Chapter 60 Measurement of Service Efficiency in Different Types of Banking Services: Mass Services, Service Factories, Service Shops, and Professional Services

Markku Tinnila

Aalto University School of Business, Aalto University, Finland

ABSTRACT

As the share of services in economies grow globally, the efficiency of service production becomes cru­cial.

1. INTRODUCTION

It has been maintained that world has turned into one huge service system (Spohrer & Kwan, 2009), as larger share of workforce is engaged in services than in manufacturing. Consequently, the efficiency of services, service processes and service production has become vital in modern

DOI: 10.4018/978-1-4666-6268-1.ch060

economies. Many studies have looked into dif­ferent types of services and provided tools for classifying them for differences. Similarly, service efficiency and service quality have been studied extensively. Still, it is not straightforward to measure the efficiency or inefficiency of a given service. It is too easy to find counter arguments, that as services are different, the differences in efficiency are due to these, and not caused by inefficient operations.

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Many service industries have now a wide range of services available, requiring different approaches to service production. For example, gourmet restaurants and fast food chains operate in the same market, but with widely distinct ap­proaches. The direction of development has been toward more production-line approach to services (Chase & Apte, 2007) embodied by McDonald’s. The wide range of services makes the measurement and comparison of efficiency more challenging. As the question is topical, many approaches for ser­vice efficiency measurement have been presented ranging from strategic alignment to operational process measures. Solutions to this challenge can be found from measurement of manufacturing ef­ficiency. The well-known Product-Process matrix (Hayes & Wheelwright, 1979a, 1979b, 1984) provides a tool for measuring the efficiency of manufacturing of different types of products, as well as, finding the right matches of production processes and products. Accordingly, it has been widely used to recognise efficient manufacturing structures and processes. Also, efficiency metrics and measurement schemes have been proposed (for a review, see e.g. Kemppainen, Vepsalainen, & Tinnila, 2008).

Superficially efficiency measurement in manufacturing or service operations seems to be straightforward. Simple measures of output compared to use of resources used should ac­cordingly be adequate. However, it is easy to confuse effectiveness and efficiency, i.e. ability to produce something, and efficiency in doing the right things. In a study of hotel services Yu and Lee (2009), divide efficiency and effectiveness into productive efficiency, as well as, service and productive effectiveness. Productive efficiency measures the amount of inputs required for a given service output, where service effectiveness measures the relationship between services pro­duced and consumer output, whereas, productive effectiveness measures the ratio between number of customers and input resources.

Also in manufacturing operations the strate­gic fit, i.e. the ability to produce efficiently the right products is a challenge. This challenge is even greater in services, as by nature services are intangible, heterogeneous, inseparable and perishable (IHIP). This reduces the tools for achieving efficiency. Also the very wide range of services poses a challenge, making it even more difficult to analyze efficiency. For example, mea­suring efficiency in a fast food restaurant is more straightforward than determining the efficiency of a financial advisor. In the latter the quality, i.e. value created, of the service, should be taken into account when determining the efficiency. This is not to claim that the quality in a McDonalds is not of importance. Given this challenge, it is no wonder that it has been approached from differ­ent viewpoints. For example, strategic service positioning studies look into finding the right position for services by combining resources in the right way. Manufacturing-related approaches to measurement use measure similar to manufac­turing operations, while financial measurement uses financial tools to analyze the performance.

Banking services are no exception to the dif­ficulty of measuring service efficiency. Despite studies showing that inefficient service production may be in order of 20% of total banking sector costs, the sources of efficiency and inefficiency are somewhat of a black box (Berger & Mester, 1997).

This paper analyses the measurement of ef­ficiency in different types of services and the different approaches used in analyses of service efficiency measurement. Many frameworks have been presented to analyse efficiency and to provide classification of services. Several of these studies propose different ways to classify services, bank­ing services included. One of the most applied is the one suggested by Schmenner (Schmenner, 1986, 2004), where a matrix, called Service process matrix, consisting of four quadrants is proposed. The quadrants present the four basic types of services, called Mass service, Service factory, Service shop and Professional service. This paper uses the classification of Schmenner as basis and analyses the efficiency measures that have been proposed to measure and characterise each quadrant. The focus of analysis is on banking services with its wide service range from internet banking and ATMs to professional investment counselling.

The paper is structured as follows: First, the dif­ferent approaches to measuring service efficiency are introduced. Secondly, the literature of service efficiency measurement is reviewed. Thirdly, the Service process matrix is analysed, followed by in-depth analysis of the four quadrants of the matrix. Fourthly, the different measures used in describing and measuring service efficiency in different services types are reviewed and sum­marised.

2. LITERATURE REVIEW OF APPROACHES TO SERVICE EFFICIENCY MEASUREMENT

In this section we will review the main approaches to determining the efficiency of different types of services, focusing particularly on measures con­nected to efficiency and performance. In addition measures describing and classifying services are reviewed and analyzed.

