Utilizing big data and machine learning for predictive modeling in the b2b supply chain

Kenneth Goodwin, Senior Managing Principal & Founder @Jeanensis Capital Markets
Main Stage
Ascent Conference 2020

[00:00:01] Hello, good day, How’s everyone doing today? This is and good one is a. a pleasure to be speaking at the conference this afternoon. My topic will be on utilizing big data and machine learning or predictive modeling in the B2B supply chain. Let me just first start off by giving you a bit of background. My firm, which is tremendous capital markets or Genesis of the Ginés, is basically we are a capital advisory firm. We focus on artificial intelligence, red tech, as well as the block chain industries. So we’ve been working in that industry for a period of time. And several firms that we’ve been concentrating on deal would be to be business, cross-border trade. So things have moved on. So let’s first start off with the idea of imagine a borderless trade system.

[00:01:04] What would that entail domestically, but also internationally? Now, essentially, this starts with a quote by Dr. Peter Drucker. Dr. Drucker once said that you don’t just look at the actual operations and you don’t just look at the actual efficiency of the operations, which you do concentrate on is the actual processes and the actual systems themselves. So within those particular comments, what you’re going to find is is maybe three elements to concentrate on. When we talk about the idea of using data management data systems for voice trace system. The first one is data analysis that we’re going to focus on. The second one is the use of block chain and digital technology, also DLT. And the third area is artificial intelligence with a focus and emphasis on not just machine learning and deep learning that we’re concentrating on, but we’re also concentrating on what we call third wave A.I. and third wave A.I. tends to be just a little bit background. It tends to be a little bit more advanced. And it looks at it from a standpoint of a cognitive approach where that algorithm acts in a way where the probes and it has a memory feature to it. That’s very significant for data and analytics. But also at the same time, it’s also very it’s very significant for predictive modeling. Next, please, Kevin.

[00:02:43] OK, Kevin. Next, please. Yes, so the world is definitely changing, as we can see, the world is gravitating, is changing drastically.

[00:02:54] Covid-19 has definitely brought on this digital transformation. And one of the areas that it’s really focusing on is the use of big data. And within that big data function, we focused mainly on natural language processing. Now natural language processing, at least with the efforts that we had at geneticists. So our clients pretty much operate businesses around here. And the focus has been on mainly on the use of data where they can smooth data out, but most importantly, being able to tell a story with the data that’s ascertain and that’s very significant. Then beyond that is another focus on cost specification management. Specification management looks at raw data at its core, and it also be able to track and measure and monitor particular data. This is a focus and do a specification management. It allows for a smooth operation as smooth processes. For example, when I did some work at Eataly Acardo, known as Seven-Eleven, they use what they call a specification management process and essentially what that was added to your do a 7-Eleven in Japan, the idea was that you as a consumer, you’re able to go into the store and when you go into that store, you’re able to purchase an item and then purchasing an item destock. Cloke is able to ascertain certain data from you that could be in terms of barcodes, that could be in terms of when you purchase that and that can be with prices and so forth. Now, the reason why that was very important in terms of specification management, what that did was that particular raw data was was being used at the very granular level. And that level includes the actual store operations, but also in terms of the distribution centers. So what you find at the store we use in data that I do ascertain from consumers that was use within distribution production as well as the accounting feature. And that’s very significant in terms of how data is being used, how it’s been analyzed and how it’s being processed. The better way to to use this data information is what we know and as to block chain system and block chain in itself. It is a distributed technology system that pretty much allows for efficiency, the speed to occur. The key with the block chain system is that there’s a trace and mechanism to that particular system. So that allows for not only data to be transparent, but most importantly allow for data to be a little bit more efficiently. And then finally, we want to touch on A.I., particularly between machine learning and deep learning, but also third wave I and I. My emphasis has been on third wave A.I. because generally that’s the next step in terms of having a memory that allows to memorialize that data, but most importantly, being able to use that data and predictive modeling. And of course, the features that have been used for that is the APIs, the apps, as well as the cloud, which is going to be used to store that particular data. So if you utilize this all in one particular system, you are able to not only to address big data, but you’re also able to execute the block chain as well as ADD is going to actually move the BTB process for most of the businesses around the world.

[00:06:33] Kevin, next, please. Next slide, please.

[00:06:37] So in the air of data proliferation, let’s concentrate on big data a bit as data becomes more proliferated and as data is being more used, what we’re finding is that this tends to be more platforms that are being created and particularly APIs. So which are finding is that the tech is basically changing us. So as you’re finding that there’s more APIs that’s more reliant on particular data. Now, the reason why that’s very significant and to give you a prime example of that, is that it’s allowing for different types of products to be produced. Those for those products could be based off of what we codify, define decentralized finance. Seifi and that’s mainly in the blotchy space, but also how it’s being used across different platforms. For example, there is a product right now called the Brewery Project that really essentially allows for multinationals to work together on a data platform. Data that is the ultimate goal is to solve between anti bribery and anti corruption. However, what are the key elements that have occurred as a result of covid-19 is that the platform has the digitization of the platform has exposed a lot faster. So what happens now is that these firms, particularly firms, large cap firms, are on a platform such as ABN InBev, such as such as a state, Loida, LVMH, all these large firms are now asking the question, how is our supply chain is being impacted? So essentially what’s happening here is that these firms are starting to look at not just data analytics, but they starting to realize that they have to go down to their particular raw materials and levels that they hadn’t had before. And that’s a part of specification management. For example, Estee Lauder makes cosmetic goods. So there’s the beauty side of that. That’s the just of substantial products that they make about InBev, make brewery and beers and alcohol, as well as LVMH, make leather goods. So the goal there is to to harmonize where you can identify families at a very local level, be able to work with those particular Formosan on boredom, but also allow that to to track and trace and measure where the raw materials, ingredients are coming from. And in doing so, you’re able to address some of the issues that may happen with the other companies, as mentioned, and providing more material and providing the final product, such as leather goods, such as alcohol, such as cosmetics, that in a sense, what it does, it mitigates the risk that may occur with these particular firms that could be anti bribery and corruption and so forth. Next, please, Kevin. So let’s move on to the blog change system. What’s significant in that particular model that I mentioned with data analytics, the blog change system has grown significantly. It’s one of the better platforms that the priviledge a platform that allows data to be transparent and data to be used nowadays. What we here with the blog change system, when we got to be to be transaction’s is that the biggest challenge is what they call a centralized government block chain currency. And that’s really very significant because with that particular centralized digital currency, it allows for global payments and remittance and sediments to occur a lot more faster being it is a centralized currency. But most importantly, that allows for a sense of stability and a stable coin. So all of this could be done in what they call particular smart contracts and in doing them with particular smart contracts with the use of data. These these B2B LogCAP firms are able to to do multiple things one day to have a peer to peer lending opportunity where they can do peer to peer online among themselves. Most importantly, they can do the particular global payments and remittance with ease. And also they can have e-commerce feature where they’re allowed to sell all the products and services via the block chain system. Now, there have been some applications of this being done before with success and ease, at least in the area of trade finance and essentially the trade finance procedure. At least, you know, we tend to take anywhere between two weeks, about one or two weeks at a bank level due to the level of documentations that are being done about the use of block chain technology as actually Expedia, that transaction transactions almost two to three days. So that’s the benefit of having block chain with the use of data. Of course, there’s other areas that block chain is well known and recognized for. That includes recordkeeping. We see a lot with securities, at least the securitization of assets. But most importantly, block chain is very significant in the process, in the process of actually doing a digitized platform that’s going to allow for B2B firms to operate globally with ease.

