Towards Organization management using exploratory screening and Big Data tests: a case study of the Spanish Red Cross

Rodríguez Ibáñez, Margarita and Muñoz Romero, Sergio and Soguero Ruiz, Cristina and Gimeno Blanes, Francisco Javier and Rojo Álvarez, José Luis (2019). Towards Organization management using exploratory screening and Big Data tests: a case study of the Spanish Red Cross. "Ieee Access", v. 7 ; pp. 80661-80674. ISSN 2169-3536. https://doi.org/10.1109/ACCESS.2019.2923533.

Description

Title: Towards Organization management using exploratory screening and Big Data tests: a case study of the Spanish Red Cross
Author/s:
  • Rodríguez Ibáñez, Margarita
  • Muñoz Romero, Sergio
  • Soguero Ruiz, Cristina
  • Gimeno Blanes, Francisco Javier
  • Rojo Álvarez, José Luis
Item Type: Article
Journal/Publication Title: Ieee Access
Date: 2019
ISSN: 2169-3536
Volume: 7
Subjects:
Freetext Keywords: Big Data, Machine learning, Organization management, Organization efficiency, Prediction model
Faculty: E.T.S. de Ingenieros Informáticos (UPM)
Department: Otro
Creative Commons Licenses: Recognition - No derivative works - Non commercial

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Abstract

With the emergence of information and communication technologies, a large amount of data has turned available for the organizations, which creates expectations on their value and content for management purposes. However, the exploratory analysis of available organizational data based on emerging Big Data technologies are still developing in terms of operative tools for solid and interpretable data description. In this work, we addressed the exploratory analysis of organization databases at early stages where little quantitative information is available about their efficiency. Categorical and metric single-variable tests are proposed and formalized in order to provide a mass criterion to identify regions in forms with clusters of significant variables. Bootstrap resampling techniques are used to provide nonparametric criteria in order to establish easy-to-use statistical tests, so that single-variable tests are represented each on a visual and quantitative statistical plot, whereas all the variables in a given form are jointly visualized in the so-called chromosome plots. More detailed profile plots offer deep comparison knowledge for categorical variables across the organization physical and functional structures, while histogram plots for numerical variables incorporate the statistical significance of the variables under study for preselected Pareto groups. Performance grouping is addressed by identifying two or three groups according to some representative empirical distribution of some convenient grouping feature. The method is applied to perform a Big-Data exploratory analysis on the follow-up forms of Spanish Red Cross, based on the number of interventions and on a by-record basis. Results showed that a simple one-variable blind-knowledge exploratory Big-Data analysis, as the one developed in this paper, offers unbiased comparative graphical and numerical information that characterize organizational dynamics in terms of applied resources, available capacities, and productivity. In particular, the graphical and numerical outputs of the present analysis proved to be a valid tool to isolate the underlying overloaded or under-performing resources in complex organizations. As a consequence, the proposed method allows a systematic and principled way for efficiency analysis in complex organizations, which combined with organizational internal knowledge could leverage and validate efficient decision-making.

Funding Projects

TypeCodeAcronymLeaderTitle
Government of SpainTEC2016-75161-C2-1-RFINALEUniversidad Rey Juan CarlosInvestigación traslacional y transferencia de un nuevo sistema de electrofisiología cardiaca no inavasiva de alta resolución
Government of SpainTEC2016-81900-REDTKERMESUniversidad de ValenciaAvances en métodos núcleo para datos estructurados

More information

Item ID: 67127
DC Identifier: http://oa.upm.es/67127/
OAI Identifier: oai:oa.upm.es:67127
DOI: 10.1109/ACCESS.2019.2923533
Official URL: https://ieeexplore.ieee.org/document/8737934
Deposited by: Memoria Investigacion
Deposited on: 19 May 2021 07:26
Last Modified: 19 May 2021 07:26
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