{"componentChunkName":"component---node-modules-draftbox-co-gatsby-draftbox-balsa-theme-src-templates-post-template-tsx","path":"/forest-for-trees/","result":{"data":{"draftboxPost":{"title":"Proverbial forest and mechanical trees","excerpt":"","markdownBody":"function _extends() { _extends = Object.assign || function (target) { for (var i = 1; i < arguments.length; i++) { var source = arguments[i]; for (var key in source) { if (Object.prototype.hasOwnProperty.call(source, key)) { target[key] = source[key]; } } } return target; }; return _extends.apply(this, arguments); }\n\nfunction _objectWithoutProperties(source, excluded) { if (source == null) return {}; var target = _objectWithoutPropertiesLoose(source, excluded); var key, i; if (Object.getOwnPropertySymbols) { var sourceSymbolKeys = Object.getOwnPropertySymbols(source); for (i = 0; i < sourceSymbolKeys.length; i++) { key = sourceSymbolKeys[i]; if (excluded.indexOf(key) >= 0) continue; if (!Object.prototype.propertyIsEnumerable.call(source, key)) continue; target[key] = source[key]; } } return target; }\n\nfunction _objectWithoutPropertiesLoose(source, excluded) { if (source == null) return {}; var target = {}; var sourceKeys = Object.keys(source); var key, i; for (i = 0; i < sourceKeys.length; i++) { key = sourceKeys[i]; if (excluded.indexOf(key) >= 0) continue; target[key] = source[key]; } return target; }\n\n/* @jsxRuntime classic */\n\n/* @jsx mdx */\nvar layoutProps = {};\nvar MDXLayout = \"wrapper\";\nreturn function MDXContent(_ref) {\n  var components = _ref.components,\n      props = _objectWithoutProperties(_ref, [\"components\"]);\n\n  return mdx(MDXLayout, _extends({}, layoutProps, props, {\n    components: components,\n    mdxType: \"MDXLayout\"\n  }), mdx(\"p\", null, \"Imagine that I\\u2019ve done extensive research on a new car. Safety, quality, reliability. I\\u2019ve read customer and professional reviews, researched warranties. After weeks of research, I make a decision, I go to a local dealer, and I buy a new car.\"), mdx(\"p\", null, \"A week later, I receive a targeted ad from Lexus, pulling me into their funnel thanks to their insights into my activity. It isn\\u2019t the invasion of privacy that bothers me most, it\\u2019s the ignorance of how the targeted ads result in reality.\"), mdx(\"p\", null, \"This theme is common in how companies are applying new technologies to the core business. Every time I see a press release on a large company\\u2019s investment in AI and machine learning, I think of the colloquialism, \\u201Cmissing the forest for the trees.\\u201D\"), mdx(\"p\", null, \"The perceived opportunity to apply these technologies has been in sales and customer service. I am maniacal about detail, so any advantage in customer-facing interactions is, in my view, worth the investment. According to Forbes, $75 billion was lost last year due to poor customer service. This compares to lost revenue of $62 billion just two years prior.\"), mdx(\"p\", null, \"A failed customer interaction is very costly to any business. This is becoming even more true. A separate study polled consumers about switching services due to poor customer service. Baby Boomers have the least propensity to switch, with only a quarter of all Boomers indicating that they would switch as a result of poor service. Millennials, on the other hand, are nearly 2.5x more likely to switch services due to a poor customer service experience.\"), mdx(\"p\", null, \"With more and more data available on customers, and with more and more technology becoming available every day, how is it that the cost of failed customer interactions continues to grow?\"), mdx(\"p\", null, \"Strategically, companies should be two steps ahead of the opportunities to use technology to make the company better. Operationally, companies should worry less about what might be different in five years, and worry more about those things that are just as true now as they have always been. In using technology to drive the business, it is sometimes easy to get caught up in everything that has changed, but it is smarter to focus on what hasn\\u2019t.\"), mdx(\"p\", null, \"First was the rise of analytics. A computer company could make inferences like, \\u201Cbased on last year\\u2019s data, 10% of our revenue comes from laptops.\\u201D\"), mdx(\"p\", null, \"The next logical step is data science. \\u201CBased on representative secondary data from last year as well as external data, next year 14% of our revenue will come from laptops.\\u201D\"), mdx(\"p\", null, \"From data science, machine learning is possible. \\u201CBecause of the activity of this user on our website today, there is a 50% chance that she buys a laptop.\\u201D\"), mdx(\"p\", null, \"And finally, even artificial intelligence. \\u201CBecause of the activity of this user on our website from two different devices today, I am going to ask her if her partner is also shopping, and, if so, there is a 50% chance that she buys two laptops.\\u201D\"), mdx(\"p\", null, \"And yet, too many organizations attempt to jump from analytics into artificial intelligence, without ever having asked the question, \\u201Cwhy are people buying our laptops?