[00:12:14] Next, please, Kevin.

[00:12:17] So that leads us to the third portion of our discussion, which is artificial intelligence and A.I. has developed at least the investment of A.I. has really progressed significantly and has gone beyond at least Vontae level of third wave A.I. But when you look in terms of predictive modeling, a lot of the predictive modeling is basically using deep learning machine learning technology that allows for data to be smoothed out, but most importantly, to tell a better story with third wave, a third wave A.I. is allowed for not just the deep learning, the machine learning to occur, but most importantly, it’s allowing for that data to be to be memory. So there’s a memory feature to that. But most importantly, it’s a probing mechanism. And then that program mechanism, it allows for that algorithm to kind of look at the data that that occurred recently and be able to to probe and see what it would be like in the future. Now, that’s very significant because that’s allowing for not only a solution, but is also given an opportunity for for for the for the consumer, for the business to react and to produce and to create. So that wave A.I. is significant in the process, along with block chain as well as with data analytics that would allow B2B firms to be able to to execute cross-border deals and trade with ease. Next, please, Kevin.

[00:13:54] So in conclusion, one of the key things that we need to focus on in terms of using predictive modeling, what goes in, data goes in, is just as is as as important as data going out.

[00:14:10] So it’s really depend on the quality of data. At the end of the day, the quality of data will determine how well that predictive modeling will work. However, this other tools that could work where that put that data could actually be used to help businesses to operate on a global scale. Most importantly, we touched on the use of data analytics, but mainly specification management and the tools. A specification management will be used to attract information at the raw material level. Not having that ability to do that allows for the systems to track and trace not just data, but also trends. So there is a level of analysis that is being done. And then of course, moving all along to scale beyond specification management is natural language generation. So being able to use that data and smooth it out and tell a nice story as to how those operations and that information is being used now in order for that to occur, the platform for the curve, the ideal platform is a block chain or distributed ledger technology system. And then using a blocking system, it allows for kind of parties to be able to see each other to share information, data with a level of transparency, but most importantly, to be able to to make decisions. At the end of the day, with the block chain technology, you want to be able to apply where you make a decisions and you allow to mitigate the risk. One of the prime examples that I talked about was the use that is being used now and the BRURIAH project where you have multiple of large cap firms. They have multiple products, but they have very similar issues and challenges. And in addressing those issues and challenges is the use of data management, but also a mixture of block chain technology. And then finally, towards the end of this is how do we incorporate a level of artificial intelligence that is being incorporated at the data analytical level in terms of the algorithms that are being produced using deep learning and machine learning, but most importantly, being able to use a memory function that allows for data analytics to occur as well as appropriate feature. Now, having that program feature is able to allow for a predictability factor where now you can make a better decision. So as you move along the scale and artificial intelligence, you’re able to able to not only just predict, but you’re able to make final decisions and faster decisions and technology. I want to thank you for the opportunity for this discussion is an ongoing discussion that’s being half an industry. But thank you again for the opportunity and I look forward for future of future discussions. Thank you very much.

[00:17:10] Next, please, Kevin.

Speakers

Investing in Software – Utilizing Data to Improve Efficiency

Lu Zhang @ Fusion Fund and Jordan French @ Grit Daily
Main Stage
Ascent Conference 2020

Jordan French [00:00:00] Lou, you are now live at a Ascent conference, wonderful, thanks, everyone. Big shout out to Ascent conference for putting this on. Welcome to 20 20 everyone. My name is Jordan, French founder, executive editor at GRET Daily News, where we’re based in New York with all sorts of exciting coverage of events that include a spent conference here with me, a much awaited panel with a rather fireside chat here with Losing Fusion Fund. Welcome, Lu.

Lu Zhang [00:00:34] Hi, Jordan. Hello, everyone. So glad to be here.

Jordan French [00:00:38] Yeah, wonderful, so, so many uninitiated in the venture capital space, just some really quick background on you. There’s, you know, certainly it’s an arena fraught with risk. Certainly there’s a lot of a lot of confusion about the space. And my aim here with you is to rise to. Luis is even with your own background. You had your own adventures before you started in venture capital, could you share those?

