International Journal of Operations & Production ManagementEmerald Article: Is lean manufacture universally relevant? An investigative methodologyS.M. James-Moore, A. Gibbons

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To cite this document: S.M. James-Moore, A. Gibbons, (1997),"Is lean manufacture universally relevant? An investigative methodology", International Journal of Operations & Production Management, Vol. 17 Iss: 9 pp. 899 - 911

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Is lean manufacture

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Is lean manufactureuniversally relevant?

An investigative methodologyS.M. James-Moore and A. Gibbons

Warwick Manufacturing Group, University of Warwick, Coventry, UK

Aims and backgroundThe concept and acceptance of lean manufacture as a set of principles is nowfairly rooted in the literature[1-3]. The principles behind lean production are notin themselves new; many of them can be traced back to the work of pioneerssuch as Deming[4], Taylor[5], Skinner[6] and more recently in the UK suchinvestigators as Hill[7], Voss[8], and Lamming[9] . However, although theconcept of lean production as now understood could have modelled from thisliterature, it was not until the Japanese auto industry was studied[1], that thetotal concept became clear.

While there are some voices of discontent[10,11] to the adoption and ultimateeffectiveness of lean production, nonetheless many case examples exist todemonstrate how companies are changing their production methods andmanagement practices to become leaner and fitter. Indeed lean manufacture hasbeen extended to encompass the whole spectrum of activities in the businesssuch that world-class companies are seeking to become lean enterprises[9,12,13].

However, both the original work and subsequent offerings have tended torestrict their field of analysis to similar industrial sectors, namely, high-volumeor mass producers, in particular the automotive and electronic sectors. Littlepublished work[14,15] seems to have explicitly addressed the issue of whetherlean methods are suitable and applicable in industrial sectors which arecharacterized by highly differentiated, low-volume production of lowrepeatability. For want of a better term, we shall refer to such products as “supervalue goods”(SVG), since one of their defining characteristics[16] is the highvalue added through the total supply chain and hence the market price of theproduct. Examples of such products would include: power generation,aerospace airframe and engine manufacturers and the like. In order to fill thisgap, researchers at Warwick Manufacturing Group (WMG)[17], embarked on acase study based investigation to compare and contrast the methods andpractices currently being adopted in a potential SVG sector (civil aerospace)with a typical lean manufacture sector (automotive). This paper describes thein-company methodology developed and some of the main findings of theresearch.

International Journal of Operations& Production Management,

Vol. 17 No. 9, 1997, pp. 899-911. © MCB University Press, 0144-3577

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Lean manufactureWhile much has been written on the subject of lean manufacture, the modelswhich exist to collect all the information available on operational practices andperformance which constitute lean manufacture and place them into a unifyingframework, are somewhat complex. Hence the first stage of the research was todevelop a model which could then act as the template from which to guide thedata collection and assess the status of an SVG company.

To begin, a definition of lean manufacture needed to be established. In simpleterms lean manufacture was defined by Womack et al.[1], as follows:

• integrated, single piece production flow, small batches, just-in-timegiving low inventory;

• defect prevention not fault rectification;• production pull not push with smoothed demand;• flexible, team-based work organization with multi-skilled workforce and

few indirects;• active involvement in root cause problem solving to maximize added

value;• close integration from raw material to customer through partnership.

We added what we believed to be one further ingredient based on the work ofClarke and Fujimoto[18]:

• greatly reduced overhead burden by the use of matrix teams, simplifyinginformation flow and processing, enabling flatter organizationstructures.

These attributes represent, at a high level, what could be described as the bestpractice principles that you would expect to see in a high-volume leanmanufacturing company.

Context and structureHowever, such principles are in fact the outcome of recognizing the externalbusiness context and drivers facing the individual sector. Consequently, theframework shown in Figure 1 was used to structure the development of thedetailed research methodology.

