Best manufacturing practicesWhat do the best-performing companies do?

Bjrge Timenes LaugenStavanger University College, Department of Business Administration,

Stavanger, Norway

Nuran Acur and Harry BoerAalborg University, Centre for Industrial Production, Aalborg, Denmark, and

Jan FrickStavanger University College, Department of Business Administration,

Stavanger, Norway

Abstract

Purpose Research on best practices suffers from some fundamental problems. The problemaddressed in the article is that authors tend to postulate, rather than show, the practices they addressto be best whether these practices do indeed produce best performance is often not investigated.

Design/methodology/approach This article assumes that the best performing companies mustbe the ones deploying the best practices. In order to find out what are those practices, the highestperforming companies in the 2002 International Manufacturing Strategy Survey database wereidentified, and the role 14 practices play in these companies was investigated.

Findings Process focus, pull production, equipment productivity and environmental compatibilityappear to qualify as best practices. Quality management and ICT may have been best practicepreviously, but lost that status. E-business, new product development (NPD), supplier strategy andoutsourcing are relatively new, cannot yet be qualified as, but may develop into, best practice. Fourother practices do not produce any significant performance effects.

Research limitations/implications There are four limitations to the research: Incompleteness ofthe set of practices tested: lack of insight into the effects of interaction between practices and the wayin and extent to which they were implemented; good explanatory but poor predictive power; and lackof contextuality.

Originality/value Taking the position that best practice must be what best performing companiesdo, the paper is useful for managers using benchmarking to review the design and performance oftheir manufacturing system, and for scholars engaged or interested in best practice studies.

Keywords Operations and production management, Performance management, Working practices,Strategic manufacturing

Paper type Research paper

IntroductionTodays market and competitive pressures require companies to develop and maintaina high level of coherence between their strategy (objectives), action programmes(implementation), practices (instantiation) and performance (realisation). A lot of efforthas been put into identifying best practices to support companies achieve superiorperformance. However, most research has failed to investigate the effect of thesepractices on performance, whilst perhaps even less is known about the extent to whichthey are indeed generic. Therefore, this paper will take a different perspective.Focusing on manufacturing practices and performance and defining best practices asthe practices used by, and having significant effect on the performance of, the best

The Emerald Research Register for this journal is available at The current issue and full text archive of this journal is available at

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Bestmanufacturing

practices

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International Journal of Operations &Production Management

Vol. 25 No. 2, 2005pp. 131-150

q Emerald Group Publishing Limited0144-3577

DOI 10.1108/01443570510577001

performing companies, the research question is: Which manufacturing practices areused by the best performing organisations?.

The article is structured as follows. First, we present the background of theresearch. Next we describe the research design (question, operationalisation,methodology). Subsequently we present and then discuss the results of an analysisof data from the Third International Manufacturing Strategy Survey. Finally, wepresent the main contributions of the research, identify the main weaknesses andpropose directions for further research.

BackgroundIn the early 1970s the MRP crusade was an attempt to spread MRP to as manycompanies as possible. Although the word best practice had not been invented yet,the underpinning assumption was that MRP is good, i.e. good in terms of practice andperformance effects, for all companies. Today we know better.

In the late 1970s and early 1980s, the best practice approach to manufacturingstrategy seriously entered the industrial and academic agenda with the recognition ofthe extraordinary process and product improvement success of Japan Inc. Westernindustries and academics alike began to look at Japanese companies achievements inorder to understand the principles behind that. Best practice achievement has sincebecome a driving force amongst industry. The best practice approach tomanufacturing strategy encapsulates the world class manufacturing (WCM)philosophy and benchmarking, and is based on the assumption that Thecontinuous improvement of best practice in all areas of the organisation will lead tosuperior performance capability leading to increased competitiveness (Voss, 1995a).

The following analysis of the WCM and best practice literature, summarised inTable I, uncovers what we think are the key weaknesses of the field.

Hayes and Wheelwright (1984) introduced the term WCM, and described this as aset of practices, including quality management, continuous improvement, training andinvestment in technology. The implementation of these best practices would lead tosuperior performance (Flynn et al., 1999, p. 250).

Schonberger (1986) argued that many lessons could be learned from the Japanesemanufacturing industry. He regarded improving the material flow in the production asone of the most important issues, and the flow could be improved throughimplementing just-in-time (JIT), total quality control and total preventive maintenance(TPM). In addition, still according to Schonberger, WCM means continual and rapidimprovement in all areas of the company, and training is the catalyst (Schonberger,1986, p. 207).

The basic principle of the best practice thinking is that operations philosophies,concepts and techniques should be driven by competitive benchmarks and businessexcellence models to improve an organisations competitiveness through thedevelopment of people, processes and technology (Greswell et al., 1998; Voss, 1995b).In these studies, e.g. JIT, total quality management (TQM) and the EuropeanFoundation of Quality Management (EFQM) model are defined as best practices andassumed to imply improved performance.

Useful as they may be, the WCM and best practice studies suffer from threeweaknesses.

