{"title":"Enabling integrated business planning through big data analytics: a case study on sales and operations planning","authors":"Alexa Schlegel, Hendrik Birkel, E. Hartmann","doi":"10.1108/ijpdlm-05-2019-0156","DOIUrl":null,"url":null,"abstract":"PurposeThe purpose of this study is to investigate how big data analytics capabilities (BDAC) enable the implementation of integrated business planning (IBP) – the advanced form of sales and operations planning (S&OP) – by counteracting the increasing information processing requirements.Design/methodology/approachThe research model is grounded in the organizational information processing theory (OIPT). An embedded single case study on a multinational agrochemical company with multiple geographically distinguished sub-units of analysis was conducted. Data were collected in workshops, semistructured interviews as well as direct observations and enriched by secondary data from internal company sources as well as publicly available sources.FindingsThe results show the relevancy of establishing BDAC within an organization to apply IBP by providing empirical evidence of BDA solutions in S&OP. The study highlights how BDAC increase an organization's information processing capacity and consequently enable efficient and effective S&OP. Practical guidance toward the development of tangible, human and intangible BDAC in a particular sequence is given.Originality/valueThis study is the first theoretically grounded, empirical investigation of S&OP implementation journeys under consideration of the impact of BDAC.","PeriodicalId":14251,"journal":{"name":"International Journal of Physical Distribution & Logistics Management","volume":" ","pages":""},"PeriodicalIF":5.9000,"publicationDate":"2020-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1108/ijpdlm-05-2019-0156","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Physical Distribution & Logistics Management","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1108/ijpdlm-05-2019-0156","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 22
Abstract
PurposeThe purpose of this study is to investigate how big data analytics capabilities (BDAC) enable the implementation of integrated business planning (IBP) – the advanced form of sales and operations planning (S&OP) – by counteracting the increasing information processing requirements.Design/methodology/approachThe research model is grounded in the organizational information processing theory (OIPT). An embedded single case study on a multinational agrochemical company with multiple geographically distinguished sub-units of analysis was conducted. Data were collected in workshops, semistructured interviews as well as direct observations and enriched by secondary data from internal company sources as well as publicly available sources.FindingsThe results show the relevancy of establishing BDAC within an organization to apply IBP by providing empirical evidence of BDA solutions in S&OP. The study highlights how BDAC increase an organization's information processing capacity and consequently enable efficient and effective S&OP. Practical guidance toward the development of tangible, human and intangible BDAC in a particular sequence is given.Originality/valueThis study is the first theoretically grounded, empirical investigation of S&OP implementation journeys under consideration of the impact of BDAC.
期刊介绍:
IJPDLM seeks strategically focused, theoretically grounded, empirical and conceptual, quantitative and qualitative, rigorous and relevant, original research studies in logistics, physical distribution and supply chain management operations and associated strategic issues. Quantitatively oriented mathematical and modelling research papers are not suitable for IJPDLM. Desired topics include, but are not limited to: Customer service strategy Omni-channel and multi-channel distribution innovations Order processing and inventory management Implementation of supply chain processes Information and communication technology Sourcing and procurement Risk management and security Personnel recruitment and training Sustainability and environmental Collaboration and integration Global supply chain management and network complexity Information and knowledge management Legal, financial and public policy Retailing, channels and business-to-business management Organizational and human resource development Logistics and SCM education.