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  4. A reference model for data-driven sales planning : development of the model's framework and functionality
 
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A reference model for data-driven sales planning : development of the model's framework and functionality

Citation Link: https://doi.org/10.15480/882.3962
Publikationstyp
Conference Paper
Date Issued
2021-12-01
Sprache
English
Author(s)
Büttner, Daniel  
Scheidler, Anne Antonia  
Rabe, Markus  
Herausgeber*innen
Kersten, Wolfgang  orcid-logo
Ringle, Christian M.  orcid-logo
Blecker, Thorsten  orcid-logo
TORE-DOI
10.15480/882.3962
TORE-URI
http://hdl.handle.net/11420/11177
First published in
Proceedings of the Hamburg International Conference of Logistics (HICL)  
Number in series
31
Start Page
441
End Page
476
Citation
Hamburg International Conference of Logistics (HICL) 31: 441-476 (2021)
Contribution to Conference
Hamburg International Conference of Logistics (HICL) 2021  
Publisher Link
https://www.epubli.de/shop/buch/Adapting-to-the-Future-Christian-M-Ringle-Thorsten-Blecker-Wolfgang-Kersten-9783754927700/121489
Publisher
epubli
Peer Reviewed
true
Purpose: Having accurate forecasts of future sales is mandatory for planning Supply Chains and providing the right distribution task resources. The usage of data in forecasting models enables precise planning and supports the company’s competitiveness. This research shows a reference model framework that helps to establish data-driven sales planning in producing companies.
Methodology: The presented framework is derived from theoretical and practical challenges in a company where data-driven sales planning is not accomplished. The scope of the study originates from an industry project, and the developed framework forms the foundation for further research.
Findings: Data-driven sales planning is neither clearly defined nor the industry's norm, though data-driven methods exist for decades. The lack of methodical knowledge, incomplete data, and company characteristics cause diverse sales planning challenges. The research shows the requirements for integrating and advancing data-driven sales planning in companies.
Originality: This study clarifies the role of data-driven sales planning, identifies theoretical and practical challenges, derives requirements for the reference model and its functionality to support the establishment and advancement of data-driven sales planning in companies. The reference model aims for a comprehensive approach to counteract the mentioned challenges and guides the development of company-specific sales planning procedures.
Subjects
Business Analytics
DDC Class
330: Wirtschaft
Publication version
publishedVersion
Lizenz
https://creativecommons.org/licenses/by-sa/4.0/
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