CHROMA model for the information-driven decision-making process

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.La fuerte y progresiva interacción existente entre el proceso de toma de decisiones (DMP) y las tecnologías de información (IT) ha conllevado a un gran avance que ha repercutido en la forma en que los negocios son conducidos. Estos avances han representado el advenimiento de tendencias significativas para el DMP impulsado por datos en términos de mayores ventajas competitivas y oportunidades de negocio. Sin embargo, existe aún una brecha entre las capacidades tecnológicas y las necesidades de la organización debido a que la adopción de soluciones tecnológicas conducidas por datos en muchas compañías es más rápida que su capacidad de adaptarse a nivel gerencial. Equilibrar este desbalance implica un proceso de auto-reconocimiento donde sean resaltados los aspectos que requieren ser atendidos para la aplicación de mejores prácticas analíticas. Tal evaluación es necesaria dentro de las organizaciones que intentan dar un uso más riguroso a sus datos y conocimientos analíticos para convertirse en compañías impulsadas por información. Esta tesis presenta una metodología de evaluación que basada en los fundamentos de los modelos de madurez proporciona un marco para evaluar y categorizar el nivel de competencia de las organizaciones en el DMP impulsado por información. En tal sentido, el modelo “Circumplex Hierarchical Representation of OrganizationMaturity Assessment” (CHROMA) y su variante “SimplifiedHolistic Approach to DMP Evaluation” (SHADE) para pequeñas y medianas empresas, ofrecen un enfoque novedoso y holístico que abarca los aspectos más relevantes a nivel tecnológico y de gestión para tomar decisiones más objetivas y mejor soportadas, en orden de hacer frente a esta situación. Al respecto, estos factores que influyen en la toma de decisiones mejor informada son agrupados en 5 dimensiones: disponibilidad de datos, calidad de datos, análisis de datos e insights, uso de la información y toma de decisiones. Tanto el modelo CHROMA con su estructura 5£5£5 (5 dimensiones subdivididas en 5 atributos clasificables en 5 niveles de aptitud) como su variante SHADE de estructura 5£3£5, fueron concebidos para ser aplicados de una forma estructurada y sistemática en concordancia con dicha estructura, en orden de caracterizar el uso de la información en el DMP de la organización desde una etapa no iniciada a una completamente embebida. En este orden de ideas, su aplicación consiste de una metodología que involucra realizar entrevistas a personal clave de la compañía más un breve cuestionario web, y la posterior evaluación de las dimensiones y atributos del modelo. Ambos modelos fueron probados en una campaña de estudios de campo en seis empresas familiares pymes, los cuales fueron desplegados en dos bloques. En el primer bloque, fueron analizadas tres pymes a través de la aplicación del modelo CHROMA. En el segundo bloque, se procedió a aplicar el modelo SHADE de CHROMA a las otras tres pymes que colaboraron con el estudio. Esta campaña de estudios de campo resultó muy significativa en términos de alcanzar una comprensión más profunda del grado en el cual las organizaciones están tomando decisiones impulsadas en la información resultante del análisis de datos y su disposición a mejorar en consecuencia. Los hallazgos señalan que, en términos generales, los problemas de calidad de datos constituyen el mayor desafío al que se enfrentan las organizaciones. Asimismo, el análisis de datos continúa siendo limitado, reactivo y poco audaz, principalmente concentrado en la alta gerencia y mandos intermedios, siendo muy escaso a niveles operativos. A pesar de esto, los hallazgos en la dimensión “toma de decisiones” demuestran que estas organizaciones, en cierta medida, han logrado aprovechar sus datos disponibles para soportar sus decisiones. Los resultados confirman que ambos modelos son útiles para recolectar información relevante y de primera mano a través de un trato cercano y personalizado para consecuentemente identificar fortalezas y debilidades de aspectos específicos, proporcionando así una visión más amplia que conduzca a las compañías a priorizar acciones de mejora, que podrían significar el éxito y crecimiento de la organización