There are several approaches to measurement of service efficiency and performance ranging from strategic level typologies to straightforward measurement of service processes. From strategic viewpoint many classifications of service types have been proposed (for reviews see Cook, Goh, & Chung, 1999; Liu, Wang, & Lee, 2008; Shafti, Van Der Meer, & Williams, 2007; Tinnila, 2011). However, classifications typically only indirectly analyse measurement of service efficiency. One approach is to look at service process efficiency by analysing the inputs and outputs, as well as, resources and financial performance. Service quality and its impacts on efficiency and per­formance has been the topic of many empirical studies. Some of them also look at the impact of innovations on service efficiency. Furthermore, as services aim at creating value to customers, there have been attempts to measure the value created. Finally, service positioning and efficient service structures have been analysed, as basis for service efficiency.

Table 1 provides review of measurement schemes and approaches, as well as, the measures and metrics used. Table 1 omits the service process matrix of Schmenner and frameworks based on it, as they will be analysed separately.

Table 1. Measurement approaches and schemes for services

continued on following page

Table 1. Continued

Next, we will analyse the measurement ap­proaches reviewed in Table 1 by dividing them according to their focus. The first group of ap­proaches focuses on process efficiency, use and management of resources, as well as, financial performance. The application areas are wide, but there are also examples of their use in bank­ing services. The second group of approaches look at service quality and its role in creating and particularly guaranteeing service efficiency. Service innovations are often connected to qual­ity improvements. Thirdly, the value creation of services and its impact on service efficiency is discussed. Fourthly, frameworks and models for strategic service positioning and recognition of efficient service structures with connected mea­surement schemes are examined.

2.1. Process Efficiency, Resources, and Financial Performance

There are multiple studies focusing on service process efficiency, efficient use of resources and financial performance. We concentrate on approaches and studies with particular relevance on banking services. McAllister and McManus (1993) analyse scale efficiencies in banking, where increasing returns to scale have been found in small banks, while decreasing scale economies in larger banks. This can be compared to manufacturing operations, where generally scale economies are found in larger production units, at least until the optimal manufacturing volumes are found. Mukherjee et al. (2003) measure the efficiency of banking services by a framework consisting of physical and human resources, service quality and performance. Their two-stage framework for measuring service efficiency has as dimensions quality and profitability efficiencies, with mea­sures such as resources, service quality features, and performance. The combined, or overall, ef­ficiency is the financial performance of a bank. Along similar lines, Matousek and Taci (2004) measure cost efficiency and production efficiency in banking services, as do also Bergendahl and Lindblom (2008) with measures such as service efficiency and performance in banks. Portela and Thanassoulis (2007) analyse the efficiency of bank branch offices and note that most studies have been made from production perspective, i.e. bank branch offices are service production units using resources to produce various services. The measure used for efficiency is typically number of transactions in a branch office. Mayer et al. (2003) propose a model for descriptors of service processes consisting of customer encounter satis­faction, including measures such as customisation, amount of interaction, accessibility, and dura­tion. Gliatis and Minis (2007) propose a Service Attribute-Process matrix for classifying services according to attributes and different dimensions of services. The goal is understand better the dif­ferent types of services and connect them to life cycle of services, and consequently to improve efficiency. They list some 30 different attribute measures including type of customer, nature of service delivery, value adding focus in front- or back office, single service or service bundle.

Meepadung et al (2009) use a model combining operating and profit efficiency in banking, while Yu and Lee (2009) analyse the efficiency and effectiveness as separate measures in services. Climent et al (2009) take business process view on bank services by identifying key service pro­cesses for process improvement and consequent improvements in efficiency.