Lu Zhang [00:01:16] Yeah, hepatocyte, so my background, my journey starts in the shadow of a scientist at the center. Before that, I was born and raised in the Mongolian came to United States years ago. So initially I was the focus of academic research. But later, one of my technology has an application for Type two diabetes diagnostic. The Manhattan was up sensor and so it’s nine basic approach, a pretty fancy attack. So I built a medical device company based on my own technology and the journey for a couple of years as a solo funder. Eventually, the company was acquired by Boston Scientific. And so that’s my journey and also the first Aliko commercial from a researcher to entrepreneur. But during my journey as an entrepreneur, I had lots of experience working with VC and also have really in-depth understanding of the lifecycle for early stage startup, first kind of experience as an operator and also understand from funder perspective how to leverage capital to grow the company and later to start to do some angel investment was my capital return from my exit and also draw on that AVC from other venture partner, which give me a sense from the other side of the table I found the fun joke about I went to the dark side, but I was like, I’m your friends in the dark side. So was the experience to a different side of the table. I was really able to better understand how capital could assist and accelerate the good technology or commercialization to really act as a catalyst. So that’s also the motivation for me to launch fusion from five years ago, not only me, all the partners, including my team of entrepreneurs, and also because of that experience, a lot of the founder we invested and the work was there repeating success or failure. So I think having the operation, the entrepreneur experience, really help us better understand the founder. We better support a founder and also be able to identify that the best company and the good technology for the next step.

Jordan French [00:03:20] And thanks for sharing that, Lou. It still begs the question, though, and not not many of us have an exit, certainly not nice clean ones. And so, like, it begs the question, why not continue after acetone, which you sold and established that earlier with a with a second company, go bigger, better, rather than, you know, effectively switched sides to the dark side, as you called it.

Lu Zhang [00:03:47] Yeah, and definitely I have other friends asking me the same questions, especially because I started my company when I was 20 years old, so when I lost and found that I was twenty five years old, so people said, OK, you’re so young, you could definitely do another company. I thought about it. I have other application and the patent technology I applied to. But during my process of doing Anjo investment, myself and all sorts of entrepreneurs, Loosley worked with the VC firms to work with the founder I really like. I have lots of passion for early stage tech investment and the meanwhile, I saw the opportunity back in 2013, 2014 that there there’s so many bases, so much capital in the market, but very few of them actually focus on deep tech and health care. Most of them are still going after the business model innovation. But I always say that innovation happens with a cycle starts on fundamental tech innovation, tech application innovation and business model innovation. I was able to do that with my background and also with the founder community. I know the next trend of the next wave of digital transformation is coming. And this innovation base is power to buy not only software but hardware software integration. That’s also a good opportunity for me and me as a former entrepreneur. Daphne, I go dancing to that area, familiar words. I did research. And you also want to see a variety of different types of innovation. I also feel like I have this responsibility not only just leverage capital, but also the resources, connection, everything to power, the next generation of the tech and health care company. That’s the reason I launched Fusion. So I launched Mutual Fund. As I mentioned, some calling their friend said, oh, you went to the dark side. But when I explained to them how I to work with founder and also where we also empower ourselves until we see from with lots of technology, with lots of data analysis. So we’re talking about using new technology to do the digital transformation for the traditional sector. See is kind of a traditional sector as well. So the approach I use and also the way we interact with founder really makes us kind of stand out and they become a strong differentiation for us compared with other see in the early stage. And meanwhile, for me personally, I created this company, Fusion Fund. That’s my second startup. Yes, it’s a B.S. industry, but it’s my second startup. So we’ve been working very hard and all the team members being working and running the firm like entrepreneurs. So that’s the part I really like about it.

Jordan French [00:06:14] Certainly, Lou. And it’s it’s an interesting point that you bring up an observation self reflecting that AVC itself can be a startup. And one very common question for any company, including startups, is how do you make money? Inquiring minds want to know.

Lu Zhang [00:06:39] Yes, happy to share that. I think it’s also important for sometime Fondo to understand how we make money and sometimes you understand why we are looking for a certain type of the founder of certain type of exit to make sure they have the funds return. So, you know, Atabaki was set up a fund that they had amendments that charge annually. And also that carried interest in the future is a return for the GOP in terms of management fee bonus that just more like a call center. That’s the basic fee for maintaining the operation of the firm, like cutting HRR and all this logistic, legal, finance, accounting, etc.. But the true return for the fund is the investment return, like reinvest the company when the company exit got very good multiple and they wouldn’t. This return would definitely return the principal to the LP and the furtherest will have carried interest as a GP. That’s also the result. When we calculate a potential exit, we need to think about. Consider the fund’s size and how how big. The exit I have from the company I invest will make sense to become to become meaningful for my fund, return for them or for my phone says one hundred million dollars. If I have a company exit for them, a words of 50 million dollars going to give me only. For example, if I have to send Fimian in return, it’s OK return, but it won’t really contribute a lot to my 100 million dollar fund. In terms of fund return that’s arisen as one hundred million dollar fund that are looking for company potential could generate at least half a billion, even billion dollar exit potential exit for us to get a sizable and meaningful return at a fund. So I think this financial structure is very important for fund there to understand that, you know, whichever company your build up and what is the target of your potential exit. And then you could trace back to which type of V.C. you should talk to. For example, some company especially was in health care there, like medical device company. That potentially exit might be lower than one and then probably better to work with. VC was a smaller fund set then, you know, this neutral benefit. And meanwhile, another type of fund there, probably the company is going to be a cash flow company rather than potentially have a big exit. Then probably better to work with, for example, individual investor. They would prefer to have, you know, kind of focus annually rather than the big exit at the end. So I think that’s also kind of some small tips for founders about how to do research about a are talking to and to choose the right partner for a different stage of fund raising.

Jordan French [00:09:16] It certainly and I think, you know, your rule that you established is so important, we’ll even invert it. It explains why agencies, for example, marketing or otherwise, basically small businesses, they don’t attract VC funding because of the way you’re incentivized as you establish. I think that’s often important. Note that’s that’s overlooked. It’s you’re looking for the the home runs and the Grand Slams most of the time, to use a baseball analogy. Speaking of speaking of Wordplay, Fusion Fund, what’s behind the name?

