{"id":160661,"date":"2022-08-11T07:23:43","date_gmt":"2022-08-11T07:23:43","guid":{"rendered":"https:\/\/swissfederalism.ch\/valore-dati\/"},"modified":"2022-08-11T07:43:27","modified_gmt":"2022-08-11T07:43:27","slug":"value-of-data","status":"publish","type":"post","link":"https:\/\/swissfederalism.ch\/en\/value-of-data\/","title":{"rendered":"The value of data"},"content":{"rendered":"<h1 class=\"entry-title\"><span class=\"font-377884\">The value of data<\/span><\/h1>\n<h3><span class=\"font-377884\"><em>In a digital economy, data can be costly to acquire and structure. Ultimately, its value is set by the benefits that derive from data-driven predictions.<\/em><\/span><\/h3>\n<h3 class=\"toc-only\" style=\"text-align: center;\"><span class=\"font-377884\" style=\"color: #ff0000;\">In a nutshell<\/span><\/h3>\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li style=\"list-style-type: none;\">\n<ul>\n<li><span class=\"font-377884\">Quality, use and volume make data a multifaceted class of goods<\/span><\/li>\n<li><span class=\"font-377884\">Data can play different roles in the digital economy<\/span><\/li>\n<li><span class=\"font-377884\">The value of data lies in how it can lead to better decision-making<\/span><\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<figure id=\"attachment_160553\" aria-describedby=\"caption-attachment-160553\" style=\"width: 840px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/swissfederalism.ch\/valore-dati\/archive-photo-by-pexels-on-pixabay\/\" rel=\"attachment wp-att-160553\"><img decoding=\"async\" class=\"size-large wp-image-160554\" src=\"https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/archive-Photo-by-Pexels-on-Pixabay-1024x683.jpg\" alt=\"Archive Photo by Pexels on Pixabay\" width=\"840\" height=\"560\" srcset=\"https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/archive-Photo-by-Pexels-on-Pixabay-1024x683.jpg 1024w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/archive-Photo-by-Pexels-on-Pixabay-300x200.jpg 300w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/archive-Photo-by-Pexels-on-Pixabay-768x512.jpg 768w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/archive-Photo-by-Pexels-on-Pixabay-1536x1024.jpg 1536w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/archive-Photo-by-Pexels-on-Pixabay.jpg 1920w\" sizes=\"(max-width: 840px) 100vw, 840px\" \/><\/a><figcaption id=\"caption-attachment-160553\" class=\"wp-caption-text\"><span class=\"font-377884\">Archive Photo by Pexels on Pixabay<\/span><\/figcaption><\/figure>\n<p><span class=\"font-377884\">&#8220;Data is the new oil,\u201d goes the saying, but it is wrong. The economics of data is intricate. It is not the abundance of data that drives value; it is the benefit one can extract from data-driven <a href=\"https:\/\/www.gisreportsonline.com\/r\/ai-prediction\/\">predictions<\/a>. Data as a good is multifaceted. And so is the economics of data.<\/span><\/p>\n<h2 id=\"h-base-good-and-complement\"><span class=\"font-377884\">Base good and complement<\/span><\/h2>\n<p><span class=\"font-377884\">Much of the digital economy, especially\u00a0artificial intelligence\u00a0(AI), is about prediction. And prediction relies on data. As economists put it, data is a complement to prediction. Complements are goods that add value to another. Usually, the base good is relatively cheap, and the complement good is relatively expensive. For example, printers are a base good and the ink cartridges are its complement;\u00a0\u00a0the printer is cheap and the cartridge expensive. The maker of printers locks in customers with the relatively more affordable base good and makes its profits via the expensive complement. In the digital world, a free application is a base good and the paid in-app services are the complement.<\/span><\/p>\n<p><span class=\"font-377884\">The same economics apply to the digital economy at large, especially for AI. The AI making the prediction, the algorithm, is made relatively cheap, locking in users. The data used by this algorithm is valuable. The cheaper the algorithm as a base good becomes, the more the value of data as a complement increases. This trend is likely to continue. Programming the mathematical calculations that make up the algorithms will become more standardized, easier, and, therefore, cheaper. Getting the \u201cright\u201d data in the \u201cright\u201d way and using it \u201ccorrectly\u201d will increasingly become the differentiating factor and, therefore, more valuable.