The key aspect of this framework is the reinforcement of the linkagesbetween drivers in the business environment and the strategic responses tothese. Hence the core business processes, practices adopted and finally theappropriate key measurement attributes, used either as a control or as a meansof comparing performance, are consequent on the environment drivers.

Thus we are adopting the view that lean manufacture practices andmeasures are the response by “best in class” companies to their changingenvironment.

Having established the guiding top-level structure, more detail was placed oneach of the key areas of interest in Figure 1. Porter’s Five Forces model was used

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and adapted to direct and summarize the collection of publicly availableinformation on the industry environment and drivers. This was ascertained forboth the aerospace and automotive sectors. In the case of the applied work, theinformation was later cross-checked with the views with key senior managersin the civil aerospace industry.

This information was important, as it set the context into which the intendedstrategic and operational responses in the sector were handled. In addition , astructured interview process was developed to ascertain how the case studycompanies had developed their strategic direction and if, as a result, they hadevolved any critical success factors or equivalent for their companies.

For the civil aerospace companies visited five core drivers (CSFs) wereidentified, namely:

(1) We must be more responsive to customer needs.

(2) We must reduce our costs.

(3) We must meet customer quality expectations.

(4) We must ensure we use our people more effectively.

(5) We must improve our partnership management.

These drivers were confirmed during the research from a survey by IngersollEngineers[19] into civil aerospace. Both our research and that by Ingersollindicated that the drivers in civil aerospace had changed and become muchmore closely aligned to those well-recognized by the automotive volumeproducers.

Internal company characteristicsFrom here the researchers concentrated their attention on the area containedinside the box in Figure 1, in other words, the important internal companycharacteristics.

Figure 1.Environment drivers

Strategic objectives andcritical success factors

OrganizationBusiness vision and

mission

Corebusiness

processes(A)

Measurementattributes

Business practices(B)

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A simple process model of an automotive company model was defined ashaving six core processes in addition to the strategy formulation aspectsalready described above. These processes were:

(1) new product introduction;

(2) manufacturing;

(3) logistics (including purchasing);

(4) sales and marketing;

(5) product support;

(6) people management.

Of course, this process specification is rather arbitrary and indeed companiesmay adapt many different organizational structures and processes to delivertheir core business activity. We also recognized that currently many companiesare actively re-engineering their business and deciding on the most appropriateprocess. However, for our purposes, we simply needed some classificationstructure to guide the data collection.

The next step was to capture the characteristics likely to be found in atypical lean automotive company based on the literature and the authors’industrial experience. It is true that the model developed does not represent anyone specific automotive company but a hypothetical company operating at fullcompliance with the perceived best practice measures. These measures beingdetermined from the theoretical and empirical literature and case studies suchas Womack et al .[1] and the Andersen Consulting Lean Enterprise Reports[20].This resulted in an initial non-quantified vision of a lean company showingcharacteristics in five areas, namely:

(1) flexibility;

(2) waste elimination;

(3) optimization;

(4) process control;

(5) people utilization.

These characteristics enabled a direct link to be made with the previouslystated definition of lean principles.

These five areas were expanded on, such that Figure 2 captures the specificcharacteristics which would contribute towards the achievement of leanness ina best-in-class company. These characteristics would be observable to aninformed visitor to such a company and, as such, enable an assessment of theextent of leanness in different processes within a company.

We were then in a position to draw all this information together and producea set of research methodology documents, which formed the hypotheticaltypical lean automotive producer. This became the bench against which theSVG case study companies could be compared. The final result was a set of pro

Is lean manufacture

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forma documents for each key process. An example, based on part of the newproduct introduction process, is given in the Appendix. It is at this level thatcommon adoption of practices and measures were compared against a leanmodel.

This format was used to structure questions for employees in the companiesvisited. First, respondents were asked to rate the key drivers identified on ascale of 1 to 3 in terms of their relevance to their organization, where 3 equalshigh relevance.