Lu Zhang [00:09:57] Thank you for asking. We will rebrand the name to future funding twenty seventeen and I really like that this was fusion. I got a fusion from nuclear fusion because it’s like beneath the surface, ocean is kind of similar mandate as we do early stage tech investment. Small atom came together, but it was able to generate a huge amount of energy. That’s also the magical part of being an early stage investor that we’re able to investing maybe not be a small amount of a couple million dollars, but serve as a catalyst to accelerating the company to become commercialization and be able to have a much bigger impact of the world. And another car that I really like about a fusion is, you know, so many people talk about offensive technology out of recession, which our scientists definitely understand are super fancy technology available in the research world. But the critical part for us, especially for commercial investment for ABC, is we need to find a good timing and also good technology, better, faster and also cheaper. Ready for commercialization. Excuse me. So this fusion is also about how to fusion between the market application and also technology itself, especially now, you know, a lot of large corporate are going through a digital transformation, are looking for solution, QSR industry problem, but they do not necessarily understand which type of technology is available to provide them the solution on the other side of the technology, not necessarily identify the true problem of the industry. That’s another fusion we try to bridge. And we also set up the Saxl Network internally at Fusion with Sorte to sealable from Fortune 1000 company. Then we were able to build up a bridge between us and to see sea level from the large concrete to understand what’s truly needed by industry. And meanwhile, Sarus, they were able to directly talk and the partnership was lost early stage startup and definitely also benefit for the company to be able to get very fast market validation. And the one last joke, I like fusion food as well.

Jordan French [00:12:17] Thank you for that slight delay on our line, and I’ll I’ll keep myself concise. You mentioned the words dark side. I just want to touch on it really quickly. There’s this reputation in the space yet. And the other hand, it seems like the VXI industry supplies much needed capital to start ups. Why? Why, though, curious, curiously, why does that description exist blue, this dark side terminology, as you call it?

Lu Zhang [00:12:49] I think it’s because somebody said a misunderstanding and also miscommunication between the both sides, because, to be honest, the woman was a founder and not necessarily have all the plans and experience working with me as well.

[00:13:02] There’s some good supporting cast also either some sort of obesity here, but that means I found that I did not like it. So that’s the result of some some form, though they probably have frustration and the difficulty working in music on one set because they don’t feel like they’ll be talking to really understand what they’re doing, but they’ll be making a decision whether to fund it or company. Another thing is, one, they even got the money from D.C. sometime this week on the board. Make a suggestion or even pressure for founder to do things they don’t want it to do. So that’s the main reason why there are some type of tension sometimes between there in D.C. But I would say for the past couple of years, things are getting much, much better. It’s also because there’s more VXI really understand that the countertrend of the technology innovation and that they were able to give in depth and also very good feedback suggestion to the founders. And the meanwhile, I’ve been telling founder that another important thing for Fungo is really to research before you talk to a busy investor to try to see what is a good match between your company and their firm, then the conversation will go much better. And you will also get very honest and useful feedback from ABC who truly understand the industry and not just in terms of portfolio management is, for example, something that really hate micromanagement. And I definitely see and heard that some B.S. from when they have a partner seat on the board, that they will try to make lots of decision and try to kind of do macro management a little bit. For the founder that definitely frustrated, especially good or good funded pilots were asked would never do macro management. We actually one way to a founder to work with. We want to choose the best founder and then I trust him as far as the captain of the as a captain. And as I said, we are the catalyst that when we sit on the board, we definitely give lots of suggestion, the feedback, but we try and also the governance of the company for sure. And meanwhile, we really respect a founder to empower him or her as the true decision maker at the end. And not only as I think a lot of them are doing that with its founder as well, is also requires both side of have a really in depth communication before the board formed and then everyone understand fully well aligned of which type of communication, communications now I wish have a collaboration style will be good and mutual benefit for both sides really working together for the company. And another thing, just a small suggestion. I want to give it to a founder, especially by working with we on your board as well. ABC not only investing, but also training as a board member. They also have a priority to to consider the companies the best interests, not just the fund, the investment. So will you have a list on the board? Really, really consider them as an employee, as a member of your company. So not necessarily just only sharing the good news with the board member. I was joking with founder that if I only heard good news from you guys, I said don’t worry about it, because I’ve been through the company building company myself. I know it’s always up and down every single day. So as a board member, I want to hear you tell me highlights and lowlights only if I know what challenges. And you’re facing an even mistake you made. I was able to truly support you and help you. I think sometimes it’s because they’re are afraid of telling one member of the lowlights how bad news and the to the end all of a sudden saw the big bump and then there will be some conflict, an argument between the investor and the founder. But I feel now with this communication getting better, definitely the relationship between the founder and investor are getting much, much better. But to the end, as I said, you need to do the research is really important for a fund there to find the right partner right away. It was at early stage and the right not necessary means that befriending B see really depends which have an investor and which type of support you need from external at a very early stage to a Saturday to the girls.

Jordan French [00:17:05] Yes, and speaking of of the ups and downs, Lou, as you call it, many industries, particularly those that are also VC funded, even in tech, are hurting this year, or at least there certainly were earlier this year. We’ve seen some light at the end of the tunnel, but the medical medical device, perhaps medtech, biotech, health care in general, elder tech, some of the some of these subindustries that you can concentrate in appear to be doing well. We all want to know for Fusion Fund, how has the landscape.

Lu Zhang [00:17:50] Jordan, you got caught up by the last couple of seconds, but I guess you you your question is about how do I deal with this idea? Any change of the last week involving vestment and also the trend of already this year about venture investment? OK, I would just answer based on I guess, in the four hours we’re being always focused on the attack and price tag on the health care tag, and for the first of two factor, our main focus is really how to leverage new technology to push the digital transformation of the traditional sector.

