Criteria for a Lean Organization - Development of LAT

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Criteria for a lean organisation: development of a leanassessment toolFatma Pakdila & Karen Moustafa Leonardb

a Industrial Engineering, Baskent University, Ankara, Turkeyb Management, University of Arkansas Little Rock, Little Rock, AR, USAPublished online: 05 Feb 2014.

To cite this article: Fatma Pakdil & Karen Moustafa Leonard (2014) Criteria for a lean organisation: development of a leanassessment tool, International Journal of Production Research, 52:15, 4587-4607, DOI: 10.1080/00207543.2013.879614

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Criteria for a lean organisation: development of a lean assessment tool

Fatma Pakdila* and Karen Moustafa Leonardb

aIndustrial Engineering, Baskent University, Ankara, Turkey; bManagement, University of Arkansas Little Rock, Little Rock, AR, USA

(Received 12 November 2012; accepted 20 December 2013)

Lean principles have long been recognised as a competitive advantage. Although there are several measures for variousaspects of lean production in the literature, there is no comprehensive measure for overall lean implementation inbusiness firms. An appropriate measurement tool is needed to assess the effectiveness and efficiency of the leanimplementation throughout the entire organisation. Based on lean research, a comprehensive tool called the leannessassessment tool (LAT) is developed, using both quantitative (directly measurable and objective) and qualitative (percep-tions of individuals) approaches to assess lean implementation. The LAT measures leanness using eight quantitativeperformance dimensions: time effectiveness, quality, process, cost, human resources, delivery, customer and inventory.The LAT also uses five qualitative performance dimensions: quality, process, customer, human resources and delivery,with 51 evaluation items. The fuzzy method allows managers to identify improvement needs in lean implementation,and the use of radar charts allows an immediate, comprehensive view of strong areas and those needing improvement.Practical uses of the LAT are discussed in the conclusion, along with possible limitations.

Keywords: leanness; lean implementation; lean operations; lean manufacturing; performance measures; performanceanalysis; quality management; Toyota production system

Introduction

Increased competition and customer expectations require organisations to gain powerful competitive advantages in theglobalised marketplace. Although a variety of tools and methods that can be used to increase competitive advantages,lean production principles and methods have been shown to be one of the most effective (cf. Abdulmalek and Rajgopal2007; Hino 2006; Li 2013; Liker 1998, 2004; Womack and Jones 1996; Womack, Jones, and Roos 1990) for manufac-turing (cf. Deflorin and Scherrer-Rathje 2012; Ehret and Cooke 2010; Ferdousi and Ahmed 2010; Hunter, Bullard, andSteele 2004) and service organisations (cf. Laureani, Antony, and Douglas 2010; Liker and Morgan 2006; Nicholas2012). Womack, Jones, and Roos (2007, 11) stated:

Lean production is ‘lean’ because it uses less of everything compared with mass production-half the human effort in factory,half the manufacturing space, half the investment tools, half the engineering hours to develop a new product in half time. Also,it requires keeping far less than half the needed inventory on site, results in many fewer defects, and produces a greater andever growing variety of products.

Lean implementation comprises organisation-wide lean practices (Mann 2005; Wilson 2010). To be successful, leanimplementation for competitive advantage requires organisations to apply lean principles in all organisational functions,including accounting, sales and marketing, and human resources.

There is an increasing interest in lean implementations (Saurin, Marodin, and Ribeiro 2011). The literature has manyempirical studies (cf. Doolen and Hacker 2005; Panizzolo 1998; Shah and Ward 2007) and review papers (cf. Behrouziand Wong 2011; Bhasin 2008, 2011) of lean assessment, but most do not concentrate on overall lean implementationwithin a qualitative and quantitative perspective. We examine these issues in the light of the following question: inassessing the success of lean implementation, which key dimensions are needed? To answer the question, the keydimensions of lean implementation identified in the literature are determined, and a measurement instrument developed.

This paper first examines existing literature on lean concepts. Following this review, a lean assessment tool (LAT) isdeveloped to use both quantitative (i.e. directly measurable and objective results) and qualitative (i.e. using perceptionsof individuals) measures of lean implementation progress and/or success in the entire organisation, with fuzzy logic

*Corresponding author. Email: [email protected]

© 2014 Taylor & Francis

International Journal of Production Research, 2014Vol. 52, No. 15, 4587–4607, http://dx.doi.org/10.1080/00207543.2013.879614

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mailto:[email protected]

http://dx.doi.org/10.1080/00207543.2013.879614

methodology. The use of a radar chart approach with the LAT analysis is also discussed, along with conclusions, practi-cal application and limitations of the tool, and suggestions for future research.

Lean concept

Lean implementations have been analysed for more than four decades in both academic and practitioner journals (Hossand Schwengber ten Caten 2013). The word lean was introduced by Krafcik (1988) to describe Toyota’s productionsystem (TPS). Lean is an ongoing drive toward perfection, sometimes difficult to envision because it is a major para-digm shift (Wilson 2010). ‘At the heart of lean is its philosophy, which is a long-term philosophy of growth by generat-ing value for the customer, society, and the economy with the objectives of reducing costs, improving delivery times,and improving quality through the total elimination of waste – muda’ (Wilson 2010, 59).

Lean production is the philosophy of eliminating waste (Heizer and Render 2004) or the creation of a lean andbalanced flow in a process (Stevenson 2007). The lean production concept identifies extremely efficient and effectiveproduction systems that consume fewer resources, creating higher quality and lower cost as outcomes. Using bothpractical and project-based perspectives, a key strategy is the elimination of waste (Pettersen 2009).

