quite 404 00:31:07.519 --> 00:31:12.559 honestly, how do I optimize each and every customer Because financial institutions, like 405 00:31:12.640 --> 00:31:18.359 mean institution, the cost of acquisition is exceptionally high, So they're trying to 406 00:31:18.359 --> 00:31:22.680 figure out, you know, for every one of my customers, now that 407 00:31:22.759 --> 00:31:27.920 I have a portfolio of different financial solutions for them, everything from banking to 408 00:31:29.079 --> 00:31:33.279 credit cards to loans or whatever else, how do I bring this to in 409 00:31:33.720 --> 00:31:37.400 a thoughtful way. And it all begins by understanding who they are, what 410 00:31:37.599 --> 00:31:44.079 is their current status, what do they have? And without that MBM you're 411 00:31:44.119 --> 00:31:48.160 looking at different pieces. You're now able to have that total three sixty perspective 412 00:31:48.319 --> 00:31:53.599 that allows you to achieve your goals of being able to deliver targeted solutions, 413 00:31:53.640 --> 00:31:59.200 targeted offerings to that customer. Right, that's right. You know, you're 414 00:31:59.440 --> 00:32:02.880 reminding me of how complex the landscape can get. But if you think about 415 00:32:02.920 --> 00:32:07.880 the amount of signal that you could acquire from a HubSpot or a Marcato or 416 00:32:07.920 --> 00:32:12.720 any one of these other tools, there's a lot of valuable information in there 417 00:32:12.720 --> 00:32:16.960 about each individual person who is in the system. Well, just you can't 418 00:32:17.000 --> 00:32:20.920 just create a pipe from one to the other and expect that data to come 419 00:32:20.960 --> 00:32:24.000 through. So what often happens is you'll use that to segment people and say, 420 00:32:24.000 --> 00:32:28.640 Okay, these are buyers of green clothes, these are buyers of red 421 00:32:28.680 --> 00:32:31.799 cars or whatever. That's one path, but that's not really a good path 422 00:32:31.839 --> 00:32:37.119 to true rich personalization. For rich personalization, you need to be able to 423 00:32:37.200 --> 00:32:44.279 understand the nature of this person and then connect that to some operational system that's 424 00:32:44.319 --> 00:32:47.039 doing the outreach. And that's where these data products come into play. Right, 425 00:32:47.079 --> 00:32:51.119 So some markey comes in says, okay, we're going to tap into 426 00:32:51.400 --> 00:32:53.799 Marcato, We're going to tap into this other operational system that you have and 427 00:32:53.880 --> 00:32:57.480 a couple other things, and we're going to give you a view of the 428 00:32:57.480 --> 00:33:00.079 world where you can start to understand, Hey, I think these people over 429 00:33:00.119 --> 00:33:05.880 here are cohort. Let's market to them now. And I'm an email marketer. 430 00:33:05.960 --> 00:33:08.079 So I've been doing email marketing, i joke, for twenty three years 431 00:33:08.079 --> 00:33:12.599 now, which is about three times as long as the average veteran in the 432 00:33:12.599 --> 00:33:15.559 field. So I've seen a lot of changes over the years, and it's 433 00:33:15.559 --> 00:33:19.519 getting a lot harder to do it. You have to get much better about 434 00:33:19.559 --> 00:33:22.599 how on target you are with a message, with when you send things like 435 00:33:22.680 --> 00:33:27.880 all these features that you used to be nice to have are now absolutely must 436 00:33:27.920 --> 00:33:30.920 haves or you're going to burn through your list and kill that list. And 437 00:33:30.000 --> 00:33:34.680 when a list is killed, it's dead. So this is really important stuff, 438 00:33:34.759 --> 00:33:38.359 right, Well, and I'll take it a step further. It sounds 439 00:33:38.359 --> 00:33:42.400 like it should be easy to bring all these different pieces together. Right, 440 00:33:42.440 --> 00:33:45.319 there's what our capital, right, Well, is there one or is there 441 00:33:45.400 --> 00:33:49.759 three? Or four? And how do I make sure I'm associating these different 442 00:33:49.759 --> 00:33:53.680 records appropriately? Maybe you have a different spelling or maybe you have a middle 443 00:33:53.720 --> 00:33:58.559 initial in some of these records are the ones you don't. So it goes 444 00:33:58.599 --> 00:34:00.759 a step further in terms of its I was like, okay, I can 445 00:34:00.799 --> 00:34:04.319 just bring all this stuff together. Well wait a second, data is not 446 00:34:04.400 --> 00:34:07.359 that simple, right, You've got to