2.2. Service Quality and Innovations

Service quali ty is regarded as important both from customer satisfaction and efficiency viewpoints. Consequently, the impact of quality on service efficiency and performance has been analysed. It is maintained that in service operations quality is more dependent on production efficiency than in manufacturing operations. Also, measurement of service efficiency is regarded as more complicated than efficiency measurement in manufacturing industries. Some researchers see it as a balance between service productivity and service quality (Gronroos & Ojasalo, 2004). They analyse produc­tivity at general level, where process productivity is the relation of input resources transformed to value for customers. This approach emphasizes customer value creation aspects, as opposed to more traditional output of the process. They maintain that manufacturing productivity assumes that changes in input resources do not change the quality of the output (constant quality assumption), whereas, in the context of services, production resources (such as personnel) and systems affect the perceived quality of services. Accordingly they propose a service productivity framework where both service providers and customer’s inputs affect the internal efficiency. Customers of the service perceive the quality of the output, which is mea­sured as external efficiency. The demand of the service affects capacity utilisation and capacity efficiency. Finally service productivity is the sum of internal, external and capacity efficiencies. Along similar lines, Calabrese (2011) presents a more complex measurement scheme where service productivity is dependent on technical efficiency focusing on internal efficiency and service quality, which presents the external efficiency dimension. In addition, the capacity efficiency, i.e. the capa­bility to adapt production to market demands, is seen as important. The service performance matrix proposed has service productivity (internal) and perceived service quality (external) as dimensions. The four quadrants include the high productivity service provider having high service productivity and low service quality, and the failing service provider with low values in both axes, and the high quality service provider with high service quality and low productivity. The fourth quadrant, called efficient service provider, is the optimal position with both high efficiency and quality. Calabrese also recognised the impacts of human and organi­zational resources to the quadrants. Olorunnivo et al (2006) operationalize measurement of service quality in a service factory, while Olorunniwo and Hsu (2006) does the same in mass services. Both studies are of particular interest as they connect the service type and service efficiency measure­ment. Service innovation researchers look into the performance of new services, i.e. the factors that affect the failure of introduction of new services (Alam, 2006). The connection to efficiency is that innovations can be connected to e.g. reposition­ing the service e.g. to lower cost position, new processes or delivery channels, which are closely connected to service efficiency, and use similar or same measures.

2.3. Value Creation in Services

As the goal of services is to create value to customer, one potential measure for efficiency is the amount of value created. As Gronroos (2008) points out, service as business logic facilitates and supports value creation at service customers. However, there are not many studies focusing on the efficiency viewpoint of value creation, and consequently few measures are proposed to evaluate the efficiency of value creations by different service types. Different value configurations, i.e. ways and structures, to create value connected to different types of services have been presented. Particularly the approach of Stabell and Fjeldstad (1998) have been applied to services. Fjeldstad and Sasson (2010) apply this approach when looking into value creation in financial and banking networks.

2.4. Strategic Service Positioning and Efficient Service Structures

Strategic service positioning and the impact of different types of service structures on efficiency have been analysed. In this area there are multiple typologies for positioning services, many of them based on Product-Process matrix of Hayes and Wheelwright (Hayes & Wheelwright, 1979a, 1979b) which provides a way to find the right match between different types of products and manufacturing processes. Along similar lines many frameworks, typically matrices, have been presented to match service types and service production in an efficient way. A service process model (Silvestro, 1999; Silvestro et al., 1992) for positioning services, ranging from professional to mass, uses number of customers per service unit as efficiency measure, combined with variety measures such as contact time and customiza­tion. The matrix framework for strategic service management (Kellogg & Nie, 1995) recognizes efficient combinations of service processes and package structures, where e.g. expert services are connected to unique service packages. The service process analysis (Tinnila & Vepsalainen, 1995) matches service types with service access and delivery channels with resulting efficient service processes. The service positioning matrix (Collier & Meyer, 1998, 2000) combines service encounter activity sequences and the number of different pathways to service in a way, that e.g. expert services have a unique encounter activ­ity sequence combined with many pathways to the service. The industrial service profiling (Johansson & Olhager, 2004) is a framework for positioning. It emphasizes the match between service offering and service process, while they also propose a further development of the same approach (Johansson & Olhager, 2006) in linking product and process matrices for analysing both manufacturing and industrial service operations.

All these positioning frameworks see service efficiency as a result of the right position of a service, and as a combination of different key service elements. As such they do not propose any single measure, or combination of measures, as the correct measure of service efficiency or performance.

3. SERVICE EFFICIENCY IN DIFFERENT SERVICE TYPES

3.1. Service Process Matrix in the Analysis of Basic Service Types

In this section, the classification of the Service Process Matrix by Schmenner is first presented, followed by review of studies applying and extend­ing it. Finally, the matrix is used to analyse different types of services and their pertinent descriptive and efficiency measures are recognised.

The Service Process Matrix consists of four quadrants called Mass service, Service factory, Service shop and Professional service, represent­ing the basic service types. The dimensions of the two axes of the matrix are degree of variation, which include customisation and interaction with customers, as well as, relative throughput time. The throughput time is compared within one industry, and starts with customer entering the service process and ends when the customer is leaving it with a fulfilled service. The throughput time is compared to other companies within the same industry, making it a relative measure. Low throughput time means that the service process takes longer time and high throughput time is faster in throughput.

These dimensions describe the crucial differ­ences between service types. As examples in this paper, we use banking and financial services, res­taurant services, professional and expert services, as well as, budget priced services. Apparently, these classes overlap, as there are professional banking services, as well as, budget priced restau­rants. It should be noted that inconsistent names have been given to the basic service classes by different researchers. However, in this paper we use mainly the terminology of Schmenner to describe these classes.

