Service Co-Production, Customer Efficiency and Market Competition

Customers’ participation in service co-production processes has been increasing with the rapid development of self-service technologies and business models that rely on self-service as the main service delivery channel. However, little is known about how the level of participation of customers in service delivery processes influences the competition among service providers. In this paper, a game-theoretic model is developed to study the competition among service providers when selfservice is an option. The analysis of the equilibria from this model shows that, given a certain level of customer efficiency, the proportion of the service task outsourced to the customer is a decisive factor in the resulting competitive equilibria. In the long run, two extreme formats of service delivery are expected to prevail rather than any mixture of both: either complete employee service or complete self-service. In the two-firm queuing game, we find that both firms are better off when they both deliver their service through self-service. It is also shown that full-service providers dominate the market if firms providing service products featuring self-service fail to have enough market demand at a profitable price. Meanwhile, the limited ranges of customer efficiency and the price for the self-service-only product are shown to be essential conditions for the coexistence of the different types of service providers.

Overcoming the Inherent Dependency of DEA Efficiency Scores: A Bootstrap Approach

This chapter summarizes a multi-year research effort to understand the role of process performance in the overall efficiency of banks. By focusing on the process as the unit of analysis, the authors consider how technology, human resources, and most importantly, the interaction between these factors of production contribute to overall performance. The results of this paper lead to a set of recommendations to managers of financial service organizations as to the most effective approaches for designing and managing their key service delivery processes.

Examining the Contribution of Information Technology Toward Productivity and Profitability in U.S. Retail Banking

There has been much debate on whether or not the investment in Information Technology (IT) provides improvements in productivity and business efficiency. Several studies both at the industry-level and at the firm-level have contributed differing understandings of this phenomenon. Of late, however, firm-level studies, primarily in the manufacturing sector, have shown that there are significant positive contributions from IT investments toward productivity. This study examines the effect of IT investment on both productivity and profitability in the retail banking sector. Using data collected through a major study of retail banking institutions in the United States, this paper concludes that additional investment in IT capital may have no real benefits and may be more of a strategic necessity to stay even with the competition. However, the results indicate that there are substantially high returns to increase in investment in IT labor, and that retail banks need to shift their emphasis in IT investment from capital to labor.

Extensions of Modified DEA

Andersen and Petersen (1993) presented an extension of the basic DEA methodology, called modified DEA, which has the desirable feature of ranking not only the inefficient DMUs, but the e ficient ones as well. However, when their basic approach is extended to the cases of variable returns to scale and non-discretionary inputs, several conceptual problems arise. This paper addresses these problems, and illustrates the proposed extensions to the modified DEA method using data from a major U.S. bank.

What Drives the Performance of Financial Institutions?

The financial sector is one of the most, if not the most significant economic sector in modern societies. In advanced countries, it employs more people than major manufacturing industries combined and accounts for a high percentage of the Gross Domestic Product. But the financial services sector also plays a large indirect role in national economies. The financial sector mobilizes savings and allocates credit across space and time, and enables firms and households to cope with uncertainties by hedging, pooling, sharing and pricing risks. This ultimately improves the quantity and quality of real investments and increases income per capita and raises standards of living. Today financial institutions are experiencing unprecedented change in a competitive global environment. Economies of scale that lead to more integrated automation lead to further economies of scope. Technological innovation adds competitive pressures, and provides opportunities for new non-traditional providers. Consumers themselves may be the strongest force of change in the financial services industry since their needs are evolving quickly. Banking institutions are being transformed from financial intermediaries to retail service providers - they now formulate products for clients or intermediaries, sell and service a range of products to customers and also provide the support functions needed for the successful execution of its primary activities. The authors ask how they can measure performance of a financial institution in this changing landscape? Traditional productivity measures are difficult to compute and tell us less than they used to. The authors also seek to identify what drives performance and identify three dimensions of performance drivers to explore: strategy; execution of strategy; and the environment. To begin, the authors define performance to mean economic performance as measured by financial indicators. Quality of services and effective risk management help explain strong performance levels. Strategic decisions that affect an institution's success involve product mix, client mix, geographical location, and distribution channels. In terms of strategy execution, the authors cite x-efficiency, human resource management, use of technology, process design, and the successful alignment of all these components as important factors in successful firm performance. Creating the right technology environment also has a significant impact on performance. The remainder of this paper summarizes the fifteen chapters of a book edited by the authors on performance and its drivers. The book is divided into three section: General; Drivers of Performance; and Environmental Drivers of Performance. There are also two chapters at the end that discuss performance and risk management. The authors then briefly discuss possible future research directions, including the relationship between operational efficiency and quality of services, the balance between risk management and retail services in bank activities, and study of interorganizational issues.