The TPS is the most successful production applications of the lean concept. TPS has been called ‘just-in-time (JIT)’,and more recently, ‘lean production’ (Womack, Jones, and Roos 1990), the common term in the West. Although thesepractices started in Japan, lean implementation is now the primary improvement methodology in the US manufacturing.

Management based on lean production principles enables firms to gain increasingly high levels of efficiency, com-petitiveness at the lowest cost, with high levels of productivity, speed of delivery, minimum stock levels and optimumquality (Cuatrecasas Arbós 2002). Eliminating waste lowers variable production costs associated with labour, materialsand energy, thus raising the unit profitability of products. Lean also attacks waste associated with the fixed costs offacilities, equipment, capital and support such as management, engineering, and so on (Swink et al. 2011, 239).

Liker (2004) identified two pillars and 14 principles of TPS. The two pillars of TPS are continuous improvement(kaizen) and respect for people. Under the two pillars are 14 principles, which have been categorised under the fourgroups of (1) philosophy – long-term, (2) process – promote flow, (3) people and partners– respect and developmentand (4) problem solving – continuous improvement. The details of 14 principles are given in Table 1.

Table 1. Liker’s (2004) fourteen principles.

Group Principal

Philosophy – Long term 1. Base your management decisions on a long-term philosophy,even at the expense of short-term financial goals

Process – Promote flow: creating a pull production system thathas continuous flow and balanced workload

2. Create a continuous process flow to bring problems to thesurface3. Use pull systems to avoid overproduction4. Level out the workload (heijunka)5. Build a culture of stopping to fix problems, to get quality rightthe first time6. Standardized tasks are the foundation for continuousimprovement and employee empowerment7. Use visual control so no problems are hidden8. Use only reliable, thoroughly tested technology that serves yourpeople and processes

People – Respect and development 9. Growing leaders who thoroughly understand the work, livingthe philosophy, and teaching it to others10. Developing exceptional people and teams who follow yourcompany’s philosophy11. Respecting your extended network of partners and suppliers bychallenging them and helping them improve

Problem solving – Continuous improvement: organise theircontinuous improvement activities

12. Go and see for yourself to thoroughly understand the situation(genchi genbutsu)13. Make decisions slowly by consensus, thoroughly consideringall options, implement decisions rapidly14. Become a learning organization through relentless reflection(hansei) and continuous improvement (kaizen)

4588 F. Pakdil and K.M. Leonard

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Leanness creates a tremendous sustainable competitive advantage (Womack, Jones, and Roos 1990) and leanimplementation is used as a tool to gain competitive advantage, but

… the lack of a clear understanding of lean performance and its measurement is a significant reason that lean practices havefailed. In other words, it is not possible to manage lean without measuring its performance. (Behrouzi and Wong 2011, 388)

Deming (1986) and Imai (1986) emphasised that the overall performance of the new or current applications and systemsmust be measured and monitored continuously through various performance measures. With a broader continuousimprovement perspective, measuring performance is not a need just for lean organisations, but for any organisation.Because ‘leanness is a process, a journey, not an end state’ (Liker 1998, 8) and ‘if you can’t measure it, you can’t man-age it’ (Shaw and Costanzo 1970), assessment is essential to identify both the deficiencies and progress of lean conceptswithin firms.

Some studies in the literature (cf. Bayou and De Korvin 2008; Goodson 2002; Singh, Garg, and Sharma 2010) focuson measuring the leanness of management systems and emphasise the need for a unifying measure of the effects ofthese practices. Bhasin (2008, 674) states that ‘companies need to understand how key performance measures can guideand focus an organisation towards superior results in their chosen area’. Similarly, Saurin, Marodin, and Ribeiro (2011)identified the importance of implementing lean assessment during the early stages of lean practices. With these ideas inmind, an assessment tool is proposed in the following section.

Lean assessment tool

After conducting a comprehensive literature review to look into the relevant concepts in detail, a LAT was developed.Searches used a variety of databases, such as EBSCO host, Wiley, Taylor & Francis, Emerald, and Science Direct. Theyalso included published books and graduate theses published online. Keywords used in the search were ‘lean assess-ment’, ‘lean evaluation’, ‘lean appraisal’, ‘lean performance’, ‘measuring lean performance’, ‘lean performance measure-ment’ and ‘lean measurement’. The literature was analysed in detail, but there were limited studies on lean assessment:30 articles, 2 graduate theses and 9 books. Interestingly, none of the books (cf. Dennis 2002; Wilson 2010; Womackand Jones 1996) included a particular chapter or materials to enable quantitative assessment of managerial or organisa-tional leanness. Only Mann’s (2005) book, titled Creating a Lean Culture, had an appendix on qualitative lean assess-ment. In research for this paper, each relevant study was analysed in terms of lean assessment approaches. As anoutcome of the comprehensive literature review, a matrix diagram overview of the current lean assessment tools, meth-ods and techniques available in the literature is presented in Table 2, demonstrating the dimensions used in each.

