Identifying issues in customer relationship management at Merck–Medco

Identifying issues in customer relationship management at Merck–Medco

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Article ID: iaor2008412
Country: Netherlands
Volume: 42
Issue: 2
Start Page Number: 1116
End Page Number: 1130
Publication Date: Nov 2006
Journal: Decision Support Systems
Authors: , ,
Keywords: artificial intelligence: decision support, management, service
Abstract:

This paper reports the results of a study designed in close collaboration with Merck–Medco to identify key barriers to the success of their customer relationship management. To identify the key factors, we first used focus groups of principal users of the system to brainstorm and generate a list of scenarios and issues. A team of managers, supervisors and customer service representatives then consolidated this list. A 54-item survey was derived from the list and used to collect 1460 responses from the user groups within the company. Data were equally divided into two sets. Exploratory factor analysis was used with the first data set to identify principal factors that explained the majority of problem areas. Structural equation modeling was used with the second data set to further examine and confirm the initial list of factors. The study results suggest a seven-factor 21-item model describing barriers to the success of customer relationship management in terms of ‘standard operating procedure compliance’, ‘accountability and ownership’, ‘callback information content’, ‘customer contact process’, ‘billing issues’, ‘dispensing and replacement process’, and ‘queuing procedure’. These factors explained the majority of customer relationship problems in the company. These measures can be used by the company to plan and monitor remedial response. Evidence of reliability and construct validity is presented for the measurement models and decision-making implications are discussed.

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