FARmAPP: a process-driven solution to prevent and oppose illegal recruitment in agriculture in Northern Italy

Illegal recruitment in agriculture is an issue that affects many different aspects, from the workers’ physical and psychological health conditions to the overall economy. This phenomenon is particularly complex, and many disciplines are trying to face it. In the domain of computer science, one of the possibilities is to improve the systems used by the recruitment/temp agencies. In this study, we propose FARmAPP, a process-driven tool used by the recruitment agencies and farms. FARmAPP was developed using an agile approach with a direct contribution from three different recruitment agencies that operates in three Italian regions. FARmAPP collects and analyzes usage data to monitor “suspect” behaviors from the farms that could lead back to illegal recruitment or workers exploitation. We also created a new custom algorithm to analyze the CVs of the unemployed people to suggest the best candidates for each different job. After the development of FARmAPP, we trained over 80 agencies employees to use and manage FARmAPP autonomously. Their feedback was overall positive, and they stated that FARmAPP is a helpful tool to be included in their system when dealing with agricultural jobs.