Existing lean assessment tools or methods in the literature have weaknesses and strengths. Devlin, Dong, and Brown(1993) stated that there are no ‘best’ or ‘perfect’ studies or methods to measure quality performance. As a generalcritique of the literature, each existing lean assessment method focuses on a different side of lean operations, not thecomplete picture. While some of the tools or methods focus only on perceptions of the employees, using a qualitativeapproach (Bhasin 2011; Connor 2001; Doolen and Hacker 2005; Feld 2000; Fullerton and Wempe 2009; Goodson2002; James-Moore and Gibbons 1997; Panizzolo 1998; Shah and Ward 2007; Soriano-Meier and Forrester 2002), oth-ers use various performance metrics, creating a quantitative assessment (cf. Bayou and De Korvin 2008; Behrouzi andWong 2011; Wan and Chen 2008). None of the existing studies utilise qualitative and quantitative approachessimultaneously.

Using just one approach may create a bias. While quantitative assessment tends to result in an acceptable perfor-mance level, qualitative assessment reflecting stakeholders’ perceptions or the context of the firm may create differentassessment perspectives. Therefore, the LAT was built using both quantitative and qualitative measures, to give an over-all view of the organisation’s leanness efforts. The quantitative measures utilise a ratio-based approach, using fuzzylogic, integrating eight main performance dimensions. In the light of Table 2, main dimensions and sub-performanceindicators for the LAT, derived from existing literature, are given in Table 3. The qualitative section integrates a percep-tional approach with 51 qualitative items (Appendix A) with five performance dimensions, using the same fuzzy logic.

Quantitative assessment

The quantitative studies reviewed in the literature implemented various assessment models and measureable performancedimensions to assess lean implementation, such as Behrouzi and Wong (2011), Camacho-Miñano, Moyano-Fuentes, andSacristán-Díaz (2013), Wan and Chen (2008), and Bayou and De Korvin (2008). Behrouzi and Wong (2011) employedwaste elimination as quality, cost and time, and analysed delivery performance in JIT systems, assessing leanness levels

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Table

2.Quantitativ

eandqu

alitativ

elean

assessmentstud

ies.

Quality

Cost

Time

JIT delivery

Inventory

Cellular manufacturing

Employee involvement

Set up time

Product value

Safety

Productivity

Market share

Capacity

Elimination of waste

Continuous improvement

Pull system

Multifunctional teams

Decentralized responsibilities

Integrated functions

Vertical information systems

Visual management

Lean change strategy and sustainability

Culture

Beh

rouz

i and

Won

g (2

011)

XX

XX

Shile

ds (

2006

)X

Mas

kell

(200

0)X

Fulle

rton

and

Wem

pe (

2009

)X

XX

XW

an a

nd C

hen

(200

8)X

XX

Alle

n, R

obin

son,

and

Ste

war

t (20

01)

XX

XX

Bay

ou a

nd D

e C

orvi

n (2

008)

XX

XSe

arcy

(20

09)

XX

XX

XB

hasi

n (2

011)

XX

XX

XX

XK

arls

son

and

Åhl

strö

m(1

996)

XX

XX

XX

XX

XX

X

Goo

dson

(20

02)

XX

XX

XX

XPa

nizz

olo

(199

8)X

XX

XX

Doo

len

and

Hac

ker

(200

5)X

XX

XX

XX

XSh

ah a

nd W

ard

(200

7)X

XX

XSh

ah a

nd W

ard

(200

3)X

XX

XX

XX

Jam

es-M

oore

and

Gib

bons

(19

97)

XT

aj (

2005

)X

XX

Pette

rsen

(20

09)

XX

XX

XX

XX

XX

XL

AT

XX

XX

XX

XX

XX

XX

X

(Con

tinued)


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Supplier issues

Investment priorities

Lean practices

Various waste

Customer issues

Environment, cleanliness, and order

Scheduling system

Movement of materials

Condition and maintenance of equipment and tools

Management of complexity and variability

Product design

Wok force management

Shop-floor management

Flow

Controlled processes

Flexibility

Processes

Standardization

Use of space

Jam

es-M

oore

an

d G

ibbo

ns (

1997

)

XX

XX

Sing

h et

al.

(201

0)X

XX

XX

Goo

dson

(200

2)X

XX

XX

X

Pani

zzo

lo (

1998

)X

XX

XX

X

Doo

len

and

Hac

ker

(200

5)X

XX

XX

X

Shah

an

d W

ard

(200

3)X

X

Shah

an

d W

ard

(200

7)X

XX

XX

X

Bha

sin

(201

1)X

XX

Pette

rsen

(20

09)

XX

XX

Taj

(200

5)X

XX

XX

LA

TX

XX

XX

XX

XX

XX

X

Table

2.(Contin

ued)


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Table 3. LAT’s quantitative performance indicators.

LAT

Time Effectiveness

Average set-up time per unit

Set up time/total production time

Average lead time per unit

Cycle time

Takt time

Takt time/cycle time

Total down time/total machine time

Total time spent on unplanned or emergency repairs/total maintenancetime

T1

T4

T3

T2

T6

T8

T5

T7

Quality

Defect rate

Total defectives $/total sales

Rework rate

Total reworks $/total sales

Scrap rate

Total scraps $/total sales

Total scraps $/total products $

Failure rate at final inspection (First time through)

# of poka-yoke devices/total defectives, scraps, reworks

% of inspection carried out by autonomous defect control (poka-yoke devices)

Total # of people dedicated primarily to quality control/total employees

Q1

Q3

Q2

Q4

Q5

Q6

Q7

Q9

Q8

Q10

Q 11

Process

Overall Equipment Effectiveness (OEE)

Size of the adjustment and repair area/total area

Capacity utilization rate (idle capacity/total capacity)