be able to go and look at 447 00:34:07.400 --> 00:34:09.800 this and be able to understand, all right, how do I bring these 448 00:34:09.800 --> 00:34:14.800 sources together so that I do have an accurate gold record? And of course 449 00:34:14.800 --> 00:34:17.119 our systems can help with that. But you know, that's a really important 450 00:34:17.159 --> 00:34:21.400 thought that often gets lost is Oh, it's just you know, we're just 451 00:34:21.480 --> 00:34:23.480 mashing all the data together. No, no, no, there's a lot 452 00:34:23.519 --> 00:34:28.840 of data quality that gets built in here to make sure that what is golden 453 00:34:29.320 --> 00:34:32.199 is truly golden. M. Well that's the other very interesting things. So 454 00:34:32.239 --> 00:34:37.400 to get back to MDM top down versus bottom up, Well, what happened 455 00:34:37.400 --> 00:34:39.639 in the old days is that you would do your requirements academy. You look 456 00:34:39.639 --> 00:34:45.119 at all the systems you want to and style you big, big project to 457 00:34:45.199 --> 00:34:47.679 do all that at some sort of foundational level. Well, what you're actually 458 00:34:47.719 --> 00:34:51.639 doing by taking this start small. And everyone says that starts small, right, 459 00:34:51.639 --> 00:34:52.880 don't buw the ocean, and yet you get people put on the ocean. 460 00:34:53.119 --> 00:34:57.400 So you got to start small. But you're going to learn things about 461 00:34:57.440 --> 00:35:00.239 each and every one of these data sources that it is going to be very 462 00:35:00.360 --> 00:35:04.639 valuable for the second and third and fourth data products that you generate, and 463 00:35:04.679 --> 00:35:07.719 also will be valuable for the teams who own these different systems. Say hey, 464 00:35:07.719 --> 00:35:13.559 did you guys know that you have this combination problem in this field and 465 00:35:13.679 --> 00:35:15.400 we're missing that data when we come over. Right, that's what all this 466 00:35:15.480 --> 00:35:21.599 observability stuff is about, to see what's going where. And because you've taken 467 00:35:21.639 --> 00:35:25.719 this I think very clever approach of starts small, build incrementally you're learning a 468 00:35:25.760 --> 00:35:30.119 lot all along the way such that each subsequent project becomes a little bit easier 469 00:35:30.119 --> 00:35:34.760 and a little bit easier. And that's how you build momentum in the organization. 470 00:35:34.840 --> 00:35:37.639 That's how you help your clients go to market with their technologies and their 471 00:35:37.679 --> 00:35:45.599 solutions. Right, absolutely, Yeah, And that concept of learning as you 472 00:35:45.679 --> 00:35:49.760 go is so important, right because we all start every project by assuming that 473 00:35:49.800 --> 00:35:53.280 we have all the answers, right, And what we find very often is 474 00:35:53.320 --> 00:36:00.360 after the first phase again ideally ten weeks or so, you know, we 475 00:36:00.440 --> 00:36:02.440 get it into hands and we learned from that, and then we can adapt 476 00:36:02.440 --> 00:36:06.280 to grow the other thing, which I just you know I've mentioned once when 477 00:36:06.280 --> 00:36:09.000 I stressed it again. Business is continuing to change, right, Right. 478 00:36:09.119 --> 00:36:15.719 We actually were with the customer working on their implantation and halfway the invitation they 479 00:36:15.800 --> 00:36:21.119 acquired in their company that obviously has profound implications to what we're trying to achieve, 480 00:36:21.320 --> 00:36:23.239 right, So right, we had to take a step back and say, 481 00:36:23.239 --> 00:36:25.760 okay, what do we want to do. That project was not twelve 482 00:36:25.800 --> 00:36:30.079 weeks, I'll be honest, because we kind of pushed it out further because 483 00:36:30.079 --> 00:36:32.400 we had to think about what are the implications, how is this going to 484 00:36:32.480 --> 00:36:36.679 work? What new data sectors are we going to go? And again, 485 00:36:36.760 --> 00:36:38.679 you know, trying to boil the ocean. But you needed to be cognizant 486 00:36:38.719 --> 00:36:44.639 of the broader business requirements that had changed posts making an acquisition. Right, 487 00:36:45.760 --> 00:36:47.039 Yeah, that's a that's a big deal. And you know, I'm connecting 488 00:36:47.079 --> 00:36:52.719 some dots in my head. Here is here talking and I'm realizing the importance 489 00:36:52.960 --> 00:36:58.360 of change and the importance of appreciating change. I was talking to some vcs 490 00:36:58.360 --> 00:37:00.119 probably six months ago, and this one guy made a really good point. 