Second, the respondents were asked to describe the practices they used torespond to those drivers, ensuring that the specific practices identified on thepro forma were established as being used or not. While respondents did notalways respond with a simple yes or no, for analysis purposes it was necessaryto record either a positive or negative answer. This approach also ensured thatpractices not covered in the pro forma were captured and the reasons associateddocumented.

The third part of the process related to whether any formal measurement ofthe effectiveness of the practice described took place and, if so, what were theunits of measurement. Again, for analysis, a simple yes or no answer wasrequired.

The advantages of this approach to the development of the documents is thatit provided a logically and strategically coherent picture and showed the keypractices being adopted by such organizations to respond to their drivers,coupled with specific metrics where known, at the second level of influence. Forexample, taking a high-level driver such as the need to improve responsiveness

Figure 2.Lean automotive vision

model

Wasteelimination Flexibility

PeopleProcesscontrol

Optimization

Customer

High productivity

Effective energy useLow warranty

Low time through system

Focused marketing No overproduction

Low distance travelledLow system inventory

High yieldHigh supplier quality

Constancy of purpose

SPC used widelyControl of 6Ms

Controlled production servicing

Total productive maintenance

Design for lean manufacture

Schedule adherence

Poka Yoke

IntegrationEffective R&D

Controlled complexity

Financial optimization

Outward lookingTrue costs known

Neutral cash flowDealer partnership

Supplier partnershipEffective IT Learning

People management

Stable employment

Respect for humanity

LeadershipHousekeeping

EmpowermentEmployee contribution

Real teamworkFlexible facilities

Multiskilled workers

Build to customer orderSupplier flexibility

Quick setup timesShort product development time

Product mix neutral

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to customer needs, this results in lower-level operational-focused drivers, suchas reducing the time of introducing new product and thus the adoption ofpractices such as shelf engineering to ensure this is achieved.

Hence in the extract shown (see Appendix) for the process underinvestigation, namely new product introduction, time to market is one externaldriver and the company response being investigated. If this proves to be ahighly relevant driver in the specific industry, then the researcher would expectto find a number of supporting practices, such as the use of shelf engineeringand presumably a number of measures to support and monitor this practice,e.g. the time from initial idea, etc.

Adopting this procedure resulted in a generic model of a companyresponding to 38 drivers, using 76 key practices and 68 performance metrics.These performance metrics were developed from published data[1], updated byresearch done in Rover and more recent benchmarking metric reports[20]. It didnot represent any specific company and indeed no one company would agreethat all the issues applied to them in the same way. Nevertheless, any companyoperating within the parameters included would be classified as “lean” by ourdefinition.

In company investigationThis model formed the company-based investigation tool kit for retrieving theinformation. At any one time, a team of two researchers spent five days onaverage in each of the companies. Interviews were conducted with over 100senior and middle-ranking executives in the companies across each of theindividual business processes identified in the model. In addition, unstructureddiscussions were held with many employees at the operational level, to addrichness and context to the data collected.

To validate the responses required the research team to observe an examplepractice or measure, even though it may be newly implemented or of limitedapplication. This was normally achieved by a combination of observing in-company paper work or by observing the practice or measure during visits tothe working areas, both in office and manufacturing environments, wherediscussions with operating personnel were held.

The information given was confirmed before analysis by sending, within 15working days, each participating company a verbatim copy of the case studyvisit findings for their comment, clarification or correction.

ResultsFrom the responses, a scoring system was put in place to establish the averagescore within a company and between companies. For usage of the practices andmeasures, a yes or no answer was expected. A yes response was given a scoreof 1, a no response was given a score of 0. As expected, often a practice ormeasure was not fully used within a company. Alternatively, more than onerespondent would answer the question. A maximum of three respondents inany one company per question, was encountered. The total scores were divided

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by the total respondents to ascertain the average level of alignment across thecompanies for each practice or measure and grouped into high, moderate or lowcategories. This enabled an analysis of company views between companies tobe undertaken and differences considered.

