Covid-19 y Business Analytics, ¿un caso asintomático?
The importance of data for decision-making has been higher today than at any other time in history. For this reason, companies have decided to use this data together with the tools provided by Business Analytics (BA) to support decision-making processes to generate value in their organizations. Howe...
- Autores:
-
Freire Tarazona, Santiago Efraín
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2021
- Institución:
- Universidad de los Andes
- Repositorio:
- Séneca: repositorio Uniandes
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uniandes.edu.co:1992/51047
- Acceso en línea:
- http://hdl.handle.net/1992/51047
- Palabra clave:
- Analítica de negocios
Organizaciones
Negocios
COVID-19 (Enfermedad)
Administración
- Rights
- openAccess
- License
- http://creativecommons.org/licenses/by-nc-nd/4.0/
Summary: | The importance of data for decision-making has been higher today than at any other time in history. For this reason, companies have decided to use this data together with the tools provided by Business Analytics (BA) to support decision-making processes to generate value in their organizations. However, the measures taken to combat the COVID-19 pandemic, such as quarantines and social distancing, have radically changed consumer behaviors, this is reflected in the data, which makes it impossible to use some models in the way they were used before the pandemic. Therefore, this document seeks to answer the question of: How has the adaptation process been in the use of Business Analytics (BA), during the pandemic? This is in order to understand, from the case study, the process of adapting Business Analytics in contexts of high uncertainty (COVID-19) in emerging countries and in industries that make intensive use of these tools. In this way, it was concluded that the process has not fundamentally changed, so it could be considered an asymptomatic case, but some additional activities have been included. Specifically, a proposition related to the calibration of the DDDM process is generated and hypotheses are generated about: the speed with which the process is carried out, the new data sources and the necessary new analyzes of the models. In addition, factors were found that have become relevant due to the context of COVID-19, these are the relationship with the real sector of the companies studied and the architecture that supports the DDDM processes. |
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