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ResearchersKey concept to bestpractice

Results regarding practice-performancerelationships

Swamidass andNewell (1987)

Cross-functionalco-operation, design formanufacturability

Corporate performance is positively related to therole of manufacturing managers in strategicdecisions

Voss (1995a) World-classmanufacturing,bench-marking, businessprocess re-engineering,TQM, learning from theJapanese, continuousimprovement (CI)

Implementation of best (world class) practices leadsto superior performance and capability

Ahmed et al. (1996) TQM, JIT, FMS, CE,benchmarking

When practices (operations strategies) are examinedindividually, companies using any of sevenpractices (FMS, CE, benchmarking, TQM, JIT,manufacturing cells and computer networking)have higher performance than those not using them

Bolden et al. (1997) WCM, employeedevelopment

The classification of manufacturing practicestaxonomies developed provides insight into the roleof individual practices, implementation andoutcomes

Flynn et al. (1997) WCM, TQM, JIT The best users of unique TQM practices, combinedwith common infrastructure practices, are capableof solving problems to improve productionprocesses

Harrison (1998) WCM, CI WCM appears to facilitate operator commitment tocontinuous improvement, but leaders become morefrustrated because they expected to achieve more.Cellular manufacturing in a UK-based companyacted as a powerful change agent, which has led tomore in terms of manufacturing improvement thanprevious initiatives, such as MRP II

Flynn et al. (1999) WCM, CI, JIT, TQM The use of WCM, alone and together with other newpractices, leads to improved competitiveperformance

Kathuria andPartovi (1999)

Cross-functionalco-operation

Better performing manufacturing managersstrongly demonstrate relationship-orientedpractices, such as team building and support,participative leadership and delegation, especiallywhen the emphasis on flexibility is high

Rondeau et al.(2000)

Work system practices,time-based competition

Time-based manufacturing practices tend to lead tostandardisation, formalisation as well as integration

Davies andKochhar (2002)

Best practices,performance,manufacturing planningand control

A structured approach used to identify directqualitative relationship between practice andperformance

Garver (2003) Benchmarking, CI Integrating customer performance measures withinternal performance measures (internal quality,productivity etc.) to identify improvementopportunities is found to be critical

Ketokivi andSchroeder (2004)

TQM, JIT, WCM,contingency

There are only few best practices contributing tocompetitive manufacturing performance in multipledimensions

Table I.Main theoretical

contributions to linksbetween best practices

and performance

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First, the field is rather scattered with many articles focusing on one or a limited set ofnew practices, while the reasons why these practices are considered best are often notaccounted for. Flynn et al. (1997), for example, investigated the influence of qualitymanagement practices on quality performance and the interrelationship between JITand quality management. Hanson et al. (1994), Hanson and Voss (1995) and Voss(1995a) focused on TQM, concurrent engineering (CE) and lean production. Ketokiviand Schroeder (2004) chose to study computer-aided design (CAD), computer-aidedmanufacturing (CAM) and statistical quality control (SQC). Why these practices, notothers, and whether the authors regard the set as comprehensive remains unclear.Related to this, WCM and best practice studies do not take into consideration that otherpractices, or configurations of practices, might be even more important for the overallperformance of the companies than the predefined best practices. There may becompanies that do not reach world-class status, due to the definition of best practices inthese studies, which are really world class in terms of performance, but haveimplemented another set of practices to reach that level of performance.

Second, best practice studies only rarely link the practices investigated to companyperformance. At best, a positive effect of the practices on performance is assumed(Voss, 1995a), or (implicitly) considered self-evident (Voss et al., 1997, p. 284). Only afew studies confirm that the use of best practices leads to improved performance (e.g.Hanson and Voss, 1995; Voss et al., 1997). However, if an explicit link is made, this isdone only for a limited set of performance criteria. An example is Davies and Kochhar(2002), who showed that the implementation of quality programmes leads to increasedquality performance. The few (Davies and Kochhar, 2002) more holistic publicationslinking practices to performance are usually based on one or a few single case studies(e.g. Peters and Waterman, 1982), which offer limited possibilities for generalisation.Finally, too little effort is put into analysing the relationship between the differentpractices and the relative effect both individual practices and their interaction have onperformance.

Third, best practices are considered generic, that is, best for all companies, always.The potential influence of factors like type of industry, company size, processes andproducts is not considered, nor is the fact that practices, even the best ones, maybecome obsolete in the course of time.

In other words, the practices studied are often not accounted for and postulated as,rather than shown to be, best, always and for all. Consequently, there may be bestpractices that have never been studied and also the relative contribution of individualpractices to performance and as well as the interaction between practices isinsufficiently studied. Accordingly, Davies and Kochhar (2002) put forward three mainpoints for future research on best practices:

(1) Best practices are those that lead to improvement in performance. That is, theyhelp a low performing company become a medium performer, a mediumperformer become a high performing company, and a high performer staysuccessful.

(2) Best practices must be investigated within the specific context in which theyoperate.

(3) The investigation of best practices should be approached holistically.

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Research questionIn fact, Davies and Kochhar (2002) suggest that the reasoning behind best practicestudies should be turned around. Focusing on these authors first suggestion (i.e. thesecond problem identified above), this article is based on the assumption that the bestperforming companies are the ones that (must) have the best practices. The questionwe address in this article therefore is: Which practices are used by the best performingorganisations?

The answer to this question will tell us what are best practices. The data we hadavailable (see below) did not allow us to pay serious attention to the other twosuggestions in the analysis presented here. The work presented here should thereforebe regarded as a first step towards developing a best performance based theory of bestmanufacturing practices.