The four quadrants of the Service Process Matrix differ in terms of service variation and service throughput time. Consequently they can be shortly portrayed in the following way:

Mass services have high relative throughput time (i.e. fast service process) and low degree of variation. These are the typical over-the-counter branch-office services in banking and other office-based services. The volumes are high, but due to labour intensive service production, also the operating costs are significant. Consequently, on most developed nations, this service type is in descendent. This class includes most of the more traditional services, such as branch-office-based banking services, wholesalers, and transport services.

Service factory has a low relative throughput time, i.e. fast service process connected to low degree of variation. The examples include the equivalents of similar large scale manufacturing operations with large number of customers and consequent large service volumes. The typical examples are airlines, transportation services, and hotels.

Service shops are low in relative throughput time associated with high degree of variation. The manufacturing equivalent is job shop manu­facturing with jumbled production flows. The high degree of variation demands typically more manual labour in service production, and also in some cases, higher level in employee know-how. Examples include hospitals, traditional restaurants and repair services. Comparing these with service factories, hospitals require highly skilled personnel of various kinds from surgeons to physiotherapists, while traditional restaurants focus on making the food from ingredients by skilled cooks, as opposed to fast food with prepared ingredients.

Professional service has a high relative throughput time and high degree of variation. The customer contact times are typically long, consisting typically more than one visit to service premises. Also the customer relations are of longer in duration, as professionals, such as medical doc­tors, lawyers, accountants, architects and similar, have their own long-term customers. Often the relations are person-related, i.e. the customer is more connected to an individual professional, than the company. Despite high labour costs and need for knowledgeable personnel, this type of service is not diminishing. Some of the more straightforward professional services may move toward service shops, but customers demanding individual customised services, based on large amount of interaction, cannot be satisfied in any other of the four basic service types.

3.2. Studies Applying and Extending the Service Process Matrix

As the most applied service positioning matrix, the service process matrix by Schmenner (1986, 2004), has been the given impetus for several theoretical and empirical applications. These include the application by Verma (2000) recog­nising the management challenges in all of the four quadrants of the service process matrix. The study tests a large number of measures empirically ranging from physical surroundings, capital deci­sions, scheduling, quality management, employee loyalty to managing growth. Other applications include connection of the matrix with service quality measurements in different service types, i.e. service factories (Olorunniwo et al., 2006) and mass services (Olorunniwo & Hsu, 2006). These studies operationalize the matrix by using a set of service quality dimensions, and also combine some behavioural measures.

The content continuum of Polito and Watson (2004) combines the product-process and ser­vice process matrices to facilitate positioning of product-service bundles, i.e. combinations of product and services which have become typical in business-to-business transactions. The continuum provides measures for classifying bundles, e.g. based on service percentage, customisation, labour intensity, and commodity-like attributes. How­ever, it does not specifically address efficiency of product or service production. Stratman (2008) looks at disaggregation of service production in different service types, particularly back-office functions, which can be off-shored. Based on service process matrix, standardised processes of mass services and service factories are easi­est to decouple and transfer offshore. Similarly, Metters (2008) provides a typology of offshoring and outsourcing services, particularly electronic services. The matrix is based on Schmenner’s quadrants and for each quadrant a strategy for outsourcing is proposed.

An application in public sector services for productivity measurement is the government services matrix of Karwan and Markland (2006), which points out that public organisations are not likely to benefit from automation as much as com­panies. However, some services with high level of customer interaction are close to service factories, and benefit from similar scale economies. Shafti et al. (2007) base their empirical testing of service dimensions and classification framework on the format of service process matrix, and use customer contact and front value added as dimensions. They also test empirically a large number of descriptive service dimensions and productivity management themes to recognize the most relevant for different types of service industries, ranging from airlines and banks to legal services and universities.

An application in service shops (Wang, 2011) analyses the staff management challenges, particu­larly in capital intensive services. The considerable investments in facilities and equipment in service shops like hospitals, repair shops, fitness centres, etc., pose new types of challenges for service companies. Mackelprang et al. (2012) analyse impact of training in the mass services and service shops quadrants. They recognise the impacts of job specific training and skills, quality training (including total quality concept and quality tools), as well as, employee capabilities in understand­ing the organisational strategies, performance in required jobs, and interaction capabilities. These differ considerably in the quadrants.

Next we will analyse each quadrant of the ma­trix separately with examples in different services.

3.3. Mass Services

Mass services are characterised by relatively slow processes and low variation in services. The class includes most of the traditional over-the-counter services. Service volumes are high, sometimes even very high, but as they are labour intensive, also the costs of operation remain at a high level. Typical examples include most of volume services, such as back-of-the-house operations and tradi­tional commercial banking. Besides Schmenner other researchers have looked into mass services. E.g. Tinnila and Vepsalainen (1995) position retail and corporate bank services with branch offices into mass services. These are offered as labour intensive traditional services with a relatively slow process. The personal service in branch offices is often regarded as customised, but although each service encounter is unique, the service process is standardised and consequently belong to mass services.