491 00:37:00.239 --> 00:37:05.880 He said, we know that whatever we design today in six months is going 492 00:37:05.880 --> 00:37:08.519 to be disrupted, So how do you plan for that? I mean, 493 00:37:08.559 --> 00:37:13.599 how do you plan for the whole market changing? And then, of course 494 00:37:13.840 --> 00:37:17.000 since that time, the large language models took center stage. So they had 495 00:37:17.039 --> 00:37:21.400 been around chat, GPT two and three, etc. It's not new, 496 00:37:22.000 --> 00:37:24.639 but when open Ai rolled it out, that was a huge eye opener, 497 00:37:24.679 --> 00:37:29.800 one of the biggest I've ever seen in terms of just shaking the foundation of 498 00:37:29.800 --> 00:37:32.880 what is accepted as normal, what is accepted as the way to do business. 499 00:37:32.960 --> 00:37:36.360 You know, we're going to go through I think probably a two to 500 00:37:36.400 --> 00:37:43.800 five year period now of just remarkable bottom line day to day workflow transformation because 501 00:37:43.960 --> 00:37:47.039 of these engines and because what they're capable of doing. But you know that 502 00:37:47.159 --> 00:37:52.159 change is really important, and it's very important for marketers and for salespeople to 503 00:37:52.239 --> 00:37:55.760 kind of understand this like you think about So let's get back to three to 504 00:37:55.840 --> 00:38:00.679 sixty view of the customer. Let's do three sixty view of the prospect. 505 00:38:00.840 --> 00:38:02.559 Right. If you're trying to figure out who to market to, who to 506 00:38:02.599 --> 00:38:08.599 spend time and money building content, sending information to, etc. Well you 507 00:38:08.760 --> 00:38:12.440 really want those teams, So it's go to market teams to be able to 508 00:38:12.440 --> 00:38:15.079 fail fast forward if they say, you want to be able to try lots 509 00:38:15.159 --> 00:38:19.400 of different things and see what works and what doesn't work. Now, there 510 00:38:19.519 --> 00:38:22.679 is something to be said for consistency and newsletters that go out once, so 511 00:38:22.719 --> 00:38:24.480 we can think of this nature. But these days, man, you better 512 00:38:24.559 --> 00:38:29.079 be trying new stuff to get through to people or you're going to be in 513 00:38:29.119 --> 00:38:31.920 trouble. What do you think? Yeah, I mean the continuous innovation is 514 00:38:32.360 --> 00:38:39.079 certainly part of everything we're doing today. You know from marketer perspective, you 515 00:38:39.119 --> 00:38:44.599 know, Chat, GPT and these other AI tools aren't truly changing the landscape. 516 00:38:45.920 --> 00:38:47.559 You know, we use them in a number of different ways as Samarchi, 517 00:38:47.559 --> 00:38:52.039 and we're a relatively small company, and I can tell you that they've 518 00:38:52.079 --> 00:38:55.639 already had profound implications in terms of how I spend dollars and how I execute. 519 00:38:57.760 --> 00:39:02.639 But I also have learned that, like with any new technology, you 520 00:39:02.760 --> 00:39:08.119 have to be careful about embracing adoption. Right So there's lots of great opportunities 521 00:39:08.159 --> 00:39:15.639 for utilizing it and helping streamline content production, helping you become more targeted in 522 00:39:15.679 --> 00:39:20.039 your outbound But at the same time, you know, like I've always said, 523 00:39:20.480 --> 00:39:24.119 you know, new technology has to be vetted and thoughtfully applied or it 524 00:39:24.159 --> 00:39:30.679 can be more detrimental than beneficial. Sure, so we've seen some of that 525 00:39:30.719 --> 00:39:36.079 with the largest language models already with the hallucinations, right yeah, because they 526 00:39:36.159 --> 00:39:38.880 are generative. So it's funny. I was covering the Data Bricks conference, 527 00:39:39.280 --> 00:39:44.280 their Generation AI conference, and the girl was talking about how she was doing 528 00:39:44.280 --> 00:39:46.360 a demo about how they train the models, etc. And you know, 529 00:39:46.440 --> 00:39:50.119 my wheels are always spinning like, Okay, how much time is it going 530 00:39:50.159 --> 00:39:52.440 to take the train these models? And you know, where does the value 531 00:39:52.559 --> 00:39:58.880 really accrue and go beyond just you know, solving some small problems like where 532 00:39:58.880 --> 00:40:00.960 do you actually get the inflect point where this thing takes off? Well, 533 00:40:01.000 --> 00:40:04.400 that's going to be a while, I think with many of these, for 534 00:40:04.400 --> 00:40:08.199 the reasons that you've outlined. But while I was tweeting about this, someone 535 00:40:08.320 --> 00:40:12.239 from chat GPT on Twitter came back and say, hey, wait a minute, 536 00:40:12.280 --> 00:40:15.440 you know we don't use that data for our models. Data bricks knows 537 00:40:15.480 --> 00:40:17.719 this, etc. So here we are in this real time conversation with the 538 00:40:17.760 --> 00:40:22.760 major players in the space, and I chose, because I'm a journalist, 539 00:40:22.840 --> 00:40:23.519 to ask a few more questions and say, well, what do you do 540 00:40:23.559 --> 00:40:27.679 about hallucinations? And he said, remember, these are really more of a 541 00:40:27.719 --> 00:40:30.079 feature than a bug, right, This is what these things are designed to 542 00:40:30.119 --> 00:40:37.039 do, to fuse together different vectors of information to create prose that will ideally 543 00:40:37.239 --> 00:40:40.280 satisfy the request and the prompt. Right. Well, there are lots of 544 00:40:40.280 --> 00:40:43.800 ways you can do that, and we talked about it on other shows. 545 00:40:43.840 --> 00:40:46.000 But you can either embed your corporate data into the model, which is pretty 546 00:40:46.039 --> 00:40:50.639 complex thing to do, or you can use a vector database and kind of 547 00:40:50.639 --> 00:40:52.960 get this anchor of truth, which I think is probably the clever way to 548 00:40:53.000 --> 00:40:58.360 go. But in that sense you can start leveraging these things, and you 549 00:40:58.360 --> 00:41:00.639 know, to your point, you do have to be careful, walk through 550 00:41:00.760 --> 00:41:04.199 step by step, make sure you know what you're doing. But the power 551 00:41:04.239 --> 00:41:07.199 of these things to just look at the world in a different way. I 552 00:41:07.199 --> 00:41:09.559 mean, I was a philosophy major many years ago when our teacher used to 553 00:41:09.559 --> 00:41:14.320 always say different perspectives, like that's what you want? And I think you're 554 00:41:14.360 --> 00:41:16.239 kind of singing that tune on the people front, right if you want to 555 00:41:16.239 --> 00:41:20.719 talk to the people, who are these people that we're working with and understand 556 00:41:20.760 --> 00:41:23.159 they're all different. Every data project is different, every person is different. 557 00:41:24.000 --> 00:41:28.199 So that seems to be core to your approach for working with them, right, 558 00:41:28.760 --> 00:41:30.119 absolutely, And I think going back to the you know, the AI 559 00:41:30.239 --> 00:41:39.400 pieces, it's something which is almost every conversation we have a customers Againstrado people 560 00:41:39.400 --> 00:41:43.000 are excited about it. Right, this is game changing, this is this 561 00:41:43.079 --> 00:41:46.880 is you know, the next you know evolution of our economy from industrial the 562 00:41:46.880 --> 00:41:53.360 digital to now you know, AI based. We've taken a very pragmatic approach 563 00:41:53.840 --> 00:41:58.400 and you know, we actually have an open architecture so you can plug into 564 00:41:58.440 --> 00:42:04.480 chet GPT and utilize chat. GPT is part of your MDIM project. We've 565 00:42:04.559 --> 00:42:07.800 long been able to tie into Google Translator and any of this recognition, so 566 00:42:07.880 --> 00:42:12.280 we've long sort of said like, hey, you know, our belief is 567 00:42:12.719 --> 00:42:16.920 there are great tools out there to help enrich your data, utilize them, 568 00:42:17.280 --> 00:42:21.400 versus jumping down the path like you were talking about of saying, Okay, 569 00:42:21.400 --> 00:42:23.440 we're going to bed a bunch of AI technology within our MBM and then it 570 00:42:23.440 --> 00:42:29.679 becomes a black box. And where that scares me is okay, if I 571 00:42:29.719 --> 00:42:35.920 don't properly train that is that going to have implications to compliance or security or 572 00:42:35.960 --> 00:42:39.079 accuracy. And especially given the fact that I mentioned we have lots of customers 573 00:42:39.119 --> 00:42:45.079 and finance, we have lots of customers in healthcare like making mistakes there pretty 574 00:42:45.079 --> 00:42:50.360 catastrophic type situation. So our perspective is, yeah, there are some really 575 00:42:50.360 --> 00:42:52.960 