Business Process Reengineering and Measuring of Company ...Company Operations Efﬁciency ... and methods such as just-in-time manufacture, total quality management (TQM), continuous

March 15, 2010 14:44 WSPC/Trim Size: 9.75in x 6.5in SPI-b778 b778-ch06

Chapter 6

Business Process Reengineering and Measuring ofCompany Operations Efficiency

NATASA VUJICA HERZOG

Faculty of Mechanical Engineering, University of MariborLaboratory for Production and Operations Management

Smetanova ulica 17, SI 2000 Maribor, [email protected]

The main purpose of the presented research is to contribute to a better understanding ofbusiness process reengineering (BPR), supported with performance measurement (PM)indicators with the purpose to improve company operations efficiency. Existing literature onthe subject warns about deficiencies in the concept of BPR, which can be extremely efficientwith its radical workings. The concept of BPR should be studied in connection with thelogical supplementary areas: manufacturing strategy and, on the other hand, performanceindicators, meant for selected manufacturing strategy and BPR performance verification.BPR and PM literature is based primarily on case studies and there is a lack of rigorouswide-ranging empirical research covering all its aspects. This chapter presents the resultsof a survey research carried out in 73 medium- and large-sized Slovenian manufacturingcompanies. Seven crucial areas were identified based on a synthesis of PM literature, whichmust be practiced to achieve effective operations: cost, quality, time, flexibility, reliability,customer satisfaction, and human resources. Variables have been constructed within theseareas, using Likert scales, and statistical validity, and reliability analyses.

Keywords: Business process reengineering; process management; performancemeasurement; survey research.

1. Introduction

Over the last 15 years, modes of operation in both manufacturing and service compa-nies have changed considerably. We could even say that today the most importantquality for a company which wants to remain successful and competitive is theability to adapt to constant changes in the global environment. Business ProcessReengineering (BPR) is classified by some theoreticians, and even practitioners,as a manufacturing paradigm, which stems from competitive environment and iscommonly known as lean manufacturing, a concept of world-class manufacturing,agile manufacturing, and methods such as just-in-time manufacture, total qualitymanagement (TQM), continuous process improvement, and concurrent engineer-ing. However, BPR is much more than just one of modern manufacture paradigms.

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To understand the true meaning of restructuring, we must examine facts whichreach far back into the past.

In 1776, Adam Smith, who was actually a philosopher, economist, and radicalthinker of that time, in his book titled The Wealth of Nations explained a principlethat he called the division and specialization of labor which resulted in the produc-tivity of a pin factory increasing a hundredfold. Smith’s principles were improved onin the field of manufacturing, especially by Henry Ford in the automotive industry,and by Alfred Sloan from General Motors in the field of management.

Many times later, when companies and especially their management instru-ments become oversized and therefore almost impossible to manage, Hammer andChampy (1990, 1993) promoted their idea about the need for radical rethinking.They pointed out that the way of thinking, caused by Smith’s central idea — divisionand specialization of labor — and as a consequence its fragmentation, will not beenough to reach competitive advantage and efficiency in the future. The authorsalso examined in detail and defined the weak points which stem from division oflabor, but have, at the same time, given clear guidelines on how to operate in thefuture. The most important idea of their work is that those processes divided for 200years must be united again and restructured, which will make them considerablydifferent from tradition.

By focusing on processes and their restructuring, they turned upside down theindustrial model which is based on a principle that workers have little knowledgeand little time or abilities for additional education, which caused their tasks to beas simple as possible. On the other hand, simple tasks demanded complex-linkingprocesses. To satisfy present demands for quality, flexibility, low cost, reliablydelivery, and customer satisfaction, the processes have to be as simple as possible.The consequences of these requirements are apparent in the design of processes,and the form of organization.

The field of BPR will be presented in connection with logically complementaryfields, the choice of manufacturing strategy, and on the other hand, indicators whichare intended for verifying the efficiency of the chosen strategies. We discoveredthat BPR is dynamic, designed for changes and, as such, difficult to transfer intodifferent environments or, one could say that it is dependent on the conditions andenvironment where we wish to realize it.

Measuring business performance has been one of the key topics of the last10 years. Traditional criteria which were based especially on cost have becomeinadequate, especially because of changes in the nature of work, the rise of mod-ern manufacturing concepts, changes in the roles in companies, new demands ofbusiness environment, and the development of information technology. Recyclingand modernization of implementation measuring systems, on the one hand, refers toinnovations of accountancy systems, especially regarding the treatment of expenseswhich are based on activities (Johnston and Kaplan, 1987), and, on the other hand,on expansion in the field of measuring the so-called non-cost measurements whichare not economic or financial in nature, but come from customer needs.


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Existing literature on the subject warns about deficiencies in the concept ofBPR, which can be extremely efficient with its radical workings. The connectionof BPR with the level of manufacturing strategies solves the problem of integratingBPR and enables us to define the starting point and set clear goals. The chosenstrategic goals of the company represented by competitive criteria become thegoals, which can be attained by BPR. Defining clear goals enables, on the otherhand, measuring efficiency or failure of implemented reengineering process, whichpoints to successful realization of chosen or planned strategy — with this approach,the reengineering process is rounded up as a whole.

2. Business Process Reengineering

Several authors have provided their own interpretation about the concept of BPR.For example, Davenport and Short (1990) have described BPR as the analysisand design of work flows and processes within, and between, the organizations.Hammer and Champy (1993) have promoted “the fundamental rethinking andradical redesign of business processes to achieve dramatic improvements in crit-ical, contemporary measures of performance, such as cost, quality, service, andspeed.”

Short and Venkatraman (1992) exposed the customer’s point of view whendefining BP redesign as the company’s action to restructure internal operationsby improving product distribution and delivery performance to the customer. ForJohansson et al. (1993), BPR is the means by which an organization can achievea radical change in performance as measured by cost, cycle time, service, andquality, using the application of a variety of tools and techniques that focus on thebusiness, as a set of related customer-oriented core businesses rather than a set oforganizational functions.

Even if the main BPR characteristic still remains in the radical nature of change,some — such as Yung and Chan (2003) — have proposed a slightly less radicalapproach, named “flexible BPR.”

Other authors such as Vantrappen (1992) or Talwar (1993) focused on therethinking, restructuring, and streamlining of business structure, processes, workmethods, management systems, and external relationships, through which value iscreated and delivered.

Petrozzo and Stepper (1994), on the other hand, believed that BPR involvesthe concurrent redesign of processes, organizations, and their supporting informa-tion systems, to achieve radical improvement in time, cost, quality, and customers’regard for the company’s products and services. Loewenthal (1994) described thefundamental rethinking and redesign of operating processes and organizationalstructure; the focus is on the organization’s core competence to achieve dramaticimprovements in organizational performance. Zairi (1997) discussed BPR, includ-ing continuous improvement and benchmarking, within Business Process Man-agement, which is a structured approach to analyzing and continually improving


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fundamental activities such as manufacturing, marketing, communications, andother major elements of a company’s operation.

BPR also has some similarities with TQM first, the process orientation, thecustomer-driven inspiration, and the wide transversal nature (Schniederjans andKim, 2003). They differ in the approach: evolutionary (continuous, incrementalimprovement) process change in the case of TQM, and revolutionary (radical, step-change improvement) process change in the case of BPR (Venkatraman, 1994;Slack et al., 2001).

