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Title: A reference model for data-driven sales planning : development of the model's framework and functionality
Language: English
Authors: Büttner, Daniel 
Scheidler, Anne Antonia 
Rabe, Markus 
Editor: Kersten, Wolfgang  
Ringle, Christian M.  
Blecker, Thorsten 
Keywords: Business Analytics
Issue Date: 1-Dec-2021
Publisher: epubli
Source: Hamburg International Conference of Logistics (HICL) 31: 441-476 (2021)
Abstract (english): 
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.
Conference: Hamburg International Conference of Logistics (HICL) 2021 
DOI: 10.15480/882.3962
ISBN: 978-3-754927-70-0
ISSN: 2365-5070
Document Type: Chapter/Article (Proceedings)
Peer Reviewed: Yes
License: CC BY-SA 4.0 (Attribution-ShareAlike 4.0) CC BY-SA 4.0 (Attribution-ShareAlike 4.0)
Part of Series: Proceedings of the Hamburg International Conference of Logistics (HICL) 
Volume number: 31
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