exciting things that are going to be coming with AI and mL, the ability 576 00:42:53.000 --> 00:43:00.360 to do match and merge to you know, have streamline and novelty, infection 577 00:43:00.440 --> 00:43:07.199 and correction. Huge implications outstanding, But just like with everything else, it 578 00:43:07.360 --> 00:43:10.840 is going to need to be unique to that individual company, certainly that imagual 579 00:43:12.039 --> 00:43:15.599 you know, sector at the very least, but ideally that individual customer because 580 00:43:15.639 --> 00:43:19.639 if not, okay, well now we have compliance implications, Now we have 581 00:43:19.679 --> 00:43:22.480 security implications, Now we have accuracy account and that you know. So it's 582 00:43:22.519 --> 00:43:27.239 exciting and we're like embracing that, you know, the potential here, but 583 00:43:27.320 --> 00:43:30.079 we're doing it as you said, and that vector database sort of approach, 584 00:43:30.119 --> 00:43:32.639 which is, don't make it a black box. Don't build this so deeply 585 00:43:32.679 --> 00:43:37.119 into your environment that I don't actually know what's happening. You're going to need 586 00:43:37.159 --> 00:43:40.719 to have still controls over that and build it in just like everything else, 587 00:43:40.760 --> 00:43:45.639 which is, you know, have an incremental plan to go and be able 588 00:43:45.639 --> 00:43:49.360 to embrace. Yeah, that's exactly right. Incremental plan, that's what you 589 00:43:49.360 --> 00:43:52.679 want. Folks, don't boil the ocean. Never boil the ocean. Step 590 00:43:52.760 --> 00:43:54.760 by step iterative, iterative development, that's what they call it. Well, 591 00:43:54.760 --> 00:43:58.400 folks, don't touch it. That will be right back with Bret Hanson of 592 00:43:58.440 --> 00:44:05.760 Simarchi or left things that inside and out. Do you own an annuity either 593 00:44:05.840 --> 00:44:08.719 fixed rate, indexed or variable? Are you paying high fees and getting low 594 00:44:08.760 --> 00:44:13.800 returns? 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Welcome back to Inside Analysis. 645 00:48:08.599 --> 00:48:19.280 Here's your host, Eric Kavanaugh. All right, folks, back here 646 00:48:19.320 --> 00:48:23.360 on Inside Analysis, talking all things data products and master data management. Top 647 00:48:23.440 --> 00:48:28.199 up or bottom I'm sorry, top down or bottom up? Bottom up is 648 00:48:28.239 --> 00:48:30.519 the way to go, folks. Top down, We tried it for years. 649 00:48:30.559 --> 00:48:32.039 We tried it. Their whole companies that disappeared, that did end, 650 00:48:32.159 --> 00:48:35.760 and they're not even around anymore because they were doing the top down. Not 651 00:48:35.840 --> 00:48:38.320 all the people like that. Well, we're talking to Brett Hanson of Samarky 652 00:48:38.440 --> 00:48:42.920 and he's getting me all excited about data products and to kind of put this 653 00:48:42.960 --> 00:48:45.840 back into the go to market framework. You know, going to market is 654 00:48:45.880 --> 00:48:51.440 a very interesting and I would say sort of dicey enterprise these days, because 655 00:48:51.480 --> 00:48:53.599 you have so many options about where you can spend money, of so many 656 00:48:53.639 --> 00:48:58.280 ways that you can do things now, all these different social engines. Of 657 00:48:58.280 --> 00:49:01.760 course, you've got first party data, email marketing, traditional stuff, conferences, 658 00:49:01.800 --> 00:49:06.079 going to talk to people, getting your messaging right. Well, data 659 00:49:06.119 --> 00:49:10.519 products can be extremely valuable in terms of understanding that in terms of developing your 660 00:49:10.559 --> 00:49:15.440 go to market strategy. Even if it's just understanding where are people coming from 661 00:49:15.480 --> 00:49:21.000 when people interact with us, what is the preponderance of people who are calling 662 00:49:21.079 --> 00:49:24.840 us on a call center versus coming into stores like Chipotle versus on the app 663 00:49:25.000 --> 00:49:30.519 or social or whatever. Just understanding how people get to you is a data 664 00:49:30.519 --> 00:49:37.719 product, right absolutely, And I think that you know, marketing go to 665 00:49:37.800 --> 00:49:44.960 market continues to evolve very rapidly, and it is easy to be overwhelmed by 666 00:49:45.000 --> 00:49:52.000 the information that's available. Right, So any channel you can look at fifteen 667 00:49:52.119 --> 00:49:57.400 twenty different data points set and tell you how to optimize PPC or your webinar 668 00:49:57.480 --> 00:50:00.320 spend, or your emails or your face. I mean, it's just goes 669 00:50:00.400 --> 00:50:05.039 on and on and on. And what I try to bring my team back 670 00:50:05.039 --> 00:50:10.840 consistently too, is what does your prospect or your customer need provide value to 671 00:50:10.880 --> 00:50:15.760 them? You know, I know we think our job is to market to 672 00:50:15.800 --> 00:50:19.920 them and sell to them and try to force them down our imaginary buyer's journey. 