Research designSampleThis article is based on the 2002 International Manufacturing Strategy Survey(IMSS-III) database, which contains data from 474 manufacturing companies in 14countries. IMSS is a co-operative research network of business schools, which aims atdeveloping, maintaining and analysing using a variety of perspectives and researchquestions, a global database for the study of manufacturing strategies, practices andperformances. The respondents are representing five industrial sectors: ISIC 381 (metalmanufacturing), 382 (machinery), 383 (electrical equipment), 384 (automotive) and 385(professional measurement equipment).

Data analysisWe analysed the data in three steps. First, based on 17 manufacturing performancecriteria investigated, we introduced four variables to measure the improvement in thecategories quality, flexibility, speed and cost (see Table II for details). We divided therespondents into two groups, high performers and low performers, for each of thesefour performance categories and for each of the eleven combinations of these categories(see Table II). Next, we performed an ANOVA to determine the differences in theadoption of action programmes between the two groups for each of the (in total) 15categories (see Table III). Finally, we developed a regression model in order to findwhich action programmes have most influence on manufacturing performance (seeTable IV).

Operationalisation of variables and descriptive resultsThis section explains the data concerning performance improvement and actionprogrammes indicated by the sample companies.

Performance improvement. Manufacturing companies must continuously adapt tonew performance requirements in terms of quality, flexibility, speed and cost. The IMSSsurvey asked the respondents to rank their companys performance improvementswithin the last three years on the basis of 17 indicators (see Table II). The questions weremeasured on a five-point Likert scale (1 performance has strongly deteriorated overthe last three years, 3 no change, 5 performance has strongly improved). Wedefined high performers as companies reporting an average score 4 or higher on all theperformance indicators taken into the analysis. Low performers are respondents

Bestmanufacturing

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135

indicating an average score 3 or lower on all the performance criteria, meaning eitherdeterioration in performance or at best maintaining status quo.

Table II shows that a relatively large percentage of the IMSS companies (187) havestrongly improved their quality performance during the last three years, and can becategorised as high performers in quality. For 70 respondents, quality performance hasstayed the same or even deteriorated. While 135 of the respondents have stronglyimproved their flexibility performance over the last three years, 76 respondents have atbest maintained status quo. A total of 145 companies have strongly improved theirspeed performance, while 102 respondents have maintained status quo or not eventhat. For cost performance the picture is that 72 of the respondents claim to havestrongly improved on cost performance within the last three years, while 110respondents failed to achieve that.

Improvement in manufacturing performanceduring the last three years Average SD

Number ofhigh performers

Number oflow performers

Quality (Q) 3.7 0.5 187 70Manufacturing conformance 3.7 0.6Product quality and reliability 3.8 0.7Customer service and support 3.7 0.7Delivery reliability 3.7 0.8Environmental performance 3.5 0.8

Flexibility (F) 3.6 0.5 135 76Product customisation ability 3.6 0.8Volume flexibility 3.8 0.8Mix flexibility 3.6 0.7Time to market 3.5 0.7

Speed (S) 3.6 0.5 145 102Delivery speed 3.7 0.8Manufacturing lead time 3.6 0.7Procurement lead time 3.3 0.7

Cost (C) 3.4 0.5 72 110Procurement cost 3.3 0.8Labour productivity 3.6 0.7Inventory turnover 3.4 0.7Capacity utilisation 3.5 0.8Overhead cost 3.2 0.8

Combination of:Quality and flexibility (Q-F) 81 19Quality and speed (Q-S) 88 41Quality and cost (Q-C) 48 33Flexibility and speed (F-S) 56 25Flexibility and cost (F-C) 27 23Speed and cost (S-C) 46 41Quality, flexibility and speed (Q-F-S) 43 12Quality, flexibility and cost (Q-F-C) 22 12Quality, speed and cost (Q-S-C) 34 22Flexibility, speed and cost (F-S-C) 22 16Quality, flexibility, speed and cost (Q-F-S-C) 18 10

Table II.Average values for themanufacturingperformance criteria andnumber of respondentsfor the groups of high andlow performingcompanies

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Table III.Differences in mean

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companies (ANOVA) forthe investigated action

programmes (1 no use,5 high use)

Bestmanufacturing

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137

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90.153

0.118

0.06

70.108

0.171

Sig

n0.

994

0.33

90.010

0.051

0.24

40.095

0.002

Q-S

-CB

eta

0.07

40.

040

0.06

70.

059

0.183

0.08

220.118

0.201

Sig

n0.

166

0.47

10.

287

0.34

30.002

0.19

10.038

0.000

F-S

-CB

eta

20.

072

0.153

0.129

0.145

0.08

50.105

Sig

n0.

172

0.011

0.035

0.014

0.12

10.055

Q-F

-S-C

Bet

a2

0.04

70.148

0.122

0.06

30.

086

0.05

70.172

Sig

n0.

361

0.014

0.042

0.27

50.

