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Data Driven Decision Making

Mabaso, Obey LU and Sagandira, Conerlious Zechariah LU (2021) INFM10 20211
Department of Informatics
Abstract (Swedish)
Decision making is one of the most critical tasks that can have an impact on organisations’ performance. To rely on decisions, organisations need to consider effective decision making. Hence to make effective decisions, most organisations are moving towards data driven deci-sion making with the aim to increase profits and reduce costs that can lead them to a compet-itive advantage. However, adopting and implementing data driven decision making has been a challenge for most organisations resulting in high failure rate in implementation of data driven decision making. This paper identifies and describes organisational factors that are influential in the implementation of data driven decision making. A qualitative research us-ing seven... (More)
Decision making is one of the most critical tasks that can have an impact on organisations’ performance. To rely on decisions, organisations need to consider effective decision making. Hence to make effective decisions, most organisations are moving towards data driven deci-sion making with the aim to increase profits and reduce costs that can lead them to a compet-itive advantage. However, adopting and implementing data driven decision making has been a challenge for most organisations resulting in high failure rate in implementation of data driven decision making. This paper identifies and describes organisational factors that are influential in the implementation of data driven decision making. A qualitative research us-ing seven semi-structured interviews with data analytics consultants and decision makers was conducted. The conclusion shows that management support, availability of skills, change management, organisational size, industry or sector, perceived value, organisational culture and organisational structure and processes are factors that have an impact in the adoption and implementation of data driven decision making. Thus, these findings can be used by other researchers as a reference for further research on the topic. (Less)
Please use this url to cite or link to this publication:
author
Mabaso, Obey LU and Sagandira, Conerlious Zechariah LU
supervisor
organization
alternative title
Organizational factors influencing the adoption and implementation of Data Driven Decision Making
course
INFM10 20211
year
type
H1 - Master's Degree (One Year)
subject
keywords
Organisational decision making, Big Data, Big Data Analytics, Data Driven Decisions, Technology adoption
report number
INF21-052
language
English
id
9054117
date added to LUP
2021-06-21 12:17:55
date last changed
2021-06-21 12:17:55
@misc{9054117,
  abstract     = {{Decision making is one of the most critical tasks that can have an impact on organisations’ performance. To rely on decisions, organisations need to consider effective decision making. Hence to make effective decisions, most organisations are moving towards data driven deci-sion making with the aim to increase profits and reduce costs that can lead them to a compet-itive advantage. However, adopting and implementing data driven decision making has been a challenge for most organisations resulting in high failure rate in implementation of data driven decision making. This paper identifies and describes organisational factors that are influential in the implementation of data driven decision making. A qualitative research us-ing seven semi-structured interviews with data analytics consultants and decision makers was conducted. The conclusion shows that management support, availability of skills, change management, organisational size, industry or sector, perceived value, organisational culture and organisational structure and processes are factors that have an impact in the adoption and implementation of data driven decision making. Thus, these findings can be used by other researchers as a reference for further research on the topic.}},
  author       = {{Mabaso, Obey and Sagandira, Conerlious Zechariah}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Data Driven Decision Making}},
  year         = {{2021}},
}