Projections onto Efficient Frontiers: Theoretical and Computational Extensions to DEA

Data Envelopment Analysis (DEA) has been widely studied in the literature since its inception in 1978 and is a key analytical technique used in Wharton's performance analysis for retail delivery systems. The methodology behind the classical DEA, the oriented method, is to hold inputs (outputs) constant and to determine how much of an improvement in the output (input) dimensions is necessary in order to become efficient. The authors extend this methodology in two substantive ways. First, a method is developed that determines the shortest projection from an inefficient DMU to the efficient frontier in both the input and output space simultaneously, and second, introduces the notion of the "observable" frontier and its subsequent projection. The observable frontier is the portion of the frontier that has been experienced by other DMUs, and thus the projection onto this portion of the frontier guarantees a recommendation that has already been demonstrated by an existing DMU or a convex combination of existing DMUs. A numerical example is used to illustrate the importance of these two methodological extensions.

Designing the Future of Banking: Lessons Learned from the Trenches

This case study in retail banking reviews the work of a Wharton School research team which has been tracking the process of change at one of the larger American commercial banks. The bank is referred to by the pseudonym "National Bank." The team's research focuses on how a bank chooses what changes to make and how to implement changes as new technologies, increasing competition, and more demanding customers force it to rethink product offerings and distribution channel design. In the case of "National," these forces resulted in a massive re-engineering effort designed to restructure the branch delivery system. The goal of the redesign was to streamline branch processes and relocate many administrative tasks and routine servicing of accounts to centralized locations. The physical layout of branches was changed so customers would be encouraged to use ATMs and call centers rather than consult with branch employees. Branch employees' efforts were to be directed toward sales rather than service and information systems and call centers were expanded. As pilot experiments developed and the project matured, the bank's initial focus on changes in physical layout of branches, information systems, and design of key business processes gave way to focus on changes in key jobs in the branch systems, human resource practices that supported these jobs, and on employees' reactions to the changes. As these changes were implemented, several problems arose and were addressed. First, rural branches in the early pilots felt that the new changes were inappropriate for their market, leading to a decision to abandon the original model of standardization across the entire system. Second, implementation of new technology proved a slower process than had been expected. Third, branch employees often found it difficult to successfully refocus on sales rather than service. Fourth, some customers were unhappy with changes that routed all their calls to a centralized location rather than to the their local branch. Finally, it was difficult to implement the human resource practices necessary to support the new organization. New position levels changed employee expectations of moving up in the hierarchy and caused some internal dissatisfaction and confusion. Employees feared layoffs. In dealing with these problems, a second pilot redesign was tested in urban and suburban markets, incorporating a number of process modifications to address these issues. New challenges have arisen, including introducing the changes to branches that have been acquired recently through mergers and acquisitions and introducing standardized innovations within a decentralized management system. These and a range of human resource issues continue to be addressed by the team. Despite the many challenges to implementing an effective new delivery paradigm at National, a number of the early pilots have demonstrated success in moving routine transactions to more official channels, while achieving the goals of increased sales and customer satisfaction. As a result of their ongoing analysis of National's redesign process, the authors have identified six key factors for success: Have a good phone center in place early and believe in it as a critical component of retail service delivery; Acknowledge the importance of human resource issues; Not only acknowledge but address the human resource issues early and clearly; Clarify employees' roles and develop new skills when needed; Not all employees need the same kinds of commitment; Be ready and willing to adapt your model, but be confident to resist attempts to maintain the status quo for the wrong reasons.