\\u201D or \\u201Cwhy aren\\u2019t they buying our desktops?\\u201D\"), mdx(\"p\", null, \"It is an honest mistake. These companies are only seeking to take advantage of what is available. They are fearful of being left behind, of missing out on the ROI of machine learning. They look to tech companies like Uber and Netflix for thought leadership.\"), mdx(\"p\", null, \"Ironically, the simplest and cleanest products win the hearts of the buyer. Netflix started by solving the customer problem of paying late fees, going to a physical location, wading through advertisements. They happened to take advantage of technology along the way.\"), mdx(\"p\", null, \"Uber solved the problem of calling a car in advance. Uber solved the problem for those who needed an on-demand taxi, but did not live on a main avenue. It turns out they had to use technology to solve those problems.\"), mdx(\"p\", null, \"For that theoretical computer company, the best ROI would not be on 2018 technology like machine learning to help them sell laptops. It would be on 2006 technology like making it easier for a customer to sign in and search for products.\"), mdx(\"p\", null, \"Don\\u2019t miss the forest for the mechanical trees.\"));\n}\n;\nMDXContent.isMDXComponent = true;","slug":"forest-for-trees","postSeoSlug":"forest-for-trees/","publishedAt":"23 July 2018","updatedAt":"06 April 2021","primaryAuthor":{"name":"rjm","slug":"ryan-mills","profileImage":{"publicURL":"/static/3c6b31ba286ae69d57e703cfb4f2a825/authorProfile_1617677634750.png"}},"authors":[{"name":"rjm","slug":"ryan-mills","profileImage":{"publicURL":"/static/3c6b31ba286ae69d57e703cfb4f2a825/authorProfile_1617677634750.png","childImageSharp":{"gatsbyImageData":{"layout":"fixed","placeholder":{"fallback":"data:image/svg+xml,%3csvg%20xmlns='http://www.w3.org/2000/svg'%20width='40'%20height='40'%20viewBox='0%200%2040%2040'%20preserveAspectRatio='none'%3e%3cpath%20d='M19%201c1%201%201%201-1%201l-2%201-3%201-4%202C7%209%207%2025%209%2026l1%201c-4%200%207%203%2011%203%206%201%207%201%205%203l2%201c2%200%205%200%207%202l4%201%201-25V0H28c-7%200-11%200-9%201m6%2013l-4%202c-3%200-3%201%200%204%202%202%202%202%202%200%200-1%201-2%202-1v2c-2%202-1%207%201%208h2c2%201%202-1%202-7-1-8-4-13-5-8'%20fill='%23d3d3d3'%20fill-rule='evenodd'/%3e%3c/svg%3e"},"images":{"fallback":{"src":"/static/3c6b31ba286ae69d57e703cfb4f2a825/f31ef/authorProfile_1617677634750.png","srcSet":"/static/3c6b31ba286ae69d57e703cfb4f2a825/f31ef/authorProfile_1617677634750.png 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Safety, quality, reliability. I’ve read customer and professional reviews,\nresearched warranties. After weeks of research, I make a decision, I go to a local dealer, and I buy a new car.\n\nA week later, I receive a targeted ad from Lexus, pulling me into their funnel thanks to their insights into my activity. It isn’t\nthe invasion of privacy that bothers me most, it’s the ignorance of how the targeted ads result in reality.\n\nThis theme is common in how companies are applying new technologies to the core business. Every time I see a press release on a\nlarge company’s investment in AI and machine learning, I think of the colloquialism, “missing the forest for the trees.”\n\nThe perceived opportunity to apply these technologies has been in sales and customer service. I am maniacal about detail, so any\nadvantage in customer-facing interactions is, in my view, worth the investment. According to Forbes, $75 billion was lost last\nyear due to poor customer service. This compares to lost revenue of $62 billion just two years prior.\n\nA failed customer interaction is very costly to any business. This is becoming even more true. A separate study polled consumers\nabout switching services due to poor customer service. Baby Boomers have the least propensity to switch, with only a quarter of\nall Boomers indicating that they would switch as a result of poor service. Millennials, on the other hand, are nearly 2.5x more\nlikely to switch services due to a poor customer service experience.\n\nWith more and more data available on customers, and with more and more technology becoming available every day, how is it that the\ncost of failed customer interactions continues to grow?\n\nStrategically, companies should be two steps ahead of the opportunities to use technology to make the company better.\nOperationally, companies should worry less about what might be different in five years, and worry more about those things that are\njust as true now as they have always been. In using technology to drive the business, it is sometimes easy to get caught up in\neverything that has changed, but it is smarter to focus on what hasn’t.\n\nFirst was the rise of analytics. A computer company could make inferences like, “based on last year’s data, 10% of our revenue\ncomes from laptops.”\n\nThe next logical step is data science. “Based on representative secondary data from last year as well as external data, next year\n14% of our revenue will come from laptops.”