<\/span><\/p>\n<figure id=\"attachment_160561\" aria-describedby=\"caption-attachment-160561\" style=\"width: 840px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/swissfederalism.ch\/valore-dati\/valore-photo-by-gerd-altmann-on-pixabay\/\" rel=\"attachment wp-att-160561\"><img decoding=\"async\" class=\"size-large wp-image-160562\" src=\"https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/Valore-Photo-by-Gerd-Altmann-on-Pixabay-1024x724.jpg\" alt=\"Valore Photo by Gerd Altmann on Pixabay\" width=\"840\" height=\"594\" srcset=\"https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/Valore-Photo-by-Gerd-Altmann-on-Pixabay-1024x724.jpg 1024w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/Valore-Photo-by-Gerd-Altmann-on-Pixabay-300x212.jpg 300w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/Valore-Photo-by-Gerd-Altmann-on-Pixabay-768x543.jpg 768w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/Valore-Photo-by-Gerd-Altmann-on-Pixabay-1536x1086.jpg 1536w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/Valore-Photo-by-Gerd-Altmann-on-Pixabay.jpg 1920w\" sizes=\"(max-width: 840px) 100vw, 840px\" \/><\/a><figcaption id=\"caption-attachment-160561\" class=\"wp-caption-text\"><span class=\"font-377884\">Value Photo by Gerd Altmann on Pixabay<\/span><\/figcaption><\/figure>\n<h2 id=\"h-aspects-of-data-value\"><span class=\"font-377884\">Aspects of data value<\/span><\/h2>\n<p><span class=\"font-377884\">While data can be a differentiator and value driver,\u00a0\u00a0not all data is the same. Quality, use and volume make data a multifaceted good \u2013 or rather, class of goods. Big data economics postulates that the more data there is, the better the results\u00a0\u00a0\u2013\u00a0for example, the predictions an algorithm can yield. However, the quality of data is equally important. The better the data, the better the predictions. Regarding data quality, architecture is critical. Data that has been correctly labeled and structured is more valuable than loose data points whose information content must be discovered and repackaged, often manually.<\/span><\/p>\n<h3 style=\"text-align: center;\"><span class=\"font-377884\"><em><strong>The optimal amount and quality of data depend on the benefits generated by AI-based prediction.<\/strong><\/em><\/span><\/h3>\n<p><span class=\"font-377884\">And then there is data usage. Data can play three different roles in the digital economy. When it comes to AI, data can be input data, namely data fed to an algorithm to make a prediction. When a user looks up directions from one place to another, AI uses maps as input data to calculate the route. But data can be training data, too, to make the AI good enough to predict the complexities of the real world. This kind of data is used to teach AI to select routes and predict arrival times.<\/span><\/p>\n<p><span class=\"font-377884\">Finally, data can be feedback data, used to improve the AI\u2019s performance with experience. When someone decides to take a different route than the one suggested by the algorithm, this provides valuable feedback data that can enhance future calculations.<\/span><\/p>\n<p><span class=\"font-377884\">In some situations, considerable overlap between these data uses exists, such as when the same data plays all three roles. The more overlap, the better the data, since its structure and labeling enable the AI to manage its simultaneous usage more readily, focusing on learning, predicting and reacting to feedback.<\/span><\/p>\n<p><span class=\"font-377884\"><strong><a href=\"https:\/\/swissfederalism.ch\/en\/artificial-intelligence-prediction-revolution\/\">Artificial Intelligence: Prediction revolution<\/a><\/strong><\/span><\/p>\n<h2 id=\"h-cost-of-data\"><span class=\"font-377884\">Cost of data<\/span><\/h2>\n<p><span class=\"font-377884\">Data can be costly to acquire and structure. Thus, the investment involves a trade-off between the benefit of more and better data and the acquisition cost. The optimal amount and quality of data depend on the benefits generated by AI-based prediction. Let us first look at the cost.<\/span><\/p>\n<h3 style=\"text-align: center;\"><span class=\"font-377884\"><em>The benefits one can extract from data are the differentiating factor in business models and value drivers.<\/em><\/span><\/h3>\n<p><span class=\"font-377884\">From the vantage point of economic theory, data as such has decreasing returns to scale. Adding a third data point to a second is much more valuable than adding a 100th<sup>\u00a0<\/sup>to a 99th point. On the other hand, adding more and better data pushes up marginal costs. Incorporating the eight-millionth data point is more difficult or costly than adding the 14th. It is like learning one\u2019s way in a new city: the first and second time one takes the bus, one learns a lot about the city\u2019s layout and mass transit system. On the three-hundredth trip, it has become routine. Only vestigial new information is being acquired (decreasing returns). Or one would have to pay an incommensurate amount of attention to the minor details to learn something new (increasing marginal costs).<\/span><\/p>\n<p><span class=\"font-377884\">Cost drivers in acquiring and structuring data are mainly opening channels for data collection and exchange, labeling, developing a flexible architecture for evaluating and using the different data points, as well as setting up, adapting and expanding the physical infrastructure enabling these activities. Even if the individual data point can be acquired free of charge, the processes for extracting their informational value and taking advantage of them are not.