Computing Performance Measures in a Multi-Class Multi-Resource Processor-Shared Loss System

This paper develops methods to compute performance measures in a specific type of loss system with multiple classes of customers sharing the same processor. Such systems arise in the modeling of a call center, where the performance measures of interest are blocking the probability of a call and the reneging probability of customers that are put on hold. Expressions for these performance measures have been derived in previous work by the authors. Given the difficulty of computing these performance measures for realistic systems, this paper proposes two different approaches to simplify this computation. The first method introduces the idea of multi-dimensional convolutions, and uses this approach to compute exact blocking and reneging probabilities. The second method establishes an adaptation of the Monte Carlo summation technique in order to obtain good estimates of blocking and reneging probabilities in large systems along with their associated confidence intervals.Queuing; loss system; processor sharing; computational analysis; approximation

Measuring Aggregate Process Performance Using AHP

When one undertakes a benchmarking study, it is quite typical to collect performance data on a set of business processes from a variety of organizations. While one can compare efficiency on a process-by-process level, how can one compare the overall efficiency of one organization versus another using this process-level data? This note presents a methodology that combines tournament ranking and AHP approaches to create a ranking scheme that deals explicitly with missing data and ties in the tournament scheme.AHP, Benchmarking, Process Efficiency

To Sell or Not To Sell: Determining the Tradeoffs between Service and Sales in Retail Banking Phone Centers

Throughout the financial services industry, the call center is being recognized as a critical delivery channel, helping firms to keep existing customers, expand their business, and control costs. For banks, call centers provide a cost effective means of servicing in customer requests, and are essential in retaining customers. The traditional role of the call center as a question and answer base for the customer is still a strong motivator for their existence, There is, however, a growing tendency to blend sales related activities with traditional transaction based activities at a financial service firm's phone center. Institutions view the opportunity to sell additional products as the key to a successful phone center operation. While service-oriented businesses in other sectors of the economy are experiencing a similar proliferation in call centers, the dichotomy of a service center and a sales center is much more apparent in banking. Other sectors do not fully blend service and sales in the call center operation as fully as is the desire of financial services firms. The move to sales elsewhere in the financial services industry has been ongoing for some time. The last decade has seen a growing number of banks implementing cross-sell programs across their branch networks in an effort to become higher profit, sales-driven organizations that leverage the delivery system expense structure. Today, these sales efforts in the branches are being extended to alternative delivery channels, a major one of which is the phone center. Lack of management focus, poor hiring practices, lack of training, ineffective organization for marketing, poor service, and not knowing customers or products are only a selection of some of the barriers between resources and sales in banking that have been documented. This paper identifies some of these roadblocks in the context of retail banking phone centers. The authors show that the nature of phone center operations makes them extremely susceptible to the increasing and changing resource needs of a sales organization. The authors provide a snapshot of retail banking phone centers, a review of related literature, and then present an analytical approach to characterize the tradeoffs between service and sales in phone centers. The situation at a specific phone center is described and analyzed. The authors demonstrate that cross-selling costs. In addition to its visible costs, such as training and technology, cross-selling is shown to have detrimental effects on customer service because of the additional burdens and operational load it creates on the system. With a move to more selling, capacity needs sharply increase in terms of customer service representatives and information processing resources. These capacity implications can be easily overlooked, since they are less visible than what one would expects to encounter. The authors show how restaffing can overcome some of the congestion related problems induced by additional sales activity. The authors use a performance model described in the paper in conjunction with an optimization model to determine economically optimal staffing levels for call centers. However, they note that staffing is not the only factor to be considered. Design of customer request processes and human resource practices that support the design are equally important in determining the success of a cross-sell program. The authors intend a second phase of this study a detailed filed study of call center operations across the entire financial services industry.