In spite of the apparent differences in definitions given by many authors, wecan extrapolate a few common, more important aspects or key words of processreengineering, which were exactly defined by Hammer and Champy (1993) in thefollowing definition:

Reengineering of business processes is a basic new consideration of the businessprocess and its fundamental remodelling, to achieve great improvements in criticaland contemporary measurements of performance, such as cost, quality, service, andspeed.

3. Correlation Between Business Strategy and BPR

In regard to literature review, the concept of BPR should be studied in connectionwith its logical supplementary areas: on one hand the manufacturing strategy, andon the other hand the performance indicators.

The need for a strategically-driven BPR approach has been perceived by numer-ous authors (Zairi and Sinclair, 1995; Sarkis et al., 1997). Tinnila (1995) ascertainedthat BPR should start from strategies. The desired strategic position should be thestarting point for redesign, rather than improvement in existing operations. Edwardsand Peppard (1994, 1998) proposed business reengineering as a natural linkage withthe strategy; they suggested that business reengineering can help bridge the gapbetween strategy formulation and implementation. In this context, BPR is seen asan approach, which defines the business architecture, thus enabling the organizationto focus more clearly on customers’ requirements.

We focused specifically on manufacturing strategy, as deriving from corpo-rate strategy, having considered manufacturing companies in our survey; however,several items about the overall strategy have been treated.

4. Performance Measurement

4.1. Definition of PM

Company PM is a chapter, which is frequently mentioned but rarely preciselydefined. This is actually a process of measuring effects where measuring is a processof defining value, and the effect is represented by implementation (Neely et al.,1995). According to the market viewpoint, a company is reaching the set goals,



when they are implemented in a way that satisfies the customers’ demands moreefficiently and more effectively than its competitors. The terms “efficiency” and“effectiveness” are used precisely in this context. Efficiency is a measure of howeconomically the organization’s resources are utilized when providing a given levelof customer satisfaction, while effectiveness refers to the extent to which customerrequirements are met. It is a very important aspect which not only defines twobasic dimensions of implementation, but also stresses the existence of external andinternal influences on operation motives. The definitions can be written as

• PM is a process for increasing the efficiency and effectiveness of a company’soperations.

• PM is a criterion for increasing the efficiency and effectiveness of a company’soperations.

• PM can be a series of criteria for increasing the efficiency and effectiveness of acompany’s operations.

Appropriate definitions are not required as simple in spite of the above definitions,what does PM system represent? On the one hand, it is true that PM is a seriesof measures for assessing efficiency and effectiveness for already-preformed pro-cesses and procedures. But the above-mentioned definition neglects the fact thatthe PM system also encompasses other support infrastructures. The data must beacquired, examined, classified, analyzed, explained, and announced. If we leaveout any of these activities or overlook them, the measuring is incomplete, and as aconsequence the adopted decisions and actions may be unsuitable. Therefore, thecomplete definition would be:

PM enables the adoption of substantiated decisions and actions, for it assesses theefficiency and effectiveness of implementations through the process of acquiring,examining, analyzing, explanation, and announcing appropriate data.

4.2. Reasons for Change in the Field of PM

There are several reasons why this area is receiving so much attention today, andwhy traditional financial measures are perceived as insufficient. An overview ofavailable literature (Eccels, 1991; Neely, 1999) provides the following differentcontent groups:

• Changes in the nature of work• Market competitiveness• Emergence of advanced manufacturing concepts• Changes of roles in companies• Demands of business environment• Information technology development• International quality awards


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4.2.1. Changes in the nature of work

Traditional accounting systems in particularly stress direct material and labor costs.The latter, especially in the 1950s and 1960s of the previous century, exceeded 50%of all costs. Because of large investments in advanced manufacturing technology,the share of direct labor costs decreased and, thus, also the suitability of traditionalaccounting systems. As direct labor cost does not represent the most important costshare, lowering costs and consequently increasing productivity do not decisivelyinfluence all the operations of a company. Narrow focus on cost lowering can cause:

• Short-term effect on investment decisions.• Local optimization without influences on entire operation.• Focus on standard solutions and prevention of constant development.• Lack of strategic focus, as data on quality, responsiveness, speed, and flexibility

is neglected.• Neglecting information on market requirements.

4.2.2. Market competitiveness

Economic dynamics, where only the change is constant, development of science,and high competitiveness on the market, shaken by the process of globalization,importantly influence the way efficiency is measured. Financial indicators measurepredominantly the consequences of past decisions and are limited with predictingefficiency of operation in the future.

Increase in competitiveness demands from companies leads to a search foran original strategic position, which is based on special resources and abilitiessignificant for the company. Companies do not only compete with prices and costsas consequential competitive criteria, but also are trying to differentiate themselveson the basis of quality, flexibility, adaptability to customer demand, innovativeness,and quick response.

4.2.3. Emergence of advanced manufacturing concepts

Study of Japanese economic growth in the 1980s and at the beginning of the 1990soverwhelms Western researchers because of the realization that Japanese com-panies usually define manufacturing differently. The world is presented by leanmanufacturing, which hides a stack of approaches and techniques for productionmanagement. The concept of lean manufacturing in the 1990s overstepped thebounds of focusing on manufacturing and transferred to the concept of lean oper-ations. Besides lean manufacturing, in the 1990s, other concepts emerged: TQM,BPR, benchmarking, mass customization, and concurrent engineering.

Implementation of advanced business concepts helped companies simultane-ously advance in the context of different competitive criteria. Efficiency of oper-ations was not measured one-dimensionally through financial criteria. Increase in



the effectiveness and efficiency of business processes demanded multidimensionalmonitoring with the help of various indicators.

4.2.4. Changes of roles in companies

The majority of criticism about the inadequacy of indicators for monitoring oper-ations was given in the 1980s and 1990s by experts from academic circles whodealt with accounting (Baiman, 2008). These academic experts form the field ofaccounting and various professional associations increased interest in implementingnon-financial indicators in systems for measuring business efficiency.

Those responsible for human resource (HR) development represent anothergroup who took a more active role in shaping indicators, and their use (Chen andCheng, 2007). These indicators were integrated into the entire management ofHRs which is composed of setting goals, measuring implementation, feedbackinformation, and rewards. Correlation between implementation measurement andrewarding is, of course, the essence of HR management.

4.2.5. Demands of business environment

Business environment cannot be limited only to competitiveness among compa-nies. Other elements of the business environment also influence the importance ofdifferent indicators. The trend for desynchronizing the economy instigated privati-zation of former public companies, and the establishment of different agencies formonitoring the operations of newly established companies.

Companies also face an increasing amount of pressure from the final users ofproducts and services, united in various associations. Consumers want more infor-mation about the product or service, and also the way this product was produced.

4.2.6. Information technology development

Information technology development has heavily influenced the possibility of usingreengineered systems for measuring business efficiency (Marchand and Raymond,2008). Development of hardware, software, and databases enables effective datagathering, analysis and presentation from different sources by more people, andin a cheaper and faster manner. Available information, which constantly monitorsbusiness operations, thus enables better business decisions in companies, whichfinally become evident in improved business results.