Prior to the company visits, based on our analysis of the likely similarity ofcivil aerospace drivers compared to those of volume automotive producers[21]and the wide availability of literature on lean manufacture, we expected a priorithat a substantial percentage of lean practices would have been adopted and wearbitrarily chose 50 per cent as a cut off.

In the light of the actual results this proved to be too simple a split. Anarbitrary scoring system was therefore used to provide a basis for analysis,grouping the average scores into high, medium or low correlation to the leanmodel. The aim of this somewhat simple and arbitrary evaluation procedurewas to provide a method of analysis which enabled comparison with the modeland between companies without ambiguity. The aim was to identify majordifferences in approach which could form the basis for more detailed researchand to assess the areas where there was little doubt of the benefits.

A score greater than 0.65 indicating high agreement with the attribute underinvestigation. A score greater than 0.45 indicating medium agreement with theattribute under investigation. A score less than 0.45 indicating low or noagreement with the attribute under investigation.

These results were then expressed as charts, and differences and similaritiesbetween companies considered and discussed, using the notes taken at thestructured interviews. Taking the adoption of practices as an example, Figure 3shows data applied to the new product introduction process only.

Figure 4 shows a summary chart of the use of lean model practices across allthe processes investigated in the industry. This enabled analysis to be carriedout both at the macro and micro levels. Figure 3 also shows that of the 16practices likely to be found in a typical lean volume automotive company in the

Figure 3.Adoption of lean

practices in new productintroduction average

Score (per cent)100

90

80

70

60

50

40

30

20

10

01 2 34 5 6 7 8 9 10 12 13 14 15 16Practice

Medium

High

Low

11

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new product introduction process, 11 of them (i.e. 69 per cent) had a high levelof adoption in the civil aerospace companies investigated. Similarly 13 per centhad a medium level of adoption and only 18 per cent had a low adoption level.

Figure 4 shows the aggregate situation for practices across all processes. It canbe seen that of the 68 practices which a typical lean automotive manufacture islikely to be using, some 41 per cent of the total were assessed as having a highlevel of adoption (scoring > 0.65) and a further 15 per cent a medium level ofadoption, leaving 44 per cent of practices at a low level of adoption.

Of course, it is possible that the level of implementation of various practicesand measures could vary not only between companies, but also within any onecompany over time. The latter would occur due to the dynamic nature of thediffusion of innovation. In terms of company transferability of lean practicesand measures, it is important to know:

• where the company stands today.• where it intends to go in the future.

Given that the data were collected for the case study companies within arelatively short time horizon and were based only on what was actuallyhappening as opposed to capturing their “wish list”, then the results will onlycapture the static (1) rather than the dynamic (2) aspect.

Hence the results for either medium or low adoption categories could merelybe picking up lags in the diffusion process. This is interesting in itself aswhether one practice had assumed a higher importance than another to adopt,or whether some practices were more difficult to apply.

Some further investigations surrounding, in particular, those practices withlow adoption were carried out to provide some light on this, as will be discussedlater on.

Summary results from the methodologyFinally, the total results for drivers, practices and measures for the aerospacecompanies surveyed can be assessed as shown in Table I.

Figure 4.Analysis example allprocesses

Score (per cent)100

80

60

40

20

01

Practice

4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67

High adoption

Low adoption

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This indicates that over 90 per cent of the drivers impacting on a typical leanautomotive industry are seen to have some relevance to the civil aerospacesector as measured by the strong and moderate categories. Yet the use ofpractices and measures in response to these drivers is only 48 per cent and 54per cent respectively in the aerospace companies investigated. There is clearlya substantial gap and from the initial investigations within the UK aerospacecompanies, it became apparent that the two customer interface processes,namely sales and marketing and service and product improvement, were verydifferent from lean automotive experience.( For example, excluding executivejets, it was stated that the number of people with the authority to buy civilaircraft numbered between 300 and 500 worldwide. Thus the whole salesprocess was much longer, involved more people per sale, had a greater technicalcontent, involved detailed lifetime cost analysis over periods up to 15 years, etc.– significantly different from the way most people buy cars, other than possiblythe UK fleet buyer).

