Please use this identifier to cite or link to this item: https://doi.org/10.15480/882.3962
DC FieldValueLanguage
dc.contributor.authorBüttner, Daniel-
dc.contributor.authorScheidler, Anne Antonia-
dc.contributor.authorRabe, Markus-
dc.date.accessioned2021-12-13T10:16:39Z-
dc.date.available2021-12-13T10:16:39Z-
dc.date.issued2021-12-01-
dc.identifier.citationHamburg International Conference of Logistics (HICL) 31: 441-476 (2021)de_DE
dc.identifier.isbn978-3-754927-70-0de_DE
dc.identifier.issn2365-5070de_DE
dc.identifier.urihttp://hdl.handle.net/11420/11177-
dc.description.abstractPurpose: 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.en
dc.language.isoende_DE
dc.publisherepublide_DE
dc.rightsCC BY-SA 4.0de_DE
dc.rights.urihttps://creativecommons.org/licenses/by-sa/4.0/de_DE
dc.subjectBusiness Analyticsde_DE
dc.subject.ddc330: Wirtschaftde_DE
dc.titleA reference model for data-driven sales planning : development of the model's framework and functionalityde_DE
dc.typeinProceedingsde_DE
dc.identifier.doi10.15480/882.3962-
dc.type.dinicontributionToPeriodical-
dcterms.DCMITypeText-
tuhh.identifier.urnurn:nbn:de:gbv:830-882.0161744-
tuhh.oai.showtruede_DE
tuhh.abstract.englishPurpose: 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.de_DE
tuhh.publisher.urlhttps://www.epubli.de/shop/buch/Adapting-to-the-Future-Christian-M-Ringle-Thorsten-Blecker-Wolfgang-Kersten-9783754927700/121489-
tuhh.identifier.doi10.15480/882.3962-
tuhh.type.opusInProceedings (Aufsatz / Paper einer Konferenz etc.)-
tuhh.gvk.hasppnfalse-
tuhh.hasurnfalse-
dc.type.drivercontributionToPeriodical-
dc.type.casraiConference Paper-
tuhh.container.startpage441de_DE
tuhh.container.endpage476de_DE
dc.relation.conferenceHamburg International Conference of Logistics (HICL) 2021de_DE
dc.rights.nationallicensefalsede_DE
tuhh.relation.ispartofseriesProceedings of the Hamburg International Conference of Logistics (HICL)de_DE
tuhh.relation.ispartofseriesnumber31de_DE
local.contributorPerson.editorKersten, Wolfgang-
local.contributorPerson.editorRingle, Christian M.-
local.contributorPerson.editorBlecker, Thorsten-
local.status.inpressfalsede_DE
local.type.versionpublishedVersionde_DE
local.publisher.peerreviewedtruede_DE
datacite.resourceTypeConference Paper-
datacite.resourceTypeGeneralText-
item.seriesrefProceedings of the Hamburg International Conference of Logistics (HICL);31-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.contributorOrcidKersten, Wolfgang-
item.contributorOrcidRingle, Christian M.-
item.contributorOrcidBlecker, Thorsten-
item.openairetypeinProceedings-
item.contributorGNDKersten, Wolfgang-
item.contributorGNDRingle, Christian M.-
item.contributorGNDBlecker, Thorsten-
item.creatorOrcidBüttner, Daniel-
item.creatorOrcidScheidler, Anne Antonia-
item.creatorOrcidRabe, Markus-
item.languageiso639-1en-
item.creatorGNDBüttner, Daniel-
item.creatorGNDScheidler, Anne Antonia-
item.creatorGNDRabe, Markus-
item.fulltextWith Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.tuhhseriesidProceedings of the Hamburg International Conference of Logistics (HICL)-
item.mappedtypeinProceedings-
Appears in Collections:Publications with fulltext
Files in This Item:
File Description SizeFormat
Büttner et al. (2021) - A reference model for data-driven Sales Planning.pdfA reference model for data-driven Sales Planning1,12 MBAdobe PDFView/Open
Thumbnail
Show simple item record

Page view(s)

167
Last Week
3
Last month
checked on Dec 6, 2022

Download(s)

162
checked on Dec 6, 2022

Google ScholarTM

Check

Note about this record

Cite this record

Export

This item is licensed under a Creative Commons License Creative Commons