From intangible assets to “digital blueprints”

Dagli intangible assets ai “digital blueprints”

Why do we talk so much about data? For over fifty years, economists talk, sometimes with some skepticism, sometimes with enthusiasm, information economy, highlighting the many difficulties that crowd on the path of those who seek to create value through the data, instructing a decision-making process And organizational based on factual evidence. From the paradox of Kenneth Arrow’s information to Ronald Coase’s transaction costs, there has been intense intensity for decades for decades to strengthen the protection of those intangible values ​​deriving from business innovation processes, from brands to trade marks, from Patents to industrial secrets, from operating processes to organizational models. Until now, the guarantee of these values ​​has been entrusted to a legal protection device made up of increasingly complex, articulated and international standards and regulations, but the ever-increasing capillary digitization process that has characterized most of the last decade most economies Developed, it has undoubtedly undermined the effectiveness of certain safeguards (for example, copyright law, especially in the music field) and has put others at a serious risk (think of industrial secrets increasingly vulnerable to Electronic crime and industrial espionage). The reason why we talk so much about data is because the data has so much to talk about. Both the Information Economy theorists and New Economy entrepreneurs have a fairly clear idea of ​​what can be done with the data: they know, like Mark Zuckerberg, that social interaction rules have changed irreversibly and by now the data Sensitive are negotiable; They know, like Larry Page, that the data is comparable to an inexhaustible nature reserve and universal value; They know, like Elon Musk, that only through more in-depth knowledge of process data is possible to automate and strengthen their competitive advantage; They know, like Jeff Bezos, that only having the data can minimize the risk of any experiment on the market. Therefore IT infrastructures are at the center of the competitive advantage of a growing number of businesses.


During many events and conferences on the Big Data theme, the tsunami is the most frequently used metaphor to describe the exponential growth of data and information in post-industrial societies. In recent years, we have witnessed the progressive multiplication of data center infrastructures, almost all major web and IT leaders have invested heavily in creating ever-increasing hyperscale data centers (the one built recently from SuperNAP to Reno is large Almost as much as the Pentagon). For at least a five-year period, there has been a rushing race among operators to contend with the scepter of the first great utility of the data and information: if we look at official communications, Google has at least fifteen sites of enormous size, Amazon’s of over 40 ” Availability “, Microsoft has over 30 infrastructure areas, IBM nearly fifty cloud data centers, and so on, with ever-growing and upgrading infrastructure, year-to-year. While appreciating the evocative character of the tsunami metaphor, however, it is imperative to make some clarity in order to better understand the actual heuristic content. If we look at the progression of the installed base of the major devices, such as smartphones, tablets, connectTVs and PCs, we easily understand how quickly the volume of data can grow over the next five to ten years – if global storage capacity in 2020 It may be around 10 zettabyte, IDC estimates that the amount of data collected and kept in business databases and not, the amount of persistent data, could amount to about half, 5 zettabyte, but the amount of transitional data produced globally – obviously we refer to all those data produced by sensors and devices that are not stored at the end of work sessions – could exceed over 40 zettabyte. It is in this unexplored space of “ephemeral” information that will play many of the competitive challenges of the coming decades.

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The main thesis we would like to argue is that Big Data Analytics platforms can allow us to substantially revise the intangible values ​​in many companies. All companies that have human capital, intellectual property, state-of-the-art processes, or even a consolidated reputation on the market can use Big Data platforms to measure and consolidate these values: for example, to accurately verify how much Its brand equity contributes to the company’s result as compared to its competitors, as some international operators in Food & Beverage have been experimenting for some time now. As we all know, when an object becomes measurable, only then it becomes manageable and hence it becomes possible to extract the maximum value possible for the company. It is possible to theorize here that the other interesting aspect of applying new analytics technologies to intangible values ​​is to allow any company to find any “capitals” that were not considered or even neglected. The purpose of the new analytics platforms will no longer be merely the data discovery in the strict sense, which is now being consolidated, but asset discovery, ie the ability to show intelligence superior to its competitors, is a cognitive advantage that It does not only depend on new levels of automation but also from the ability to reinvent its business with great lucidity. For example: What happens when a furniture company discovers that it can invest in superior “intimacy” with its customers, becoming a platform for any other competitor? How much does your business model change if you decide to rent furniture instead of selling it to a court? These transformations are only possible to those who know their customers and their processes better than any competitor.


A company’s ability to move from a data-driven approach to a knowledge-driven approach obviously goes far beyond the ability to employ IT to automate core business or to create new products and services that consider well I am only the most obvious result of a deeper transformation that is hidden behind appearances. The central point is to recognize that any business problem is primarily a data problem, a matter of “digital logistics”, and so the level of competition moves, so to speak, a step back from market comparison Reality, where imitation and homologation processes are so strong that any follower after some time succeeds in mimicking the most sophisticated solutions set up by market leaders, a sort of virtual meta-market where contestants are confronted with the ability to develop An increasingly sophisticated knowledge of market demands and production processes, and where it competes on digital images of processes, products and solutions (“digital twins”). As businesses begin to compete on the ground of what we might call “digital logistics”, the rules of competition take on a new form and begin to transcend the traditional boundaries between industrial sectors. If from the material production of goods and services entrusted to the increasingly intelligent machines of Industry 4.0, competition moves on the digitization of business models entrusted to the “data architects” involved in the digital twin processes, then it could come Very soon a moment in which the most important determinants of business value will be these “digital blueprints”, that are aggregates of perfectly coherent, integrated and coordinated intangible values ​​in their elementary components, reified in increasingly liquid data and infrastructures that can be transferred Easily from a matrix of productive factors to another, from one sector to another. In such a futuristic scenario, there would be only two industrial sectors: the manufacturing industry (broadly), and the data industry.



Shirley is your guy if you want to choose a perfect smartphone in your budget. He is always abreast with the latest news on smartphones and various tech products. In his free time, she loves to visit famous tourist attractions.

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