Central to this initiative was a commitment to harnessing collective intelligence – the notion that diverse perspectives and experiences can yield deeper insights and understanding. By tapping into the extensive knowledge held by individuals managing budgetary programs and actively engaged in policy implementation, the experiment aimed to distill valuable lessons and inform future decision-making processes. 

Employing a multifaceted methodology, the experiment utilized various approaches including Performance Assessment System outcome indicator monitoring, data science techniques, Natural Language Programming (NLP), and principles of collective intelligence. Through the application of advanced analytical tools and methodologies, the team endeavored to identify meaningful patterns and trends within the vast textual data extracted from program evaluations. 

The findings of this text mining experiment provided valuable insights into the challenges and opportunities encountered in public program implementation. By leveraging the collective wisdom of those at the forefront of program delivery, the initiative aimed to foster a deeper understanding of the complexities involved in achieving sustainable development goals. 

Ultimately, this experiment underscored the power of collaboration, innovation, and data-driven decision-making in driving positive change. Through the exploration of new technologies and methodologies, the UNDP Acceleration Lab unlocked the full potential of collective intelligence, paving the way for more effective and impactful public policies and programs. 

This article was originally published at: https://www.undp.org/es/mexico/blog/how-text-mining-can-help-us-learn-about-public-spending-performance