163

0.33

80.001

Notes:

aA

pro

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ipm

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B

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gca

pac

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auto

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;H

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;J

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t;K

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;L

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t;M

NP

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N

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tal

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ity

.C

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cien

tsin

bol

dar

est

atis

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lly

sig

nifi

can

tat

p#

0:1

Table IV.Regression analysis:standardised coefficients

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This distribution indicates that quality performance is (still) important for theengineering industry. Cost reduction is the least important goal. This finding isconsistent with recent research by Cagliano et al. (n.d.), which showed that price islosing ground as a competitive priority. Another explanation may be that costreduction programmes have been used in manufacturing companies for so long now,that possibilities for further reductions are small, leading companies to focus onimproving in other areas.

Action programmes. In the survey questionnaire, the term action programmes isused instead of (manufacturing) practices, for two reasons. First, the termprogramme reflects the implementation of bundles of practices. Pull production, forexample, is an action programme; Kanban and single-minute exchange of dies (SMED)are practices underpinning pull production. Second, following Davies and Kochhars(2002) recommendations for best practice studies, we are interested in performanceimprovements and, thus, changes in practices (i.e. action programmes), rather than(bundles of) practices in place.

In the survey we investigated 14 action programmes (i.e. implementation of newpractices), which are listed and defined in Table V. The degree of use during the lastthree years, measured on a 1-5 Likert scale (1 no usage, 5 high usage), representsthe independent variable we used in our analysis.

ResultsThe adoption of action programmesThe ANOVA (Table III) shows that there are many significant differences in the degreeof implementation of action programmes between high and low performing companies.This indicates that most of the single action programmes have been implementeddifferently among the high and low performing companies.

E-business, process automation and outsourcing are the least implementedprogrammes among the respondents in all categories of performance. The differencebetween the high and low performers is not significant in any of the performancecategories.

High performers in all categories implement programmes directed towardsupdating process equipment, process focus, pull production and equipmentproductivity to a significantly (p # 0:01) higher degree than the low performers.The exception to this is the difference in implementation of process equipment forflexibility-cost (F-C), which is non-significant. These four action programmes are alsoused more by the high performers in the single performance categories, although thesignificance is lower (p # 0:05).

Finally, programmes directed towards supplier strategy, quality, workplacedevelopment, new product development and environmental compatibility are ingeneral also significantly more adopted by the high performers.

The differences between high and low performers suggest that high performersimplement more and gain more from the action programmes they adopt. Anotherpossible explanation is that high performers continue implementing the programmeuntil it is finished, instead of stopping the implementation after a short period, forexample if the results are not as expected. So, the difference between high and lowperformers seems to be related to implementation width and depth.

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The performance effects of the action programmesThe ANOVA does not reveal the performance impact of the different actionprogrammes. In order to investigate that, we performed a regression analysis. Theresults are shown in Table IV and discussed next.

Quality performance. Implementing action programmes that aim at improvingmanufacturing capacity, improving quality management and environmentalcompatibility, and obtaining process focus are positively related to qualityperformance improvement.

The effect of quality management and environmental compatibility programmes onquality performance and its underpinning indicators, especially product quality andreliability, manufacturing conformance and environmental performance, is notsurprising. Essentially, this finding confirms that these programmes pay off asintended.

Action programme Operationalisation

Process equipment Updating the companys process equipment to industry standardor better

Manufacturing capacity Expanding manufacturing capacity (e.g. buying new machines,hiring new people, building new facilities)

Process automation Engaging in process automation programmesICT Implementing information and communication technologies

and/or enterprise resource planning softwareE-business Reorganising the company towards e-commerce and/or

e-business configurationsSupplier strategy Rethinking and restructuring the companys supply strategy,

and the organisation and management of the companyssuppliers portfolio

Outsourcing Concentrating on the companys core activities and outsourcingsupport processes and activities (e.g. IS management,maintenance, material handling)

Process focus Restructuring the companys manufacturing processes andlayout to obtain process focus and streamlining (e.g. re-organizeto plant-within-a-plant, cellular layout)

Pull production Undertaking actions to implement pull production (e.g. reducingbatches, set-up time, using kanban systems, etc.),

Quality management Undertaking programmes for quality improvement and control(e.g. TQM programmes, 6s projects, quality circles)

Equipment productivity Undertaking programmes for the improvement of the companysequipment productivity (e.g. total productive maintenance)

Workplace development Implementing actions to increase the level of delegation andknowledge of the companys workforce (e.g. empowerment,training, improvement or autonomous teams)

NPD Implementing actions to improve or speed-up the companysprocess of new product development through, e.g. platformdesign, product modularisation, component standardisation,concurrent engineering (CE), quality function deployment (QFD)

Environmental compatibility Putting efforts into and commitment to improving the companysenvironmental compatibility and workplace safety and healthy

Table V.The 14 actionprogrammes investigated

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The observation that increased process focus has positive effects on quality isless trivial. One explanation might be that process focus often is implemented toimprove delivery reliability, one of the quality indicators. Additionally,process-based production is more transparent than function-based production.Thus, quality problems are visible and, thus, solved sooner. Finally, process-basedmanufacturing requires high and predictable quality in order to become a success.This may indicate that it is not the action programme alone, but a combinationwith other programmes, that explains the impact of increased process focus onquality performance.

Somewhat surprisingly, actions aimed at improving NPD have a significantnegative effect on quality. The most obvious explanation is that some of the practicesunderpinning this action programme, in particular platform design andmodularisation, are relatively new and actually quite complex and difficult toimplement. Involving a review of the companys whole product portfolio, but also arange of organisational and managerial changes throughout the companys valuechain, the implementation of platform design and modularisation may have an,initially, negative effect on product quality.