4.2.7. International quality awards

Establishment of movements for quality and recognizing the importance of improv-ing effectiveness and efficiency in business processes instigated the establishmentof different awards for quality. The first one appeared in 1950 in Japan, the DemingQuality Award. In the United States, the Baldridge Award is highly valued. The


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European Foundation for Quality Management (EFQM) gives awards for businessproficiency. Companies which compete for such awards must undertake an exten-sive evaluation and give detailed information about their organizational strategies,resources, information flow, relationship to social issues, quality policy, and alsofinancial results.

4.3. Review of Individual Measurements and Performance Indicators

Based on the literature review, we can summarize the most important individualmeasurements of performance, which are as follows:

• Quality• Flexibility• Time• Costs• Customer satisfaction• Employee satisfaction or HR management

One of the fundamental problems that we face when implementing a useful PMsystem is trying to achieve a balance between the smaller number of key criteria(clear and simple, but which might not reflect all organizational goals), on one hand,and a greater number of detailed criteria or performance indicators (complex andless appropriate for management but able to show a lot of different possibilities ofperformance) on the other. In general, we can achieve a compromise by ensuringa clear connection between the chosen strategy, key parameters of performance,which reflect the main performance goals, and a series of performance indicatorsfor individual key parameters (Slack et al., 2001). When dealing with individualperformance measures, the most important fact is that they must follow from thestrategy (Neely, 1998).

Based on the manufacturing strategies literature review, Leong et al. (1990) con-clude that generally accepted and useful key dimensions of performance are quality,speed, delivery reliability, price, and flexibility. In spite of this, there is still somevagueness about what different authors actually mean by these terms. Wheelwright(1984), for example, uses flexibility in the context of flexible extent of production.Other authors such as Garvin, Schonberger, Stalk, Gerwin, and Slack mention dif-ferent dimensions for measuring key dimensions of performance. Therefore, it isalmost impossible to review all performance indicators.

One of the problems of PM literature is its diversity. This means that differentauthors focus on different viewpoints when shaping PM systems. Business strate-gists and managers treat measurements on a higher, different level than managerswho are responsible for PMs in production.

De Toni and Tonchia (2001) state that traditional measuring systems focusedpredominantly on production costs and productivity on the basis of changes which



Wait and move times

Productioncosts

Productivity

Materials andlabor

Machinery

Total

Specific

Capital (fixed and working)

Production (labor productivity,machinery saturation, inventoryand WIP level)

“non-cost”

Time

Flexibility

Quality

Internal

External

Produced quality

Perceived quality

In-bound quality

Quality costs

Run and set-up timesPerformancemeasures

System times

Delivery speedand reliability

Time to market

Supplying lead times

Manufacturing lead timesDistribution lead times

“cost”

Figure 1. Performance measures. (Adopted from De Toni and Tonchia, 2001.)

come from competitive environment, were reshaped into two types of measure-ments (Fig. 1):

Cost PMs; including production costs and productivity. These costs displayclear correlations, which can be treated in mathematical form when we get finalresults of the company, which is its net income and profitability.

Non-cost PMs; without direct cost connection which are gaining importance.Non-cost performances are usually measured with non-monetary units, which donot enable a direct link to economic and financial statements (net income andprofitability) in the exact manner that is characteristic for performance connectedto cost, for example delivery date, shorter than 3 days, or a higher quality products(for which we use 5% less) have undoubtedly a positive influence on economic andfinancial performance, but this cannot be expressed in an incremental manner bynet income and/or profitability.

The main goal of the presented review is developing a system of indicators forestimating the reengineering of business processes, as the tool for implementingradical changes in a company, with the aim of meeting those guidelines, providedby strategy. Using an extensive survey research of Slovene companies, we triedto develop a system of indicators which would be able to assess the success ofthe implemented reengineering. For this purpose, we had to study the measure-ment systems according to individual performance indicators and then again tryto determine the connections and accuracy of the proposed theoretical model. The


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following chapters show the review of performance indicators on the basis of propo-sitions from different authors and contributions from theory, to the final shape andselection that we have given to companies in the questionnaire, when performingsurvey research.

4.3.1. PMs, cost-based

Development of accounting management is, among others, very well documentedby Johnson (1975, 1983). His work reveals that the majority of accounting systemswhich are used today are based on assumptions that were made 60 years ago.Actually, Garner’s (1954) review of the accounting literature indicates that themajority of the so-called sophisticated cost accounting theories and practices weredeveloped around 1925 (for example, return on investment — ROI).

Johnston and Kaplan (1987) stress that, due to dramatic changes in businessenvironments that had occurred over the last 60 years, accounting systems are basedon premises that are no longer valid. One of the mostly widely criticized practices isthe allocation of indirect labor and overheads according to direct labor cost. In 1900,direct labor cost represented the majority of product costs. Therefore, it is prudentto allocate overhead cost to the product in accordance with its labor extent. With theincreasing use of advanced manufacturing technologies, today direct labor costs areregarded as 10%–20% of product costs, while overhead costs represent 30%–40%(Murphy and Braund, 1990). This means high burden of overhead costs influencescost structure greatly, with a relatively small change in the content of direct laborproduct cost. Moreover, the distribution of overhead costs, in accordance with directlabor hours, stimulates managers to focus on minimizing the number of direct laborhours which are prescribed in their cost centre, and with this they neglect overheadcosts. Johnston and Kaplan (1987) prove that these problems will only increasein the future, when the life-cycle time becomes shorter and thus the continuousincrease in the share of total product costs will overtake the share of overhead’costs intended for research and development.

As a result of criticisms connected to traditional management accounting,Cooper (1988) developed an approach known as “activity-based costing” (ABC).ABC overcomes a lot of management accounting’s traditional problems, such asmanagement accounting has become distorted by the needs of financial reporting;in particular, costing systems are driven by the need to value stock, rather than toprovide meaningful product costs.

In the majority of manufacturing companies, the share of direct labor, as thepercentage of total cost, has decreased but is still by far the most common basis ofloading overheads onto products.

Overhead costs are not only a burden that must be minimized. Overhead func-tions such as product design, quality control, customer service, production planning,and sales order processing are as important to the customer as the physical processes



on the shop floor increase in complexity. Production processes are more complex,product ranges have expanded, product life-cycles are shorter, and quality is higher.

The marketplace is increasingly competitive. In the majority of sectors, globalcompetition has become a reality. Every business should be able to assess the trueprobability of the sectors it trades in, understand product costs, and know whatdrives overhead. Cost management systems should support process improvements,and the PMs should be connected to strategic and commercial objectives.

In 1985, Miller and Vollman pointed out that, despite many managers focusingon visible costs, e.g., direct labor, direct material, etc., the majority of overheadsare caused by invisible transaction costs. Cooper (1988) also in one of his earliestworks warned about this and one of his major discoveries that support ABC wasthat, more than by just the product itself, the costs are caused by activities whichare required for the production and delivery of the product. Later, it became clearthat the major benefit of ABC is process analysis. This is in accordance with theconcept of business processes reengineering, which offers a view of informationaccording to transverse (horizontal) and not vertical flows in a company.

