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Artificial intelligence for cooperatives and small agricultural enterprises to improve the efficiency of commercial decisions

Researchers from the UOC are working on optimizing data on billing, international trade, internet traffic and customer segmentation.

Food and Natural Resources

At this turbulent time for the economy, the viability of many companies depends on their commercial efficiency. The huge volume of data they generate is an opportunity to turn this information into knowledge that will help them come up with more efficient and competitive commercial solutions. Researchers at the Universitat Oberta de Catalunya (UOC) are taking part in a new project to develop a comprehensive methodology based on the use of artificial intelligence and business intelligence tools to improve the commercial decision-making processes of small enterprises. The two-year project is being led by the Falset Marçà Agricultural Cooperative in conjunction with Centre Vinícola del Penedès and the Federation of Agricultural Cooperatives of Catalonia, and is funded by the European Agricultural Fund for Rural Development and the Ministry of Agriculture, Livestock, Fisheries and Food of the Government of Catalonia. According to Xavi Domènech, manager of the Falset Marçà Cooperative and a graduate of Computer Engineering from the UOC, "Companies today amass enough data to be able to take much more calculated commercial decisions than they are generally taking. Personalizing their commercial structure and equipping it with rigorous methods and processes is key to guaranteeing their survival. We believe that supporting this process by introducing the intelligence of analytics can be a differentiating factor." The aim of the project is to develop and operate a system that helps to minimize the subjective variables that distort commercial decision-making, hence giving it greater rigour and analytical consistency. "In the business world, we have traditionally worked very intuitively and unsystematically, entrusting much of the sales process to salespeople's own communication skills. This emotionally-based relational approach to sales is very difficult to adapt with good results in a business context in which purchasing has been professionalized and systematized and now includes a very large analytical component," emphasized the cooperatives behind the project. Improved targeting of potential customers The Internet Computing & Systems Optimization (ICSO) group of the Internet Interdisciplinary Institute (IN3) at the UOC, headed by professor at the Faculty of Computer Science, Multimedia and Telecommunications Ángel A. Juan and joined by researchers John Cardona and Diego Oliva, will be responsible for the more technical side of the project, taking advantage of their extensive experience in the research and transfer of data analytics and intelligent algorithms. Ángel A. Juan said: "Our role is to provide support for the digitization process of agricultural enterprises. Specifically, this entails analysing the huge amount of data generated by their e-commerce platforms and, based on the results, develop intelligent algorithms that will help them to better reach their market of potential customers, optimize their digital marketing processes, and efficiently adapt their offering to the specific needs of their target market." The Decision Making project - Comprehensive and circular methodology for making business decisions is developed by the operational group formed by the cooperatives Agrícola Falset-Marçà and Secció de Crèdit, AFALMA, SCCL, who leads the project, Centre Vinícola del Penedès, SCCL and the FCAC, as well as with the UOC's ICSO group for the technological part. This project is co-financed by the European Agricultural Fund for Rural Development (EAFRD) and the Ministry of Agriculture, Livestock, Fisheries and Food of the Government of Catalonia by the Catalan Rural Development Programme 2014-2020's Operation 16.01.01 (Cooperation for Innovation). This UOC research supports Sustainable Development Goal (SDG) 9 industry, innovation and infrastructure.