The agri-food system is facing numerous challenges in recent years, which impact significantly on the companies’ production and profitability. Meanwhile, the consumer evolved, becoming increasingly aware of sustainable food and nutrition choices to safeguard the health. This transformation resulted in the creation of a new target market, which demands to intercept the needs of providing intelligible information associated to the food product. This paper aims of supplying empirical and procedural guidance on this strategy, which is feasible as a result of the digitisation of the agri-food supply chain and technological solutions of the Industry 4.0. It investigated how the use of analytics techniques can improve efficiency in agri-food supply chain data sharing by enabling companies with the quality description of the food product. To this aim, a reasoned procedure was proposed: starting from raw data collected by IoT sensors, several analytics were processed, through mathematical operations that considered the complexity of the data itself and the frequency of measurement. The analytics were converted into a quality scale that classifies the intervals of the variable into quality categories of increasing order. Finally, the analytics and qualitative scales were combined to obtain an overall indicator of product quality. The studied procedure was therefore applied to a case study, by including an Apulian (Italy) company involved in organic olives production. Results of this study represent a way for agri-food companies to increase their awareness on digitalization strategies, focusing on how technologies, big data and analytics could provide insights to increase operational efficiency and consumer communication and how a completely transparent data-driven approach towards the customer could foster new management approaches.