Space productivity

P1

P2

P3

P4

Cost

Annual transportation costs/total sales

Inventory costs/total sales

Total warranty costs/total sales

Total cost of poor quality/total costs

Total cost/total sales

Average cost per unit

Total prevention costs/total costs

Total prevention costs/total sales

Profit after interest and tax/total sales

C1

C2

C3

C4

C5

C6

C7

C8

C9

DIMENSIONS INDICATORS

(Continued) (Continued)


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LAT

DIMENSIONS INDICATORS

Delivery

# of times that parts are transported/total sales

Total transportation distance of materials/total sales

Average total # of days from orders received to delivery

Order processing time/total orders

D1

D2

D3

D4

Total # of orders delivered late per year/total # of deliveries per year

D5

Human Resources

Labor turnover rate

Absenteeism rate

Total # of managers/total employees

Total # of suggestions/total employees

Total # of implemented suggestions/total suggestions

Total # of employees working in teams/total employees

Total # of job classifications/total employees

The # of hierarchical levels

Total indirect employees/total direct employees

Total # of employees involved in lean practices/total employees

Total # of problem solving teams/total employees

H1

H3

H2

H4

H5

H6

H7

H9

H8

H 10

H 11

Sales per employeeH 12

Customer

Customer satisfaction index

Market share (market share by product group)

The customer complaint rate

Customer retention rate

Total number of products returned by the customer/total sales

C1

C2

C3

C4

C5

Inventory

Total # of suppliers/total # of items in inventory

Stock turnover rate (Inventory turnover rate)

Total inventory/total sales

Raw material inventory/total inventory

Total work in progress/total sales

Raw material and WIP inventory/current assets

Finished goods inventory/total inventory

Finished goods inventory/current assets

I1

I4

I3

I2

I6

I8

I5

I7

Table 3. (Continued )


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with ratios, instead of raw data, using fuzzy logic. Bayou and De Korvin (2008) considered lean as a matter of degreeand developed a fuzzy logic model to compare the manufacturing leanness level. They categorised organisations as‘lean, leaner, and leanest’, employing JIT, kaizen, and quality control as lean dimensions. Similarly, Singh, Garg, andSharma (2010) developed a leanness measurement methodology on a fuzzy logic base. The key dimensions in theirstudy were supplier issues, investment priorities, lean practices, waste and customer issues. Although their study has aquantitative base, it allows for subjectivity, since the current performance level for key indicators were ranked byrespondents. Wan and Chen (2008) proposed an integrated quantitative measure of overall leanness using time, cost andproduct value. In their study, organisations weight performance indicators so that they align with the organisation’sstrategic focus and goals.

In another primarily quantitative study, Karlsson and Åhlström (1996) proposed a model that contains nine maindimensions using lean production principles. The authors found that the dimensions determining lean systemperformance should be related to specific indicators, including productivity, quality, lead time, and cost.

Searcy (2009) developed a lean performance score (LPS). Using an analytic hierarchy process weighted lean assess-ment system, he indicated that various leanness metrics could be weighted on the basis of firm’s prioritisation prefer-ences and objectives. His LPS model creates a single-composite measure that monitors the overall success of anorganisation’s lean efforts, with an assessment of quality, capacity, productivity, inventory and costs (Searcy 2009). Inan empirical study, Fullerton and Wempe (2009) examined how non-financial manufacturing performance measuresimpact the lean manufacturing/financial performance relationship. They used profit as a financial performance dimension,while employing set-up time, production quality, lot size, employee involvement and cellular manufacturing applicationsas dimensions of lean manufacturing.

Even though each study has a unique assessment structure, there are weaknesses because particular performancedimensions are employed for specific parts of the organisation, resulting in a limited perspective. While some importantperformance indicators are taken into consideration in detail, none of the existing studies present a comprehensive modelincluding all primary aspects of lean operations. The LAT developed in this paper uses: (1) Time Effectiveness, (2) Quality,(3) Process, (4) Cost, (5) Human Resources, (6) Delivery, (7) Customer and (8) Inventory, since each dimension is corre-lated with a type of the seven forms of waste defined by authors such as Ohno (1988), Taj (2005), Karlsson and Åhlström(1996), Liker (1998), and Womack and Jones (1996): excessive inventory, over production, motion, handling, and process-ing, waiting time and correction of defects. Each performance dimension in LAT measures a unique part of leanimplementation. The match between the seven wastes and the performance dimensions in LAT is shown in Table 4.

As seen in Table 4, the dimension of time effectiveness, along with eight performance indicators employed in LAT,is associated with waiting time. Time is a powerful variable that can be used to assess many organisational activities,such as operations, strategic planning and transportation (Karlsson and Åhlström 1996). The correction of defects is cor-related with the quality dimension of LAT, including defect, rework and scrap rates. Process in LAT is a performancedimension that is related to waste through over processing. Even though the dimension of cost is not directly associatedwith any specific type of waste in lean, cost is totally related to lean implementation. TPS is a production system whosegoal is cost reductions, and the primary means to reduce cost is the absolute elimination of waste (Ohno 1988). Thedimension of human resource with twelve performance indicators in LAT is linked with over motion or underutilisedpeople (Agus and Hajinoor 2012). The delivery dimension in LAT refers to over handling. This dimension, along withfive performance indicators, measures how effectively firms perform related processes to reduce over handling. The cus-tomer dimension in LAT was not directly linked with any types of waste, but reflects the final performance of leanassessment, considering that meeting customers’ needs and expectations is the main objective in lean (Shah and Ward2003; Singh, Garg, and Sharma 2010). The inventory dimension in LAT is associated with excess inventory and overproduction, since getting rid of excessive inventory and production is a vital aim in lean implementation (James-Mooreand Gibbons 1997).

