TY  - CONF
A1  - Schröer, Tobias
A1  - Janßen, Jokim
A1  - Schuh, Günther
A1  - Stich, Volker
A2  - Herberger, D.
A2  - Hübner, M.
A2  - Stich, Volker
T1  - Systematisation Approach
T2  - Proceedings of the Conference on Production Systems and Logistics: CPSL 2023
N2  - Current megatrends such as globalisation and digitalisation are increasing complexity, making systems for well-founded and short-term decision support indispensable. A necessary condition for reliable decision-making is high data quality. In practice, it is repeatedly shown that data quality is insufficient, especially in master and transaction data. Moreover, upcoming approaches for data-based decisions consistently raise the required level of data quality. Hence, the importance of handling insufficient data quality is currently and will remain elementary. Since the literature does not systematically consider the possibilities in the case of insufficient data quality, this paper presents a general model and systematic approach for handling those cases in real-world scenarios. The model developed here presents the various possibilities of handling insufficient data quality in a process-based approach as a framework for decision support. The individual aspects of the model are examined in more detail along the process chain from data acquisition to final data processing. Subsequently, the systematic approach is applied and contextualised for production planning and supply chain event management, respectively. Due to their general validity, the results enable companies to manage insufficient data quality systematically.
KW  - Data Quality
KW  - Insufficient Data
KW  - Supply Chain Event Management
KW  - SCEM
KW  - Production Planning
KW  - PPC
KW  - rev
Y1  - 2023
UR  - https://epub.fir.de/frontdoor/index/index/docId/2531
UR  - https://www.repo.uni-hannover.de/handle/123456789/13575
SP  - 469
EP  - 478
PB  - publish-Ing.
CY  - Hannover
ER  -