TY - JOUR
T1 - Exploring data conditions to improve business performance
AU - Grimaldi, Didier
AU - Fernandez, Vicenc
AU - Carrasco, Carlos
N1 - Publisher Copyright:
© 2019 Operational Research Society.
PY - 2021
Y1 - 2021
N2 - Past researches drew from the industrial organization perspective have examined the role of the data to generate competitive advantage. Their analysis show data is a valuable resource that can leverage business partnerships, vertical integration, or diversification. The emergence of data science has created new opportunities to understand better clients’ needs and to manage more efficiently the organizations’ processes. Nevertheless, if data analytics represent an enormous potential, many organizations are still looking the conditions to obtain value from them. Our study contributes to this topical subject analysing the relationship between different combinations of data conditions and the company performance that we measure through the Customer management and Provider operations efficiency. Our methodology is novel compared to previous researches which are based in linear algebra. It is based on the use of a fuzzy-set qualitative comparative analysis (fsQCA) which allows to reveal multiple paths to achieve the possible outcomes. Our results show that the consistency, completeness, and protection of the data along with a data-driven company profile are different possible solutions to a better Customer management and Provider operations efficiency. Our conclusions allow practitioners to uncover the strength of the data in the hopes of solving many of their business performance concerns.
AB - Past researches drew from the industrial organization perspective have examined the role of the data to generate competitive advantage. Their analysis show data is a valuable resource that can leverage business partnerships, vertical integration, or diversification. The emergence of data science has created new opportunities to understand better clients’ needs and to manage more efficiently the organizations’ processes. Nevertheless, if data analytics represent an enormous potential, many organizations are still looking the conditions to obtain value from them. Our study contributes to this topical subject analysing the relationship between different combinations of data conditions and the company performance that we measure through the Customer management and Provider operations efficiency. Our methodology is novel compared to previous researches which are based in linear algebra. It is based on the use of a fuzzy-set qualitative comparative analysis (fsQCA) which allows to reveal multiple paths to achieve the possible outcomes. Our results show that the consistency, completeness, and protection of the data along with a data-driven company profile are different possible solutions to a better Customer management and Provider operations efficiency. Our conclusions allow practitioners to uncover the strength of the data in the hopes of solving many of their business performance concerns.
KW - business performance
KW - competitive analytics
KW - data science
KW - qualitative comparative analysis
UR - http://www.scopus.com/inward/record.url?scp=85064495581&partnerID=8YFLogxK
U2 - 10.1080/01605682.2019.1590136
DO - 10.1080/01605682.2019.1590136
M3 - Article
AN - SCOPUS:85064495581
SN - 0160-5682
VL - 72
SP - 1087
EP - 1098
JO - Journal of the Operational Research Society
JF - Journal of the Operational Research Society
IS - 5
ER -