[00:18:26] And meanwhile, it’s not only about like data, artificial intelligence, and also for the whole network of technology. There are big support and invest a very good portfolio of compute as computing technology. So I think the digital transformation also got accelerated by the pandemic. Daphne, this year, 2020 is a challenging year for the whole of innovation community, for the tech sector. But on the other side, it also kind of accelerated the adoption of the new technology from the not only tech company, but even traditional sector. And also the digital transformation is kind of happened every time when we have a downturn. For example, back in 2008, when the financial crisis happened, they kind of on this side effect is pushing about the cloud computing. So this time is the digital transformation. That really is a good news for for the company working on that application. The good news for us, because our portfolio company actually goes through a period of rapid growth of the revenue and also when they’re doing the new round of fundraising to support another sector, as you mentioned, is health care. I’m very happy to see that there’s more capital and more talent fund. Our focus on health complication right now, because to be honest, as a former health care funder is health care, especially medical devices. It’s not very attractive for funding for a long time. But copper isn’t definitely in the hardware components of another thing. It’s FDA approval. But for the past couple years, I think the things are getting better and also being very proactive. Try to promote, for example, in health care. Edgecumbe for health care. Is this important for new attack with the traditional like like health care, medical device, innovation like microfluidics really provide a new new potential and a big market for us to explore how to better try to personalize the diagnostic, personalized the treatment plant. Even digital digital transformation of the health care industry itself and the industry in general is 20 percent of the US GDP by the during pandemic. We also saw this challenges huge challenges that could potentially be solved by technology. So our house car company was doing very well and also lots of funding are in this area right now for for investment. So especially I feel like an housecoats for not only cancer diagnosis, but for mental disease or mental wellbeing. Another thing, just the general enterprise to application for the health care, no matter regulator and insurance company, our traditional medical device company. So that’s out. A big trend happening right now. And also at last, I want to share a little bit good news with everyone and that regarding FDA approval for both investor and founder for most of our company, health care, medical device and health care, they were able to get FDA approval within half a year. So the celebrating of this whole process of approval definitely cleared out for innovation to to do commercialization, to be much faster to adopt it by the market. So really wanted to see more funding and more capital concentrate either on the dose confirmation and the health care.

Jordan French [00:21:32] Certainly a lot of a lot of insights there and and one one to one to distill of many points that you make, there are regulators out there that can be very helpful, especially from the four investors as well in the investment landscape. And that sounds like that’s within your core competencies, Lou. At Fusion Fund on our last minute here, I do want to market you a bit and I know some in the audience. They do want to pitch you, especially after hearing this. They do. They do run companies that are likely within your wheelhouse. How can everyone in the U.S. audience reach you?

Lu Zhang [00:22:24] Yeah, so love to hear from you guys if you are doing some interesting company, I’m looking for early stage investment. We do see too serious a Texas could range from half a million to two million dollars for the show. Also have a capital reserve for Parada to support a fund. So if you want to contact, contact me. Feel free to either connect me linking you could email me without genital contact, email contact at Phusion Townhall.com, then we’ll be back to you. And we’d love to potentially work with some of you to fund the company and be able to support you to the next stage.

Jordan French [00:23:05] Certainly now you all have Lucy email the picture, she’s open to questions, that’s all the time that we have. My name again is Jordan French Grit Daily News. Check us out. Big shout out again to Troy and the ascent team for putting this together. A lot of hard work behind the curtain, so to speak, and look forward to seeing you all in person live in New York next time. We’ll see how that goes. And certainly, Lou, some of the companies she’s working with should help us all mitigate the impact of the current pandemic. Lou, thanks again.

Lu Zhang [00:23:45] Great. Thank you, Jordan. Thank you, everyone. So glad to be here. Everyone one, I look forward to see you in person next year.

Jordan French [00:23:53] Until next time.

Speakers

Enterprise Automaton: AI-powered integration to connect disparate SaaS apps and data sources

Dayle Hall, CMO @ SnapLogic
Sales & Marketing Stage
Ascent Conference 2020

[00:00:00] But let’s oh, let’s do it. OK. Hi, I’m Dayle Hall, the CMO of SnapLogic. It’s great to be here today sharing some some insights, some ideas. Obviously, being at home is a challenge. You may hear some kids running in the background, may hear the dog moving around in the background, but I’m at home, so I get to wear an England football shirt just because when you’re at home, you can pretty much manage it how you like.

[00:00:35] So anyway, today I am here to talk about what we mean by an automated enterprise. First of all, what it means in general, how we think about it. It’s not logic. But beyond that, I’m going to give you some tips and tricks and things to think about as a marketing leader and the things that I think about around automation itself. So first of all, let’s start at the beginning. Like, what does every organization want? What are we trying to deliver? These are three things. I don’t care where you are in the organization. I don’t care where you are in a business or what your role is. These are three things that you definitely want to try and achieve. If you can nail these three things, you and then your organization, you’re going to be one of the heroes and who doesn’t want to be a superhero in their organization. But we’re all trying to do this. Yes, we want to deliver amazing business results. Of course we do. But we also want to provide better customer experiences because we know if we do, that will acquire more customers, will retain more customers that will ultimately achieve those business results. But even before that, if we have the right data, if we can make the right decisions, we can actually deliver the right products to the market. So these three things, everyone in our organizations, everyone’s looking at them will see first thing went backwards. So. So what’s holding this back? Well, let’s start with this. If you want to deliver better products, all those customer experiences or something like that, the one of the biggest challenge of doing that is how you actually get access to the right information, how you make sure that your organization and your application to set up in the right way. The biggest challenge with that is as we create these different applications in our organization, as we putting more technology, trying to get these things to talk to each other is a challenge. One of the big challenges today is we moved from on premise to cloud. So this was something that’s been happening over the last 10 years. But I’m still surprised how many people are still using on premise applications. So this is where I think you’ve seen the dawn of things like these digital transformation strategies, because everyone’s trying to adopt these new best in class applications, them mainly cloud based. So basically what you’ve got is that you’ve basically seeing an organization that has multiple applications, that they’ve built themselves different new technologies, best in class that they’re trying to bring to the cloud and actually getting them to talk to each other is a massive problem, a massive problem and. A small example, what do we mean by massive problems? Well, do you know how many applications do you have in your organization and guarantee that maybe you don’t want your I.T. team are running around trying to trying to keep on top of them? And this is the problem as you add best in breed, as you move to the cloud, you’ve got this mass of applications and data and a lot of them don’t talk to each other. I’m not talking about whether Marketo talks to Salesforce or something like that. I’m talking about how data is proliferate across every application. Think of the customer journey. Think of how many times a customer touches a single part of your organization and those organize those apps are not connected today. So what you end up with is multiple points of integration and challenges with the data, meaning you’re losing data across organizations. You’re also losing insights because you can’t look all the data together. What does this mean? Someone’s managing it. They’re either writing right in code. They either have a bunch of resources on it or they’re actually just not even aware of the data that they’re missing today. And obviously, that’s. That is literally one of the biggest challenges, how much are you missing out on just because you don’t really know what’s going on today? Well, according to research, that SNAP Logic did early this year with an organization called Venson Volume. On average, organizations have more than one hundred and fifteen applications. You could see from that from that previous slide. So that’s a lot. I’m sure your organization, you’re out there thinking, yeah, we probably have more. If you’re in a marketing team, you probably have 20 or 30 that you’re managing just to try and run the business.