<\/span><\/p>\n<p>&nbsp;<\/p>\n<figure id=\"attachment_160557\" aria-describedby=\"caption-attachment-160557\" style=\"width: 840px\" class=\"wp-caption aligncenter\"><a href=\"https:\/\/swissfederalism.ch\/valore-dati\/ricerca-su-google-photo-by-firmbee-on-pixabay\/\" rel=\"attachment wp-att-160557\"><img decoding=\"async\" class=\"size-large wp-image-160558\" src=\"https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/ricerca-su-google-Photo-by-Firmbee-on-Pixabay-1024x680.jpg\" alt=\"ricerca su google Photo by Firmbee on Pixabay\" width=\"840\" height=\"558\" srcset=\"https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/ricerca-su-google-Photo-by-Firmbee-on-Pixabay-1024x680.jpg 1024w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/ricerca-su-google-Photo-by-Firmbee-on-Pixabay-300x199.jpg 300w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/ricerca-su-google-Photo-by-Firmbee-on-Pixabay-768x510.jpg 768w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/ricerca-su-google-Photo-by-Firmbee-on-Pixabay-1536x1020.jpg 1536w, https:\/\/swissfederalism.ch\/wp-content\/uploads\/2022\/08\/ricerca-su-google-Photo-by-Firmbee-on-Pixabay.jpg 1920w\" sizes=\"(max-width: 840px) 100vw, 840px\" \/><\/a><figcaption id=\"caption-attachment-160557\" class=\"wp-caption-text\"><span class=\"font-377884\">Search on google Photo by Firmbee on Pixabay<\/span><\/figcaption><\/figure>\n<h2 id=\"h-benefits-of-data\"><span class=\"font-377884\">Benefits of data<\/span><\/h2>\n<p><span class=\"font-377884\">Data is more than a cost factor in the digital economy at large, especially for AI. The benefits one can extract from data are the differentiating factor in business models and value drivers. Conceptualizing these benefits requires a shift of vantage point. The economic value of data cannot be measured by the investment required to acquire and maintain it. Neither can it be assessed with how data technically fits the results of calculations. The critical economic insight about data benefits is that the value of data is a function of how it improves the value one gets from the algorithm using it. To use the example of predictions again: the value of better data is not in how much more precise a prediction is but in how the prediction improves the user\u2019s choices.<\/span><\/p>\n<p><span class=\"font-377884\">Take internet search engines. Most of them yield the same results. At the time of this writing,\u00a0<em>Google, DuckDuckGo<\/em> and <em>Bing\u00a0<\/em>produce roughly the same results for \u201cBeethoven.\u201d In this context, data is not a differentiator. However, in a less conventional search, as for \u201carbitrage,\u201d differentiation kicks in. Bing mainly yields definitions; DuckDuckGo shows definitions and links to financial sites, while Google comes up with definitions, financial sites and some academic references.\u00a0<\/span><\/p>\n<p><span class=\"font-377884\">Incorporating more data and better-structured data into its architecture gives Google an advantage. It shows results that increase the choices of the user. This enhanced benefit offered by Google translates disproportionately into the company\u2019s market share. Economists call this phenomenon increasing returns to data differentiation.<\/span><\/p>\n<p><span class=\"font-377884\">Most users use Google for both rare and common searches. Being even a little better in search results can lead to a big difference in market share. To \u201cbe even a little better,\u201d the digital company needs to pay special attention to data acquisition and quality. An additional effort in these areas leads to a differentiating factor via enhancing user benefits. That results in an overproportionate increase in the market position, revenues, and improvement in the digital business model.<\/span><\/p>\n<p style=\"text-align: left;\"><span class=\"font-377884\"><a href=\"https:\/\/swissfederalism.ch\/en\/gianluca-tirozzi-this-is-how-bitcorp-will-conquer-metaspace\/\"><strong>Gianluca Tirozzi: &#8220;This is how bitCorp will conquer metaspace!&#8221;<\/strong><\/a><\/span><\/p>\n<h2><span class=\"font-377884\">Facts &amp; figures<\/span><\/h2>\n<h3 id=\"h-summary\"><span class=\"font-377884\" style=\"color: #ff0000;\">Summary<\/span><\/h3>\n<ul>\n<li><span class=\"font-377884\">Data is essential for digital economies and AI; however, it is a multifaceted class of goods.\u00a0<\/span><\/li>\n<li><span class=\"font-377884\">Data differentiates itself according to volume, quality, and use.\u00a0<\/span><\/li>\n<li><span class=\"font-377884\">While data can be costly to obtain and structure, only slightly better data can generate overproportionate benefits to users, which, in turn, creates a market advantage for the digital business models providing this add-value.\u00a0<\/span><\/li>\n<li><span class=\"font-377884\">The critical economic insight about data is that its value is not a function of how it improves a result; it is about how data enhances user benefits.\u00a0<\/span><\/li>\n<li><span class=\"font-377884\">Often, there are increasing returns to data differentiation: the additional benefit that users derive from better data translates overproportionately into market share and revenues.