Flexibility performance. Implementing process focus, pull production andprogrammes to improve equipment productivity and NPD are all positively relatedto improvement in flexibility performance.

Process focus especially has a positive influence on volume and mix flexibility, asthe development and manufacturing of different products are managed separately andtake place on different production lines (plant-within-a-plant). Pull production(including reduced batch sizes and set-up times) increases the speed and reduces thecost of changing the mix of existing, and launching new products, thus allowing acompany to produce to order rather than to forecast. This helps the company improveits mix and volume flexibility as well as its customisation capability. Reduction ofset-up times is also an important element of TPM, which is one programme to improveequipment productivity.

While negatively associated with quality performance, the findings indicate thatimproving NPD is positively associated with improvement in flexibility performance.The most obvious explanation is that some of the practices underpinning NPDimprovement support customisation (modularisation) and time to market reduction(CE).

Speed performance. Process focus, quality and environmental programmes allsignificantly contribute to better speed performance. Increased process focus helpsreduce manufacturing lead time and delivery speed. In addition, quality programmesreduce scrap, losses and rework, and through that improve the speed performance.

A little surprising is that improving and speeding up NPD does not have asignificant influence on speed performance. The reason for this is probably that themeasurements for speed performance are related to procurement and manufacturing,not to the whole process from product development to customer delivery.

Cost performance. For cost performance, programmes that are implemented toimprove equipment productivity appear to have a positive influence, as should beexpected. After all, one of the main purposes with equipment productivityprogrammes, e.g. TPM, is to increase the Overall Equipment Efficiency (OEE),which is closely related to cost reduction and improvement of capacity utilisation.

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There is a positive relationship between pull production and cost performance.Although, the relationship is not significant, the level of significance is fairly good.Reduced inventory levels and higher inventory turnover are important goals with pullproduction and explain the effect found.

The other action programmes do not affect cost performance. The most obviousexplanation is that actually relatively few respondents go for cost reduction, whichconfirms findings reported elsewhere (Cagliano et al., n.d.) that cost seems to havebecome a less important performance indicator for ISIC 38 companies.

Combination of quality and flexibility performance. The regression analysis showspositive relationships between the implementation of process focus, pull production,equipment productivity and environmental compatibility, and improvement ofquality-flexibility (Q-F) performance. While this is hardly surprising, the finding thatimproved quality management practices do not lead to improved Q-F performance is.The only explanation we can think of is that the product quality/reliability andmanufacturing conformance aspects of quality have long been solved, while thedelivery reliability and environmental aspects have not. The four programmes justmentioned address these aspects.

Combination of quality and speed performance. Programmes aiming to implementprocess focus and increased environmental compatibility are positively related toimproved quality-speed performance, which is not surprising given the influence ofthese programmes on quality and speed considered individually. Improving andspeeding up the NPD processes is negatively related to quality-speed improvement. Wecould not find a reasonable explanation for that other perhaps than that the negativeimpact on quality (see above) is larger than the positive impact on speed.

Combination of quality and cost performance. Pull production, equipmentproductivity and environmental compatibility have a positive effect on quality-costperformance. The most likely quality aspects affected are delivery reliability andenvironmental performance. Through reduction of inventory, batch sizes and set-uptimes, pull production leads to cost reduction. Apparently, equipment productivityprogrammes such as TPM also do what they are supposed to do: contribute to qualityimprovement and cost reduction.

Combination of flexibility and speed performance. In line with the improvementprogrammes being positively related to flexibility performance, implementing processfocus, pull production and equipment productivity are also positively related toimproving flexibility-speed performance. While implementing a clear supplier strategydoes not have a significant effect on flexibility and speed considered individually, itdoes in companies pursuing improvement on the combination of these performanceareas, and that effect is positive. In other words, one of the cornerstones of supply chainmanagement does indeed have positive effects on the logistical aspects ofmanufacturing performance.

Combination of flexibility and cost performance. The pattern of relationshipsbetween action programmes and flexibility-cost performance does not produce anysurprises, except for the negative effect of implementing e-business. The most likelyexplanation is not flexibility but cost/benefit related: e-business is a relatively recentphenomenon and as in many other previous innovations, the initial costs are higherthan expected, while the financial benefits are lower. It will be interesting to see if thecost effects of e-business are still negative in a couple of years time.

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Combination of speed and cost performance. Pull production, equipmentproductivity and environmental compatibility are positively associated withimproving speed-cost performance. Interestingly, the relationship between pullproduction and speed-cost performance is significant, while not significant for speedand cost performance analysed separately. This may indicate that pull productionprovides a good basis for achieving a good speed performance and, through that, alsohas significant impact on cost.

Combination of quality, flexibility and speed. Companies with a high performanceimprovement in quality-flexibility-speed appear to be able to achieve that byimplementing process focus, pull production and environmental compatibility. Thisconfirms the picture starting to emerge, namely that these three action programmestaken together produce a range of different performance effects. The fourth apparentlyrather influential action programme, equipment productivity, does not have significantinfluence on Q-F-S improvement, and the question is why. We do not have an answer.