There has been discussion about the future of mass services, and Schmenner and many other researchers argument that this type of service is less important in the future, as it can be to a large extent replaced with service factories. The high personnel costs drive these services also to digi­tal channels. In banking, branch office services have typically been regarded as mass services. As pointed out by Portela and Thanassoulis (2007), the role of branch offices has been changing from service production toward marketing, i.e. bank of­fices exist to provide the necessary customer touch points for information, advisory services, while the actual service processes are moved over to service factories. Olorunnivo et al. (2006) analyse the role of service quality in different quadrants of the Service process matrix, and find that mass services face challenges in turning services more customer responsive, develop new attractive mar­keting practices, and develop the physical service facilities adequately. The high labour intensity of mass services makes them inflexible to respond to changes in volume, necessitating a large permanent workforce. This also brings along hierarchical organisational structures in service processes for maintaining quality. Climent et al (2009) model the business processes of banks, and among the key processes are private customer service, new customer acceptance, telephone answering, af­fluent customer treatment, etc. These processes are mostly mass processes, and are estimated to occupy 80% of the operative work in banks. Consequently, process improvements include call centres reducing the load to office personnel. In new customer acceptance, the process through­put time has been reduced by 33% in a more service factory-type operation. In mass services the personnel need skills in quality management techniques (Mackelprang et al., 2012) for better measurability and consistency of operations. Also job specific training improves both the per­formance and quality. Typical measures used in mass services include process time, throughput time, repeatability of service encounter sequence, as well as, number of customers and transac­tions, contact time, customisation, orientation of service offering (product/process) product, focus in service production, i.e. value creation, such as front- or back-office.

To sum up, mass services aim at offering vol­ume services with little variation and with high standardisation level. The reliance on labour-inten­sive production mode emphasizes the importance of labour costs and streamlined service processes. Consequently, appropriate efficiency measures are contact time, i.e. time spent in service customers, and number of customers, and transactions in a time unit. The metrics further describing the nature of mass services include standardisation and customisation levels, repeatability of services encounters and service personnel discretion.

3.4. Service Factory

Service factory is a streamlined service process connected to highly standardised services. As the name implies, it is the equivalent of factory operations for best possible efficiency in service production. Schmenner strongly argues that this is the dominant direction of development for many services, particularly high volume services. Ex­amples include services with highly standardised service offering. The proliferation of budget priced services, such as “no frills” or budget-priced airlines, seems to support the argumentation for the growth of service factories. The term service factory has also been used to describe industrial services (Chase, 1991).

Celebrated examples of service factories in­clude McDonalds, Ryan Air and Virgin Airlines. All are prominent in their fields for introducing cut-priced services with very limited service range. Typical is also a well streamlined service production process. McDonalds is well-known for its efficiency research, and development of de­tailed manuals how its main product, hamburgers, should be produced. The service system is tightly designed for service scripts, and documentation is by e.g. video training program and own ham­burger university (Collier & Meyer, 1998). Along similar lines, Ryan Air and Virgin Airlines have changed the business model of airlines by offer­ing basic-only service as standard, and charging extra for everything else. Consequently, a higher degree of self-service is expected from custom­ers, who need to buy the tickets in the internet, pay them, do the check-in themselves, etc. Many traditional airlines have been forced to follow the lead by offering their own versions of budget services. Similar budget versions of services can be found in abundance, e.g. Ikea can be regarded as a budget priced version of furniture store, with streamlined production, supply chain, and warehousing processes.

Can it be maintained that service factory is a prerequisite for creating this new type of budget services? These are exemplified typically with limited product or service range, as compared to more traditional ones. We find this correct in restaurant services, where fast food chains have proliferated. The very name “fast food” reflects the idea of service factory with fast throughput time for customers. The design of service facility, also called servicescape (Bitner, Brown, & Meuter, 2000), reflects this by providing less comfortable seating for fast consumption. The range of offer­ing, i.e. variation, is limited and standardised. Consequently, Buzacott (2000) describes fast food as “take it or leave it”-service with very little customisation for individual customers. Collier and Meyer (1998) look into customer’s service encounter activity sequences and point out that gourmet restaurants are unique, while McDonalds has a very repetitive activity sequence, i.e. service processes, and highly repeatable and standardised service offering. Kellogg and Nie (1995), as well as Collier and Meyer (2000), place fast-food restaurants, such as McDonalds, as service fac­tories, as they have generic service package, with customers influencing the service structure at low level. Similarly, service shops, such as education and healthcare clinics have medium influence and restricted or selective service package.

Typical representative examples of service factories in banking include ATMs and check book services as highly repeatable services and with few pathways, or access channels (Collier & Meyer, 1998, 2000). Tinnila and Vepsalainen (1995) classify also home banking and terminal connections to banks as volume transactions. Within banking services also machine room opera­tions are regarded as service factories (Silvestro, 1999). Measures used in service factories are similar to those in mass services, but also reflect the higher use of organisational resources (Ca­labrese, 2011) and investments in infrastructure, equipment and service systems. Other measures include standardisation degree of service packages with little discretion in service delivery in service factories (Kellogg & Nie, 1995).