\n\nFrom data science, machine learning is possible. “Because of the activity of this user on our website today, there is a 50% chance\nthat she buys a laptop.”\n\nAnd finally, even artificial intelligence. “Because of the activity of this user on our website from two different devices today,\nI am going to ask her if her partner is also shopping, and, if so, there is a 50% chance that she buys two laptops.”\n\nAnd yet, too many organizations attempt to jump from analytics into artificial intelligence, without ever having asked the\nquestion, “why are people buying our laptops?” or “why aren’t they buying our desktops?”\n\nIt is an honest mistake. These companies are only seeking to take advantage of what is available. They are fearful of being left\nbehind, of missing out on the ROI of machine learning. They look to tech companies like Uber and Netflix for thought leadership.\n\nIronically, the simplest and cleanest products win the hearts of the buyer. Netflix started by solving the customer problem of\npaying late fees, going to a physical location, wading through advertisements. They happened to take advantage of technology along\nthe way.\n\nUber solved the problem of calling a car in advance. Uber solved the problem for those who needed an on-demand taxi, but did not\nlive on a main avenue. It turns out they had to use technology to solve those problems.\n\nFor that theoretical computer company, the best ROI would not be on 2018 technology like machine learning to help them sell\nlaptops. It would be on 2006 technology like making it easier for a customer to sign in and search for products.\n\nDon’t miss the forest for the mechanical trees.","postSeoTitle":"Proverbial forest and mechanical trees | the hype machine blog","canonicalUrl":"","ogTitle":"Proverbial forest and mechanical trees | the hype machine blog","ogDescription":"Imagine that I’ve done extensive research on a new car. Safety, quality, reliability. I’ve read customer and professional reviews,\nresearched warranties. After weeks of research, I make a decision, I go to a local dealer, and I buy a new car.\n\nA week later, I receive a targeted ad from Lexus, pulling me into their funnel thanks to their insights into my activity. It isn’t\nthe invasion of privacy that bothers me most, it’s the ignorance of how the targeted ads result in reality.\n\nThis theme is common in how companies are applying new technologies to the core business. Every time I see a press release on a\nlarge company’s investment in AI and machine learning, I think of the colloquialism, “missing the forest for the trees.”\n\nThe perceived opportunity to apply these technologies has been in sales and customer service. I am maniacal about detail, so any\nadvantage in customer-facing interactions is, in my view, worth the investment. According to Forbes, $75 billion was lost last\nyear due to poor customer service. This compares to lost revenue of $62 billion just two years prior.\n\nA failed customer interaction is very costly to any business. This is becoming even more true. A separate study polled consumers\nabout switching services due to poor customer service. Baby Boomers have the least propensity to switch, with only a quarter of\nall Boomers indicating that they would switch as a result of poor service. Millennials, on the other hand, are nearly 2.5x more\nlikely to switch services due to a poor customer service experience.\n\nWith more and more data available on customers, and with more and more technology becoming available every day, how is it that the\ncost of failed customer interactions continues to grow?\n\nStrategically, companies should be two steps ahead of the opportunities to use technology to make the company better.\nOperationally, companies should worry less about what might be different in five years, and worry more about those things that are\njust as true now as they have always been. In using technology to drive the business, it is sometimes easy to get caught up in\neverything that has changed, but it is smarter to focus on what hasn’t.\n\nFirst was the rise of analytics. A computer company could make inferences like, “based on last year’s data, 10% of our revenue\ncomes from laptops.”\n\nThe next logical step is data science. “Based on representative secondary data from last year as well as external data, next year\n14% of our revenue will come from laptops.”\n\nFrom data science, machine learning is possible. “Because of the activity of this user on our website today, there is a 50% chance\nthat she buys a laptop.”\n\nAnd finally, even artificial intelligence. “Because of the activity of this user on our website from two different devices today,\nI am going to ask her if her partner is also shopping, and, if so, there is a 50% chance that she buys two laptops.”\n\nAnd yet, too many organizations attempt to jump from analytics into artificial intelligence, without ever having asked the\nquestion, “why are people buying our laptops?” or “why aren’t they buying our desktops?”\n\nIt is an honest mistake. These companies are only seeking to take advantage of what is available. They are fearful of being left\nbehind, of missing out on the ROI of machine learning. They look to tech companies like Uber and Netflix for thought leadership.