Assessment of information-driven decision-making in the SME

The use of analytics in decision -making processes is a key element for organizations to be competitive. However, experience indicates that many organizations still have not managed to fully understand how to use properly the available data for diagnosing, improving a nd controlling processes or modelling, predicting and discovering business opportunities. This situation is even more exaggerated among small and medium enterprises (SMEs). An essential first step for SMEs to start using analytics is a correct assessment o f their decision -making processes and use of data. This will help them understanding their current situation, seeing the potential of adopting analytical practices and decide their approach to analytics. Therefore, the assessment we propose is managerial a nd strategic; thus, it is not aimed at detecting problems such as: errors in the data to make an invoice, not having the correct version of a drawing in the shop or a wrong date in a project plan... Undoubtedly, t hese issues are very important but they are not the objective. The results from applying the proposed assessment tool in several pilot SMEs are expected to serve as the basis for improving the tool and developing a maturity model and a roadmap for improving their proficiency in information -driven d ecision -makingPostprint (published version

Redefinition of the Amplitude Probability Distribution Measuring Function for Electromagnetic Emissions Assessment

The amplitude probability distribution (APD) is a measuring function for assessing electromagnetic disturbances, especially those with a stochastic and time-varying distribution. According to the CISPR 16-1-1, the APD has been defined as the cumulative distribution of the probability of time that the amplitude of disturbance exceeds a specified level. The APD is highly correlated to the bit error rate of digital communication systems, and therefore, a redefinition of radiated emission limits based on the APD would be very meaningful in terms of protecting wireless systems from unintentional interferences. However, establishing emissions requirements based on the current standard APD method can be misleading and not completely traceable metrology-wise. This is because, when analyzing electromagnetic compatibility (EMC) standards, the current specifications for APD measurements are unclear and ill-posed. For instance, the APD is only defined for applications above 1 GHz and with a fixed resolution bandwidth of 1 MHz; both conditions are arbitrarily set due to legacy considerations. Given the capabilities and flexibility of available instrumentation technology, we will propose an improved and more general APD definition accompanied by a calculation algorithm. Moreover, we argue that the APD measurements shall move from a histogram-based approach and implement kernel density estimation instead. We deliver evidence that exemplifies and supports our revised APD definition through numerical simulations. The study closes with a critical discussion about why the APD is so relevant and how it can be redefined to become widely employed as part of EMC assessments.The project (21NRM06 EMC-STD) has received funding from the European Partnership on Metrology, co-financed by the European Union's Horizon Europe Research and Innovation Programme and by the Participating States. EMC Barcelona's project under grant number SNEO-20211223 has received funding from CDTI, which is supported by "Ministerio de Ciencia e Innovación" and financed by the European Union - NextGenerationEU - through the guidelines included in the `Plan de Recuperación, Transformación y Resiliencia". Dr. Azpúrua has received funding from the StandICT.eu 2023 project, financed by the European Union's Horizon Europe - Research and Innovation Programme - under grant agreement No. 951972

Redefinition of the amplitude probability distribution measuring function for electromagnetic emissions assessment

© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.The amplitude probability distribution (APD) is a measuring function for assessing electromagnetic disturbances, especially those with a stochastic and time-varying distribution. According to the CISPR 16-1-1, the APD has been defined as the cumulative distribution of the probability of time that the amplitude of disturbance exceeds a specified level. The APD is highly correlated to the bit error rate of digital communication systems, and therefore, a redefinition of radiated emission limits based on the APD would be very meaningful in terms of protecting wireless systems from unintentional interferences. However, establishing emissions requirements based on the current standard APD method can be misleading and not completely traceable metrology-wise. This is because, when analyzing electromagnetic compatibility (EMC) standards, the current specifications for APD measurements are unclear and ill-posed. For instance, the APD is only defined for applications above 1 GHz and with a fixed resolution bandwidth of 1 MHz; both conditions are arbitrarily set due to legacy considerations. Given the capabilities and flexibility of available instrumentation technology, we will propose an improved and more general APD definition accompanied by a calculation algorithm. Moreover, we argue that the APD measurements shall move from a histogram-based approach and implement kernel density estimation instead. We deliver evidence that exemplifies and supports our revised APD definition through numerical simulations. The study closes with a critical discussion about why the APD is so relevant and how it can be redefined to become widely employed as part of EMC assessments.The project (21NRM06 EMC-STD) has received funding from the European Partnership on Metrology, co-financed by the European Union’s Horizon Europe Research and Innovation Programme and by the Participating States. EMC Barcelona’s project under grant number SNEO-20211223 has received funding from CDTI, which is supported by “Ministerio de Ciencia e Innovaci´on” and financed by the European Union — NextGenerationEU — through the guidelines included in the ‘Plan de Recuperaci´on, Transformaci´on y Resiliencia”. Dr. Azp´urua has received funding from the StandICT.eu 2023 project, financed by the European Union’s Horizon Europe — Research and Innovation Programme — under grant agreement No. 951972.Peer ReviewedPostprint (author's final draft

