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Computer Science. 1 (2012) 1700-1705. 2nd World Conference on Information Technology (WCIT-2011). A New Approach for Performance Management in ...
AWERProcedia Information Technology & Computer Science 1 (2012) 1700-1705

2nd World Conference on Information Technology (WCIT-2011)

A New Approach for Performance Management in Banking Industry based on CLV Neda Abdolvand a, Amir Albadvi b* a

PostDoctoral Researcher, Engineering Faculty, Tarbiat Modares University, Chmaran- Al Ahmad Cross road, Tehran, 14115-115, Iran b Professor, Engineering Faculty, Tarbiat Modares University, Chmaran- Al Ahmad Cross road, Tehran, 14115-115, Iran Abstract Performance management has been a significant area of research for both researchers and practitioners for several decades. As an ongoing improvement in performance management, new leading, collaborative, managerial and “close to customers” measures should be introduced based on the literature. This research suggests an integration of customer relationship management system and PMS. Organizations have recognized that building a dynamic substantial relationship with individual customers may lead to sustained business success. Customer has gained more attention as one of the most important and valuable assets for every enterprise. Enterprises attempt to retain customers to increase their value. The novelty of this research is that it proposes the application of CLV as a financial metric in strategic decision making in performance measurement. This research has studied empirically in banking industry in assessing branches performance. In fact, the performance has always exerted significant influence on the bank’s operation. It helps managers in investigating efficiency of various decision making units including the branches of a bank. This research follows a performance assessment approach using data envelopment analysis (DEA) and based on CLV, which can bring value for both customers and shareholders Keywords: Customer Relationship Management (CRM), Customer lifetime Value (CLV), Performance Management, Data Envelopment Analysis (DEA). Selection and peer review under responsibility of Prof. Dr. . ©2012 Academic World Education & Research Center. All rights reserved.

* ADDRESS FOR CORRESPONDENCE : Engineering Faculty, Tarbiat Modares University, Chmaran- Al Ahmad Cross road, Tehran, 14115-115, Iran

E-mail address: [email protected] / Tel.: +98-21-8288-3395

Amir Albadvi & Neda Abdolvand / AWERProcedia Information Technology & Computer Science (2012) 1700-1705

1. Introduction Organizational Performance has always significant influence on the actions of the companies [1]. Enterprises attempt to assess their performance to improve their efficiency and productivity, enhance services, and hence enhance value for customers. Subsequently, Busi and Bitici (2006) believe that PM should be evolved from measurement to management, individual to collaborative and lagging to leading performance measurement. Moreover, various researchers stated that current performance measurement, management systems and available measures are not capable to draw the reality of business performance [1-5]. It means that new approaches to PM are necessary, which define new measures close to customer [1], have a potential to clear the operational status of the business, and facilitate the strategic performance management [6]. In this research, it is attempted to utilize customer relationship management (CRM) outputs in performance management. In CRM, customers’ processes and services are considered as an investment that should result an increase in acquisition, retention, and add-on selling, which in turn leads to increase in customer life-time value (CLV) [7, 8]. CLV fundamentally measures financial return on the customer and the firm relationship [8, 9]. Although various applications have been introduced for the CLV, it has more capability in improving decision- and strategy-making. We believe that CLV can be used as a metric for assessing performance. For this purpose, we have used data envelopment analysis to assess the performance of bank branches and compared it to traditional measures. There are two main reasons to select the banking industry as a case. First, the performance measurement has a critical influence on banking operation. It enables managers to investigate the efficiency of decision-making units including branches. Additionally, measuring CLV requires comprehensive customer data, which is available in banking industry. In the following, at first the benefits of CLV in performance management are reviewed. Then, performance management model based on data envelopment analysis (DEA) is mentioned. In this section, DEA is concisely reviewed, too. The next section presents and discusses the results of the model. Finally, the results and implications of the paper are concluded. 2. PM Evolution and Benefits of CLV as a measure Performance measurement has been evolved from measuring some financial output variables, which assess past performance to evaluating the performance based on various measures, which presents the current status. In other words, managerial accounting has been evolved to include more strategic approaches, which concentrate on identifying, measuring and managing critical financial and nonfinancial stimulus of strategic success and shareholder value. Although performance measurement has evolved during years and now is more than an instrument of control, various researchers stated that current performance measurement and management systems and available measures are not capable to draw the reality of business performance [1-5]. Busi and Bitici (2006) introduced three categories for PM evolution: from measurement to management, individual to collaborative, and lagging to leading performance management. Moreover, it is suggested to define new measures close to customer [1], which have a potential to clear the operational status of the business, and facilitate the strategic performance management [6]. This paper extends the use of CLV in performance measurement from marketing campaigns to collaborative performance of the business. In fact, CLV has been addressed as an output measure instead of ROI. Using CLV brings several advantages including extending the time frame of performance measurement, and encompassing several measures in the format of one measure. Moreover, CLV is a proper measure because of the following reasons. First, CLV is calculated based on cash flow and hence can demonstrate a schema of financial performance of the enterprise. Second, the future value of customers is estimated in CLV calculation; so, it has a capability to predict the 1701