Each dimension including detailed performance indicators is discussed in the following sections, along with themanner in which they fit into the LAT. Table 3 also presents performance indicators used in each main dimension indetail.

Time effectiveness

Time effectiveness is related to the whole organisation in different levels or segments. There are many different ways toevaluate time-related variables or indicators in lean implementations. Previous studies utilising time effectivenessindicators in very broad types of organisations are listed in Table 2.

Lead time is a key metric, considered to be the most descriptive measure of the health of a lean manufacturing unit.Lead time is the amount of time that passes between the beginning and ending of a set of activities (Swink et al. 2011),


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calculated using the sum of the processing and inventory times (McDonald, Van Aken, and Rentes 2002). Cumulativelead time can be defined as the total elapsed time a company requires to fill a new order, from date of entry to deliveryto the customer site (Shileds 2006, 78). Having a short lead time not only improves quality responsiveness and cashflow, but also increases the possibility of getting future customers. Cycle time is the amount of time required for a unitto be processed at any given operation in the overall process (Swink et al. 2011). Therefore, a low cycle time indicatesa high probability that the system will be punctual in fulfilling the customer’s order (Li and Rong 2009).

Reducing set up times creates leaner production lines (Karlsson and Åhlström 1996; Womack, Jones, and Roos1990), because there is less process downtime between product changeovers (Taggart 2009; Shingo 1981). According toShingo (1981), the waste caused by overproduction can be reduced in manufacturing primarily through set-up reductiontechniques, such as his Single-Minute-Exchange-of-Dies methodology.

‘To counter the effects of demand variability, lean production focuses on takt time’ (Shah and Ward 2007, 791). Takttime is the ideal operating time allocated for each customer demand, the pace that matches customer requirements(McDonald, Van Aken, and Rentes 2002), found by dividing the total available time into the number of batches (Yavuzand Tufekci 2006). As defined by Monden (1998), while takt time refers to a planned standard operation time percustomer demand, cycle time may be longer or shorter than takt time because of unplanned delays or improvements.

Machine down time indicates machine effectiveness, typically reported in terms of overall equipment effectiveness(OEE) (Taggart 2009). Any machine that stops a production line causes waste and delays in the throughout productionlines. However, this machine down time may occur in support functions as well, such as accounting, human resourceand marketing, and can include computer break downs and failures in Internet access. Also, the time spent on unplannedor emergency repairs is related to machine effectiveness.

Considering the previous literature, the LAT includes (T1) average set up time per unit, (T2) the ratio of set up timeto total production time, (T3) average lead time per unit, (T4) cycle time, (T5) takt time, (T6) the ratio of takt time tocycle time, (T7) the ratio of total down time to total machine time and (T8) the ratio of time spent on unplanned oremergency repairs to total maintenance time as time-related performance indicators.

Quality

In any lean operation, quality specifications and standards should be met at the first time, without control activities, atleast in theory. However, eliminating quality control entirely is not possible because both chance and assignable causesoccur (Montgomery 2005). Previous studies utilising quality-related indicators are listed in Table 2. Quality can bejudged on defect, rework and scrap rates in the manufacturing industry. Defect rate is the ratio of the products or ser-vices that do not meet at least one of the quality specifications to total output. Rework rates are the ratio of product orservice that needs additional effort to meet quality specifications to total output. Scrap rate is the ratio of the products orservices that do not meet quality specifications, even after rework, compared to total output (Kolarik 1995).

Failure rate at final inspection is another performance indicator in lean assessment efforts. Plants with leanproduction policies manufacture a wide range of models, while maintaining high degrees of quality and productivity

Table 4. The associations between seven wastes and the dimensions of LAT.

LAT dimensions Seven wastes

QuantitativeTime effectiveness Waiting timeQuality Correction of defectsProcess Over processingCostHuman resources Over motionDelivery Over handlingCustomerInventory Excess inventory and over productionQualitativeQuality Correction of defectsCustomerProcess Over processingHuman resources Over motionDelivery Over handling


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(Krafcik 1988). The ultimate quality is zero defects (Crosby 1979; Karlsson and Åhlström 1996), that is, preventingdefects or scraps instead of reworking them.

Numerous poka-yoke devices are implemented in the production and service delivery systems and are essential tolean operations. High quality is ensured not only through control (reactive), but also by prevention (proactive). In lean,instead of controlling the parts produced, the process is kept under control (Karlsson and Åhlström 1996).

Karlsson and Åhlström (1996) focused on the percentage of people dedicated to quality control activities. Instead ofmaximising machine use, Toyota seeks to maximise the appropriate use of people (Dennis 2002), so that feweremployees are needed for quality control.

From the examination of these previous studies, (Q1) defect rate, (Q2) the ratio of total defectives total sales, (Q3)rework rate, (Q4) the ratio of total reworks to total sales, (Q5) scrap rate, (Q6) the ratio of total scraps to total sales,(Q7) the ratio of total scraps to total products, (Q8) failure rate at final inspection, (Q9) the ratio of number of poka-yoke devices to total defectives, scraps and reworks, (Q10) the percentage of inspection carried out by autonomousdefect control and (Q11) the ratio of number of people dedicated to quality control to total employees were used asquality-related indicators in the LAT.