To summarise, service factories provide a standard service range with maximum efficiency, relying largely on infrastructure systems providing automation and streamlined processes. This facili­tates novel service types, such as budget-priced versions of many standard services. The metrics reflect the aims of service factories by focusing on e.g. the ratio of output with time and person­nel. The describing measures include automation and self-service levels, range of services, and standardisation of service processes.

3.5. Service Shop

Service shops have higher variation in service range than mass services or service factories. The service process is slower, and typically has higher labour intensity than in service factory. The per­sonnel demands in terms of knowledge and skills are higher, as is understandable in services such as hospitals and higher class restaurants. The division between service factory and service shop is not quite clear cut, as Schmenner (1986) positions restaurants, and to some extent also fast foods, as service shops, although in the later version of the matrix (2004) the latter are positioned in service factory. Although Schmenner proposes similar throughput times for service shops and factories, this is debatable. Typically the larger variety, i.e. larger range of services and more customisation, also require longer customer contact phases and more interaction. In terms of customisation and interaction service shops can be claimed to be “budget” versions of professional services, in the sense that the degree of professionalism, personalisation and customisation is not as high. Typically the personnel do not consist of quite as specialised experts as in truly professional services. The professionalism is more akin to gen­eral expertise within the service area. The service range typically has a degree of standardisation and consequently, services are offered in packages or service bundles.

Wang and Xu (2011) have looked into the challenges of managing different types of ser­vices based on Schmenner’s quadrants, focusing particularly on service shops. They pointed out, that service shops with high interaction needs are more for providing personalized services than standardised ones. The second observation is related to high capital intensity of some service shops with reliance on equipment and facilities to provide the services. This is typical for e.g. hospitals, repair shops and similar. In service shops personnel requires increased level of specific skills related to their tasks (Mackelprang et al., 2012), as the customer requirements have high variation. However, quality management is off lesser importance for efficiency.

In banking, branch offices offer a menu of services by a specialised service system structure, offering e.g. different service points for customers different services, depending on complexity and throughput time of services (Buzacott, 2000). Sil­vestro et al. (1992) place in the service shop class retail banks and some corporate bank services, as well as, personal banking and small business lend­ing (Silvestro, 1999). Typical measures include those reflecting the degree of customisation and standardisation, such as those used by Kellogg and Nie (1995) measuring limited or considerable customisation ofthe service. Most or considerable part of service is standardised, and customers can select from predetermined choices, such as selecting from service modules.

To sum up, service shops meet the customer demands for more customised and personalised services. Reflecting this, the range of services is typically wider, and relies on service personnel knowledge. The measurement of service shops is less straightforward than in mass services and service factories, as many of the measures used a given the value “medium.”Service shops balance labour intensity and requirements of the wide service range and interaction needs. Therefore, direct metrics of the type, output per person, do

not give adequate information. The more descrip­tive measures include customisation and standar­disation, as well as, service range, discretion and customer interaction.

3.6. Professional Service

Professional services have, according to the definition, a high relative throughput time con­nected with high degree of service variation. Professional services are characterized by slow service processes, e.g. a legal “service process” may take months, as compared to minutes of a typical service factory process. Consequently, also the customer relationships are longer, sometimes continuous. The services are very labour intensive, and fulfilled with highly knowledgeable personnel, as exemplified by medical doctors and investment consultants.

The measurement of efficiency in this quad­rant is more complicated than in others. Stabell and Fjeldstad (1998) call this service type value shop, where the value creation is not dependent on typical measures of efficiency, but depends on the customer value created by an expert. Fjeldstad and Sasson (2010) look into bank services, where value created is largely due to large networks of banks, and being embedded in networks increases the value of banking services for customers. In professional services the value creation is based on information asymmetry, i.e. the professional has more expertise than the customer, and this creates value by solving the customers’ problems.

Examples of professional services typically include management consultants, lawyers, medi­cal doctors and similar experts. Also gourmet restaurants are included, as Collier and Meyer (1998) include the celebrated Ritz as having non-repeatable and unique customer encounter. Similarly positioned is Merrill Lynch, as one of the leading financial management and investment advice companies. Other banking and financial examples include corporate banking, investment counselling, notary services and tax accountants. Kellogg and Nie (1995) call this quadrant as ex­pert service, placing accounting and consulting here with high degree of customer influence on services and unique service package.