Amir Albadvi & Neda Abdolvand / AWERProcedia Information Technology & Computer Science (2012) 1700-1705

future performance. Finally, CLV is the closest performance measure to the customers, which is mentioned as a requirement in PM literature [6]. 3. DEA & Performance of Bank Branches According to Paradi & Schaffnit (2004), both academics and practitioners are interested in evaluating branches activities. Branches’ assessments have changed from traditional profitability measures to more comprehensive benchmarking programs. Sherman and Gold first used DEA in evaluating branches performance in 1985. Since then, DEA has been used in various researches in evaluating branches performance [10]. Specifications of inputs and outputs of a bank branch vary in DEA efficiency models. For assessing operating efficiency and service quality, inputs are labor, supplies, office space and technology. In profitability efficiency model, input is operating expenses, and output is income generated from different activities [11, 12]. However, determining right inputs and outputs is one of crucial issue in building a model [12] so that it is mentioned as a never ending debate [10]. Selecting appropriate approach can help in determining inputs and outputs. Various approaches have been introduced in the associated literature, including production, intermediation, asset, user-cost, and value-added approaches in which two first are the most often used. In production approach, a bank/branch is considered as a service provider to customer that uses resources (human resource, equipments, and so on) to produce outputs (deposits, loans, and so on). In intermediation approach, a bank/branch is intermediating deposits and loans. In this research, we considered production approach and improved it to a customer-centric valuebased approach. The concept of value has been received growing interest and importance in recent years. From organizational behavior view, the focus of work is creating value using deployment of organizational resources [13]. We extended this view to performance management. In performance management in banking industry, a bank/branch is considered as a value producer for that spends resources and provides services including deposits saving and loans offering. This model (section B of figure 1) is comparable to a traditional model, which is suggested by Decker and Post (2001) as illustrated in section A. The proposed model for assessing performance provides a good benchmark of customer-centric best-practices in the branches, which aims at maximizing the CLV and in turn shareholder value. Indeed, using CLV for assessing performance has several advantages for the enterprises. First, it brings a vision of the enterprise based on the effect of its performance on customer return. Second, it brings possibility to more strategic decision making on improving performance, customer services, process reengineering, etc. Finally, it brings more touchable vision of best practices, which have a potential to direct more value for customers and shareholders, simultaneously. We have experienced an adapted version of this model in assessing branches’ performance of a commercial Iranian bank as it is discussed in next section. 4. Data & Calculation In this research, we need customer data for calculating CLV and branch data for assessing their performance. Our case study looks at an Iranian bank that has recently been privatized. In discussion with bank managers, we decided to narrow the study to 10 branches and 25,000 customers. The customers were excluded if they had been idle for the past 6 months. In the following, data and implemented models for CLV, retention rate, and DEA is described.

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4.1. CLV Data and Calculation Model A common method for calculating CLV is summing current value and net potential value [14, 15]. We used this method. For calculating the potential benefit, we have used retention rate as the probability whether a customer is active, as Gupta and Lehman (2003) offered [9]. 4.2. DEA Inputs, Outputs, and the Model We used an input-oriented model and measure efficiency assuming constant returns to scale (CRS) DEA model for empirical test. For defining inputs of the model, we discussed to bank managers. Indentified inputs data are: cost of personnel and operation, number of computers and tellers, and office space. Moreover, we considered a traditional model. Its outputs are total savings deposits and loans. For running DEA model, we have used DEAOS that is online software. Environment - Rivalry - Demographic - I/O Price. -…

Bank Branch Outputs - Loans - Investments - etc.

Inputs - Employees - Work Space - Computers - etc.

Environment - Rivalry - Demographic - I/O Price -…

Bank Branch

Inputs - Employees - Work Space - Computers

- Loans - Deposits - etc.

CLV

A

B Figure 1- A. Traditional Approach [16], B. Proposed customer-centric Approach

5. Results & discussion Most of the time, it is assumed that branches has no direct control over the amount of services that their customers require. Thus, input-oriented model is a natural choice to assess the branches [10]. Results of traditional and customer-centric models were different (Table 1), as we suggested. In traditional model, 6 out of 10 DMUs were efficient. Three of them had efficiency more than 0.7, and just one DMU efficiency was close to 0.6. In customer-centric model, just two of ten DMU remained efficient. Other DMUs illustrated 5-20 percent efficiency reduction. The two efficient DMUs in customer-centric model are proper references for other DMUs in both traditional and customercentric models. The main reason of the difference between results is that the proposed model also reveals the future efficiency. Therefore, efficient DMUs in proposed models will be also efficient in future; but more effort is necessary by other DMUs to avoid customer churn and increasing customer values. Besides revealing future performance, the proposed model brings three improvements in performance management. First improvement is facilitating performance management rather than measurement. Performance literature shows a movement from measurement to management. As it is mentioned, it is necessary to introduce leading performance measures [2], and close to customers measures [1]. These features are covered by CLV. Clarity of value of customers brings the potential of more accurate strategic decision making in business plans and relationship marketing. It is repeatedly stated that customers are the most valuable assets of an enterprise; therefore, the performance management should shift from returns on investments (ROI) that is a lagging monetary measure, to returns on customers (ROC) [17, 18] that is a leading value-based measure. Finally, as customer 1703