Process

Operational measures are clearly identified as key indicators in successful lean implementation (Shah and Ward 2007,785). Lean production techniques have contributed to a spectacular improvement in efficiency, speed of response andflexibility in production at many industrial enterprises, through process-based management and highly flexibleimplementation of these processes (Cuatrecasas Arbós 2002). As shown in Table 2, process has been employed as aunique performance dimension in lean assessment in previous studies.

One of the techniques used in lean process management is total productive maintenance (TPM), and the mainperformance indicator is OEE, discussed previously. In addition, the best plants use space efficiently (Goodson 2002).Therefore, the ratio of size of adjustment and repair area to total area should be a process-based performance indicatorin lean assessment.

Capacity utilisation is a crucial indicator in lean (Bhasin 2008; Searcy 2009), even in service industries (Zarbo2011). According to Hines, Holweg, and Rich (2004, 1006), if ‘the focus within lean thinking is to create capacity byremoving waste’ then it can also be achieved with the application of improvements in OEE. Lean systems minimisefloor space to maximise production and profit per square foot (Kwak and Anbari 2006). Kokuryo (1996) stated that alean approach works well in industries where efficient use of space is a key consideration.

This literature review supports the use of (P1) OEE, (P2) the ratio of size of adjustment and repair area to totalarea, (P3) capacity utilisation rate and (P4) space productivity as process-related performance indicators in the LAT.

Cost

Womack and Jones (1996) and Comm and Mathaisel (2000) suggested that the lean system provides organisations withreduced costs, continuously improving quality and enhanced customer satisfaction. Deming (1986) developed the chainreaction model to explain relationships among productivity, quality and cost. Therefore, cost reduction, which gives asignificant competitive advantage to the organisation, is a dimension in lean assessment. Previous studies employing acost indicator are listed in Table 2.

Deming (1986), Juran (1951, 1989), and Juran and Gryna (1988) advised organisations to systematically measure thecost of good and poor quality to assess quality systems. Berry and Parasuraman (1992) found that most companies spend10–30% of sales revenue on quality costs. Superville, Jones, and Boyd (2003) stated that corporations like Xerox, GeneralElectric and Motorola reduced their quality costs from 30 to 2% of sales, while improving the quality of their products.

Organisations may implement advanced and sophisticated production and quality control systems, but it is still possi-ble to have customer complaints or returned product. Therefore, the ratio of annual total warranty costs to annual totalsales should be a component in lean assessment. Due to their importance in financial evaluations and audits, the ratio ofprofit (after interest and tax) to annual total sales (Bhasin 2008), the inventory cost ratio (Behrouzi and Wong 2011), theratio of total cost to total sales and average cost per unit should be monitored in assessing lean implementation. Theratio of total cost to total sales demonstrates how much of the total sales are dedicated to total costs. Average cost perunit is an indication of the firm’s competitiveness; the lower the average cost per unit, the higher the competitiveadvantage.

These studies demonstrate that cost-related performance indicators implemented in LAT are relevant to a thoroughanalysis of lean. In LAT the indicators are: (C1) the ratio of annual transportation cost to total sales, (C2) the ratio of


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inventory cost to total sales, (C3) the ratio of total warranty costs to total sales, (C4) the ratio of total cost of poorquality to total costs, (C5) the ratio of total costs to total sales, (C6) average cost per unit, (C7) the ratio of totalprevention costs to total costs, (C8) the ratio of total prevention costs to total sales and (C9) the ratio of profit afterinterest and tax to total sales.

Human resources

Research clearly shows that, without strategic human resource management, overall lean practices will not work (see forexample Agrawal and Graves 1999; Bamber and Dale 1999; Longoni et al. 2013; Rothstein 2004; Wood 2005; Yauchand Steudel 2002). Lean operations can only be performed by trained human operators (Birdi et al. 2008). MacDuffie(1995) believed that it was essential to consider lean production as a package, including human resources.

Good human resource practices improves knowledge capture, which can then be exploited for firm benefit as com-petitive advantage (Appelbaum et al. 2000; Lawler, Mohrman, and Ledford 1992, 1995; Pfeffer 1994; Way 2002). Oneof the most comprehensive studies on the human factor in lean implementation is a multi-analysis which examinedresearch on 308 firms over 22 years (Birdi et al. 2008). They found that empowerment, training and teamwork directlylead to performance pay benefits, while operational lean processes on their own did not. Strategic human resource man-agement creates a competitive advantage for any firm because the knowledge of the firm resides within the employeesthemselves and, therefore, are inimitable by another firm (Lado and Wilson 1994), a requirement for competitive advan-tage in the Resource Based View of the firm (Barney 2001; Harvey and Denton 1999; Power and Waddell 2004; Wrightand McMahan 1992).

Empowerment and employee development are key to the high-performance work practices that are necessary forlean implementation (Huselid 1995; Lawler 1986). Empowerment outcomes include more productive and more flexibleemployees (Hackman and Oldham 1976); proactivity and self-initiating attitudes among individuals and teams (Freseet al. 1996; Parker, Williams, and Turner 2006); reductions in control costs (Batt 2001; Parker and Wall 1998); anddevelopment and use of knowledge and skills, mostly due to the trust building required in empowerment (Leach, Wall,and Jackson 2003).