[00:05:04] But a huge concern is that most of them feel like this is completely disconnected from the other. And that start on the right hand side is, by the way, your I.T. organizations. And they’re also very concerned. They actually feel like data that stuck in certain parts of the organization is actually holding the enterprise back 90 percent, 90 percent of 500 of the top enterprise organizations are saying that like they’re one of their major concerns is that you’re stuck in those silos, like we should all be paying a lot of attention to this.

[00:05:39] Right. And why is that?

[00:05:41] Like, this is just a very illustrative example of what we mean. You’ve got organizations that touch different parts of the customer that touch different parts, potentially, partner. Jovani, how you’re managing things like, quote, to cash. Right. All of these are disconnected. So this creates a lot of pain, a lot of friction and a lot of delays, delays in rolling out new organizations and onboarding customers or employees. This is caused because you can’t successfully integrate the data and have these applications all talking to each other. A matter where you view the data you can pick if you want a visualization tool or somewhere in CRM. But it’s really difficult for all these all these elements to all come together so you can get that holistic view of the enterprise. And that’s kind of what we mean by enterprise automation.

[00:06:40] Now, of course, who’s currently carrying the weight of this?

[00:06:44] Well, guess what, 80 to 80 organization that does a lot of manual effort there. Lots of people in organizations that are doing coding or they are running book fixing on the rewiring things.

[00:06:58] They’re typically the ones that are feeling the pain.

[00:07:03] As a marketing leader in these organizations, we don’t see that, but what we see is like, why is this taking so long? Why does it take so long for me to get on board an application? Why can I not see data that I need to that I need to make decisions around what product, what campaigns, what’s going on with the customer? So it’s under a lot of pressure. And then business leaders from functions like marketing, you know, we actually we don’t want to wait all that time. So we’re implementing our own solutions. We’re taking organizations.

[00:07:42] We get I get 200 emails a day that talk about the next best marketing tool. And and I want I want most of these things. But I think it can add value to my business. But I’m certainly not going to wait for it to go through the process and do governance and security and privacy and control like that slows the business down. Me as a as a business leader. What I see is that I feel like that slow my business down. So typically what happens is you may be I don’t know if you’re in it or if you’re in a line of business, but it’s usually not fast enough. So the speed and the times to value, which is critical for me as a line of business, it’s not that. So basically I’m like, you know, I’ll got to figure out myself. And this is where you get this shadow IT organizations or your marketing operations running it in the marketing organization. You get get these pockets of technology and my tech stocks that are not linked back with it. This causes a massive issue. I’m sure I’m sure you all of you have at some point heard some of this. But you know what? That does ultimately not just cause frustration between those two teams, but that kills the business agility, that kills the opportunity for the enterprise to make better decisions. Right. So that’s why you now see this growing trend in that a lot of analysts, you talk to Gartner and they’ll see they’ll say that a lot of the enterprises now are moving to a platform to be able to support this, meaning they’re enabling functions to be able to implement their own solutions. But it’s it’s a challenge. Right. And this this from from one of the reports last year is like they see these enterprises are asking for it. So how do you do it? How do you make sure it happens without making sure that teams are in the background, just sweating on manual coding and scripting and making sure that they’re actually adding value and not basically running around doing fixes for all the technology that the marketing or sales or or are actually implementing. It’s it’s a challenge, not to mention things like app and data process is very can be very complex. And obviously lines of businesses, they they really they honestly don’t want to be involved in that. Did you all hear my dog barking in background? Yeah. Sorry. That’s how you know, it’s that’s so you know, it’s a real presentation. Gordon Anyway, so it’s today’s challenge requires a different approach. And some of these words you will have heard that you have heard across different presentations and different analyst reports and media outlets and so on. So basically, I.T. need to get to the point where they can push some of this work out, OK, less oversight, less governance and control. But really the possibility of the lines of businesses supporting them, not just hindering them, starts with things like local platforms. So business users want the capability but don’t want to have to learn how to code. So a lot of that is available today. And then things like self-service user interfaces that don’t require you to have an engineering or an architecture degree to be able to figure out how those things work. And then finally, the last piece, which is important is automation. Get the low level manual coding, pulling data, get that out of the organization, an automated automated in a way where I don’t get frustrated as a business user. So I actually get access to my data and then I’m not frustrated because they’re not worrying like where the data is going or what kind of applications are being put into a business.

[00:11:38] And guess what?

[00:11:39] Yes, I’m at home where my English, but the age we’re in right now is it’s amazing, stunning change in environment for all of us, but it is accelerating the requirement for this.

[00:11:51] It’s accelerating the need for us to use new technologies to take some of that, that reliance on humans being in the office and coding and checking spreadsheets and so on. How can we get better at this? How can we be more self-sufficient and twilly a very respected company? Did the state of customer engagement report I mean, this this this is a hundred percent. It says 97. It’s 100 percent. I’m going to currently pause that recording because my dog is blocking.