\n\nIronically, the simplest and cleanest products win the hearts of the buyer. Netflix started by solving the customer problem of\npaying late fees, going to a physical location, wading through advertisements. They happened to take advantage of technology along\nthe way.\n\nUber solved the problem of calling a car in advance. Uber solved the problem for those who needed an on-demand taxi, but did not\nlive on a main avenue. It turns out they had to use technology to solve those problems.\n\nFor that theoretical computer company, the best ROI would not be on 2018 technology like machine learning to help them sell\nlaptops. It would be on 2006 technology like making it easier for a customer to sign in and search for products.\n\nDon’t miss the forest for the mechanical trees.","twitterTitle":"Proverbial forest and mechanical trees | the hype machine blog","twitterDescription":"Imagine that I’ve done extensive research on a new car. Safety, quality, reliability. I’ve read customer and professional reviews,\nresearched warranties. After weeks of research, I make a decision, I go to a local dealer, and I buy a new car.\n\nA week later, I receive a targeted ad from Lexus, pulling me into their funnel thanks to their insights into my activity. It isn’t\nthe invasion of privacy that bothers me most, it’s the ignorance of how the targeted ads result in reality.\n\nThis theme is common in how companies are applying new technologies to the core business. Every time I see a press release on a\nlarge company’s investment in AI and machine learning, I think of the colloquialism, “missing the forest for the trees.”\n\nThe perceived opportunity to apply these technologies has been in sales and customer service. I am maniacal about detail, so any\nadvantage in customer-facing interactions is, in my view, worth the investment. According to Forbes, $75 billion was lost last\nyear due to poor customer service. This compares to lost revenue of $62 billion just two years prior.\n\nA failed customer interaction is very costly to any business. This is becoming even more true. A separate study polled consumers\nabout switching services due to poor customer service. Baby Boomers have the least propensity to switch, with only a quarter of\nall Boomers indicating that they would switch as a result of poor service. Millennials, on the other hand, are nearly 2.5x more\nlikely to switch services due to a poor customer service experience.\n\nWith more and more data available on customers, and with more and more technology becoming available every day, how is it that the\ncost of failed customer interactions continues to grow?\n\nStrategically, companies should be two steps ahead of the opportunities to use technology to make the company better.\nOperationally, companies should worry less about what might be different in five years, and worry more about those things that are\njust as true now as they have always been. In using technology to drive the business, it is sometimes easy to get caught up in\neverything that has changed, but it is smarter to focus on what hasn’t.\n\nFirst was the rise of analytics. A computer company could make inferences like, “based on last year’s data, 10% of our revenue\ncomes from laptops.”\n\nThe next logical step is data science. “Based on representative secondary data from last year as well as external data, next year\n14% of our revenue will come from laptops.”\n\nFrom data science, machine learning is possible. “Because of the activity of this user on our website today, there is a 50% chance\nthat she buys a laptop.”\n\nAnd finally, even artificial intelligence. “Because of the activity of this user on our website from two different devices today,\nI am going to ask her if her partner is also shopping, and, if so, there is a 50% chance that she buys two laptops.”\n\nAnd yet, too many organizations attempt to jump from analytics into artificial intelligence, without ever having asked the\nquestion, “why are people buying our laptops?” or “why aren’t they buying our desktops?”\n\nIt is an honest mistake. These companies are only seeking to take advantage of what is available. They are fearful of being left\nbehind, of missing out on the ROI of machine learning. They look to tech companies like Uber and Netflix for thought leadership.\n\nIronically, the simplest and cleanest products win the hearts of the buyer. Netflix started by solving the customer problem of\npaying late fees, going to a physical location, wading through advertisements. They happened to take advantage of technology along\nthe way.\n\nUber solved the problem of calling a car in advance. Uber solved the problem for those who needed an on-demand taxi, but did not\nlive on a main avenue. It turns out they had to use technology to solve those problems.\n\nFor that theoretical computer company, the best ROI would not be on 2018 technology like machine learning to help them sell\nlaptops. It would be on 2006 technology like making it easier for a customer to sign in and search for products.