Teamwork is important in lean efforts, particularly because it provides knowledge sharing opportunities (Birdi et al.2008). The existence of multifunctional teams is considered an indicator in the lean implementation efforts by manyresearchers (Table 2). Cross-functional teams reduce supervision costs, allow interdependent tasks to be completed andrequire knowledge sharing (cf. Allen and Hecht 2004; Leach et al. 2005; Orsburn and Moran 2000).

Given the research on human resources, LAT uses the following rates and ratios as indicators: (H1) labour turnoverrate, (H2) absenteeism rate, (H3) the ratio of total number of managers to total employees, (H4) the ratio of total num-ber of suggestions to total employees, (H5) the ratio of total number of implemented suggestions to total suggestions,(H6) the ratio of total number of employees working in teams to total employees, (H7) the ratio of total number of jobclassifications to total employees, (H8) the number of hierarchical levels, (H9) the ratio of total indirect employees tototal direct employees, (H10) the ratio of total number of employees involved in lean practices to total employees,(H11) the ratio of total number of problem solving teams to total employees and (H12) sales per employee.

Delivery

Delivery performance can be classified into two categories: internal and external activities. The first category deals withinternal delivery activities, such as transporting parts, raw materials and semi-finished materials, from one station toanother. Transportation of any parts or finished product in the organisation or among various organisations and factoriesin different locations does not add any value (Karlsson and Åhlström 1996), but instead increases operation costs andlead time. Behrouzi and Wong (2011) investigated the ratio of annual transportation costs to total annual sales, findingthat they were critical to a comprehensive examination of leanness in organisations.

Delivery reliability and delivery performance were found to be two of the most important performance indicators instudies (see for example Behrouzi and Wong 2011; Bhasin 2008; Bond 1999; Dimancescu, Hines, and Rich 1997;Doolen and Hacker 2005; Fullerton and Wempe 2009). In lean organisations, JIT philosophy is not applied only toinventory-based operations, but also to customer delivery processes.

After examining these studies, (D1) the ratio of number of times that parts are transported to total sales, (D2) theratio of total transportation distance of materials to total sales, (D3) the average total number of days from ordersreceived to their delivery, (D4) the ratio of order processing time to total orders and (D5) the ratio of total number oforders delivered late to total deliveries per year were considered essential to lean implementation and thus incorporatedinto the LAT.


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Customer

All actions and plans in organisations have a bottom-line objective: Higher customer satisfaction and loyalty (Singh,Garg, and Sharma 2010). Naumann and Giel (1995) and Bhasin (2008) stated that customer complaint rate, customersatisfaction and retention levels should be watched closely. In the competitive market place, customers’ expectations,needs and demands shape the variety of products and services provided by organisations. According to Panizzolo(1998), the challenge is how to integrate customers into the organisation. Doolen and Hacker (2005), Goodson (2002),Panizzolo (1998), Shah and Ward (2007), Bhasin (2008) and Singh, Garg, and Sharma (2010) incorporated customer-related items in their studies.

Market share is a powerful organisational metric in corporate performance, used as a performance indicator by Di-mancescu, Hines, and Rich (1997) and Bhasin (2008). Management of returns is a critical supply chain managementprocess (Rogers et al. 2002). In the U.S., retail customer returns was estimated at six percent of revenue. Additionally,cost associated with managing the returns was estimated at 4% of total logistics costs (Rogers et al. 2001).

In this study, both raw data and ratios were selected as part of the LAT. The performance indicators used as raw datain LAT are (C1) customer satisfaction index and (C2) market share. The customer-focused ratios used in the LAT are(C3) customer complaint rate, (C4) customer retention rate and (C5) the ratio of total number of products returned bythe customer to total sales.

Inventory

The largest source of waste is inventory (Karlsson and Åhlström 1996), as parts and finished products in warehouses donot create value for either customers or the firm. Operating with smaller (or zero) inventory requires systems with mini-mum machine down time and very well organised supply chain operations.

The fewer the number of suppliers, the better the organisational performance (Deming 1986). Dealing with fewersuppliers lowers supply chain management costs. Inventory in a system can be reduced by either eliminating excesscapacity or lowering throughput time, but the latter is preferred, but it requires reliable suppliers and a process reducinglead time (Shah and Ward 2007). Reducing lead time directly results in inventory reductions (Wilson 2010).

Swamidass (2007) used the ratio of total inventory to sales as the only performance indicator of lean assessment,but an individual metric focusing on a specific performance aspect cannot represent the overall leanness level (Wan andChen 2008). Karlsson and Åhlström (1996) used JIT as a major measurement factor in their assessment of lean: eachprocess should be operated with the right part, in the right quantity, at exactly the right point time (Shingo 1981). Suc-cessful inventory management requires assessing various performance indicators, such as stock turnover rate, work inprocess and raw material ratios (Zipkin 2000).

In developing the LAT, (I1) the ratio of total number of suppliers to total numbers of items in the inventory isincluded as an indicator. Other crucial indicators include: (I2) stock turnover rate, (I3) the total inventory to total sales,(I4) the ratio of raw material inventory to total inventory, (I5) the ratio of total work in process to total sales, (I6) theratio of raw material and work in process inventory to current assets and (I7–I8) the ratio of finished goods inventoryto total inventory and to current assets.

