Real-time data processing in supply chain management: revealing the uncertainty dilemma

Purpose Particularly in volatile, uncertain, complex and ambiguous (VUCA) business conditions, staff in supply chain management (SCM) look to real-time (RT) data processing to reduce uncertainties. However, based on the premise that data processing can be perfectly mastered, such expectations do not...

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Bibliographic Details
Published in:International journal of physical distribution & logistics management Vol. 49; no. 10; pp. 1003 - 1019
Main Authors: Lechler, Sabrina, Canzaniello, Angelo, Roßmann, Bernhard, von der Gracht, Heiko A, Hartmann, Evi
Format: Journal Article
Language:English
Published: Bradford Emerald Publishing Limited 10.12.2019
Emerald Group Publishing Limited
Subjects:
Complexity
Data processing
Decision making
Delphi method
Digitization
Economic conditions
Employees
Globalization
Industry 4.0
Information processing
Information technology
Logistics
Real time
Reduction
Researchers
Supply chain management
Supply chains
Trends
Uncertainty analysis
Velocity
Delphi survey
Uncertainty
Supply chain management
Real-time data processing
VUCA
ISSN:0960-0035, 1758-664X
Online Access:Get full text
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Summary:Purpose Particularly in volatile, uncertain, complex and ambiguous (VUCA) business conditions, staff in supply chain management (SCM) look to real-time (RT) data processing to reduce uncertainties. However, based on the premise that data processing can be perfectly mastered, such expectations do not reflect reality. The purpose of this paper is to investigate whether RT data processing reduces SCM uncertainties under real-world conditions. Design/methodology/approach Aiming to facilitate communication on the research question, a Delphi expert survey was conducted to identify challenges of RT data processing in SCM operations and to assess whether it does influence the reduction of SCM uncertainty. In total, 14 prospective statements concerning RT data processing in SCM operations were developed and evaluated by 68 SCM and data-science experts. Findings RT data processing was found to have an ambivalent influence on the reduction of SCM complexity and associated uncertainty. Analysis of the data collected from the study participants revealed a new type of uncertainty related to SCM data itself. Originality/value This paper discusses the challenges of gathering relevant, timely and accurate data sets in VUCA environments and creates awareness of the relationship between data-related uncertainty and SCM uncertainty. Thus, it provides valuable insights for practitioners and the basis for further research on this subject.
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ISSN:0960-0035
1758-664X
DOI:10.1108/IJPDLM-12-2017-0398