<\/span><\/li>\n<\/ul>\n<h2><span class=\"font-377884\">Scenarios<\/span><\/h2>\n<p><span class=\"font-377884\">There are three base scenarios for picturing how data can further impact the value of digital economies, especially AI.<\/span><\/p>\n<h3 id=\"h-market-monopolization\"><span class=\"font-377884\" style=\"color: #ff0000;\">Market monopolization<\/span><\/h3>\n<p><span class=\"font-377884\">In the first and least likely scenario, some companies will specialize even more in data acquisition and structuring, giving them a widening lead in generating user benefits. This will allow them to expand their market share to quasi-monopolies able to gather even more data and invest in improved architecture, which, in turn, will solidify their position. Such a feedback loop ends in the monopolization of markets. It is the least likely scenario because of data\u2019s multifaceted and dynamic nature, which makes its monopolization nigh impossible.<\/span><\/p>\n<h3 id=\"h-abundance-of-data\"><span class=\"font-377884\" style=\"color: #ff0000;\">Abundance of data<\/span><\/h3>\n<p><span class=\"font-377884\">In a second and more likely scenario, data could lose its differentiating power. This process can occur if channels for data acquisition and their structuring become abundant. And that can happen if\u00a0data protection\u00a0and intellectual property\u00a0regulations\u00a0are relaxed, if agents agree on complete and real-time unconstrained data diffusion, or with the advent of new and simpler paradigms in data architecture. In this case, it will be easier to acquire and structure data. However, the specific advantage derived from harvesting it and creating a differentiating factor is likely to diminish too. This scenario depends on the convergence of various elements in regulation, technology, and values. In the medium term, such a convergence is only likely in\u00a0smaller communities\u00a0of users.<\/span><\/p>\n<h3 id=\"h-unfettered-competition\"><span class=\"font-377884\" style=\"color: #ff0000;\">Unfettered competition<\/span><\/h3>\n<p><span class=\"font-377884\">A third and most likely scenario is a gradual improvement of data acquisition and architecture paired with intense competition by incumbents to enhance the users\u2019 benefits. Additionally, incumbents will be challenged by new firms trying to increase the added value of predictions or unlock more information from less data to create the same value as others but with cheaper processes. This case is the continuation of the economic logic exposed here and can significantly enhance user experiences while also increasing the revenues and gains of digital companies.<\/span><\/p>\n<p>&nbsp;<\/p>\n<p><span class=\"font-377884\">Author: <strong>Henrique Schneider<\/strong> professor of economics<\/span><\/p>\n<p><span class=\"font-377884\">Source:<\/span><\/p>\n<blockquote class=\"wp-embedded-content\" data-secret=\"xeo76qAnKN\"><p><a href=\"https:\/\/www.gisreportsonline.com\/r\/the-value-of-data\/\">The value of data<\/a><\/p><\/blockquote>\n<p><iframe class=\"wp-embedded-content\" sandbox=\"allow-scripts\" security=\"restricted\" style=\"position: absolute; clip: rect(1px, 1px, 1px, 1px);\" title=\"&#8220;The value of data&#8221; &#8212; GIS Reports\" src=\"https:\/\/www.gisreportsonline.com\/r\/the-value-of-data\/embed\/#?secret=QCdTgQuh83#?secret=xeo76qAnKN\" data-secret=\"xeo76qAnKN\" width=\"600\" height=\"338\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\"><\/iframe><\/p>\n","protected":false},"excerpt":{"rendered":"<p>In a digital economy, data can be costly to acquire and structure. Ultimately, its value is set by the benefits that derive from data-driven predictions.<\/p>\n","protected":false},"author":14,"featured_media":160558,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[256,985,988,260,210,1999],"tags":[2090,1255,2196,1021,1224,795,2195],"class_list":["post-160661","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-economy","category-finance","category-geopolitics","category-highlights","category-magazine","category-technology","tag-artificial-intelligence","tag-business-en","tag-data","tag-digital","tag-digitization","tag-economy","tag-value"],"_links":{"self":[{"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/posts\/160661","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/users\/14"}],"replies":[{"embeddable":true,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/comments?post=160661"}],"version-history":[{"count":3,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/posts\/160661\/revisions"}],"predecessor-version":[{"id":160664,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/posts\/160661\/revisions\/160664"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/media\/160558"}],"wp:attachment":[{"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/media?parent=160661"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/categories?post=160661"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/swissfederalism.ch\/en\/wp-json\/wp\/v2\/tags?post=160661"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}