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Achieving Business Advantages of Big Data Investments

Bagge, Oscar and Lännevall, Johanna (2015) MIO920
Production Management
Abstract
Problem definition The distance between customers and retail companies and their customers has been a problem for quite some time. Seeking to increase the customer understanding is a general quest for many retailers to bridge the gap and become more customer oriented.
As the amount of data keeps growing, the opportunities increase for organisations to become more customer oriented by using technical tools. However, what business advantages different tools for customer insight give lacks of framework.
Purpose This thesis aims to find the business advantages of different kinds of investments in customer insight for retail
© 2015 VI
businesses. The business advantages should bridge the gap between the strategic level and the technological... (More)
Problem definition The distance between customers and retail companies and their customers has been a problem for quite some time. Seeking to increase the customer understanding is a general quest for many retailers to bridge the gap and become more customer oriented.
As the amount of data keeps growing, the opportunities increase for organisations to become more customer oriented by using technical tools. However, what business advantages different tools for customer insight give lacks of framework.
Purpose This thesis aims to find the business advantages of different kinds of investments in customer insight for retail
© 2015 VI
businesses. The business advantages should bridge the gap between the strategic level and the technological nature of the statistical and analytical tools that are used to create deeper understanding of customers. A special assessment of the IBM Action Cluster methodology as a novel method for comparison is also included.
Methodology An exploratory case study with an abductive approach was performed, consisting of nine retail companies. The data collection mostly includes external secondary data but also internal secondary data from IBM, as well as open structure qualitative interviews.
Conclusion Several business advantages were identified in the study but to create structure between the advantages, a framework of capabilities was created that enables each or several advantages. The capabilities work as a translation from the strategic level towards the technological base of methods on the market. It is suggested that the capabilities are achieved in a certain order, making the prediction of the outcome of investment easier when the different cases can be compared and the sought capabilities can be known on beforehand. (Less)
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author
Bagge, Oscar and Lännevall, Johanna
supervisor
organization
course
MIO920
year
type
M1 - University Diploma
subject
keywords
customer loyalty, Action Clusters, clustering, segmentation, business advantages, Big Data, customer insights
other publication id
15/5529
language
English
id
7869303
date added to LUP
2015-09-18 09:59:00
date last changed
2015-09-18 09:59:00
@misc{7869303,
  abstract     = {Problem definition The distance between customers and retail companies and their customers has been a problem for quite some time. Seeking to increase the customer understanding is a general quest for many retailers to bridge the gap and become more customer oriented.
As the amount of data keeps growing, the opportunities increase for organisations to become more customer oriented by using technical tools. However, what business advantages different tools for customer insight give lacks of framework.
Purpose This thesis aims to find the business advantages of different kinds of investments in customer insight for retail
© 2015 VI
businesses. The business advantages should bridge the gap between the strategic level and the technological nature of the statistical and analytical tools that are used to create deeper understanding of customers. A special assessment of the IBM Action Cluster methodology as a novel method for comparison is also included.
Methodology An exploratory case study with an abductive approach was performed, consisting of nine retail companies. The data collection mostly includes external secondary data but also internal secondary data from IBM, as well as open structure qualitative interviews.
Conclusion Several business advantages were identified in the study but to create structure between the advantages, a framework of capabilities was created that enables each or several advantages. The capabilities work as a translation from the strategic level towards the technological base of methods on the market. It is suggested that the capabilities are achieved in a certain order, making the prediction of the outcome of investment easier when the different cases can be compared and the sought capabilities can be known on beforehand.},
  author       = {Bagge, Oscar and Lännevall, Johanna},
  keyword      = {customer loyalty,Action Clusters,clustering,segmentation,business advantages,Big Data,customer insights},
  language     = {eng},
  note         = {Student Paper},
  title        = {Achieving Business Advantages of Big Data Investments},
  year         = {2015},
}