Combination of quality, flexibility and cost performance. Programmes directedtowards process focus, pull production, equipment productivity and environmentalcompatibility are positively related to improving quality-flexibility-cost performance.The essence of the explanation has been given above.

Combination of quality, speed and cost performance. Improving qualitymanagement practices and environmental compatibility affect quality-speed-costperformance positively. Attempts to improve NPD, however, have a negative effect onthis performance combination. The most obvious explanation is that introducingstandardisation and especially modularisation, though possibly beneficial in the longerterm, involves a major and grossly underestimated change process, in spite of all theglossy stories currently being told. Some negative effects, especially on conformancequality, delivery reliability, manufacturing lead time, labour productivity and capacityutilisation, should therefore be expected, at least initially so.

Combination of flexibility, speed and cost performance. Companies that haveachieved a high degree of performance improvement in flexibility-speed-cost haveimplemented process focus, pull production, equipment productivity andenvironmental compatibility. Again, these programmes do exactly as they aresupposed to do.

Combination of quality, flexibility, speed and cost performance. Apparently a highdegree of improvement on all four categories of performance is associated with theimplementation of programmes aimed at process focus, pull production andenvironmental compatibility. Exactly why equipment productivity is missing in thislist is not clear to us.

DiscussionAction programmes directed towards improving environmental compatibility have asignificant positive effect on all combinations involving quality performance. This isnot surprising considering that environmental performance is one, relatively recent yetkey, aspect of quality performance (see Table II). Similarly, all performanceimprovement combinations including quality, except the combination of quality, speedand cost (Q-S-C), are positively affected by the implementation of either pullproduction, increased process focus, or both. Again, this is hardly surprising as bothpull production and process focus will have a positive effect on delivery reliability, one

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of the other aspects of quality (see Table II). We do not have a good explanation forwhy these two programmes do not appear to have a significant effect on the Q-S-Ccombination.

More surprising is the finding that action programmes aimed at improving qualitymanagement practices are only related to quality, speed and the combination ofquality, speed and cost (Q-S-C), but not to any of the other combinations includingquality. A possible explanation is that most companies today have solved the qualityproblem, especially as regards manufacturing conformance and also the mostlydesign-determined product quality and reliability. Putting more effort into improvingthese aspects of quality is likely to produce only marginal effects.

Flexibility, whether stand-alone or in combination with any other (set of)performance area(s), is affected positively by the implementation of process focus andpull production. Attempts to improve equipment productivity have the same effect,with the exception of the Q-S-F and Q-S-F-C combinations. A possible explanation isthat this action programme is too narrow. That is, especially in order to achieve qualityplus speed in addition to flexibility effects, this programme has to be combined withother actions. Programmes focused on the improvement of quality managementpractices seem to be the most obvious candidate.

All combinations in which cost performance is included, except Q-S-C and Q-S-F-C,are affected positively by actions aimed at improving equipment productivity. Thiscorresponds well with the main targets of equipment productivity programmes,namely reducing waste and increasing OEE. In many of these combinations, pullproduction and/or process focus also have a positive effect.

Which action programmes represent best practices?Process focus, pull production, equipment productivity and environmental compatibility.The combination of process focus, pull production, equipment productivity andenvironmental compatibility has a significant positive effect on three of the fifteen(combinations of) performance areas. Any combination of three of the fourprogrammes leads to significant improvement in another seven (combinations of)performance areas. A combination of two of the four programmes positively affectsthree combinations of performance areas. Only in the case of cost, and of cost combinedwith speed and quality (Q-S-C), a combination of these programmes does not show anysynergetic effect. This finding suggests that these four programmes should bequalified as best practice, that is, they support companies achieve significantimprovements in most performance areas and combinations thereof. Furthermore,these programmes seem to reinforce each other.

E-business, supplier strategy and outsourcing. E-business is the least adopted actionprogramme among the 14 studied here. The action programme is negatively related toall combinations of flexibility performance. That pattern indicates that companieshave problems gaining benefit of programmes directed towards e-business. This maybe due to the fact that the concept is rather new, especially in the engineering industry.Furthermore, it is not likely anyway that e-business will have a great impact on theperformance of manufacturing operations; the opposite effect, that manufacturing isone of the enablers of successful e-business performance, is much more likely. Weconclude that, from a manufacturing performance perspective, e-business is notcurrently a best practice.

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The impact of the supply chain management related action programmes supplierstrategy and outsourcing on manufacturing performance is rather limited. To be sure,especially outsourcing does have positive effects, mainly on cost, but they are notsignificant. The effects of supplier strategy on operations performance are muchweaker. As with e-business, the main reason could be that the effects of these actionplans are mostly outside the operations function. Anyway, the conclusion is thatespecially supplier strategy, but also outsourcing, do not appear best practices from anoperations performance perspective.

NPD improvement. Attempts to improve the NPD function have mixed effects onmanufacturing performance. The effects on flexibility and the combination offlexibility and cost are positive; the effects on quality, quality-speed, andquality-speed-cost are negative. NPD improvement does not have any significanteffect on any of the other performance areas. The mixed role of NPD is probably due tothe way we operationalised this action plan. Concurrent engineering, for example, andalso standardisation of components are likely to have positive effects. Platformthinking and modularisation, in contrast, may, certainly initially, produce negativeresults, due to the fact that these programmes require companies to review their wholeproduct portfolio, quite likely change at least part of the products, and also implementa range of organisational and managerial changes in order to make these practices asuccess. Learning about new products and practices is not for free. We conclude that,currently, NPD improvement does not qualify as a best practice.

