Skip to main content

LUP Student Papers

LUND UNIVERSITY LIBRARIES

Decision-making under uncertainty - The role of Descriptive, Predictive and Prescriptive Analytics

Stålhammar Holm, Olle LU ; Segui, Felix LU and Weidler, Ingrid LU (2025) FEKH38 20242
Department of Business Administration
Abstract
This study examines how descriptive, predictive, and prescriptive analytics are applied in decision-making during stable operations and disruptive events, focusing on the Swedish food retail sector during the Covid-19 pandemic. Using a qualitative case study approach with semi-structured interviews and pattern-matching analysis, the research reveals key differences in analytics usage. During stable conditions, analytics tools provide reliable insights and forecasts, enabling efficient decision-making. However, during crises, their reliance on historical data and static models limits applicability, emphasizing the critical role of human expertise in recalibrating systems and interpreting incomplete data. The findings highlight the... (More)
This study examines how descriptive, predictive, and prescriptive analytics are applied in decision-making during stable operations and disruptive events, focusing on the Swedish food retail sector during the Covid-19 pandemic. Using a qualitative case study approach with semi-structured interviews and pattern-matching analysis, the research reveals key differences in analytics usage. During stable conditions, analytics tools provide reliable insights and forecasts, enabling efficient decision-making. However, during crises, their reliance on historical data and static models limits applicability, emphasizing the critical role of human expertise in recalibrating systems and interpreting incomplete data. The findings highlight the importance of balancing data-driven tools with human judgment to navigate disruptions effectively. This study contributes to understanding the interplay between analytics and human decision-making and offers practical recommendations for improving organizational resilience in volatile environments. (Less)
Please use this url to cite or link to this publication:
author
Stålhammar Holm, Olle LU ; Segui, Felix LU and Weidler, Ingrid LU
supervisor
organization
course
FEKH38 20242
year
type
M2 - Bachelor Degree
subject
keywords
Descriptive analytics, Predictive analytics, Prescriptive analytics, Decision-making, Disruptive events
language
English
id
9184692
date added to LUP
2025-02-11 13:55:31
date last changed
2025-02-11 13:55:31
@misc{9184692,
  abstract     = {{This study examines how descriptive, predictive, and prescriptive analytics are applied in decision-making during stable operations and disruptive events, focusing on the Swedish food retail sector during the Covid-19 pandemic. Using a qualitative case study approach with semi-structured interviews and pattern-matching analysis, the research reveals key differences in analytics usage. During stable conditions, analytics tools provide reliable insights and forecasts, enabling efficient decision-making. However, during crises, their reliance on historical data and static models limits applicability, emphasizing the critical role of human expertise in recalibrating systems and interpreting incomplete data. The findings highlight the importance of balancing data-driven tools with human judgment to navigate disruptions effectively. This study contributes to understanding the interplay between analytics and human decision-making and offers practical recommendations for improving organizational resilience in volatile environments.}},
  author       = {{Stålhammar Holm, Olle and Segui, Felix and Weidler, Ingrid}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Decision-making under uncertainty - The role of Descriptive, Predictive and Prescriptive Analytics}},
  year         = {{2025}},
}