A maturity model for the information-driven SME

Purpose: This article presents a maturity model for the evaluation of the information-driven decision-making process (DMP) in small and medium enterprises. This model is called “Simplified Holistic Approach to DMP Evaluation (SHADE)”. The SHADE model is based in the “Circumplex Hierarchical Representation of the Organization Maturity Assessment” (CHROMA) framework for characterizing the information-driven DMP in organizations Design/methodology/approach: The CHROMA-SHADE provides a competency evaluation methodology regarding the SME’s use of data for making better-informed decisions. This model groups the main factors influencing the information-driven DMP and classifies them into five dimensions: data availability, data quality, data analysis and insights, information use and decision-making. It addresses these dimensions systematically, delivering a framework for positioning the organization from an uninitiated to a completely embedded stage. The assessment consists of interviews based on a standardized open-ended questionnaire performed to key company personnel followed by an analysis of the answers and their scoring performed by an expert evaluator. Findings: The results of its application indicate this model is well adapted to the SMEs resulting useful for identifying strengths and weaknesses, thereby providing insights for prioritizing improvement actions. Originality/value: The CHROMA-SHADE model follows a novel, holistic approach that embraces the complexities inherent in a multiplicity of factors that, at the technological and management level, converge to enable more objective and better-supported decisions to be made through the intelligent use of information.Peer Reviewe

Chronological evolution of the information-driven decision-making process (1950–2020)

The version of record os available online at:https://doi.org/10.1007/s13132-022-00917-yThe decision-making process (DMP) is essential in organizations and has changed due to multidisciplinary research, greatly infuenced by the progress in information technologies and computational science. This work’s objective is analysing the progressive interaction between DMP and information technologies and the consequent breakthroughs in how business is conducted since 1950 to recent times. Therefore, a chronological review of the information-driven DMP evolvement is presented. The major landmarks that defned how technology infuenced how information is generated, stored, managed, and used for making better decisions, minimizing the uncertainty and gaining knowledge, are covered. The fndings showed that even if current data-driven trends in managerial decision making have led to competitive advantages and business opportunities, there is still a gap between the technological capabilities and the organizational needs. Nowadays, it has been reported that the adoption of technology solutions in many companies is faster than their capacity to adapt at managerial level. Aware of this reality, the “Circumplex Hierarchical Representation of Organization Maturity Assessment” (CHROMA) model has been developed. This tool makes it possible to evaluate whether the management of organizations is making decisions using the available data correctly and optimizing their information systems.Peer ReviewedPostprint (published version

Maturity model for the information-driven SME

Purpose: This article presents a maturity model for the evaluation of the information-driven decision-making process (DMP) in small and medium enterprises. This model is called “Simplified Holistic Approach to DMP Evaluation (SHADE)”. The SHADE model is based in the “Circumplex Hierarchical Representation of the Organization Maturity Assessment” (CHROMA) framework for characterizing the information-driven DMP in organizations Design/methodology/approach: The CHROMA-SHADE provides a competency evaluation methodology regarding the SME’s use of data for making better-informed decisions. This model groups the main factors influencing the information-driven DMP and classifies them into five dimensions: data availability, data quality, data analysis and insights, information use and decision-making. It addresses these dimensions systematically, delivering a framework for positioning the organization from an uninitiated to a completely embedded stage. The assessment consists of interviews based on a standardized open-ended questionnaire performed to key company personnel followed by an analysis of the answers and their scoring performed by an expert evaluator. Findings: The results of its application indicate this model is well adapted to the SMEs resulting useful for identifying strengths and weaknesses, thereby providing insights for prioritizing improvement actions. Originality/value: The CHROMA-SHADE model follows a novel, holistic approach that embraces the complexities inherent in a multiplicity of factors that, at the technological and management level, converge to enable more objective and better-supported decisions to be made through the intelligent use of informatio