Quality management. With new quality aspects, especially delivery reliability andenvironmental performance, playing an ever-more important role, and traditionalquality problems such as conformance quality and product reliability solved in manycompanies, the role of TQM as a best practice in the sense of contributing toperformance improvement is over these aspects of quality have become qualifyingcriteria, and their realisation a routine.

Other action programmes. Here the conclusion is straightforward: none of the otheraction programmes investigated in the IMSS III survey appears to produce anysignificant effect on performance improvement. These programmes are: implementingnew process equipment, increasing production capacity, process automation,implementing ICT, and work place development.

How valid are our conclusions?Table VI summarises our conclusions. The question is, how valid and complete theyare.

The analysis does make unambiguously clear that process focus, pull production,equipment productivity and environmental compatibility have a variety ofperformance effects and reinforce each other. Thus, these four action programmesinvestigated appear to represent best practice.

ICT and quality management, which may have been best practices in the past, havelost that status. Both are quite common in industry, and they do not distinguishanymore between high and low performers. It is routine to be and stay up-to-date inboth areas.

The status of NPD, e-business, supplier strategy and outsourcing is lessstraightforward. NPD produces mixed results. CE and standardisation seem to havepositive effects, while platform design and modularisation have a negative impact on

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performance. All practices underpinning NPD improvement programmes are actuallyquite complex, involving considerable changes in organisation, management and, quiteoften, products and possibly also in processes and technology. Furthermore, variouspractices are relatively new. So, our analysis suggests NPD improvement asoperationalised in this article is not a best practice. However, the programme mayactually well develop into a best practice. E-business does not produce significantmanufacturing performance effects. Similar to NPD, though, this action programmemay develop into best practice, however with manufacturing as an enabler. The directeffects on manufacturing performance will be limited while, conversely, a companyse-business success will greatly depend on its manufacturing performance. Two supplychain management practices, a well-developed supplier strategy and outsourcing, willaffect the functioning of operations and may have impact on manufacturingperformance, but such effects are not visible, yet. We conclude that NPD, e-business,

Action programme Best practice Remarks

Process equipment No No manufacturing performance effectsManufacturing capacity No No manufacturing performance effectsProcess automation No No manufacturing performance effects

ICT No longer

No manufacturing performance effects. Probably sowidely adopted that the programme does notdistinguish between high and low performers

E-business Possibly

Hardly any manufacturing performance effects.E-business success likely to depend on operationsrather than the other way around. May develop intosales best practice

Supplier strategy Possibly Hardly any manufacturing performance effectsOutsourcing Possibly Hardly any manufacturing performance effects

Process focus Yes

Strong manufacturing performance effects, oftentogether with pull production, equipmentproductivity and/or environmental compatibility

Pull production Yes

Strong manufacturing performance effects, oftentogether with process focus, equipment productivityand/or environmental compatibility

Quality management No longer

Hardly any manufacturing performance effects.Probable cause: the quality aspects covered arequalifiers. The underpinning practices have becomeroutines

Equipment productivity Yes

Strong manufacturing performance effects, oftentogether with process focus, pull production and/orenvironmental compatibility

Workplace development No No manufacturing performance effects

NPD Possibly

Mixed manufacturing performance effects: CE andstandardisation probably positive, platform designand modularisation probably negative. Potential bestpractice, though, but rather complex and difficult toimplement successfully

Environmental compatibility Yes

Strong manufacturing performance effects, oftentogether with process focus, pull production and/orequipment productivity

Table VI.Practices (14) and bestpractices (four)

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supplier strategy and outsourcing are not currently, but may develop into, bestpractices.

The other four practices, aimed at process equipment and manufacturing capacityimprovement, process automation and workplace development, respectively, do nothave any significant manufacturing performance effects and should therefore not beconsidered as best practice.

As to the influence of context on the choice of practices and their influence onmanufacturing performance, the study has focused on a limited set of industries (ISIC38), representing a variety of companies in terms of size and process type. An analysisnot presented in this article suggests that the influence of industry type is very weak,while size and product type do not play any role whatsoever. This means that thefindings are valid for all ISIC 38 companies, but whether they also hold for other typesof industry is not clear.

Finally, we believe this article presents an improvement in best practice research interms of its starting point: the best performing companies are the ones that (must) havethe best practices. Our findings seem valid for the fourteen action programmesinvestigated, in ISIC 38 companies, irrespective of process and size, at present.However, our analysis suffers from four weaknesses, each reducing the validity of thefindings. First, the study is based on, and only allows an evaluation of, pre-listedpractices. We cannot exclude the possibility that the best performers manufacturingperformance is based on additional practices, unknown to us. Second, the data suggestthat the four best practices identified reinforce each other. They do appear together, inpairs, trios or even as a quartet having a significant positive effect on manufacturingperformance. We are not sure though whether this is coincidence or not. A thirdweakness of the study is that it does not allow for an estimation of the potential ofemerging practices. Fourth, it is not clear whether or to what extent the findings alsohold for non-ISIC 38 companies.