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lifetime value derives shareholders values [13, 19], this performance management model has a potential to align business performance with shareholders values. Table1. Comparing results of numbers of efficient and inefficient DMUs in traditional and customer-centric models

Traditional Customer-Centric

Number of Efficient DMUs 6 2

Number of Inefficient DMUs 4 8

6. Conclusion This research proposes a customer-centric value-based approach for evaluating performance. In this approach customer life time value is considered as an output in the performance management model. It is mentioned that CLV is a proper performance measure because of several reasons including, the capability of predicting customer value, extending the time frame, and being a combination of financial and nonfinancial components. Moreover, the proposed model is value-based which means it considers resources are spent and works are done to produce value from an organizational view. The proposed model has been implemented in banking industry to assess branches’ performance. DEA used for measuring performance of bank branches in both traditional and proposed approaches. The comparison of the results of these two approaches reveals differences in the assessment. The difference could mainly be originated from different in the nature of traditional models and valuebased customer-centric model. The traditional model assesses the past performance. However, the customer-centric model is value-driven and makes it possible to assess the performance of past and predict future performance. It could be caused to change organizational culture to strategic change and continuous improvement. References 1. Folan, P. and J. Browne, A review of performance measurement: Towards performance management. Computers in Industry, 2005. 56(7): p. 663-680. 2. Busi, M. and U.S. Bititci, Collaborative performance management: present gaps and future research. International Journal of Productivity and Performance Management, 2006. 55(1): p. 7-25. 3. Rodriguez, R.R., J.J.A. Saiz, and A.O. Bas, Quantitative relationships between key performance indicators for supporting decision-making processes. Computers in Industry, 2009. 60(2): p. 104-113. 4. Wouters, M., A developmental approach to performance measures--Results from a longitudinal case study. European Management Journal, 2009. 27(1): p. 64-78. 5. Wouters, M. and C. Wilderom, Developing performance-measurement systems as enabling formalization: A longitudinal field study of a logistics department. Accounting, Organizations and Society, 2008. 33(4-5): p. 488-516. 6. Sapri, M., A. Kaka, and B. Alias, Performance Measurement In The Service Business: The Facilities Management Function, in Real Estate Educators and Researchers Association (REER) Seminar 2005: Malasya. 7. Hidalgo, P., et al., Customer retention and price matching: The AFPs case. Journal of Business Research, 2007. 61(6): p. 691-696. 8. Jain, D. and S.S. Singh, Customer Lifetime Value Research in Marketing: A Review and Future Directions. Journal of Interactive Marketing, 2002. 16(2): p. 34-46. 9. Gupta, S. and D.R. Lehman, Customers as assets. Journal of Interactive Marketing, 2003. 17(1): p. 9-24. 10. Paradi, J.C. and C. Schaffnit, Commercial branch performance evaluation and results communication in a Canadian bank-a DEA application. European Journal of Operational Research, 2004. 156(3): p. 719-735. 11. Manandhar, R. and J.C.S. Tang, The evaluation of bank branch performance using data envelopment analysis A framework. Journal of High Technology Management Research, 2002. 13: p. 1-17. 12. Camanho, A. and R.G. Dyson, Cost efficiency measurement with price uncertainty: a DEA application to bank branch assessments. European Journal of Operational Research, 2005. 161(2): p. 432-446. 13. Payne, A. and S. Holt, Diagnosing Customer Value: Integrating the Value Process and Relationship Marketing. British Journal of Management, 2001. 12: p. 159-182.

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14. Hwang, H., T. Jung, and E. Suh, An LTV model and customer segmentation based on customer value: a case study on the wireless telecommunication industry. Expert Systems with Applications, 2004. 26(2): p. 181-188. 15. Kim, S.-Y., et al., Customer segmentation and strategy development based on customer lifetime value: A case study. Expert Systems with Applications, 2006. 31(1): p. 101-107. 16. Dekker, D. and T. Post, A quasi-concave DEA model with an application for bank branch performance evaluation. European Journal of Operational Research, 2001. 132(2): p. 296-311. 17. Peppers, D. and M. Rogers, Hail to the Customer. Sales and Marketing Management, 2005. 157(10): p. 49-52. 18. Peppers, D. and M. Rogers, Return on Customer: A new metric of value creation - Return on investment by itself is not good Enough. Journal of Direct, Data and Digital Marketing Practice, 2006. 7(4): p. 318-331. 19. Bayon, T.S., J. Gutsche, and H. Bauer, Customer Equity Marketing: Touching the Intangible. European Management Journal, 2002. 20(3): p. 213-222.

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