Optimal configuration of a service delivery network: An application to a financial services provider

Geoffrey A. Meester, Anuj Mehrotra, Harihara Prasad Natarajan, Michael J. Seifert

Research output: Contribution to journalArticle

3 Scopus citations

Abstract

Driven by market pressures, financial service firms are increasingly partnering with independent vendors to create service networks that deliver greater profits while ensuring high service quality. In the management of call center networks, these partnerships are common and form an integral part of the customer care and marketing strategies in the financial services industry. For a financial services firm, configuring such a call center service network entails determining which partners to select and how to distribute service requests among vendors, while incorporating their capabilities, costs, and revenue-generating abilities. Motivated by a problem facing a Fortune 500 financial services provider, we develop and apply a novel mixed integer programming model for the service network configuration problem. Our tactical decision support model effectively accounts for the firm's costs by capturing the impact of service requirements on vendor staffing levels and seat requirements, and permits imposing call routing preferences and auxiliary service costs. We implemented the model and applied it to data from an industry partner. Results suggest that our approach can generate considerable cost savings and substantial additional revenues, while ensuring high service quality. Results based on test instances demonstrate similar savings and outperform two rule-based methods for vendor assignment.

Original languageEnglish (US)
Pages (from-to)725-741
Number of pages17
JournalProduction and Operations Management
Volume19
Issue number6
DOIs
StatePublished - Nov 1 2010

Keywords

  • applied optimization
  • call center management
  • financial services
  • mathematical modeling

ASJC Scopus subject areas

  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Management of Technology and Innovation

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