Measures for professional services include uniqueness of customer encounter and number of pathways built into system, i.e. different ways to access the service. Other similar measures are e.g. customisation of service packages with consider­able discretion in defining the service. Silvestro et al. (1992) point out that professional services have few transactions, are highly customised, have long contact times, have value added at front­office by skilled personnel, and have high level of judgement in meetings the customer needs. The complexity of diagnosing customer problem is used by Buzacott (2000) as a measure, using law firms as examples with top-down service system structure. Typically it is regarded that professional services are more focused on creating value in back-offices, rather than in front-offices (Metters & Vargas, 2000). Calabrese (2011) finds that in professional services, it is mainly the individual human resources that create the value, while in service shops organisational systems and modules are the central sources.

Professional services are at the other end of the service scale as service factories. These provide the most personalised services with highly skilled and professional personnel. The expertise of the staff plays an important role in the value creation to customers. Consequently, measures looking at number of customers per expert are not suitable. In this quadrant, the best measures would reflect the value created as pointed by Stabell and Fjeldstad (1998). However, we currently lack good measures for this. Other measures describing the type of service include contact time, uniqueness, judge­ment level and specialisation level of personnel.

4. SUMMARY AND ANALYSIS OF SERVICE EFFICIENCY MEASURES

Based on the analysis of the four quadrants, as well as, the literature review and analysis of measures used to describe various services and measure their efficiency, we can conclude that the range of measures used is wide. However, within each quadrant there is considerable commonality of measures, as observed by Johansson & Olhager (2004) and Shafti et al. (2007). Johansson and Olhager (2004) present an extensive review of dimensions and measures used in services, ranging from degree of customization to service process structure. They use the measures for describ­ing services in the service profiling framework, analyzing also the four quadrants. Shafti et al. (2007) test the different dimensions empirically to recognize the measures best describing different types of services. Verma (2000) tests empirically the management challenges and their relationships with different service dimensions and descriptive measures. Based on their research and analysis of the four quadrants, Table 2 summarizes the typical and most used measures for efficiency, as well as, descriptive measures for classifying services for their type. Also typical values for the four quadrants are presented.

The measures presented in Table 2 contain the synopsis of measurement of service efficiency, as well as, the measures describing the various services of the four quadrants. The use of these multiple measures facilitates the comparison of efficiency between different services. They can also be used to classify services into the four quadrants and finding the right measures for each of them. For example, the main goals of service factories are shortest possible throughput time, minimum variation and maximum standardisation for greatest possible operational efficiency, while professional services create value to customers by more personalised and knowledge-based service. Therefore the measuring rod for them should also be differing.

4.1. Application of the Measurement Scheme

Next, four basic banking services are represented to illustrate the use of measures in the four quadrants of the matrix. They illustrate the use of descriptive measures for each service. Further operational­ization and testing of measures requires further empirical studies. However, even the illustrative cases show some efficiency related challenges, as e.g. the traditional over-the-counter service has very high infrastructure and labour costs. This explains why this type of service is in decline and is being replaced by more automated self-services. The illustrative case services are:

• Traditional over-the-counter banking ser­vices in branch offices;

• Home banking in the Internet;

• Consumer loan application by service personnel;

• Investment services for professional investors.

Traditional over-the-counter banking services in branch offices represents the typical mass ser­vices relying on service personnel. The service range is relatively large, but the greatest volumes are in very simple transactions, such as money withdrawals. Home banking is one of the most used services over the Internet. It is also an example of the impacts of automation on services, with high infrastructure costs and very low operative costs. Consumer loan applications are a typical service shop, offered in branch offices by skilled personnel. Although consumers can today apply for loans in home banking, many still prefer to do so in traditional channel, where interaction is en­abled. Finally, Investment services for professional investors are among the most complex services offered by highly expert staff. The Table 3 presents the indicative measures for these services.

Traditional over-the-counter banking services in branch offices provide a relatively large range of

Table 2. Measurement scheme for service quadrants

services, which may present challenges, as the per­sonnel needs to know a wide service range, while most of the volumes are focused on a relatively few services. This adds to the staff requirements and increases costs. Also, the labour intensity of the service results in high operative costs, although the service is supported by automated back-office systems. Finally, offering the service over-the- counter in branch offices incurs high infrastructure costs. Consequently, it is hardly surprising that the trend is away from this service type.

Home banking has the highest customer and transaction volumes for services that are highly standardized and automated. The service offers no discretion or variation for differing customer needs, and accordingly, is suitable only to services where the consumer needs are very similar. Home banking also demonstrates the nature of ICT-based

Table 3. Banking services analysed with measures

services, where development and infrastructure costs are high, but running costs very low. Con­sequently, they can be applied only for services with very high volumes.

Consumer loan applications are a typical ser­vice shop operations, where the customer interac­tion face-to-face with personnel is an important part of the service encounter. This incurs relatively high labour costs. However, as these services are in fact consisting of service modules, this enables self-services for customers. Consequently, part of the challenge is to convince consumers to use less labour intensive channels.

