Application of customer lifetime value model in make-to-order manufacturing

Thomas Brashear Alejandro, Oya I. Tukel, Ashutosh Dixit

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


The applicability of the customer life time value (CLV) concept goes beyond consumer markets. Specifically, the purpose of this paper is to show how a make-to-order manufacturing company in a supply chain can set customer-focus manufacturing strategies using CLV. Data from an integrated steel plant is used to calculate the life time value of customers based on the past value, the potential value, and their loyalty. The past value of a customer is based on the historical data and the future value of a customer is then forecasted. The loyalty index of a customer is determined by survey results. In general, it was found that the CLV for the most valuable customers increases exponentially and the top 28 percent of customers constitute 80 percent of the total value of all customers. This study focuses on make-to-order manufacturing organizations and the three strategies suggested for business process improvement need to be re-evaluated for make-to-stock or mass production. Based on these results, the authors suggest three strategies for business process improvement and revenue growth for the plant. This study constitutes an initial effort to develop a CLV model for make-to-order manufacturing organizations for improving plant performance. The model links customers with not only the front office functions but also with ERP systems. Organizations that are part of value chains can benefit significantly from CLV applications.

Original languageEnglish (US)
Pages (from-to)468-474
Number of pages7
JournalJournal of Business and Industrial Marketing
Issue number6
StatePublished - Jul 26 2013
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Business and International Management
  • Marketing


  • Business improvement
  • Business process improvement
  • Customer lifetime value
  • Make-to-order
  • Manufacturing industries
  • Operations and production management
  • Process management


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