Big Data are re-shaping the world. As a disruptive “Mega Trend” they involve many sectors and, inevitably, the AgriFood Industry. Agriculture, in particular, is one of the most promising stages of the AgriFood Supply Chain for the implementation of Big Data Analytics answering the future challenges that are going to arise for what concern the food production. Latest FAO Reports show that Agriculture is asked to a 70% increase of actual production due to a forecasted growth of the global population that will reach 10 billion in 2050. Today the Agriculture is part of the so-called Revolution 4.0, it is actually possible to refer to Agriculture 4.0 as a new paradigm where digital technologies are fundamental assets to achieve standard level of competitiveness and to gain profitability and sustainability. As a result, agriculture is becoming a Cyber-Physical System where a massive generation of data is registered: from this assumption the issue of strategically manage them naturally emerges. In recent years, farmers recognised the potential for big data in agriculture to increase productivity and the crop yield leveraging data analytics which are generated by the new concept of Smart Farming. Data themselves have not value, but it is possible to rely on an array of technologies that extract powerful insights from them, that are mainly used in business operations, but still perceived as a by-product and not as a core asset of the farm. Several agricultural companies showed very interesting cost reduction and higher process efficiency after the use of big data. However, it is possible to see a lack in strategic approach on the theme of big data in agriculture that could provide a wider, more comprehensive and long-term oriented view: agricultural companies, as both data sources and data users have the opportunity to strategically leverage them to increase profitability and sustainability. The objective of this thesis is first to discover how to strategically enhance data in Agriculture and if it implies business model innovation. Secondly, it could be possible to demonstrate that investing on data as key resources of the Farm 4.0 would have significant benefits and, in parallel, it could strengthen the position of the farmers in a stakeholder network which is really complex and unbalanced in term of power allocation. These results are derived by a deep analysis of the existing literature and by empiric evidences from a case studies mapping. At last, some systematic considerations on the Platforms and the Exchange facilities are proposed, in order to evidence their pivotal role in the integration of data along the supply chain, which seems to be the most effective way to establish a Data-driven Strategy.
I Big Data stanno cambiando il mondo. Essendo un “Mega Trend” senza precedenti, coinvolge numerosi settori produttivi e, inevitabilmente anche l’industria agro-alimentare. L’Agricoltura, in particolare, è uno degli anelli della filiera agro-alimentare più promettenti per l’implementazione di Big Data Analytics, per rispondere alle sfide future in termini di produzione primaria e nutrizione. La FAO stima un aumento del 70% della produzione a causa di una crescita fino a 10 miliardi della popolazione globale entro la fine del 2050. Oggi l’agricoltura fa parte della cosiddetta Rivoluzione 4.0, è infatti possibile riferirsi all’Agricoltura 4.0 come nuovo paradigma dove le tecnologie digitali sono una risorsa fondamentale per ottenere livelli accettabili di competitività, sostenibilità e redditività. Il risultato è che l’agricoltura sta diventando un Sistema Cyber-fisico in cui si registra una imponente generazione di dati: da ciò, la tematica di gestire strategicamente tali dati emerge in modo spontaneo. Negli ultimi anni, gli agricoltori hanno riconosciuto il potenziale dei big data applicati in agricoltura per incrementare la produttività e la resa dei raccolti, sfruttando tecniche di data analytics, al centro del nuovo concetto di Smart Farming. I dati da soli non hanno un vero e proprio valore, ma si può fare affidamento su tecnologie che estraggono una potente conoscenza, principalmente utilizzata in business operations, tuttavia questi vengono ancora percepiti come un by-product e non come un asset chiave dell’azienda agricola. Molteplici aziende mostrano una riduzione dei costi e un’altra efficienza dei processi produttivi. In ogni caso, si registra l’assenza di un approccio strategico sul tema che potrebbe fornire una più ampia, completa e lungimirante visione: le aziende agricole, contestualmente fonti e utilizzatrici di dati, hanno l’opportunità di sfruttarli in modo strategico per incrementare sostenibilità e profitti. L’obiettivo della tesi è quello di scoprire come valorizzare i dati in modo strategico e se questo comporterebbe un’innovazione dei modelli di business. Si potrebbe dimostrare che investire sui dati come risorse primarie avrebbe significativi vantaggi e, in parallelo, rafforzerebbe ed arricchirebbe la posizione dell’agricoltore in un mercato complesso e sbilanciato dal punto di vista dell’allocazione del potere contrattuale. Questi risultati derivano dall’analisi della letteratura e da evidenze empiriche dallo studio di casi. Infine, alcune considerazioni di sistema sul ruolo fondamentale delle Piattaforme e delle Exchange Facilities nell’integrazione dei dati lungo la filiera, che risulterebbe essere il modo più efficace per stabilire una strategia orientata ai dati.
Strategic enhancement of big data in AgriFood industry : a focus on agriculture
MINGARELLI, MATTEO
2018/2019
Abstract
Big Data are re-shaping the world. As a disruptive “Mega Trend” they involve many sectors and, inevitably, the AgriFood Industry. Agriculture, in particular, is one of the most promising stages of the AgriFood Supply Chain for the implementation of Big Data Analytics answering the future challenges that are going to arise for what concern the food production. Latest FAO Reports show that Agriculture is asked to a 70% increase of actual production due to a forecasted growth of the global population that will reach 10 billion in 2050. Today the Agriculture is part of the so-called Revolution 4.0, it is actually possible to refer to Agriculture 4.0 as a new paradigm where digital technologies are fundamental assets to achieve standard level of competitiveness and to gain profitability and sustainability. As a result, agriculture is becoming a Cyber-Physical System where a massive generation of data is registered: from this assumption the issue of strategically manage them naturally emerges. In recent years, farmers recognised the potential for big data in agriculture to increase productivity and the crop yield leveraging data analytics which are generated by the new concept of Smart Farming. Data themselves have not value, but it is possible to rely on an array of technologies that extract powerful insights from them, that are mainly used in business operations, but still perceived as a by-product and not as a core asset of the farm. Several agricultural companies showed very interesting cost reduction and higher process efficiency after the use of big data. However, it is possible to see a lack in strategic approach on the theme of big data in agriculture that could provide a wider, more comprehensive and long-term oriented view: agricultural companies, as both data sources and data users have the opportunity to strategically leverage them to increase profitability and sustainability. The objective of this thesis is first to discover how to strategically enhance data in Agriculture and if it implies business model innovation. Secondly, it could be possible to demonstrate that investing on data as key resources of the Farm 4.0 would have significant benefits and, in parallel, it could strengthen the position of the farmers in a stakeholder network which is really complex and unbalanced in term of power allocation. These results are derived by a deep analysis of the existing literature and by empiric evidences from a case studies mapping. At last, some systematic considerations on the Platforms and the Exchange facilities are proposed, in order to evidence their pivotal role in the integration of data along the supply chain, which seems to be the most effective way to establish a Data-driven Strategy.| File | Dimensione | Formato | |
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https://hdl.handle.net/10589/148597