{"title":"Control and optimization of workforce outsourcing decisions","authors":"Kannan Nilakantan","doi":"10.1093/imaman/dpac007","DOIUrl":null,"url":null,"abstract":"With outsourcing of work having become ubiquitous, and more importantly, given its potential to become controversial, the need for such outsourcing decisions to be drafted carefully, managed effectively and controlled accurately cannot be underscored. In this context, this paper has constructed a mathematical model of organizations with ‘outsource’ employees to study the problem of the monitoring and control of the extent of outsourcing, and the number and distribution of outsource manpower. Control policies for maintaining desired blends of internal and outsource manpower have been mathematically derived, thereby obviating the need for further statistical validation. The cost savings that could be expected to accrue due to outsourcing, as also the problem of optimal outsourcing have been investigated and illustrated with numerical examples. This paper thereby studies a problem of contemporary relevance and importance, and organizations could use the suggested models as a decision-making tool, to generate alternative trade-off scenarios between cost savings due to outsourcing on the one hand, and the need to restrict the extent of outsourcing on the other.","PeriodicalId":56296,"journal":{"name":"IMA Journal of Management Mathematics","volume":"34 2","pages":"307-332"},"PeriodicalIF":1.9000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IMA Journal of Management Mathematics","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10075387/","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MANAGEMENT","Score":null,"Total":0}
引用次数: 0
Abstract
With outsourcing of work having become ubiquitous, and more importantly, given its potential to become controversial, the need for such outsourcing decisions to be drafted carefully, managed effectively and controlled accurately cannot be underscored. In this context, this paper has constructed a mathematical model of organizations with ‘outsource’ employees to study the problem of the monitoring and control of the extent of outsourcing, and the number and distribution of outsource manpower. Control policies for maintaining desired blends of internal and outsource manpower have been mathematically derived, thereby obviating the need for further statistical validation. The cost savings that could be expected to accrue due to outsourcing, as also the problem of optimal outsourcing have been investigated and illustrated with numerical examples. This paper thereby studies a problem of contemporary relevance and importance, and organizations could use the suggested models as a decision-making tool, to generate alternative trade-off scenarios between cost savings due to outsourcing on the one hand, and the need to restrict the extent of outsourcing on the other.
期刊介绍:
The mission of this quarterly journal is to publish mathematical research of the highest quality, impact and relevance that can be directly utilised or have demonstrable potential to be employed by managers in profit, not-for-profit, third party and governmental/public organisations to improve their practices. Thus the research must be quantitative and of the highest quality if it is to be published in the journal. Furthermore, the outcome of the research must be ultimately useful for managers. The journal also publishes novel meta-analyses of the literature, reviews of the "state-of-the art" in a manner that provides new insight, and genuine applications of mathematics to real-world problems in the form of case studies. The journal welcomes papers dealing with topics in Operational Research and Management Science, Operations Management, Decision Sciences, Transportation Science, Marketing Science, Analytics, and Financial and Risk Modelling.