Velocita' ed efficacia: quando l'innovazione e' guidata dai dati
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Velocita' ed efficacia: quando l'innovazione e' guidata dai dati

BIG DATA, INTELLIGENZA ARTIFICIALE E MACHINE LEARNING SODDISFANO LA NECESSITA' DI IDENTIFICARE RAPIDAMENTE L'INNOVAZIONE OVUNQUE SI SVILUPPI, SPESSO AL DI FUORI DELLE GRANDI ORGANIZZAZIONI, SECONDO UN LIBRO DI TORBEN PEDERSEN E MICHAEL MOESGAARD ANDERSEN. LEGGI UN ESTRATTO

Oggi, l'innovazione non si verifica solo nelle grandi organizzazioni. Invece, spesso emerge dalla comunità delle start-up. Nella nuova economia dell'innovazione, la chiave è trovare rapidamente pezzi di innovazione, alcuni dei quali possono essere già sviluppati. Perciò, c'è bisogno di mezzi più avanzati che cerchino e identifichino l'innovazione ovunque essa si verifichi. Allo stesso tempo, c'è una crescente capacità di raccogliere, memorizzare e analizzare enormi quantità di dati, molto più di quanto la mente individuale potrebbe elaborare da sola. Questa enorme quantità di informazioni denominata Big Data, insieme all'intelligenza artificiale (AI) e all'apprendimento automatico, sta creando nuove opportunità. È il fondamento del processo decisionale informato e la chiave per sbloccare nuove attività e business più efficienti. Nel loro nuovo libro (Data-Driven Innovation. Why the data-Driven Model Will Be Key to Future Success, Routledge, 2021), Torben Pedersen, professore di International Business alla Bocconi, e Michael Moesgaard Andersen (Copenhagen Business School) sottolineano l'importanza dell'innovazione guidata dai dati e basata su piattaforme digitali, poiché la loro impronta sta crescendo rapidamente e in sincronia con il passaggio da analogico a digitale dei flussi di lavoro di innovazione. Per gentile concessione degli autori, Bocconi Knowledge pubblica un estratto del libro (in inglese).
 
We do not suggest that all innovation can easily be purchased externally—that would essentially be the same as pleading for complete outsourcing of corporations’ innovation and R&D. Rather, our aim is to point to the need for a new balance between build and buy, as the buy option is often either overlooked or under prioritized.
 
Many possibilities exist with regard to the buy option. There are already a considerable number of platform vendors through which corporations can gain access to start-ups and, thereby, innovation.
 
The Big Data explosion
 
 

Within the big data space, patterns can be detected in the data. For example, Google was better at predicting the spread of the SARS virus than the World Health Organization, which was supposed to be the expert. Google simply assumed that the origination of searches from a geographical perspective was identical to the actual spread of SARS. The correlation was high, although one could question whether there was causality.
 
A completely different situation is evident with regard to innovation, where there is no easy method of measuring it, such as Google searches, IBM’s Watson database, or other databases. In fact, for many years, there was no database on innovation.
 
Today, one can search the internet for “innovation.” However, what comes out of such a search is less than adequate. Whether you use search engines or AI, the result is highly dependent on the quality of the data. If you, for instance, google “innovation,” you will receive no less than 2,150 million hits. You can reduce this by a factor of 31 if you search for “innovation water pumps,” which results in only 68.5 million hits. The number can be further dramatically by searching for start-ups within this field, recognizing that much modern innovation comes from start-ups.
 
Interestingly, a number of platforms have recently emerged that offer access to innovations developed by start-ups. As significant amounts of data are collected on these platforms, we see a new industry developing that revolves around digital platforms for data-driven innovation. One of the major advantages of digital platforms is that they extend the search for start-ups and innovation beyond firms’ own collaborators. While open innovation is typically conducted in collaboration with close counterparts like suppliers and customers, data-driven innovation platforms search for innovative start-ups all over the world. As such, they move open innovation to a new level, where the search for innovation becomes global

Therefore, we need to take a closer look at this type of platform. One underlying rationale for building these platforms lies in the obvious advantages of collaboration between corporations and start-ups, which are captured in the table below.
 
Complementarity between start-ups and corporations
 


As illustrated in the table, complementarity exists between innovation, resources, customers, and scale. Corporations have what start-ups lack and start-ups have what corporations need. How should this general match be supported?
The answer to this question was blowing in the wind for several years during which experiments were launched with a number of modalities, such as start-up events, incubator and accelerator programs, direct investments, partial investments, and M&A activities. Most of these initiatives were introduced by corporations. However, none of them were data driven.
 
Finding the “right” piece of innovation is sometimes like finding a needle in a haystack. Such exercises are not easy and they are often more emotional than rational, especially when the traditional modalities are utilized. Therefore, it is only natural that a number of digital platforms have emerged in order to untie the Gordian knot of matching the different qualifications of corporations and start-ups.
 
One of many advantages of relying on digital platforms is speed. While some traditional methods may be cumbersome and time consuming, it is easier and faster to undertake searches using qualified databases. Speed here goes hand in hand with effectiveness. Instead of contacting a limited and serendipitously selected number of start-ups located nearby, corporations can search among millions of starts-ups globally and in real time.
 

di Torben Pedersen e Michael Moesgaard Andersen
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