\n\nDon’t miss the forest for the mechanical 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Safety, quality, reliability. I’ve read customer and professional reviews, researched warranties. After weeks of research, I make a decision, I go to a local dealer, and I buy a new car.</p><p>A week later, I receive a targeted ad from Lexus, pulling me into their funnel thanks to their insights into my activity. It isn’t the invasion of privacy that bothers me most, it’s the ignorance of how the targeted ads result in reality.</p><p>This theme is common in how companies are applying new technologies to the core business. Every time I see a press release on a large company’s investment in AI and machine learning, I think of the colloquialism, “missing the forest for the trees.”</p><p>The perceived opportunity to apply these technologies has been in sales and customer service. I am maniacal about detail, so any advantage in customer-facing interactions is, in my view, worth the investment. According to Forbes, $75 billion was lost last year due to poor customer service. This compares to lost revenue of $62 billion just two years prior.</p><p>A failed customer interaction is very costly to any business. This is becoming even more true. A separate study polled consumers about switching services due to poor customer service. Baby Boomers have the least propensity to switch, with only a quarter of all Boomers indicating that they would switch as a result of poor service. Millennials, on the other hand, are nearly 2.5x more likely to switch services due to a poor customer service experience.</p><p>With more and more data available on customers, and with more and more technology becoming available every day, how is it that the cost of failed customer interactions continues to grow?</p><p>Strategically, companies should be two steps ahead of the opportunities to use technology to make the company better. Operationally, companies should worry less about what might be different in five years, and worry more about those things that are just as true now as they have always been. In using technology to drive the business, it is sometimes easy to get caught up in everything that has changed, but it is smarter to focus on what hasn’t.</p><p>First was the rise of analytics. A computer company could make inferences like, “based on last year’s data, 10% of our revenue comes from laptops.”</p><p>The next logical step is data science. “Based on representative secondary data from last year as well as external data, next year 14% of our revenue will come from laptops.”</p><p>From data science, machine learning is possible. “Because of the activity of this user on our website today, there is a 50% chance that she buys a laptop.”</p><p>And finally, even artificial intelligence. “Because of the activity of this user on our website from two different devices today, I am going to ask her if her partner is also shopping, and, if so, there is a 50% chance that she buys two laptops.”</p><p>And yet, too many organizations attempt to jump from analytics into artificial intelligence, without ever having asked the question, “why are people buying our laptops?” or “why aren’t they buying our desktops?”</p><p>It is an honest mistake. These companies are only seeking to take advantage of what is available. They are fearful of being left behind, of missing out on the ROI of machine learning. They look to tech companies like Uber and Netflix for thought leadership.</p><p>Ironically, the simplest and cleanest products win the hearts of the buyer. Netflix started by solving the customer problem of paying late fees, going to a physical location, wading through advertisements. They happened to take advantage of technology along the way.</p><p>Uber solved the problem of calling a car in advance. Uber solved the problem for those who needed an on-demand taxi, but did not live on a main avenue. It turns out they had to use technology to solve those problems.</p><p>For that theoretical computer company, the best ROI would not be on 2018 technology like machine learning to help them sell laptops. It would be on 2006 technology like making it easier for a customer to sign in and search for products.</p><p>Don’t miss the forest for the mechanical trees.</p>"},"draftboxSettings":{"content":{"cta":{"showAfterPostContent":true},"subscribe":{"showAfterPostContent":true},"misc":{"loadComments":"Load Comments","share":"Share","minRead":"min read"}}},"site":{"siteMetadata":{"pathPrefix":""}},"prevPost":{"title":"A new system","excerpt":"I have been reading a lot of commentary recently from “outsiders” (those who do not partake in the capital markets) on the\nlimitations of our system for investing in companies. I think it is safe to say that our system, which is largely unchanged over\nthe last century, could use some modernization.\n\nTechnology has certainly changed the way we trade. The frequency of trading and volumes have changed. Quant funds have built\nsoftware to automate investment decisions. Investing has opened up to retail investors and spreads have shrunken tremendously.