So by excluding these two processes, the revised results become as shown inTable II.

This changes the figures to 97 per cent of the drivers are relevant and yetonly 57 per cent of the practices and 56 per cent of the measures respectively arebeing used to a significant level in the companies. While there is someintensification in driver relevance and the practices and measures considereduseful to adopt, the impact is not substantial. This may reflect the fact thateither the civil aerospace companies have not yet completed their lean journeyand/or that the practices and measures are not thought applicable.

In support of the latter conclusion, key differences emerged surrounding theissues of:

• new product refinement for manufacture;

• sales and marketing;

Driver relevance % Practice use % Measure use %

High 62.0 30.0 26.5Medium 31.0 18.0 27.5Low 7.0 52.5 46.0

Table I.All process results

Driver relevance % Practice use % Measure use %

High 68.5 41.0 24.0Medium 28.5 16.0 32.0Low 3.0 43.0 44.0

Table II.Process results

excluding sales, marketing, service and product improvement

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• ability to predict and control costs;

• operations management.

In these areas the adoption of lean practices and measures was not as widelyused. Consequently the average of the results was lower.

Further investigation showed that key differences emerged in these lowadoption areas:

(1) New product refinement for manufacture:• difficulty in refining the manufacturing process prior to initial sale;• greater importance of solid modelling and digital definition; and• difficulty in fully shelf engineering feature prior to product sale.

(2) Customer interface• importance of external finance to sales; and• long product life and the many years of product support demanded.

(3) Ability to control costs• limited use of full target costing, which may be due to the perceived

complexity of the product;• uncertainty of the use of full open book purchasing;• greater global sourcing of large subassemblies and parts, rather

than systems creating complex logistical chains;• time span of control on much work is long; and• manufacturing not key owners of in-field quality.

(4) Operations management• lower importance given to manufacturing complexity (e.g. the cost

impact of handling large numbers of part at one location isconsidered critical to lean auto producers – less so with theaerospace companies visited);

• MRP under question, balanced production not possible;• impact of late changes to specification( airframers only);• more prescriptive method of defining quality – partly regulatory;• higher technical support required for support of manufacturing

cells; and• structurally not possible to provide labour stability due to cyclicity

and non-integrated supply chains.

Thus it is likely that the product derived unique characteristics of SVGcompanies producing low-volume highly differentiated products with lowrepeatability may help to explain the low level of practice adoption in these fourkey areas rather than as a result of lags in the diffusion process. This conclusion

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should be treated with caution since it is based on the aerospace sector at apoint in time and ideally more SVG products need investigating before a genericstatement can be made. Also, the move in many of the companies visited toreduce the uniqueness of the engineering of their products, while still providingcustom product for their customers, may speed up adoption in the future.Again, the relevance of this approach to other SVG goods would needinvestigation.

ConclusionThese results, while tentative, have helped to focus on areas of research wheredifferences exist and have confirmed to participating companies key areas tomaintain the implementation of lean approaches and those in which a certainamount of modification will be required or even a fundamentally differentapproach needed.

The methodology itself proved a useful method for establishing the relativeimportance of operational drivers in the business and comparison of therelevance of practices and their control between companies in two apparentlyvery different industries. The authors consider that the approach could be usedto carry out such comparisons over a wide range of industrial operations,identifying areas where significant research is required to identify best practiceand highlighting those where the effort should be on implementation. Thiscould add much-needed research to our level of understanding of the suitabilityand applicability of lean manufacturing approaches to a wide range of super-value goods producers.

Notes and references1. Womack, J.P., Jones, D.T. and Roos, D., The Machine that Changed the World, Rawson

Associates, 1990.2. Krafcik, J.F., “Triumph of the lean production system”, Sloan Management Review, Vol. 30

No. 1, 1988.3. Monden, Y., Toyota Production System, Norcross, GA, 1983.4. Deming, W.E. Many of his works, the principles perhaps being best captured in Out of the

Crisis, Quality, Productivity and the Competitive Position, Cambridge University Press,Cambridge, 1986.