The other cost-based PM which is very extensively researched in literatureis productivity. Traditionally, it is defined as a relationship between total out-put and total input (Burgess, 1990). Productivity, therefore, measures how wellresources are combined and used to accomplish specific, desirable results (Bain,1982). Ruch (1982) cite that higher productivity can be achieved through severaldifferent methods:

• Faster increase of output in comparison to input (growth management)• Producing higher output with the same level of input (rationalizing work process)• Producing higher output with lower input (ideal)• Maintaining the level of output at lowering of input (higher efficiency)• Lowering of output level with even lower input levels (decrease management)

Different problems arise when measuring productivity, not only when defininginputs and outputs, but also when estimating their amounts (Burgess, 1990). Craigand Harris (1973) propose that companies focus more on total rather than partialproductivity measurements. To define the most typical partial cost measurements,called measurement indicators, cost-based, we will take a look at propositions fromdifferent authors.

Hudson et al. (2001) define the following as the critical dimensions of cost-based performance:

• Cash flow• Market share• Cost reduction• Inventory performance• Cost control• Sales


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• Profitability• Efficiency• Product cost reduction

Performance indicators cost-based, according to De Toni and Tonchia (2001), aredivided into:

• Material cost• Labor cost

}Material and labor cost

• Machinery energy costs• Machinery material consumption• Inventory and WIP level

Machine operation cost

• Machinery saturation• Total productivity• Direct labor productivity• Indirect productivity• Fixed capital productivity• Working capital productivity

Production cost

• Value-added productivity• Value-added productivity/employee

Some typical PM measurement cost-based, according to Slack and Lewis (2002):

• Minimum delivery time/average delivery time• Variance against budget• Utilization of resources• Labor productivity• Added value• Efficiency• Cost per operation hour

Neely et al. (1995) propose the following categories as the critical dimensions ofcost measurements:

• Manufacturing cost• Added value• Selling price• Running cost• Service cost

4.3.2. PMs, time-based

Time has been described as both a source of competitive advantage and the fun-damental measure of PM. According to JIT manufacturing philosophy, just-too-early or just-too-late production or delivery of goods is seen as a waste. Similarly,one of the objectives of optimal production is minimization of throughput times



(Goldratt and Cox, 1986). Galloway and Waldron (1988,1989) developed a costsystem based on time, also known as throughput accountancy; it is based on thefollowing premises:

1. Manufacturing units are an integrated whole whose operating costs are estimatedhighly in the short term. It is more suitable and much simpler to consider theentire costs, without material as fixed ones, and name them “total factory costs”.

2. For all companies, profit is a function of the time required to respond to theneeds of the market. This means that profitability is inversely proportioned tothe level of inventory, as the reaction time itself is the function of all inventories.

3. Relative profitability of the product is defined as the level at which the productcontributes money. This is also a level where the product contributes money,comparable to the level regarding use of money in the company, and definesabsolute profitability.

Galloway and Waldron (1988, 1989) believe that these contributions should bemeasured as a share, with which the money is received, and not as an absolutevalue. Therefore, they defined the relationship of accounting flow as income perwork hour, separated from cost per work hour:

Return per factory hour = sale price − material costs

time on the key resources(1)

Cost per factory hour = total factory cost

total time available on the key resources(2)

Moreover, House and Price (1991) recommend the use of a Hewlett-Packard returnmap for monitoring the effectiveness of a new-product development process. Fooks(1992) reports that Westinghouse used similar cost-time profiles for more than adecade. The basic idea is that any set of business activities or processes can bedefined as a collection of costs over time. An interesting approach for designingtime-based PMs is proposed by Azzone et al. (1991). According to their findings,companies that wish to use time for competitive advantage should use a series ofmeasurements.

Let us review the partial PMs, time-based, as different authors propose. Thevarious types of performance, time-based, are fundamentally divided into perfor-mances, which are implemented (De Toni and Tonchia, 2001):

1. Inside the company:

• Work time and preparation of work (travel, preparation, and finishing times)• Waiting and transport times

2. Outside the company:

• System time (time for delivery, production, and distribution)• Speed of delivery and reliability of delivery (customers and suppliers)• Time to market (time, required for new product development)


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Furthermore, we can enumerate the indicators of external and internal timeperformance:

• Time to market• Lead times distribution• Delivery reliability

External times

• Supplying lead times• Supplier delivery reliability• Manufacturing lead times• Standard run times• Actual flow times

Internal times

• Wait times• Set-up times• Move times• Inventory turnover

}Externally-internal times

• Order carrying-out times −→ External times

Slack and Lewis (2002) propose the following typical partial time measurements:

• Customer query time• Order lead time• Frequency of delivery• Actual versus theoretical throughput time• Cycle time

Critical dimensions of time performance according to Hudson et al. (2001):

• Lead time• Delivery reliability• Process throughput time• Process time• Productivity• Cycle time• Delivery speed• Labor efficiency• Resource utilization

Neely et al. (1995) propose the following typical partial measurements, time-based:

• Manufacturing lead time• Rate of introducing production• Delivery lead time• Due-date performance• Frequency of delivery



4.3.3. PMs, flexibility-based

Although the area of flexibility over the last 15 years has generated a lot of litera-ture, there is still some vagueness. Vagueness concerning the concept of flexibilityrepresents a critical obstacle to competitive abilities in effective management per-formance (Upton, 1994). Definitions of flexibility, which can be found in literature,are divided mainly into two ways:

• To definitions which are directly linked to a company• To definitions which arise from general definitions of flexibility, and can be found

in other scientific fields

Although measuring flexibility in academic circles and among managers is of greatimportance, these kinds of measurements are still under development — particularlybecause flexibility is a multidimensional term and because there are usually no indi-cators that can be obtained by direct measuring (Cox, 1989). Proposed measure-ments are somewhat naive and general. In spite of the need, there are no generallyor widely accepted measuring methods. The robustness of proposed measurementsis hardly researched (Chen and Chung, 1996).

Direct, objective flexibility measurements are very hard to put into prac-tice. Examples of such measurements are estimating the possibility of a certainmoment — a decisive viewpoint and analysis of certain output characteristics. In thearea of direct measurements, there are also direct subjective measurements, whichare based on the Likert scale. For different angles of flexibility, we give opinionswhich represent a degree of agreement/disagreement with given statements.

Due to problems that arise with direct definition of performance flexibility,different authors propose the use of indirect indicators which take into account:

1. Characteristics of manufacturing system, which enable flexible production andcan be:

• Technological (for example, availability of excess production capacity, exis-tence of preparation time, etc.)

• Organizational and managerial (for example, improvement/increase of workand team work, etc.)

2. Performance, which is, in a way connected to flexibility, and can be:

• Economical (cost and value)• Non-cost based — not connected to costs (time for product development,

delivery time, quality, and services).

Because flexibility can be treated in several dimensions, partial measurementsare especially appropriate for measuring the flexibility in manufacturing systems.In this case, we must be familiar with unification procedures which include allimportant individual indicators that take into account different kinds of flexibility(Tonchia, 2000).


