Chroma model for the information-driven decision-making process
- Autores: Xileidys Parra
- Directores de la Tesis: Xavier Tort-Martorell Llabrés (dir. tes.)
- Lectura: En la Universitat Politècnica de Catalunya (UPC) ( España ) en 2018
- Idioma: inglés
- Tribunal Calificador de la Tesis: Lourdes Pozueta Fernández (presid.), Pedro Grima Cintas (secret.), Carmen Ruiz Viñals (voc.)
- Programa de doctorado: Programa de Doctorado en Estadística e Investigación Operativa por la Universidad Politécnica de Catalunya
- Materias:
- Texto completo no disponible (Saber más ...)
- Resumen
The strong, progressive interaction between decision-making processes (DMP) and information technologies has led to breakthroughs in how business is conducted. These developments represent the advent of significant trends for data-driven DMP in terms of increased competitive advantages and business opportunities. However, there is still a gap between technological capabilities and organizational needs due to the fact that the adoption of technology solutions in many companies is faster than their capacity to adapt at the managerial level. Balancing this situation implies a process of self-recognition in which aspects that need to be addressed for the application of better analytical practices must be highlighted. Such evaluation is necessary to embrace more rigorously the use of data and analytics insights within organizations attempting to become information-driven companies. This thesis presents an evaluation methodology that is based on the foundations of maturity models and provides a framework for assessing and ranking the level of organizations' proficiency regarding their information-driven DMP. In this vein, the “Circumplex Hierarchical Representation of Organization Maturity Assessment” (CHROMA) model and its variant, “Simplified Holistic Approach to DMP Evaluation” (SHADE), which is applied to small and medium-sized enterprises (SMEs), provide a novel and holistic approach that embraces the most relevant aspects at the technological and management level to make more objective and better supported decisions. In this respect, the key factors that influence making better-informed decisions are grouped into 5 dimensions: data availability, data quality, data analysis & insights, information use, and decision-making. Both the CHROMA model with its 5X5X5 structure (5 dimensions subdivided into 5 attributes, each classifiable into 5 proficiency levels) and its SHADE variant with a 5X3X5 structure, were conceived to be applied in an organized and systematic way in accordance with this structure in order to characterize the organization’s use of information in DMPs from an uninitiated stage to a completely embedded one. In this sense, its application consists of a methodology that involves interviewing key company personnel plus a brief web questionnaire, and the subsequent evaluation of the dimensions and attributes of the model. Both models were tested in a field study campaign in six family-run SMEs, which were deployed in two blocks. In the first block, three SMEs were analyzed through the application of the CHROMA model. In the second block, the SHADE version of the CHROMA model was applied to the other three SMEs that collaborated with the study. This field study campaign was very significant in terms of reaching a deeper understanding of the extent to which organizations are supporting their decisions with information obtained from data analysis and their willingness to improve accordingly. The findings indicate that, overall, data quality problems are the biggest challenge facing organizations. Moreover, data analysis remains limited, reactive and timid, is mainly focused on senior management and middle managers, and is very scarce at operational levels. Despite this, the findings in the “decision-making” dimension demonstrate that these organizations have, to some extent, been able to leverage their available data to support their decisions. These results confirm that both models are useful for collecting relevant and firsthand information through a close and personalized treatment to consequently identify strengths and weaknesses of specific aspects, thus providing a broader view that leads companies to prioritize improvement actions that could have a meaningful impact on the success and growth of the organization.