[00:12:31] Very minor, back in normal service resumed, dog is sorted out anyway, look, 100 percent of enterprise decision making, that is 97 percent. There’s no one out there that doesn’t feel like the need for digital transformation hasn’t been hasn’t had to speed up because, of course, of covid, this is where we are as a as a business, where we are as vendors, where we are as customers. Like we need to get to this point where we can get access to better data, not rely on a bunch of coding and people being in the office to to make sure all those things happen. So where do we go from here? Well, this is I talked earlier about the concept of the on premise and moving to cloud. But the next step is this concept of thinking across the enterprise and and looking at automation across all those applications and across what you’ve got on premise and across every data. So this is also where you have the actual power to leverage A.I. because it can learn across multiple data sources. The critical thing with artificial intelligence is that you have data to learn from. If you’re just running artificial intelligence on one piece, on one piece of data from one application, you’re not getting as much as the value. And how about automation across business flow? So not just what we do in the marketing, looking at customer side employee onboarding, you know how many organizations out there have manual processes to to you know, when you start an organization, when you join an organization to to provision your services, to hand over to payroll, to know all the way to actually when you when you leave an organization, a lot of that is manual. And we can actually we can actually get around that. If we if we look at automation across the enterprise, that’s kind of breaking down those silos of silos disappear. It end up being happy because they can still control the key data, but because the applications and data is talking to each other, they’re less concerned about losing control of the organization. And, of course, business users, we get the data that we need to make decisions around what’s the next best campaign, which customers should be worried about, and ultimately that should lead us all to the faster business decisions. How does this look from an architecture perspective? Well, the key thing here is to focus on two things. One, doesn’t matter what organization you’re in or how much of a specialist you are, you could be a data engineer. You could be all the way on the other side, which is a business analyst. So maybe someone and someone’s wearing sales operations or marketing operations and they’re just looking at the data. You don’t have to be a serious technologist to be able to leverage this, because what’s coming through is all the data from all the databases, what you’ve already potentially put in place with things like that and what you’ve got from your data centers, even if that’s coming through, you can still aggregate that information and run run modeling. You can run on it. You can actually use that to potentially create better models because you looking at every single piece of data across the enterprise, like that’s that doesn’t happen today. We may think we’re we’re using enterprise data across every single point, but typically we’re not. Typically what’s happening is we’re looking at a piece and then we may look at a different a different tool that we’re using. And then we try and put that together and make some assumptions. How about if all that talk to each other like that is the massive opportunity? So what do I mean by the challenge for marketing? So we’ve talked about enterprise automation. We’ve got to know what it is, where it can impact. What about marketing? I’m a marketer. I’m a CMO. I’ve been doing this for for many years now. What do you think these numbers are? Yeah, these numbers are basically the average tenure of a CMO. If you look at different different studies, that’s that’s actually eighteen months is is kind of scary, but I’m familiar with it. Guess what, eight thousand is eight thousand is the number of solutions, mainly cloud solutions that are available to that. You’ve all most of you probably seen that Martek landscape with thousands of thousands of solutions on. OK, so guess what. How do I balance the things that I’m looking for? I want to drive revenue for the business. I’m really looking at reputation. So I have my marketing goals. I also have eight thousand tools to to choose from and I’m trying to keep my job. OK, so that’s a challenge. Where could I start? Well, one of the things you could look at is what about the customer journey? How do you make sure that you’re really responsible and looking across all these pieces? I’m going to build this out and we’re going to go into detail, but I’m going to go through some examples in a second. These are all pieces of the custom. Acquisition journey, and they’re all pieces that you can automate through things like flows, so, for example, you want a higher conversion with content, where should you be looking? You should be looking at lead scoring and routing. You should be looking at your nurture tracks. You should be looking at your website. You should also be looking at what sales are using. So I just mentioned three or four things. Then guess what? There’s 14 tools that help you do that. But guess what? Most of them don’t actually talk to each other. That is a challenge, right? We’re all agreed. That’s a challenge. Go further down. Look at something like ask. OK, so how about customer service management? So what customers are raising cases? What are they doing on your community? Are they engaging with any campaigns that you may be running around new products? How do you how do you match those pieces together? If you have the right automation platform, you can actually marry the data from campaigns and current campaigns that you’re running in marketing all the way down to what customer service is seeing around case management. Get a view a a more of a holistic view of what the customer is doing. Many vendors talk about customer 360, if you don’t have this automation across the enterprise, you don’t really you will never really have a a customer 360 strategy. So something to think about. Let’s go a bit further. Let’s give you some examples. Three things that I think marketing can automate today, I don’t mean marketing automation like Marketo or HubSpot. Those are great tools. They already integrate, integrate, Point-to-point and CRM. That’s not what I’m talking about. I’m talking about some some broader pulling together, multiple different aspects with not just with CRM. How about we add things like some of the outreach channels and we can actually view all that together. So clearly filling the sales funnel is something that my objective, a steady stream of qualified leads, making sure that that’s pretty much how I get measured suspects. What what translates to opportunities, right? That’s how I get it. So but the volume is massive and variety of sources. Now, these are just a few, right. You can have web channels to this to like that’s it can get overwhelming. So what you have to do is separate the signal from the noise, identify and engage those prospects most likely to buy. So maybe you add a predictive tool or an intent tool like still these are very separate tools that often don’t talk to each other. And you can’t do everything on one platform today. So by automating that that lead management process, you get to have a better view and you get to look at what’s most likely to convert. You get to see what the sales teams are prospecting. And this is where automation really helps.

[00:20:21] Basically, it combines the existing CRM tools with other applications and event platform so you can automate workflows. So, again, remember, this is not just a point to point integration. This is really looking at how you generate this holistic view of a prospect and their intent to buy by pulling all those separate pieces together.