CHROMA model for the information-driven decision-making process

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.La fuerte y progresiva interacción existente entre el proceso de toma de decisiones (DMP) y las tecnologías de información (IT) ha conllevado a un gran avance que ha repercutido en la forma en que los negocios son conducidos. Estos avances han representado el advenimiento de tendencias significativas para el DMP impulsado por datos en términos de mayores ventajas competitivas y oportunidades de negocio. Sin embargo, existe aún una brecha entre las capacidades tecnológicas y las necesidades de la organización debido a que la adopción de soluciones tecnológicas conducidas por datos en muchas compañías es más rápida que su capacidad de adaptarse a nivel gerencial. Equilibrar este desbalance implica un proceso de auto-reconocimiento donde sean resaltados los aspectos que requieren ser atendidos para la aplicación de mejores prácticas analíticas. Tal evaluación es necesaria dentro de las organizaciones que intentan dar un uso más riguroso a sus datos y conocimientos analíticos para convertirse en compañías impulsadas por información. Esta tesis presenta una metodología de evaluación que basada en los fundamentos de los modelos de madurez proporciona un marco para evaluar y categorizar el nivel de competencia de las organizaciones en el DMP impulsado por información. En tal sentido, el modelo “Circumplex Hierarchical Representation of OrganizationMaturity Assessment” (CHROMA) y su variante “SimplifiedHolistic Approach to DMP Evaluation” (SHADE) para pequeñas y medianas empresas, ofrecen un enfoque novedoso y holístico que abarca los aspectos más relevantes a nivel tecnológico y de gestión para tomar decisiones más objetivas y mejor soportadas, en orden de hacer frente a esta situación. Al respecto, estos factores que influyen en la toma de decisiones mejor informada son agrupados en 5 dimensiones: disponibilidad de datos, calidad de datos, análisis de datos e insights, uso de la información y toma de decisiones. Tanto el modelo CHROMA con su estructura 5£5£5 (5 dimensiones subdivididas en 5 atributos clasificables en 5 niveles de aptitud) como su variante SHADE de estructura 5£3£5, fueron concebidos para ser aplicados de una forma estructurada y sistemática en concordancia con dicha estructura, en orden de caracterizar el uso de la información en el DMP de la organización desde una etapa no iniciada a una completamente embebida. En este orden de ideas, su aplicación consiste de una metodología que involucra realizar entrevistas a personal clave de la compañía más un breve cuestionario web, y la posterior evaluación de las dimensiones y atributos del modelo. Ambos modelos fueron probados en una campaña de estudios de campo en seis empresas familiares pymes, los cuales fueron desplegados en dos bloques. En el primer bloque, fueron analizadas tres pymes a través de la aplicación del modelo CHROMA. En el segundo bloque, se procedió a aplicar el modelo SHADE de CHROMA a las otras tres pymes que colaboraron con el estudio. Esta campaña de estudios de campo resultó muy significativa en términos de alcanzar una comprensión más profunda del grado en el cual las organizaciones están tomando decisiones impulsadas en la información resultante del análisis de datos y su disposición a mejorar en consecuencia. Los hallazgos señalan que, en términos generales, los problemas de calidad de datos constituyen el mayor desafío al que se enfrentan las organizaciones. Asimismo, el análisis de datos continúa siendo limitado, reactivo y poco audaz, principalmente concentrado en la alta gerencia y mandos intermedios, siendo muy escaso a niveles operativos. A pesar de esto, los hallazgos en la dimensión “toma de decisiones” demuestran que estas organizaciones, en cierta medida, han logrado aprovechar sus datos disponibles para soportar sus decisiones. Los resultados confirman que ambos modelos son útiles para recolectar información relevante y de primera mano a través de un trato cercano y personalizado para consecuentemente identificar fortalezas y debilidades de aspectos específicos, proporcionando así una visión más amplia que conduzca a las compañías a priorizar acciones de mejora, que podrían significar el éxito y crecimiento de la organización