673 00:50:20.639 --> 00:50:25.119 Our real responsibility is to help them with whatever tasks they have in front 674 00:50:25.159 --> 00:50:28.719 of them. It might be the fact that we're not the right company for 675 00:50:28.760 --> 00:50:30.440 them, and what our help is to point them in some other direction. 676 00:50:31.440 --> 00:50:38.320 But you know, ideally we're providing valuable information that helps them along their buyer's 677 00:50:38.400 --> 00:50:43.400 journey, not ours theirs. Right now, what I like for that buyer's 678 00:50:43.440 --> 00:50:46.320 journey to ultimately be a product purchase from my company? Absolutely. Do I 679 00:50:46.360 --> 00:50:51.079 feel confident that I have a great product, Yes, I do, But 680 00:50:51.159 --> 00:50:57.119 that doesn't mean that I should be forcing my views down their throats, right, 681 00:50:57.159 --> 00:51:00.760 So the whole constpt of the Golden rule and really trying to understand what 682 00:51:00.760 --> 00:51:04.159 they need and then being able to speak to them and their and their language 683 00:51:04.159 --> 00:51:08.360 that their point in their buyer's journey is absolutely essential. Yeah, that's right. 684 00:51:08.360 --> 00:51:12.239 I just throw out this down our imaginary buyers journey. That's a book 685 00:51:12.239 --> 00:51:15.199 title. By the way, that's a very book title. I like that 686 00:51:15.239 --> 00:51:20.719 you're honest about recognizing that, yes, every company will have their imaginary buyer's 687 00:51:20.800 --> 00:51:23.159 journey what they think people are going to do to get to them. And 688 00:51:23.199 --> 00:51:27.840 sometimes you're right and sometimes you're not right, but you do have to keep 689 00:51:27.880 --> 00:51:30.639 an open mind that people come to you various ways, and then people use 690 00:51:30.719 --> 00:51:32.360 the technology in different ways too. I mean, one of the coolest things 691 00:51:32.400 --> 00:51:37.400 about software that I've learned, it was actually the MDM company in particular, 692 00:51:37.800 --> 00:51:39.679 is that you can have your thoughts about how people are going to use your 693 00:51:39.719 --> 00:51:43.679 tech, and then you'll do a user conference and you get all these people 694 00:51:43.679 --> 00:51:46.480 coming to you showing you things that you never imagined which are possible because of 695 00:51:46.519 --> 00:51:51.400 your tech. So I would tend to think that's especially true with you guys, 696 00:51:51.440 --> 00:51:54.719 because again, you're focused on building data products, right, and the 697 00:51:54.719 --> 00:51:59.760 thing is you don't have to do some sort of one to one map between 698 00:51:59.760 --> 00:52:02.840 the product and an Excel spreadsheet, which is kind of how people still think 699 00:52:02.880 --> 00:52:06.960 in terms of accessing data for the app, right. Don't think of it 700 00:52:07.000 --> 00:52:08.880 that way. You know, we've had data marks, for example, we've 701 00:52:08.880 --> 00:52:13.280 had old app cubes. There are all these sort of constructs we've come up 702 00:52:13.280 --> 00:52:17.119 with over the years, but they're all fairly linear and staid, I guess, 703 00:52:17.280 --> 00:52:22.480 Whereas what's interesting about your approach is that you're working with the business to 704 00:52:22.559 --> 00:52:27.199 figure out how to solve some particular challenge. And let's say it's this understanding 705 00:52:27.239 --> 00:52:30.039 your prospects, so we could do go to market, Well, who are 706 00:52:30.079 --> 00:52:32.320 our prospects? You sit down, you look at what are the prospect databases? 707 00:52:32.360 --> 00:52:37.039 Our email database, our social media feeds, things of these nature. 