\n\nHowever, the system itself is not fundamentally different. Even my fellow stock-traders will often comment that the stock market\nis rigged in favor of the big money.\n\nThe current system of investing through public exchanges and common shares has plenty of flaws. Just this week, Bernie Sanders and\nChuck Schumer launched a public debate (at least it seems like a hot debate for my fellow #FinTwit nerds) on stock buybacks and\ntheir effect on the public.\n\nThe criticism for share buybacks is largely in promoting further wealth disparity. My personal criticism in share buybacks is that\nthey are largely used to pump vanity metrics for investors. It is also not the best allocation of capital from recent tax cuts in\nterms of long-term health of the company.\n\nWhat if a better system already exists but has simply been publicly-shamed a a fraud and a scam?\n\nLast week I was at lunch with some clients. These clients are some of the more intelligent technologists that I know, having spent\n20 years building platforms for one of the world’s largest investment banks.\n\nI mentioned that I am excited by the future of cryptocurrencies and distributed ledgers. “Still?” they asked.\n\nIt can be difficult to be a believer in crypto. The precipitous drop in Bitcoin price. The abject failure and fraud of several\nICOs.\n\nAn ICO, or Initial Coin Offering, is a means of raising capital through the issuance of a new token. This token represents\nownership in the company, app, cryptocurrency, or other representation. “Shares” are purchased using cryptocurrencies or\ntraditional fiat currencies. ICOs provide for a tangible representation of ownership share in a company.\n\nThe truth is, buzzwords aside, an ICO is the purest form of investment because it connects an investor directly to the investment.\nRemember, that the whole initial point of the stock market was to make it possible to aggregate capital from believers in a\nbusiness to promote growth in that business.\n\nThe ICO is an alternative to the Initial Public Offering (IPO) that every publicly-traded company has used as a means for selling\nshares of the company to the public. IPOs on traditional exchanges are heavily-regulated and have a very robust “supply chain”\nwith many intermediaries such as the listing exchange, several investment banks, clearing-houses, market-makers, brokerages,\nregulatory bodies, and on and on.\n\nThe truth is that both of these systems allow for, and in some cases promote, fraud. Recent ICO frauds have been highly-publicized\nas being ponzi schemes that prey upon unsuspecting “investors.”\n\nA quick trip tohttps://deadcoins.com/will reveal how many ICOs have failed or led to complete and total loss of investment.\n\nThe potential of an ICO should not be dismissed, however, as we search for a system of investment in companies that is not morally\nbankrupt. Our existing “safe” system for investing in companies may not necessarily bankrupt an investor overnight, but it\ncertainly can (and does) bankrupt investors over time.\n\nIn what ways could a new system like an ICO present a solution to the problems of public investing?\n\nCutting out intermediaries and creative accounting\n\n“Trusted intermediaries” are intended to create comfort for investors that their money is safe, that there is transparency in the\nsystem. Publicly-traded securities are regulated by the Securities Exchange Commission and there are thousands of laws that govern\nthe issuance and trading of shares in publicly-traded companies.\n\nThe idea is that there is safety also in the complex supply chain of filing for an IPO to raise capital for a business and in the\nongoing trading of shares. However, these trusted intermediaries each rely upon their piece of this supply chain for profit. While\nnot colluding per se, the profit incentive for each component company is an opposing force to the buyer of common shares.\n\nFurthermore, many of these companies are using creative accounting to attempt to meet the expectations of analysts and investors.\nFrom falsely driving up user counts to padding Earnings per Share (EPS), many growth stocks will tell a narrative for as long as\npossible to satisfy consensus expectations on financial performance.\n\nAt the end of the “value chain,” regular investors are often left holding the bag. Previously hot companies often completely\ncollapse after redistribution of ownership, which allows early investors to cash out while retail investors are left holding the\nstock as it approaches $0.\n\nAn ICO could largely eliminate these inefficiencies and misleading representation. Direct investment and direct issuance of shares\nin a company cuts out the “trusted intermediary.” It reduces the supply chain in issuance of common stock, therefore adding more\ntrust and less cost to investing.\n\nAdditionally, many cryptocurrencies are designed to limit the supply. Therefore, both share buybacks and dilution could be\nimpossible under the ICO construct. Since the ownership share would be directly tied to the value of the currency itself,\nopportunity for deceit would be limited.