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To define the most typical partial-flexibility measurements, also called “flex-ibility indicators”, we will review the different authors’ propositions. Slack andLewis (2002) propose the following typical partial flexibility measurements:

• Time required for developing new products/services• Range of products/service• Machine change-over time• Batch size• Time to increase activity rate• Average capacity/maximum capacity• Time to change schedules

Hudson, et al. (2001) propose, as critical flexibility measurements, the followingdimensions:

• Manufacturing effectiveness• Resource utilization• Volume flexibility• New product introduction• Computer systems (IT)• Future growth• Product innovation

De Toni and Tonchia (2001) propose the division and, thus, also measuring of thefollowing types of flexibility:

• Volume flexibility• Mixed flexibility• Product modification flexibility• Process modification flexibility• Expansion flexibility

Neely et al. (1995) propose the following as typical partial flexibility measurements:

• Material quality• Output quality• New product development• Modify product• Deliverability• Volume• Mix flexibility• Resource mix

4.3.4. PMs, quality-based

Traditionally, quality has been defined in terms of conformance to specificationand, therefore, the quality-based measurements of performance generally focus



on measurements such as the number of defects produced, and the cost of quality.Feigenbaum (1961) was the first to propose that the true cost of quality is a functionof the prevention, appraisal, and failure costs. Campanella and Corcoran (1983)defined three types of cost:

Prevention costs are costs, which are used for the purpose of preventing incon-sistencies such as quality planning costs, survey of supplier quality, and educationcosts.

Appraisal costs are costs, which are used for the purpose of estimating productquality and to define discrepancies like monitoring costs, testing, and calibrationcontrol or dimension control.

Failure costs are costs, which are used for correcting discrepancies and areusually divided as follows:

• Internal failure costs; these are costs that arise before delivery to the customer,such as cost of repairs, waste, and material examination.

• External failure costs are costs that arise regarding the delivery of goods tothe customer, such as costs connected with processing customer complaints,customer refunds, maintenance, and warranties.

Crosby’s (1972) claim that “quality is free” is based on the assumption that anyincrease in prevention costs is more than offset by a decrease in failure costs. Qualitycosts are measured as special costs, which arise in a company, for they are usuallyhigher or lower than the performance. Usually they represent 20% of the net price.

Crosby warns that the majority of companies made a mistake by integrating thequality-costs model within the management process. This means that, even if man-agers estimate the quality cost, they lack appropriate activities for lowering them.With the emergence of TQM, the emphasis has shifted away from “conformance tospecification” and toward customer satisfaction. As a consequence, a larger num-ber of surveys on customer satisfaction and market research have emerged. Thisreflects the emergence of the Malcolm Baldridge National Quality Award in theUnited States and the European Quality Award in Europe.

Other common measures of quality include statistical process control (SPC)(Deming, 1982; Price, 1984) and the Motorola six-sigma concept. Motorola is oneof the world’s leading manufacturers and suppliers of semiconductors. In 1992,the company set the goal in the area of quality to meet the six-sigma capacity (3.4errors per million parts). The last two measurements are especially important forthe design of PM systems, because they focus on process and not on output. DeToni and Tonchia (2001) defined the following indicators of performance quality:

• SPC measures — achieved quality• Machinery reliability• Reworks — quality costs• Quality system costs• In-bound quality


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• Vendor quality rating• Customer satisfaction — Quality perception• Technical assistance• Returned goods• To sum up• Production quality• Quality costs

}Internal quality

• Quality perception (understanding market demands)• Delivery quality

}External quality

Some of the typical partial quality measurements as proposed by Slack and Lewis(2002):

• Number of defects per unit• Level of customer complaints• Scrap level• Warranty claims• Mean time between failures• Customer satisfaction score

Hudson et al. (2001) propose the following as the critical performance qualitydimensions:

• Product performance• Delivery reliability• Waste• Dependability• Innovation

Neely et al. (1995) propose the following indicators as typical PMs, pertaining toquality:

• Performance• Features• Reliability• Conformance• Technical durability• Serviceability• Aesthetics• Perceived quality• Humanity• Value



4.3.5. Dependability

Some of typical partial-dependability measurements, as proposed by Slack et al.(2002):

• Percentage of orders delivered date• Average lateness of orders• Proportion of products in stock• Mean deviation from promised arrival• Schedule adherence

4.3.6. Measuring customer satisfaction

To measure customer satisfaction Hudson, et al. (2001) propose the following crit-ical dimensions:

• Market share• Service• Image• Integration with customers• Competitiveness• Innovation• Delivery reliability

4.3.7. Measuring employee satisfaction

Human capacity or human resources (HR) are surely the most important resourcesof every company. Often, two equally large companies which are involved in similaractivities and work in the same environment achieve substantially different businessresults. The reasons can be numerous, but the difference is usually a consequenceof different work abilities of employees or different quality of HR.

Knowledge about the value of HR is not new. Even the pre-classic economistswere aware of its value and treated a person as an integral part and a source ofnational wealth. These realizations matured in time, but human capacities todayonly rarely find their place in accounting statements. Some of the critical dimensionsof measuring employee satisfaction as proposed by Hudson et al. (2001):

• Employee relationships• Employee involvement• Workforce• Learning• Labor efficiency• Quality of work-life• Resource utilization• Productivity


136 N. V. Herzog

5. Research Methodology

The consequences of the change termed BPR can be perceived in companies allover the world including Slovenian companies (Herzog et al., 2006, 2007; Tennant,2005).An exploratory survey research methodology was taken up when consideringthe presented problem. This performed research was the first large-scale studycarried out in Slovenia on this theme.

The research was divided into three phases:

(i) A wide-ranging analysis was conducted, of the existent literature aimed atdetermining the major dimensions of BPR.

(ii) A questionnaire was designed to investigate the real BPR, pre-tested on expertsand pilot-firms (as suggested by Dillman, 1978), and later sent by post to theGeneral and Plant/Production Managers responsible or participating in theBPR project. This questionnaire contained 56 items, designed according tothe Likert scales.

(iii) The resulting data were subjected to reliability and validity analyses, and thenanalyzed using uni- and multivariate statistical techniques.

5.1. Data Collection and Measurement Analysis

The research was carried out in 179 Slovenian companies within the mechanicalindustry and 90 Slovenian companies within the electromechanical and electronicindustries. The criterion for the choice of sample was the size of the company. Welimited it to medium- and large-sized companies, because the complexity of theBPR activities is more distinctive in these companies. According to the SlovenianCompanies Act (Ur. L. RS nr. 30/1993), companies are divided into small, mediumand large, according to the number of employees, respectively, less than 50, from50 to 249, from 250 upwards; and on revenue respectively less than 0.83 million,from 0.83 to 3.34 million, from 3.34 million EUR upwards.

The response rate was very good for the post-contact methodology (27.14%),and showed that firms were interested in the subject. The subsequent statisticalanalysis was, therefore, carried out on the results of those 73 companies, whichreturned the questionnaires correctly filled in. Of the 73 companies analyzed, 53belong to the mechanical and 20 to the electromechanical industries.

To indicate the degree or extent of each item, as practiced by their business unit, afive-point Likert scale (Rossi and Wright, 1983) was used, ranging from “stronglydisagree” to “strongly agree”. In determining the measurement properties of theconstructs used in the statistical analysis, reliability and validity were assessed (Dickand Hagerty, 1971), using respectively Cronbach’s alpha and principal componentsanalysis (PCA).