708 00:52:37.079 --> 00:52:39.800 These are all the sort of entrance points. But who is coming here? 709 00:52:40.599 --> 00:52:44.960 How can we analyze this? Can we get web trends data to see who 710 00:52:45.039 --> 00:52:47.320 is clicking, who's not? What are the RL's pointing to us? All 711 00:52:47.400 --> 00:52:52.760 this stuff, which lives in lots of different silos doesn't have a lot of 712 00:52:52.840 --> 00:52:57.880 value until you've pulled it together in some meaningful way. And that's what you're 713 00:52:57.920 --> 00:53:02.280 doing with these data products, right absolutely. And I mean we actually have 714 00:53:02.360 --> 00:53:07.079 an Indian project going on in our way in our own company. So we're 715 00:53:07.119 --> 00:53:13.519 a relatively small company. I mean we're not you know, global fifty type 716 00:53:13.519 --> 00:53:15.199 company. We're talking about hundreds of employees. As I said, we have 717 00:53:15.199 --> 00:53:21.039 a few hundred customers globally. But we have found actually that even we have 718 00:53:21.119 --> 00:53:24.440 the need to really very able to bring all these different data sources together so 719 00:53:24.480 --> 00:53:30.840 that I can have more intelligent conversations with my customers and prospects. And I 720 00:53:30.840 --> 00:53:34.480 think that's that's the key is it's I'm marking to them. It's not I'm 721 00:53:34.480 --> 00:53:37.119 selling to them. I'm trying to have an intelligent conversation so that I can 722 00:53:37.199 --> 00:53:43.599 help provide them what they need right now. In that process, I am 723 00:53:43.679 --> 00:53:47.039 learning more about them. I am gathering more information about who they are and 724 00:53:47.440 --> 00:53:52.920 what business challenges they might have, what technologies are utilizing, so I can 725 00:53:52.039 --> 00:53:59.559 become a better communicator back into them, while at the same time, you 726 00:53:59.679 --> 00:54:02.639 know, progressing them ideally through a buyers journey that ultimately results in a sale 727 00:54:02.639 --> 00:54:07.920 with us. But as I mentioned, you know, and you called this 728 00:54:07.960 --> 00:54:10.519 out, I thought, really well, because we have a data product, 729 00:54:10.920 --> 00:54:15.360 and yes, there are certainly use cases that are consistent, like customer three 730 00:54:15.440 --> 00:54:22.239 sixty or product three sixty, but even then that spans a tremendous amount of 731 00:54:22.440 --> 00:54:25.599 range. Right what I consider be a customer three sixty might be very different 732 00:54:25.639 --> 00:54:30.360 than you know, a financial institution that's global versus of mid tier bank. 733 00:54:30.480 --> 00:54:36.840 I mean, they all have different requirements and so I can't force my perspective 734 00:54:36.840 --> 00:54:40.039 onto them. I can provide them with information and education and tools to help 735 00:54:40.079 --> 00:54:45.280 them learn, but I can't be you know, our way is the only 736 00:54:45.280 --> 00:54:49.559 way, and I think that's how we have found success is. It's a 737 00:54:49.599 --> 00:54:52.400 massive market out there. There's a lot of noise. As you mentioned, 738 00:54:52.920 --> 00:54:57.239 the market has been a top down approach for a decade and if you look 739 00:54:57.280 --> 00:55:00.639 at the largest customers or companies excuse me, that are servicing MBM, they're 740 00:55:00.679 --> 00:55:04.599 all cops down and they have a lot more money to spend it. They're 741 00:55:04.599 --> 00:55:06.480 going to tell everyone that this is the best way to do it. And 742 00:55:06.760 --> 00:55:09.679 I can't compete with that. But why can do is provide an educational package 743 00:55:09.679 --> 00:55:15.000 back into the marketplace saying okay, that's an option, here's how we approach 744 00:55:15.079 --> 00:55:19.039 things, and here are some of the best practices that we have. Hopefully 745 00:55:19.039 --> 00:55:22.679 this will help you learn as you're going through your buy journey. That's great. 746 00:55:22.119 --> 00:55:24.679 I think that's really cool and I love this quote you just said. 747 00:55:24.840 --> 00:55:29.880 I can't force my perspective on them, and that's very smart. Right. 