\n\nSlack recently announcedits plans to IPO via direct listing. This means they will not use an Investment Bank to create a market\nfor investors, and the company will list directly on the exchange. Spotify did this previously, and this is an intermediate step\nthat shows we are gravitating to a more direct-to-investor model.\n\nPromoting investments over trades\n\nThis one is my biggest personal issue with the nature of owning stocks today. Many old-school investors will write about “trading\nversus investing,” but it’s virtually all trading at this point.\n\nA stock that does not pay a dividend almost has no intrinsic relationship to the actual financial success of the company. The\nInitial Public Offering of a company is a receipt of dollars directly from an investor to the company. The initial goal of an IPO\nwas truly to raise capital for growth from investors.\n\nHowever, beyond the IPO, the relationship between common stock holders and the company itself is loose. A growing share price\nactually does little to impact the company itself other than through a display of investor confidence. If the company does not pay\na dividend to a shareholder, the “investor” likewise has no connection to the actual success of the business. In non-dividend\nyielding stocks, the only way to realize a gain is to actually trade the stock.\n\nActive trading can be fun and can even be a source of income. But investing means owning stocks that pay a dividend and holding\nthem over time. In fact,Shark Tank’s Kevin O’Leary recently saidthat 71% of wealth from investing has come rom dividends over the\nlast 40 years.\n\nA blog did a fact-checkanalysis on this and actually found that O’Leary’s number was not far off. Even in dips, the reinvested\ndividends number is often higher than peak amount not re-invested.\n\nHowever, our current paradigm promotes trading over investing. With $0 stock trades, and many traders choosing options over common\nstock, the trend is moving to shorter holding periods. As of this writing, 3 of the 5 largest stocks by market capitalization\n(AMZN, FB, BABA) do not offer a dividend.\n\nBlockchain transactions tend to be more costly which does have the effect of encouraging longer holding (HODLing) periods.\nCompanies with a coin offering could reward these long-term investors with dividends, which allows investors to profit without\ntrading the position. There is no certainty that coin offerings would incentivize investing over trading, but the closer that an\ninvestor feels to the success of the business itself, the more likely the investor is to hold.\n\nPromoting early investment by all\n\nFinally, the most important benefit to a new ICO-based system would be to facilitate early investment to a broader audience. There\nare several limitations to the current system. Oftentimes the biggest believers in a company’s purpose do not have access to\ninvestment in the company at an early stage. This privilege is reserved for those that are closely-tied to venture capital firms.\nWith growing wealth disparity in America, the vast majority have no access to the single-greatest source of wealth-building.\nThrowing change in a piggy bank may be good for your psyche, but it does nothing for building wealth.\n\nI much prefer early stage investing to buying stocks in publicly-traded companies. It makes the investor feel closer to the\ncompany’s vision and success. Promoting broader access to private an early stage investing would promote healthier investing\npractices and more motivated investors. It also creates the potential for tremendous upside and prevents investor FOMO which\ndrives bubbles. A good example would be to consider the returns of early bitcoin HODLers versus those who bought around the peak\ntwo years ago.\n\nSo, what is holding us back from building a new system?\n\nNothing. And everything.\n\nThat big fat investor supply chain that I mentioned is the biggest barrier. As a company grows from an idea to a stock, there are\nventure capitalists, attorneys, investment banks, hedge funds, clearinghouses, exchanges, and financial advisors that all get a\ncut. Making that all go away over night is not a possibility.\n\nThere is also that thing called regulation. The Securities Exchange Commission oversees the creation, sale, and distribution of\ncompany shares and replicating a parallel exchange while circumventing the SEC ain’t gonna happen.\n\nThere is hope, however. Today it is fairly easy to invest in private and early stage companies for accredited investors. An\naccredited investor is anyone who has earned north of $200,000 ($300,000 for couples) for two consecutive years or who has a net\nworth north of $1,000,000.\n\nBuying common stock, however, does not have such requirements. I find this ironic if you consider the trajectories of some\nwell-known stocks in recent years. Take a look at the performance of Blue Apron and GoPro stocks below and tell me if being\npublicly-traded removes investor risk.\n\nBlue Apron\n\nGoPro\n\nIn fact, it is even more likely that the average person will be the eventual bag-holder for common stocks, but that is a topic for\nanother day.