[00:20:45] So that is the first one, and that is lead generation. So let’s go beyond that. What else is marketing’s job? It doesn’t end once we acquire the customer, right? This is what I talk about. We talk about customer 360. We want to help you get immediate value from the product. So how are you using it? Do we get telemetry from a product tool that you may be using? And how do we make sure that we see additional projects that might come up in your organization? OK, this requires very clear strategies to keep customers informed and engaged, not just about new offerings, but understand what they’re using today and make sure that doesn’t overwhelm how to do this ideally in a timely and accurate manner. To get insights, you have to face specific.

[00:21:35] You have to look at these specific technologies so automation will do automation across the enterprise. Again, remember, it’s not one tool to one tool. It brings all these touch points together from sales or support or finance and provides that single source because all the data can get aligned.

[00:21:53] And if you get it right, you’ll see everything from what products or services have been used or not used, which ones are creating the most cases. So when you look at that, you can then cross-reference it with a financial system to how many resources are you using on that customer for that product? Again, you start to really see that. But again, there’s to do this today. A lot of it is manual. A lot of it is being coded in the background and automation and integration and automation tool will do all that manually. So you’re the people that are doing all the coding and just creating the connections they can actually running more models for you. They can actually be looking at new technologies that can keep driving the business forward. And that’s that’s pretty simple. OK, so that’s we’ve acquired customers, we’ve done some lead generation, we’ve done some cross-sell up sell. What’s this? Well, massive impact marketing year around customer retention and loyalty. A lot of it is a marketing thing. Sometimes that becomes, you know, the services support organization. But this is you know, we have we actually have the opportunity here as marketers to do it, to do a better job on this. So. We all want customers for life, and obviously keeping them is important. So with A.I. and automation, we can drive retention and loyalty. So we track that track what customers are talking about, systems of record, things that they may have conducted, surveys. Have they responded in the products? Are you using product telemetry or are they using survey tools? Are they writing reviews on some of these Jita and capturing sites? Wouldn’t be good if you could actually pull all those pieces together, but it’s not limited to to those kind of typical tools. What about things on social media? What about if you could use your your listening and analytics tools for social media to also linked together and really look at do they say one thing in a survey and do they say something else when they’re out on social media? Trust me, I’ve been in organizations where, you know, we we spent hours and weeks and months really looking at what some was saying online versus what they were saying in a product meeting or a cab, for example. So you can establish things like triggered recommendations or when a customer does something well, you can create an automation that then says, please go and review that on the GTA and capture a site. You can actually create that as an automated piece. Imagine that customer likes the product, uses the product, wants to talk about it, gives you some good survey and you automate something that gives them an offer to go to a third party review site and review it. I’m not talking about creating separate campaigns where you’re pulling lists of people and emailing list of people saying please write a review. This is all automated, right? That I mean, that would save I mean, I use that in my own organization where I’m trying to to do things like GTA and Katara. We want those reviews. Right. You’re trying to get those out. But but guess what? If it was automated, I’d have one less person focus on trying to just pull pull customer names and reach out to customers. Like that’s the power of the product. Right. That’s the power that you’ve got, something like automation. OK, those are three things. Again, this is this the thing to remember about this is. Those three things are all things that exemplar markets, the things about. These processes, these interaction points can be automated to take out the manual work that you do to try and link the the systems and data together, it doesn’t matter what system you want to use. You might want to use a CRM. You might want to use an analytics tool to to kind of visualize this. But you can create these automations that happen in the background. So your marketing ops, your sales ops, whoever it is, can be looking at different pieces of data, looking at new tools to actually get more out of make better business decisions because a lot of the manual work is done in the background. OK, we’re coming to the end now, so as I was thinking through this, those are a bunch of different things. We talked about customer journeys, we’ve talked about move to cloud and automation and how you use A.I. because you need masses of data. So as I was thinking about what are the what are the there’s the three things that I think you should think about. So as you look to how do I automate and doesn’t matter which part of the organization but you should be looking at, this is like how do you automate? So so based on that, what should you look at? So three days, three days to think about first A.I. A.I. means how do I start to pull all my data together to get better at making decisions so I can use artificial intelligence to look at models, to look at customer behavior, customer data and actually have have have a tool, an artificial intelligence to give me those insights without me having to run, run foam’s run processes, run spreadsheets, download, do some, do some assessment. That’s a challenge. Second day automation. This is what we’ve talked about for the whole thing. So how do you really look at that? Automation tools, automation processes, automation platforms to make sure that you’re actually connecting the pieces that need to get connected? This isn’t point to point. What I mean by this is this is a way of linking all pieces of data that you might not be thinking about Lincoln today, or you just know that it’s impossible to do. Or, you know, if you’re like me and you get hundreds of vendors, vendor requests each day, they’re all saying you can link you know, you link this back to your CRM, for example, and that’s great. But but all the other pieces are all linked back separately and they don’t talk to each other. So it’s really critical to make sure that you get all those pieces together.

[00:27:46] And finally, anyone, anyone should be able to access that.

[00:27:50] Anyone should be able to use it. You shouldn’t have to be a professional coder. You shouldn’t have to be a data architect or data scientist to be able to use it. Anyone should be able to use this and make sure that the I.T. organizations and line of businesses are talking to each other. And we actually do want to work together. I.T. and lines of business want to help each other. But as of right now, it’s just becoming a challenge because I want to do so many things with data and applications and they want to do so many controls. If you think of it this way and find the right automation integration platform, you can actually both win from this deal. And I think, to be honest, that’s the, you know, being able to to dynamically, intelligently connect the enterprise like there. That’s that’s what we do. And that’s ultimately what we’re trying to do to to be more profitable to to deliver the products because we know what customers are using to make sure that we’re delivering value to the business. We’re not just spending money, we’re actually delivering value because we’re seeing in sight seeing places across the organization where there’s too many service people engaged in this account because I see they’re not using the right product. I mean, think of the possibilities. It’s massive. Anyway, that’s it for my presentation from today. So I appreciate your time. I’m happy to to follow up afterwards. You find me on social media and any other any other public profile. I’m happy to have conversations. And that was great to be with you today. Thanks.

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