ConclusionThe purpose of this article was to investigate what are the differences, in terms of theadoption of a range of action programmes, between the high and low performers in asample of 474 manufacturing companies from the IMSS III database.

High and low performers differ in terms of implementation width and depth ofaction programmes. Not only do the high performers implement more of the conceptscompared to the low performers, they also seem to be more committed to continueimplementing the programmes even if the results are not improved on the short term.

An apparently very strong configuration is process focus and pull production,combined, in many cases, with actions aimed at increasing equipment productivityand/or environmental compatibility. These action programmes currently representbest practice. Reinforcing each others effects, they contribute to improvement inall the four manufacturing performance areas addressed in this article.

NPD, e-business, supplier strategy and outsourcing are emerging practices, donot currently represent best practices, but may develop into that direction.

Former best practices, in particular quality management and ICT, have lost thatposition. They should now be regarded as a routine practice, supporting companies toqualify for the market place and, thus no longer distinguishing between the best andthe rest.

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Surprisingly many action programmes, notably process equipment andmanufacturing capacity improvement, process automation and workplacedevelopment, do not have a significant influence on manufacturing performance,either negatively or positively.

Weaknesses and further researchThe analysis presented in this article suffers from four weaknesses, which are relatedto:

(1) Completeness we tested a list of pre-defined practices but cannot exclude thepossibility that there are additional practices explaining the best performersmanufacturing performance. We propose the use of expert panels and openinterviews with manufacturing directors of highly successful companies toidentify such practices, and a survey study to test their role in and impact onmanufacturing performance.

(2) Interaction and implementation although our findings suggests thatimplementation width and depth makes the difference, further research isneeded to unravel how companies make various best practices reinforce eachother. We propose in-depth longitudinal case studies of implementationprocesses to find out more about this question.

(3) Predictive power new practices are emerging all the time, some of which willdevelop into best practices, others will not. Probably the only way to tackle thisproblem is identification of, followed by in-depth case studies at,innovators/early adopters.

(4) Contextuality we checked the influence of industry type, company size andprocess type, did not find these factors to exercise major influence, but cannotexclude the possibility that a wider set of industry sectors and also othercontingencies not included in the present analysis will produce a differentpicture. Further survey-based research involving a broader set of industries andinquiring a wider set of contingencies will contribute to addressing thisproblem.

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Further reading

Collins, R.S., Cordon, C., Cornaz, J.L., Eugster, H.R., Gemoets, O.G., Jakob, R., Julien, D. andStucheli, G. (1996), Made in Switzerland: A Benchmarking Study of Manufacturing Practiceand Performance in Swiss Industry, IBM, Zurich.

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Dixon, J.R., Nanni, A.J. and Vollman, T.E. (1990), The New Performance Challenge: MeasuringOperations for World Class Competition, Dow Jones-Irwin, Homewood, IL.

Miles, R.E. and Snow, C.C. (1978), Organisational Strategy, Structure, and Process, McGraw-Hill,New York, NY.

Rathuria, R. and Partovi, F.Y. (1999), Work force management practices for manufacturingflexibility, Journal of Operations Management, Vol. 18, pp. 21-39.

(Bjrge Timenes Laugen is a PhD student at the Department of Business Administration atStavanger University College, Norway. He received his MSc in engineering from AalborgUniversity in 2000. His main research interest is the link between new product development,production, organisational development and continuous innovation.

Dr Nuran Acur is a graduate of Yildiz Technical University, Turkey, where she gained a BScin Statistics. This was followed by a Masters degree in Statistics from Istanbul University. Thefollowing year she came to the University of Strathclyde (UK), where she gained a PhD inStrategic Management. After graduation, she joined Worldmark as an Engineering Consultant.During this period she developed a detailed understanding of Strategic Management and QualityManagement. In 2002 she joined Aalborg University. Her current research focuses onbenchmarking, operations management and strategy.

Dr Harry Boer is Professor of Organisational Design and Change at the Center for IndustrialProduction at Aalborg University, where he teaches various courses in organisation design andchange, operations and service management and innovation management. He also teaches at theMBA programmes at TSM Business School, The Netherlands, and Politecnico di Milano, Italy,the EurOMA Doctoral Consortium and the CINet Doctoral Seminar on Research in ContinuousInnovation. His main research interest is in resourcing, organising and managing the linkbetween day-to-day operations, continuous improvement/learning and radical innovation, so asto improve both the short-term and the long-term performance of industrial companies. HarryBoer has written numerous articles and (co-)authored four books in the fields of organisationtheory, operations management and strategy, innovation management, and continuousimprovement.

Dr Jan Frick is Associate Professor at School of Hotel and Business Management, StavangerUniversity College. He holds an MSc in Operations Management and ICT from the NorwegianInstitute of Technology in Trondheim, Norway, and a PhD in Industrial Production fromAalborg University, Denmark. Jan Frick has previously worked at the research institutesSINTEF and Rogaland Research Institute and at the industrial collaboration institutions Jrtekat Bryne, and TESA at Sandnes, all in Norway. He has managed several Norwegian andinternational research projects, and published at several international conferences, journals andbook chapters. Jan Frick is member of the IFIP workgroup 5.7 Integration in ProductionManagement.)

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