\n\nThere is a long way to go to for ICOs to become the next best system for the investing public, but it is clear that the current\nsystem has room for improvement.\n\nCurrently some of the biggest and most successful “startups” are planning to IPO. The pendulum could swing to this new paradigm if\none of these respected firms were to break the mold and announce an ICO. Of course, with founders and early employees having\nsacrificed so much to build these companies, I wouldn’t expect anyone to easily turn down the big payday of an IPO anytime soon.","customExcerpt":"","postSeoSlug":"a-new-system-finance/","updatedAt":"06 April 2021","publishedAt":"10 February 2019"},"nextPost":{"title":"Why this “Tech Bubble” is much tamer than Tech Bubble of 2000","excerpt":"This post was originally written for LinkedIn and published on March 6, 2015.\n\nTwo days ago, Mark Cuban postedthis articleclaiming that we are in the midst of a tech bubble that is worse than the tech bubble\nof 2000. Mark Cuban is my favorite entrepreneur, and I am both inspired and motivated by his success. I also trust his business\ninstincts (who wouldn’t?) as well as his technology prowess (software is where he got his start).\n\nHe raises a valid point with regards to the valuation and liquidity of technology investments. On the technology front for\npublically traded companies, valuations have reached outlandish proportions. New technology companies are seemingly all pegged for\n$B+ IPOs, and the average Price/Sales ratios amongst technology companies is well over 10, and sometimes much higher than that.\nCompare the P/S ratios of cloud companies to those of more mature firms such as SAP, Oracle, and Microsoft, and the story is more\ntelling. New arrivals on the scene have far more investor capital than reasonably forecasted cash flows.\n\nI still disagree with Mr. Cuban’s position, however, for the following reasons:\n\n1.This time is different\n\nCloud companies and other tech startups driven by apps do have trouble with liquidity. Cloud is a low-margin business, and many of\nthese companies are struggling to balance profitability with expansion. Other applications based on development platforms struggle\nto equate users with dollars.\n\nI do believe that we are seeing a bubble in the market. There are too many overvalued companies at the moment, but I believe that\npersonal investors are better hedged than in the past.\n\nThe exposure was also more widespread upon the average investor in 2000. Venture capitalists and “angels” have provided much of\nthe capital backing these illiquid tech companies. I’d like to think that these investors are savvy enough to have well-rounded\nportfolios and be sufficiently guarded against riskier assets.\n\nAdditionally, in 2000 the tech world truly was a house of cards whereby dotcom companies with legitimate business models were\nreliant upon other dotcom companies for ad revenue. When one fell, a domino effect ensued. The current environment has a far\ndifferent model. One tech company is not reliant on another; the larger companies are buying up the smaller for user base. This is\nmore in line with traditional, non-tech industries.\n\nBy the same token, there is a more collaborative environment. Software companies are engaging in partnerships with hardware\ncompanies to help grow margins on hosted applications. Large financial institutions like American Express are recognizing the\nvalue of technology and partnering with technology companies like Apple to jointly go to market. My own company, SAP, has a\nprogram called StartupFocus where mutually beneficial profit models are created for startups to build their business on an\nestablished platform with little risk.\n\n2. Really, this time is different\n\nThese technology companies are emerging with focus on changing business models through technology. Technology can be new and\nexciting, but it doesn’t necessarily become innovation unless it changes the world of business. Many dotcom companies did not\nfundamentally change the world of the consumer.\n\nMuch has been written on the emergence of the “Uber” economy, and the truth is that technology companies are changing the way we\nbuy, interact, procure goods and services, and transact. Technology is moving from a delivery model to an innate function of how\nwe do business. Emerging technology companies understand that offerings that change how the consumer lives will win in the\nlong-run. The question is simply if these same companies can easily jump the hurdles to profitability before the money runs dry.\n\nTime will only tell whether the eventual correction on overvalued tech companies will be as disastrous as it was in 2000. I would\nsuspect that it won’t be.","customExcerpt":"","postSeoSlug":"why-this-tech-bubble-is-much-tamer-than-tech-bubble-of-2000/","updatedAt":"06 April 2021","publishedAt":"06 March 2015"}},"pageContext":{"postSeoSlug":"forest-for-trees/","prev":"a-new-system-finance/","next":"why-this-tech-bubble-is-much-tamer-than-tech-bubble-of-2000/"}},"staticQueryHashes":["126537975","1898930737","1956324895","3147518746","333656818","3485313408"]}