5.1.1. Reliability

Reliability has two components (Flynn et al., 1990): stability (in time) and equiv-alence (in terms of the means and variances of different measurements of thesame construct). The main instruments for reliability assessment are the test–retestmethod (for stability) and Cronbach’s alpha (for equivalence) (Cronbach, 1951).We concentrated on the second aspect, because these variables were being devel-oped for the first time. All of the multiitem variables have a Cronbach’s alpha of atleast 0.6383 (for single variables 0.6030), otherwise most of the multiitem variableshave Cronbach alpha greater than 0.7 or even 0.8, well exceeding the guidelines setfor the development of new variables (Nunnally and Bernstein, 1994).

5.1.2. Validity

The validity of a measure refers to the extent to which it measures what it wasintended to measure. Three different types of validity are generally considered:content validity, criterion-related validity, and construct validity. Content validitycannot be determined statistically but only by experts, and by referring to literature.Criterion validity regards the predictive nature of the research instrument to obtainthe objective outcome. Construct validity measures the extent to which the itemsin a scale all measure the same construct.

We derived content validity from two extended reviews of recent literature aboutBPR. O’Neil and Sohal (1999) exposed six main dimensions of BPR on the basisof a review of over 100 references covering the period from the late 1980s to 1998.They concluded that the empirical research in BPR has been lagging and it presentsthe academic community with a considerable opportunity. Rigorous, empiricallybased research can help in demystifying the confusion that still exists concerningBPR and simultaneously enables better understanding of manufacturing company’sfunction. Another source was an extended literature study based on 133 references(selected from a start of 900) performed by Motwani et al. (1998). These authorsidentified four main research streams in the BPR area and determined defectivenessand directions for further research.

To establish criterion validity, each item of the questionnaire was criticallyreviewed by five academics in operations management at the University of Maribor(Slovenia) and the University of Udine (Italy), and also by three general managersfrom different manufacturing companies. Following the pre-tests of the items, 142items remained appropriate for conducting research.

Of the different properties that can be assessed from measurements, constructvalidity is the most complex and, yet, the most critical to substantive theory testing.A measurement has construct validity if it measures the theoretical construct or traitthat it was designed to measure. Construct validity can also be established throughthe use of PCA.


138 N. V. Herzog

At this point PCA was carried out to uncover the underlying dimensions, elimi-nate problems of multicollinearity (Belsley et al., 1980) and, ultimately, reduce thenumber of variables to a limited number of orthogonal factors.

First, each multiitem variable was factor-analyzed separately: for the itemsloaded on more than one factor, the items responsible for the other factors beyondthe first were eliminated (or considered in another variable) and Cronbach’s alphawas re-calculated. The presented variables are all in their final version.

A similar procedure was then adopted to group several variables to get a moremanageable set of variables without surrendering too much information. Rotationwas applied to aid interpretation. For interpretation of the factor loading’s matrix,only loadings superior to 0.5 were considered (except in a few cases where a variableis transverse to several factors): imposing such a limit allows the retaining of onlythose variables which contribute in a high degree, to the formation of a given factor,called according to the name of the variables with higher factor loadings.

6. Performance Indicators for BPR Evaluation

From the survey and comparison of theoretical models of PMs in existing literature,we gained an insight into the entire extent of the field. One of the basic problemsthat we face when implementing a useful PM system is an attempt to achievea balance between the lower number of key PMs (clear and simple, but mightnot reflecting all organizational goals) on the one hand, and a greater number ofdetailed measurements or performance indicators (complex and less appropriate formanagement, but able to show many different possibilities of performance), on theother. Generally, we reach a compromise by ensuring a clear connection betweenthe chosen strategy, key performance parameters, which reflect main performancegoals, and a series of performance indicators for individual key parameters.

When dealing with individual PMs, the most important aspect is the fact thatthey must come from the strategy. Measuring can be a qualification process, butits main aim is to instigate positive working and, as Mintzberg pointed out, thisstrategy can be realized only by consistency between operation and performance.

As the most important contribution of the survey, we can highlight the develop-ment of the system of indicators for BPR evaluation. Figure 2 shows the PM systemof BPR, which we developed on the basis of real information from the companieswhich have gone through this process; we based it on the method of question-naires. To form new variables, we used methods which are not as widespread andcome from the scientific field of psychometrics. When forming the variables, weused a measurement instrument which we thoroughly examined from the aspectsof reliability and validity. Thus, we can say with certainty that the newly developedvariables are empirically based, and thus reliable and valid.

The first subfield was designated for forming new variables for cost assess-ment in reengineering. When verifying reliability and validity, we designed newcombined variables which then, on the basis of coefficient of variation, classified



Time

Flexibility

Reliability

Internal quality External quality

Internal company time External time

Product flexibility Process flexibility General flexibility

Delays Product inventory Employee reliability

General indicators of customer satisfactionDirect cooperation with customer

Costs

Quality

Customer satisfaction

Human resources

Absence from work Workforce qualification Promotion and character development of employees Working experiences

Material costsWork and maintenance costs Inventory costs Total productivity Money flow Costs of new product development

System of indicators for estimating reengineering

Figure 2. Performance indicators for BPR evaluation.

according to importance. Between different types of costs in a company, the ques-tioned persons attribute the greatest importance to the group or total productivity.According to the coefficient of variation, defined as a ratio between standard devi-ation and mean value of survey research results, opinions in companies about totalproductivity were very uniform. Total productivity is then followed by materialcosts, labor costs and services, and cash-flow.

If we try to connect the results of the study with the findings of numerous otherauthors, we can discover that productivity as a PM correlated to costs is most widelytreated in literature. Here arises the question: is this of great importance that thequestioned people attribute to productivity measurement, perhaps a consequenceof wider studying and promoting of productivity in literature? Here, we must notforget that the field of productivity, which is traditionally defined as the relationshipbetween total output and total input, still generates problems, not only definingoutputs and inputs but with their amount assessments (Burgess, 1990). Craig and


140 N. V. Herzog

Harris (1973) propose that companies should rather focus on total measurementsinstead of partial productivity measurements. This idea was also adopted by Hayeset al. (1988) who discovered how companies could measure total productivity.

Regarding De Toni and Tonchia’s (2001) research, we can deduce that tradi-tional measurement systems, focusing especially on production costs and produc-tivity, on the basis of changes that stem from a competitive environment, werereengineered, especially in the direction of measurements which they call PMs,without direct cost-correlation. These measurements are becoming increasinglyimportant. Non-cost performance is usually measured as non-monetary units; there-fore, a direct correlation with economic and financial statements in the exact methodis impossible, which is the distinctiveness of cost-based performance. In the fol-lowing text, we will present discoveries gathered from the questionnaire using thesequence used in the questionnaire. Quality was examined as the first solution,which is not in direct correlation with cost.

Traditionally, quality has been defined in terms of conformance to specificationand, therefore, the quality-based measurements of performance generally focus onmeasurements such as the number of defects produced, and the cost of quality.Quality costs are measured as special costs that arise in a company for they areusually higher or lower than when implemented, and commonly represent 20% ofnet price share.

When defining costs, a question arises — does optimal quality level actuallyexist? In the field of PM, the most appropriate viewpoint is proposed by Crosby.He warns that the majority of companies made a mistake by integrating a modelof quality costs with the management process. This means that, even if managersestimate the quality cost, they lack appropriate activities for their lowering. Withthe emergence of TQM, the stress from adapting to detail moved to the direction ofcustomer satisfaction. As a consequence, a larger number of surveys on customersatisfaction and market research have emerged. This reflects the emergence ofMalcom Baldridge National Quality Award in the USA and the European QualityAward in Europe.