Investment services for professional investors have typically long term customer relationships, often at personal level between bank experts and customers. The professionals offer a very high level of expertise, which creates the value of the service. The challenge in the service is thus to retain and motivate the personnel. The very high cost structure necessitates high fees for services, making them to some extent vulnerable to competition.

5. DISCUSSION AND CONCLUSION

The diversity of services has been regarded as an obstacle for proper measurement of their ef­ficiency. Despite this, many classifications and frameworks have been proposed for analysing and measuring service efficiency, either at service or service process levels. Lacking appropriate efficiency measures, many researchers have ap­proached the challenge by proposing metrics and measurement sets describing the type of services. By matching services and resources in a right way, the result would be an efficient service. However, no commonly accepted measurement framework has so far emerged. Consequently, it can be maintained, that straightforward measure­ment of service efficiency is not a simple task, and there is a need for multidimensional measurement frameworks to determine both service efficiency and describe the type of service.

The review of measurement literature reveals a large number of studies analysing service ef­ficiency from different viewpoints, as well as, a wide range of measures used for determining the efficiency of services and describing them. In this study four distinct approaches for measur­ing service efficiency were recognised. The first looks at service process efficiency by analysing process inputs and outputs, in addition to resources and financial performance. The second approach analyses service quality and its impacts on ef­ficiency. There are also several empirical studies within this area, as well as, in service innovations and their impact on service efficiency. Thirdly, value creation in services has turned out to be a topical issue, but there are still challenges in measuring the value created. Fourthly, there are many service positioning frameworks recognising efficient service matches and structures. Among them the Service process matrix by Schmenner is one of the most widespread, with several ap­plications and extensions.

This study contributes by reviewing different studies and by connecting them to the four quad­rants of Schmenner’s framework. Consequently, we find that there is a lot of commonality in the measures used for analysing the efficiency of dif­ferent types of services, as well as, in describing the various service types. Therefore, there are solutions to compare the efficiency of “apples and oranges,” i.e. different service types. Furthermore, the framework of Schmenner has been used for classifying services into four main basic types, or quadrants, which cover the typical service range offered to customers. Each of the main types have been analysed separately for their features, measures used to describe the service, as well as, the measures for analysing efficiency of the ser­vice. The main focus of the analysis has been on banking services, although other types of services have been used to illustrate the commonalities and differences of the four basic service types. This is of academic and managerial interest, as the goals and drivers for each service category are different.

The analysis of the four quadrants facilitates recognition of pertinent measures for each basic type of service. For mass services, aiming at of­fering volume services with little variation and with high standardisation level, the appropriate measures include e.g. standardisation and customi­sation levels, number of customer and transactions in a time unit, as well as, repeatability of service encounters. The very labour-intensive service production emphasizes the significance of labour costs. Service factories offer a standard service range with maximum efficiency, depending on automation and streamlined processes. This ap­proach has facilitated service innovations, such as budget-priced air travels. The measures focus also on standardised service output, and e.g. the ratio of output with time and personnel, automa­tion level, and service range. Service shops offer a wider service range than mass services or service factories, typically with more customised and personalised services relying on service personnel. Measurement includes a variety of measures, as the conflicting demands of personalisation and efficiency make the determination of efficiency complex. Consequently, we need a range of mea­sures, such as labour intensity, service range, interaction needs, and employee discretion and customisation level. Finally, professional services provide the most personalised and customised services. These are based on expertise knowledge of personnel, and the value created in the service is largely dependent on this. Measures such as uniqueness, judgement level and specialisation level of personnel are deemed as most appropriate.

Based on the literature review of measurement studies, and analysis of service belonging to four quadrants, a set of measures is proposed for de­scribing and determining service efficiency. The use of multiple measures facilitates the compari­son of efficiency between different service types. The use of measures is illustrated by analysing four basic banking services, such as, traditional over-the-counter banking services in branch of­fices, home banking in the Internet, consumer loan applications by service personnel, as well as, investment services for professional investors. Further empirical studies and testing are required to validate the proposed measures for determining efficiency in the basic service types.

The measurement of service efficiency is of interest generally, and in banking services particularly. Some services are by nature more efficient than others. The streamlining of these mass services by using the service factory approach has had tremendous impact in banking industry. Compared to traditional over-the-counter services, for example online banking is an incredibly ef­ficient service factory operation. With costs of approximately $0.01 per transaction (Wu & Wu, 2010) no wonder that on-line or home banking is preferred by banks. However, all services can­not, and should not, be transformed into service factories. There are still requirement for more personalised and customised services. However, there are opportunities to streamline, bundle and modularise also more customised services for greater efficiency by using the right measures to guide the transformation.

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This work was previously published in International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), 4(1); edited by Ghazy Assassa and Ahmad Taher Azar, pages 47-67, copyright 2013 by IGI Publishing (an imprint of IGI Global).