748 00:55:29.920 --> 00:55:32.519 They're coming to you because they want to solve some problem. Maybe they had 749 00:55:32.519 --> 00:55:37.079 a different problem to solve before they started talking to you, But it's in 750 00:55:37.119 --> 00:55:43.119 the conversation, the meaningful, intelligent conversation that you can come across certain touchstones 751 00:55:43.360 --> 00:55:46.320 and then leap forward and they'll mention something about, oh, what this friction 752 00:55:46.360 --> 00:55:50.320 point we have, Oh what is that about. That's when you can kind 753 00:55:50.320 --> 00:55:52.679 of dig in and you do have to share information. You have to share 754 00:55:52.719 --> 00:55:55.760 your insights. You know. It's not like the old days of just showing 755 00:55:55.760 --> 00:56:00.199 someone a brochure and say, oh, here we buy our product online or 756 00:56:00.239 --> 00:56:05.039 I mean, you're talking about complex enterprise software that is designed to give a 757 00:56:05.079 --> 00:56:08.159 better view of a particular business aspect, is really what you're talking about. 758 00:56:08.480 --> 00:56:12.679 But that's been the vision all along. Like that's the funny thing is that 759 00:56:12.760 --> 00:56:16.039 was the vision even in the top down monolithic age. It's just that you 760 00:56:16.119 --> 00:56:22.400 had to hope that someone on the client on the vendor side would listen to 761 00:56:22.440 --> 00:56:25.239 you enough for your feature to make the next release right. And how often 762 00:56:25.320 --> 00:56:30.239 was that? Not very often? And so you're kind of again pulling an 763 00:56:30.320 --> 00:56:37.159 end around on that old monolithic waterfall approach to building things, and you're saying, 764 00:56:37.199 --> 00:56:39.280 no, we can build you a product. It'll only take six to 765 00:56:39.360 --> 00:56:44.880 twelve weeks or so and you'll have something functional. And by the way along 766 00:56:45.000 --> 00:56:49.440 that path, you're going to get better and better at really understanding what your 767 00:56:49.679 --> 00:56:52.840 de facto reference architecture is. It's going to be unique, it's going to 768 00:56:52.880 --> 00:56:58.039 be different than anyone else is in the world. And thus the more intel 769 00:56:58.079 --> 00:57:00.159 you gat about your environment, the better off you're going to be for the 770 00:57:00.199 --> 00:57:04.639 next data product and the next data product. Right. Yea, yeah, 771 00:57:04.679 --> 00:57:09.239 every company, every solution is a saflake. It is unique, right and 772 00:57:09.599 --> 00:57:14.119 as if you if you think about it that way, you think about and 773 00:57:14.199 --> 00:57:17.760 we say this all time. Data is the blood of your of your organization, 774 00:57:17.880 --> 00:57:22.599 right, It's what drives your decisions, what helps shoot different to your 775 00:57:22.599 --> 00:57:25.440 srself from your competitors. Right. If that's really true, then you're going 776 00:57:25.519 --> 00:57:30.199 to need a solution that's unique, bespoke and you're not going to achieve that 777 00:57:30.559 --> 00:57:36.760 if you're starting off with a template tops down approach. You know, being 778 00:57:36.760 --> 00:57:44.239 able to generate a bespoke application that services your specific business requirements, whether it 779 00:57:44.320 --> 00:57:51.760 again that's a customer three sixty or you know, you know location inventory product, 780 00:57:52.400 --> 00:57:54.960 that's what's going to allow you to be successful. And it's it's not 781 00:57:55.039 --> 00:58:00.000 a single exercise, it's journey. We're going to be on a journey. 782 00:58:00.079 --> 00:58:04.280 It's you to help you achieve your business outcomes. Yeah. And the difference 783 00:58:04.639 --> 00:58:07.079 in when you use this term, because I've heard that term before talking about 784 00:58:07.119 --> 00:58:12.960 things changing over time. The difference is that ten years ago, that journey 785 00:58:13.159 --> 00:58:15.599 was going to be like six months to two years, and it was going 786 00:58:15.679 --> 00:58:19.599 to be to stand up one big honk in the thing that was going to 787 00:58:19.639 --> 00:58:22.199 allow you to do all sorts of amazing magic with your data. And that 788 00:58:22.440 --> 00:58:24.800 is not the correct path. Like, what you want to do is have 789 00:58:24.840 --> 00:58:30.360 a journey where you get small winds than bigger winds and bigger winds but targeted 790 00:58:30.400 --> 00:58:37.000 focused on particular business use cases, solving problems for the business while you're incrementally 791 00:58:37.039 --> 00:58:42.159 building out what is essentially your de facto data fabric. But folks, what 792 00:58:42.280 --> 00:58:45.840 a fantastic conversation with Brett Hanson. Send me an email. You're listening to 793 00:58:45.920 --> 00:58:54.880 them inside analysis. 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