Other common measures regarding quality include SPC (Deming, 1982; Price,1984) and Motorola’s six-sigma concept. The two latter measurements are espe-cially important for the design of PM systems, for they focus on process and noton output.

On the sublevel of quality, we designed, on the basis of survey results, two newunited variables — internal and external quality. The questioned persons attributegreater importance to external quality, which includes in bound quality, customersatisfaction, quality perception, and delivery reliability. A somewhat lesser impor-tance is attributed to internal quality, which includes the level of rework, warrantyclaims, costs of rework, and costs of the quality system.

Time is described as the source of competitive advantages and also as the basicPM.According to JIT production philosophy, early and late production or delivery isshown as a loss. Similarly, one of the goals of optimal production is minimizing flow



times (Goldratt and Cox, 1986). Galloway and Waldron (1988, 1989) developed acost system based on time, known also as flow accountancy.

The participants believe that time in the company, like time for machine prepa-ration, waiting times, transport times, and inventory circling are very importantfor company operations. Although measuring flexibility in academic circles andamong managers is of great importance, these types of measurements are still beingdeveloped, especially because flexibility is a multidimensional term and becausethere are usually no indicators which we could obtain by direct measurements(Cox, 1989).

Direct, objective flexibility measurements are very difficult to implement inpractice. Due to problems which arise at direct definition of performance flexibility,different authors propose the use of indirect indicators. In this case, we must befamiliar with procedures for unification which include all important individualindicators, which take into account different kinds of flexibility. The synthesis ofmeasurement must include clear rules on including individual (elementary) andunited measurements and elementary data which must be perfect, homogenous(related), and in the appropriate phase to be united optimally.

The results of descriptive statistics in the subfield of flexibility show that com-panies attribute greater importance to general flexibility, including changing time-possibilities, reaction to customer demands, and product innovations. As the mostimportant measurement in the subfield of reliability, participants from companiespointed out delays particularly — a share of orders performed too late and averageorder delays. The low value for the coefficient of variation shows the uniformity ofopinions regarding this issue. Somewhat lesser importance is given to reliability ofemployees, but the opinions on this vary considerably. In the subfield of customersatisfaction, participants were in agreement about the great importance of directcooperation with customers; they also attributed great importance to other generalcustomer satisfaction indicators.

The results of descriptive statistics in the subfield of HR pointed out as the mostvaluable characteristic that influences the efficiency of the company — the employ-ees’ education. The opinion of participants about the importance of employee edu-cation is very uniform in all mid-sized and large companies.

HR (employees) are surely the most important resource of every company(Milost, 2001). Often, two equally large companies which are involved in similaractivities and work in the same environment achieve substantially different businessresults. The reasons can be numerous, but the difference is usually a consequenceof the different work abilities of employees or different quality of HR.

The problem which arises is contributed to the fact that the work abilities ofemployees are not shown in classical balance sheets. Accounting gives individualevents in company operations a value statement. The accounting thus shows onlythose means and obligations connected to resources, which can be expressed invalue. The result of this approach is that HR, the highest quality and most importantmeans of a company, are not shown in balance statements.


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This does not necessarily mean that the quality of HR in a company is treatedas something unimportant. The positive contribution of employees is usually men-tioned at the presentation of business results. But a few dry sentences cannot expresstheir real contribution to successful business operations.

At the end of this chapter, guidelines for following up research must be men-tioned, especially on the basis of findings that surfaced during research implemen-tation. Due to the mentioned problems with measuring employee abilities, a veryinteresting field of research is opening where it would be favorable to study anddevelop a series of subjective measurements for measuring the abilities of employ-ees, and for measuring employee integration in companies. The option to furtherstudy correlations between individual newly developed variables is still open.

References

Azzone G, C Masella and U Bertele (1991). Design of performance measures for time-based companies. International Journal of Operations & Production Management,11(3), 77–85.

Baiman S (2008). Special double issue on the use of accounting data for firm valuation andperformance measurement. Review of accounting studies, 13(2–3), 167–167.

Bain D (1982). The Productivity Prescription — The Manager’s Guide to Improving Pro-ductivity and Profits. New York: McGraw-Hill.

Belsley DA, E Kuh and RE Welsch (1980). Regression Diagnosis: Identifying InfluentialData and Source Collinearity. New York: John Wiley & Sons.

Burgess TF (1990). A review of productivity. Work Study, January/February, 6–9.Campanella J and FJ Corcoran (1972). Principles of quality costs. Quality Progress, April,

16–22.Chen IJ and CH Chung (1996).An examination of flexibility measurements and performance

of flexible manufacturing systems. International Journal of Production Research,34(2), 379–394.

Chen CC and WY Cheng (2007). Customer-focused and product-line-based manufac-turing performance measurement. International Journal of Advanced ManufacturingTechnology, 32(11–12), 1236–1245.

Cooper R (1988). The rise of activity-based cost systems: Part II — When do I need anactivity based cost system? Journal of Cost Management, 41–48.

Cox T (1989). Towards the measurement of manufacturing flexibility. Production & Inven-tory Management Journal, 68–89.

Craig CE and CR Harris (1973). Total productivity measurement at the firm level. SloanManagement Review, 14(3), 13–29.

Cronbach LJ (1951). Coefficient alpha and the internal structure of tests, Psychometrika,16, 297–334.

Crosby PB (1972). Quality is Free. New York: McGraw-Hill.Davenport TH and JE Short (1990). The new industrial reengineering: Information tech-

nology and business process redesign. Sloan Management Review, 31(4), 11–27.De Toni A and S Tonchia (2001). Performance measurement systems, models, charac-

teristics and measures. International Journal of Operations & Production Management,21(1/2), 46–70.



Deming WE (1982). Quality, Productivity and Competitive Position. Cambridge: MIT.Dick W and N Hagerty (1971). Topics in Measurement: Reliability and Validity. New York:

McGraw-Hill.Dillman DA (1978). Mail and Telephone Surveys: The Total Design Method. New York:

John Wiley & Sons.Eccles RG (1999). The performance measurement manifesto. Harvard Business Review,

69(1), 131–137.Edwards C and J Peppard (1994). Forging a link between business strategy and business

reengineering. European Management Journal, 12(4), 407–416.Edwards C and J Peppard (1998). Strategic Development: Methods and Models. NewYork:

Jossey-Bass.Feigenbaum AV (1961). Total Quality Control, New York: McGraw-Hill.Flynn BB, S Sakakibara, RG Schroeder, KA Bates and EJ Flynn (1990). Empirical

Research Methods in Operations Management. Journal of Operations Management,9(2), 250–285.

Fooks JH (1992). Profiles for Performance: Total Quality Methods for Reducing Cycle Time.Reading, MA: Addison-Wesley.

Galloway D and D Waldron (1988). Throughput accounting part 1 — The need for a newlanguage for manufacturing. Management Accounting, November, 34–35.

Galloway D and D Waldron (1988). Throughput accounting part 2 — Ranking productsprofitability. Management Accounting, December, 34–35.

Galloway D and D Waldron (1989). Throughput accounting part 3 —A better way to controllabour costs. Management Accounting, January, 32–33.

