Identifying issues in customer relationship management at Merck-Medco
Introduction
There are great expectations for what CRM can accomplish in terms of customer profile, product information, rapid response, predicting customer needs, retaining customers, conducting market research, promoting sale, and reducing cost. However, despite considerable organizational and executive commitments these expectations have not always been met. The perception of a widening gap between the potential of customer relationship management (that is, what it can ideally achieve) and its actual accomplishments has increased the need for better understanding of the nature of the problem and for better measures of factors that influence outcomes. This research was designed to address the perceived gap that exists between the potential of customer representative management and what it actually accomplished in a large U.S. pharmaceutical company. Although this research is company specific, we believe that our findings have relevance to other CRM environments (similar to [20], [32]).
Merck-Medco is a wholly owned subsidiary of Merck and Co. Inc. that specializes in prescription benefit management. Merck focuses on discovering breakthrough medicines and subsequently manufacturing, marketing and selling them. Merck-Medco dispenses medications produced by over 60 manufacturers on behalf of its clients. Merck-Medco clients include major employers, government agencies, health management organizations, and insurance providers. The employees or members of these organizations are provided with a prescription drug benefit that Merck-Medco manages on behalf of its clients. Currently, Merck-Medco represents over 60 million Americans through its various clients and fills over 500 million prescriptions per year.
In this paper, we report the results of a collaborative effort between academe and practice to improve customer relationship management at Merck-Medco. With a few exceptions such as BP and IBM [13], [31], very few studies of this kind are reported in research journals. This study was designed to accomplish two objectives that together will help management develop strategies for increasing CRM success. The first objective was to identify primary factors that result in member dissatisfaction with customer relationship management, more specifically with the call center. The second objective was to produce a reliable and valid set of measures that can be used by the company and others to monitor employee training effectiveness and remedial plans. The methodology, sample, and procedures were decided with these objectives in mind.
The subjects in this study were people who directly interacted with the system on a daily basis to make decisions and serve customers. Through close collaboration with the firm, we collected a large sample that represents over 75% of all user groups. The level of participation was influenced by the users' desire to improve the system and management involvement in the study. In the following section we will review the literature on CRM and clarify the construct. The literature review describes call center issues in a broader perspective of customer relationship management. Section 3 provides the background for Merck-Medco. Section 4 describes research methodology followed by Section 5 that describes data analysis and results. Discussion and conclusions are provided in 6 Discussion, 7 Conclusions, respectively.
Section snippets
Customer relationship management
Customer relationship management incorporates information acquisition, information storage, and decision support functions to provide customized customer service [28]. It enables customer representatives to analyze data and address customer needs in order to promote greater customer satisfaction and retention. It helps organizations to interact with their customers through a variety of means including phone, web, e-mail, and salesperson. Customer representatives can access data on customer
Background
To manage prescription drug benefit, Merck-Medco has made a significant investment in its customer relationship management (CRM) over recent years. Computer applications and system procedures are developed and used to schedule customer service representatives and balance call traffic to ensure speed and service quality. With 60 million customers to support, customer service handles over 40 million calls per year through its network of six call centers. They are located in Tampa (Florida),
Research methods
Measures of service quality have been developed by researchers in marketing [34], [35], information systems [50], and call centers [9]. These measures, however, are more general and do not relate to specific issues such as CSR and queuing process that are important components of the CRM system at Merck-Medco. Thus, we decided to start with a clean slate for identifying and prioritizing problems that caused customer dissatisfaction and were primary concerns of the management at Merck-Medco.
The
Data analysis
There are two objectives in this data analysis. The first is to identify salient factors that affected CRM process at Merck-Medco. This would help the company develop an action plan for improving the process. An exploratory factor analysis is an appropriate tool to identify these salient factors. The second objective is to develop a reliable and valid instrument that can be used to assess the effectiveness of the action plan. A confirmatory factor analysis is recommended to reinforce confidence
Discussion
Organizations continuously rethink their processes in order to improve them by extending the boundaries of information technology application. Practitioners and academics alike have long accepted the delivery of quality service to customers as a success factor. Information technology has played an increasingly important role in the successful delivery of this service to the customer. This study illustrates the complexity of customer relationship management function and employee concerns
Conclusions
This study identifies factors that affect the success of customer relationship management at a US pharmaceutical company, Merck-Medco. Through a close collaboration with the company, we generated a comprehensive list of potential issues, developed a survey, collected company wide data, and used multivariate methods to determine salient factors that caused problem in their CRM. Results of the exploratory factor analysis suggest seven factors (standard operating procedure compliance,
Gholamreza Torkzadeh is Professor and Chair of MIS at the University of Nevada, Las Vegas. He has published on management information systems issues in academic and professional journals including Management Science, Information Systems Research, MIS Quarterly, Communications of the ACM, Decision Sciences, Journal of MIS, Omega, Journal of Operational Research, Information and Management, Structural Equation Modeling, Journal of Knowledge Engineering, Educational and Psychological Measurement,
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Gholamreza Torkzadeh is Professor and Chair of MIS at the University of Nevada, Las Vegas. He has published on management information systems issues in academic and professional journals including Management Science, Information Systems Research, MIS Quarterly, Communications of the ACM, Decision Sciences, Journal of MIS, Omega, Journal of Operational Research, Information and Management, Structural Equation Modeling, Journal of Knowledge Engineering, Educational and Psychological Measurement, Long Range Planning, and others. His current research interests include impacts of information technology, e-commerce success measures, computer self-efficacy, and information systems security. He holds a PhD in Operations Research from The University of Lancaster, UK and is a member of Association for Information Systems, The Institute for Operations Research and the Management Science, and Decision Sciences Institute.
Jerry C. J. Chang is Assistant Professor in the Department of MIS, College of Business, University of Nevada Las Vegas. He has a BS in Oceanography from National Ocean University (Taiwan), an MS in Computer Science from Central Michigan University, an MBA from Texas A and M University, an MS in MoIS and PhD in MIS from the University of Pittsburgh. His research interests include performance measurement, IS strategy, management of IS, self-efficacy, group support systems, human computer interaction, organizational learning, and strategic planning. His articles have appeared in MIS Quarterly, Journal of MIS, Information and Management, Decision Support Systems, Communications of the ACM, DATA BASE, and others.