5. Taylor, The Principles of Scientific Management, Harper Bros, New York, NY.6. Skinner, W., “Manufacturing – missing link in corporate strategy”, Harvard Business

Review, May-June, 1969.7. Hill, T., Manufacturing Strategy – The Strategic Management of the Manufacturing

Function, Macmillan, 1993.8. Management & New Production Systems, International Journal of Operations &

Production Management, Vol. 14 No. 3, 1994, Voss and Karlson (Eds), in particular, Voss,C.A., Chiesa, V. and Caughlan, P., “Developing and testing benchmarking in self-assessment frameworks for manufacturing”.

9. Lamming, R., Beyond Partnership – Strategies for Innovation and Lean Supply, Prentice-Hall, London, 1993.

10. Gordon, T. “The underlying fallacies of lean and mean, The Ironbridge group, USA”,BPICS CONTROL, August 1995.

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11. Berggren, Alternatives to Lean Production, ILR Press, Ithaca, NY, 1992.12. Harrison, A., Just-in-Time Manufacturing in Perspective, Prentice-Hall, London, 1992.13. Jones, D.T., “Managing lean processes and lean logistics”, Logistics Technology

International, 1994.14. Jina, J., Bhattacharya, A.K. and Walton, A.D., “High product variety and low volumes: a

challenge for lean manufacturing”, 28th ISATA Conference, Stuttgart, September 1995.15. “McDonnell Douglas – Bigger & Better”, Flight Magazine, February 1995.16. Gibbons, A. and Nelson, M. “The importance of super value goods to Britain’s

manufacturing sector in the future”, internal Warwick paper awaiting publication. Thedefinition of a super value good is fully developed in this article.

17. Gibbons, A., Walton, A., Manton, S. and Bhattacharya, S.K., principal investigators, James-Moore, S.M.R., Chapman, P. and Nelson, M., researchers, EPSRC ref. GR/J96772.

18. Clarke, K.B. and Fujimoto, T., Product Development Performance Strategy, Organizationand Management in the World Auto Industry, Harvard Business School Press, Cambridge,MA, 1991.

19. “Stacking up to compete”, an international survey of critical success factors in the civilaircraft manufacturing industry survey by Ingersoll Engineers, Rugby, 1994.

20. Andersen Consulting, Cardiff Business School and University of Cambridge, The SecondLean Enterprise Report, 1992, published 1994.

21. Chapman, P. and Gibbons, A., “An assessment of civil aerospace drivers using Porteranalysis”, internal Warwick paper and James-Moore, M., internal Rover paper on“Automotive industry drivers based on lean literature and benchmarking visits”.

Appendix. Exemplar survey questionnaire for part of one processNew product introduction – the process of design and development of new products andtechnologies to meet a defined market need to the point of initial manufacture

Used Used Relevance or not ? or not?

Key drivers 1-3 Practices yes or no Measures yes or no Values/targets

Is the time it takes Do you develop Do you measure BIC: 24 to introduce a new technologies the length of monthsnew product to before introducing time from initial the market key? them into new idea to (Fashion/ products (i.e. programme Legislation) do you always approval?

shelf engineer)?

In developing Do you measure BIC: 33%new products is the ratio of the responsibility number of initial given to a large concepts to the project leader? number finally

approved?

(Continued )

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Used Used Relevance or not ? or not?

Key drivers 1-3 Practices yes or no Measures yes or no Values/targets

For new projects Do you measure BIC: 20 do you use a the time from monthsmulti-functional programme team? approval to initial

volume production?

In developing Do you measure the new products % of your product do you have designed by supplierssupplier guest engineers working in-house with your design group?

How relevant to Do you use solid Do you measure you is the use of computer the % of your computer aided modelling? product designed design? on a computer?

Do you use computers for adding parametrics?

Do you buy complete systems, not components, when developing new products?