Galloway D and D Waldron (1989). Throughput accounting part 4 — Moving on to complexproducts. Management Accounting, February, 40–41.

Goldratt EM and J Cox (1986). The Goal: Beating the Competition. Hounslow: CreativeOutput Books.

Hammer M and J Champy (1990). Reengineering. Work: Don’t Automate, Obliterate, Har-vard Business Review, 68(4), 104–112.

Hammer M and J Champy (1993). Reengineering the Corporation: A Manifesto for BusinessRevolution, Harper Business.

Hayes RJ, SC Wheelwright and KB Clark (1988). Dynamic Manufacturing: Creating theLearning Organisation. New York: Free Press.

Herzog NV, A Polajnar and P Pizmoht (2006). Performance measurement in business pro-cess re-engineering. Journal of mechanical engineering, 52(4), 210–224.

Herzog NV, A Polajnar and S Tonchia (2007). Development and validation of businessprocess reengineering (BPR) variables: A survey research in Slovenian companies.International Journal of Production Research, 45(24), 5811–5834.

House CH and RL Price (1991). The return map: Tracking product teams. Harvard BusinessReview, January–February, 92–100.

Hudson M, A Smart and M Bourne (2001). Theory and practice in SME performancemeasurement systems. International Journal of Operations & Production Management,8(8), 1096.

Johansson HJ, P McHugh, and J Pendleburv WA, (1993). Wheeler Business ProcessReengineering: Breakpoint Strategies for Market Dominance. New York: John Wileyand Sons.


144 N. V. Herzog

Johnson HT (1975). The role of history in the study of modern business enterprise. TheAccounting Review, July, 444–450.

Johnson HT (1983). The search for gain in markets and firms: A review of the historicalemergence of management accounting systems. Accounting Organisations and Society,2(3), 139–146.

Johnston HT and RS Kaplan (1987). Relevance Lost — The Rise and Fall of ManagementAccounting. Boston, MA: Harvard Business School Press.

Leong GK, DL Snyder and PT Ward (1990). Research in the process and content ofmanufacturing strategy. OMEGA International Journal of Management Science, 18(2),109–122.

Loewenthal JN (1994). Reengineering the organization: A step-by-step approach to corpo-rate revitalization. Quality Progress, 27(2).

Marchand M and L Raymond (2008). Researching performance measurement systems —An information system perspective. International Journal of Operations & ProductionManagement, 28(7–8), 663–686.

Milost F (2001). Racunovodstvoa cloveskih zmoznosti, ISBN 961-6268-59-7.Motwani J, A Kumar, J Jiang and M Youssef (1998). Business process reengineering, a

theoretical framework and an integrated model. International Journal of Operations &Production Management, 18(9/10), 964–977.

Murphy JC and SL Braund (1990). Management accounting and new manufacturingtechnology. Management Accounting, February, 38–40.

Neely A (1998). Measuring Business Performance. London: The Economist in Associationwith Profile Books Ltd.

Neely A (1999). The performance measurement revolution: Why now and what next? Inter-national Journal of Operations & Production Management, 19(2), 205–228.

Neely A, M Gregory and K Platts (1995). Performance measurement system design: A lit-erature review and research agenda. International Journal of Operations & ProductionInternational Journal of Operations & Production Management, 18(9/10), 964–977.

Nunnally JC and IH Bernstein (1994). Psychometrics Theory, 3rd Edn. NewYork: McGraw-Hill.

O’Neil P andAS Sohal (1999). Business process reengineering:A review of recent literature.Technovation, 19, 571–581.

Petrozzo DP and JC Stepper (1994). Successful Reengineering, New York: Van NostrandReinhold.

Price F (1984). Right First Time. Aldershot: Gower.Rossi PH JD and Wright AB (1971). Anderson, Handbook of Survey Research. New York:

Academic Press.Ruch WA (1982). The measurement of white-collar productivity. National Productivity

Review, Autumn, 3, 22–28.Sarkis J,A Presley and D Liles (1997). The strategic evaluation of candidate business process

reengineering projects. International Journal of Production Economics, 50, 261–274.Schniederjans MJ and GC Kim (2003). Implementing enterprise resource planning systems

with total quality control and business process reengineering. International Journal ofOperations & Production Management, 23(4), 418–429.

Short JE and NVenkatraman (1992). Beyond business process redesign: Redefining Baxter’sbusiness network. Sloan Management Review, 34(1), 7–21.

Slack N and M Lewis (2002). Operations strategy. Pearson Education Limited.



Slack N, S Chambers and R Johnston (2001). Operations Management, 3rd Edn. London:Pearson Education Limited.

Talwar RR (1993). Business re-engineering — A strategy-driven approach. Long RangePlanning, 26(6), 22–40.

Tennant C (2005). The application of business process reengineering in the UK. The TQMMagazine, 17(6), 537–545.

Tinnila M (1995). Strategic perspective to business process redesign, Business ProcessManagement Journal, 1(1), 44–59.

Tonchia S (2000). Linking performance measurement system to strategic and organizationalchoices. International Journal of Business Performance Measurement, 2(1/2/3).

Upton DM (1994). The management of manufacturing flexibility. California ManagementReview, 36(2), 72–89.

Vantrappen H (1993). Creating customer value by streamlining business processes. LongRange Planning, 25(1), 53–62.

Venkatraman N (1994). IT-enabled business transformation: From automation to businessscope redefinition. Sloan Management Review, Winter, 73–87.

Wheelwright SC (1984). Manufacturing strategy — defining the missing link. StrategicManagement Journal, 5, 77–91.

Yung WK-C and DT-H Chan (2003). Application of value delivery system (VDS) andperformance benchmarking in flexible business process reengineering. InternationalJournal of Operations & Production Management, 23(3), 300–315.

Zairi M (1997). Business process management: A boundaryless approach to moderncompetitiveness. Business Process Management Journal, 3(1), 64–80.

Zairi M and D Sinclair (1995). Empirically assessing the impact of BPR on manufacturingfirms. International Journal of Operations and Production Management, 16(8), 5–28.

Biographical Note

Dr. Natasa Vujica Herzog is an Assistant Professor in the Laboratory for Pro-duction and Operations Management at the Faculty of Mechanical Engineeringin Maribor (Slovenia). She received her M.Sc. and Dr. Sc. degrees in MechanicalEngineering at the Faculty of Mechanical Engineering, Maribor, in 2000 and in2004. She is author of more than 70 referred publications, many of them in inter-national journals, scientific books and monographs. Her research area is operationsand production management, in particular, business process reengineering (BPR),performance measurement (PM), lean manufacturing (LM) and Six-Sigma. Sheacquired further knowledge and research experience at two other European univer-sities. The University of Udine, Italy granted her a three months scholarship forresearch work with Prof. Stefano Tonchia in Department for Business & Innova-tion Management. She spent several months at the University of Technology, Graz,Austria, working with Prof. Wohinz at the Institute for Industrial Management andInnovation Research. She is a member of the Performance Measurement Associa-tion (PMA) and the European Operations Management Association (EUROMA).

Documents

Business Process Reengineering and Measuring of Company ...Company Operations Efﬁciency ... and methods such as just-in-time manufacture, total quality management (TQM), continuous