Club Excelencia en Gestión
Business Associations
Natural Language Processing (NLP) for Topic Detection in Successful Evaluations
In an increasingly competitive business environment, achieving excellence in management has become a key factor for organizational success. The ability to identify and learn from the most effective practices is crucial to staying ahead and achieving outstanding results.
In this context, Club Excelencia en Gestión, a business association dedicated to promoting excellent, innovative, and sustainable management, faces the challenge of extracting valuable knowledge from the evaluations conducted on its member associates. These evaluations, based on the EFQM Model, offer a rich source of information on the most effective strategies and approaches implemented in various industrial sectors.
Leveraging this vast repository of data could provide significant insights to guide companies in their pursuit of operational excellence. By thoroughly analyzing the common factors driving success in different areas, the Club could identify exemplary, replicable practices, as well as emerging trends and improvement opportunities.
This effort would help strengthen the competitiveness of its associates, including some major companies in the IBEX35, and promote a more robust and innovative business ecosystem.
Challenge
Club Excelencia en Gestión faced the need to efficiently process and synthesize the vast wealth of information resulting from the EFQM evaluations conducted on its associates over the years. These documents contain a large amount of textual information, which can be challenging to process manually and extract relevant insights to draw actionable conclusions that drive transformation and sustainable growth for the associated organizations.
The main challenge was to identify the key topics and concepts present in the highest-scoring evaluations, which could indicate successful practices. Additionally, it was crucial to segment and analyze these findings by sector and organization size to offer personalized and relevant recommendations to the Club Excelencia en Gestión’s associates.
Solution
Foqum has adapted its Natural Language Processing (NLP) algorithms to develop a solution based on advanced techniques that enable Club Excelencia en Gestión to efficiently and scalably overcome this challenge.
Our solution analyzes the complete texts of the EFQM evaluation reports, along with the scores obtained in each criterion and sub-criterion. Using tf-idf vector models and machine learning algorithms, we detect the most relevant topics and concepts present in the highest-scoring evaluations.
These findings are anonymized, segmented by sector, and organization size, allowing Club Excelencia en Gestión to generate detailed market reports and personalized recommendations for its associates. Additionally, the solution is deployed via a REST API, facilitating integration with existing systems and enabling the automatic processing of new evaluations.
The adoption of this solution by Club Excelencia en Gestión represents a significant advancement in its ability to extract value from EFQM evaluations, providing its associates with valuable information and proven strategies to improve their management and achieve business excellence.