CHROMA model for the information-driven decision-making process

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.La fuerte y progresiva interacción existente entre el proceso de toma de decisiones (DMP) y las tecnologías de información (IT) ha conllevado a un gran avance que ha repercutido en la forma en que los negocios son conducidos. Estos avances han representado el advenimiento de tendencias significativas para el DMP impulsado por datos en términos de mayores ventajas competitivas y oportunidades de negocio. Sin embargo, existe aún una brecha entre las capacidades tecnológicas y las necesidades de la organización debido a que la adopción de soluciones tecnológicas conducidas por datos en muchas compañías es más rápida que su capacidad de adaptarse a nivel gerencial. Equilibrar este desbalance implica un proceso de auto-reconocimiento donde sean resaltados los aspectos que requieren ser atendidos para la aplicación de mejores prácticas analíticas. Tal evaluación es necesaria dentro de las organizaciones que intentan dar un uso más riguroso a sus datos y conocimientos analíticos para convertirse en compañías impulsadas por información. Esta tesis presenta una metodología de evaluación que basada en los fundamentos de los modelos de madurez proporciona un marco para evaluar y categorizar el nivel de competencia de las organizaciones en el DMP impulsado por información. En tal sentido, el modelo “Circumplex Hierarchical Representation of OrganizationMaturity Assessment” (CHROMA) y su variante “SimplifiedHolistic Approach to DMP Evaluation” (SHADE) para pequeñas y medianas empresas, ofrecen un enfoque novedoso y holístico que abarca los aspectos más relevantes a nivel tecnológico y de gestión para tomar decisiones más objetivas y mejor soportadas, en orden de hacer frente a esta situación. Al respecto, estos factores que influyen en la toma de decisiones mejor informada son agrupados en 5 dimensiones: disponibilidad de datos, calidad de datos, análisis de datos e insights, uso de la información y toma de decisiones. Tanto el modelo CHROMA con su estructura 5£5£5 (5 dimensiones subdivididas en 5 atributos clasificables en 5 niveles de aptitud) como su variante SHADE de estructura 5£3£5, fueron concebidos para ser aplicados de una forma estructurada y sistemática en concordancia con dicha estructura, en orden de caracterizar el uso de la información en el DMP de la organización desde una etapa no iniciada a una completamente embebida. En este orden de ideas, su aplicación consiste de una metodología que involucra realizar entrevistas a personal clave de la compañía más un breve cuestionario web, y la posterior evaluación de las dimensiones y atributos del modelo. Ambos modelos fueron probados en una campaña de estudios de campo en seis empresas familiares pymes, los cuales fueron desplegados en dos bloques. En el primer bloque, fueron analizadas tres pymes a través de la aplicación del modelo CHROMA. En el segundo bloque, se procedió a aplicar el modelo SHADE de CHROMA a las otras tres pymes que colaboraron con el estudio. Esta campaña de estudios de campo resultó muy significativa en términos de alcanzar una comprensión más profunda del grado en el cual las organizaciones están tomando decisiones impulsadas en la información resultante del análisis de datos y su disposición a mejorar en consecuencia. Los hallazgos señalan que, en términos generales, los problemas de calidad de datos constituyen el mayor desafío al que se enfrentan las organizaciones. Asimismo, el análisis de datos continúa siendo limitado, reactivo y poco audaz, principalmente concentrado en la alta gerencia y mandos intermedios, siendo muy escaso a niveles operativos. A pesar de esto, los hallazgos en la dimensión “toma de decisiones” demuestran que estas organizaciones, en cierta medida, han logrado aprovechar sus datos disponibles para soportar sus decisiones. Los resultados confirman que ambos modelos son útiles para recolectar información relevante y de primera mano a través de un trato cercano y personalizado para consecuentemente identificar fortalezas y debilidades de aspectos específicos, proporcionando así una visión más amplia que conduzca a las compañías a priorizar acciones de mejora, que podrían significar el éxito y crecimiento de la organización

CHROMA: a maturity model for the information-driven decision-making process

A novel maturity model for the information-driven decision-making process (DMP) in organisations is presented. The 'circumplex hierarchical representation of organisation maturity assessment' (CHROMA) model was developed for evaluating organisations regarding their competence and readiness in using information to support decisions. This model groups the most important informed decision factors into five dimensions data availability, data quality, data analysis and insights, information use and decision-making. The model addresses these dimensions in an organised and systematic way, providing a framework for characterising the organisation's use of information in DMPs from an uninitiated stage to a completely embedded one. This model was tested in a pilot study on three small/medium-sized enterprises. The assessment involves interviewing key company personnel and evaluating the attributes and dimensions of the CHROMA model. Results indicate that the model is useful for identifying strengths and weaknesses, thereby providing insights for prioritising improvement actions.Peer ReviewedPostprint (author's final draft