Qualitative assessment

Although lean concepts have a strong quantitative component, a qualitative component is needed. Perceptions are impor-tant data, which often cannot be incorporated using quantitative systems. According to Mann (2005), assessment of leanimplementation efforts should be conducted on the production floor by looking and asking. Many LATs reported in theliterature utilised qualitative methods as well as quantitative ones (Bhasin 2011; Connor 2001; Doolen and Hacker2005; Feld 2000; Fullerton and Wempe 2009; Goodson 2002; James-Moore and Gibbons 1997; Panizzolo 1998; Shahand Ward 2007; Soriano-Meier and Forrester 2002).

Doolen and Hacker (2005) assessed leanness level on the basis of average points given by the respondents, incorpo-rating six areas into their study. In a very different format, Bhasin (2011) categorised 104 sub-indicators in 12 mainleanness components, rated by respondents on a five-point Likert scale. Using a survey format, James-Moore andGibbons (1997) tested key constructs such as flexibility, waste elimination, optimisation, process control and peopleutilisation through close-ended questions ending with ‘yes’ or ‘no’. Panizzolo (1998) developed a qualitative modelincluding face-to-face structured interviews with high-level managers from 27 sample organisations and perceptionalquestions were ranked on a five point-Likert scale. Shah and Ward (2007) conducted a survey among variousmanufacturing firms incorporating three main indicators (suppliers, customers and internal processes).


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Others used the qualitative lean enterprise self-assessment tool (LESAT) and lean processing programme to assesscompany-wide lean implementation (Wan and Chen 2008). However, solely qualitative methods generally evolve withthe respondents’ perceptions and responses and contain subjectivity and bias, due to individual judgments (Wan andChen 2008).

The LAT developed here includes qualitative assessment along with qualitative indicators. Previous studies of vari-ous tools, questions and approaches for qualitative assessment, discussed previously, suggest the use of five performancedimensions, which are categorised as: quality, process, customer, human resources and delivery. The qualitative sectionof LAT contains five performance dimensions measured by 51 items, as shown in Appendix A. Items are measured onfive-point Likert scales with end points of strongly disagree (1) and strongly agree (5).

Applying the LAT

The LAT should be integrated into a comprehensive problem solving methodology. Problem solving processes entail avariety of tasks, such as problem formulation, diagnosing the root causes and development of solutions (Mast 2011).The flow chart in Figure 1 integrates LAT into solving problems associated with lean implementation.

Analysis using fuzzy methodology

Many organisations have attempted to implement lean manufacturing. However, most attempts do not give a true picturebecause organisations decide implement parts of the system rather than the entire system. In addition, lean performanceis often not evaluated using a comprehensive measurement system or tool, possibly because managers believe that theanalysis will be too costly or too difficult.

Behrouzi and Wong (2011) developed a dynamic and innovative lean performance evaluation model using fuzzy meth-odology. Their study proposes a simple and usable method. It also allows the investigator to determine performance indi-cator preferences. Behrouzi and Wong’s (2011) approach creates a comprehensive analysis of the lean implementationefforts of a single company. Multiple companies within a single industry or in different industries can then be compared,because the underlying structure of the methodology is the same – with qualitative as well as quantitative measures.

Fuzzy sets were presented by Zadeh to define human knowledge in mathematical expressions (Aydin and Pakdil2008). Fuzzy set theory accounts for the uncertainty inherited in natural language using particular words, such as most,much, not many, very many, not very many, few, quite a few, large number, small number, frequently (Zadeh 1965).Fuzzy models use fuzzy sets to represent non-statistical, uncertain and linguistic values (Behrouzi and Wong 2011).Uncertainty in the model can be eliminated by using fuzzy numbers and crisp intervals can be provided for decision

Determine possible solutions and select the best/most appropriate one

Assess leanness level using LAT

Determine improvement needs and root causes of the lower performance

Implement the selected solution

Reassess the leanness level using the LAT

Figure 1. Flow chart of applying LAT.


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makers. Crisp intervals are called α-cut sets in fuzzy theory and they reflect optimal decisions. Fuzzy numbers are pre-sented with their membership functions, which indicate the degrees of belonging (Aydin and Pakdil 2008). To formulatea fuzzy-logic model, the basic definitions are given below.

Definition 1. A fuzzy set ~A in a universe of discourse X is characterised by a membership function l~AðxÞ whichassociates with each element x in X, a real number in the interval [0, 1]. The function value l~AðxÞ terms the grade ofmembership of x in ~A (Zadeh 1965).

Definition 2. Let ~A be a fuzzy set and l~AðxÞ be the membership function for x 2 ~A, if l~AðxÞ is defined as given inEquation (1) (Aydin and Pakdil 2008). In this function, ‘a’ and ‘b’ represent the best and worst lean performance ofeach indicator, respectively (Behrouzi and Wong 2011).

l~AðxÞ ¼1 if xi � a0; if xi � b1� ðxi�aÞ

ðb�aÞ ; if a\xi\b

8<: (1)

After performance indicators are measured using LAT in an organisation, the fuzzy membership values are calculatedfor each indicator. As a final step of the lean measurement, the final lean score is calculated as the mean of allmembership values taken into consideration in lean assessment (Behrouzi and Wong 2011).

To clearly demonstrate the lean measurement method for LAT, an example is given for eight dimensions in LATquantitative assessment. Measurement using fuzzy membership functions and LAT scores are performed successfully asgiven in Table 5. As seen in the table, organisations may be able to calculate and measure as much as possible perfor-mance indicator defined in LAT. In other words, even if they cannot measure all of the indicators proposed in LAT, theycan measure and calculate fuzzy membership functions and LAT score as they could do. According to this measurementmethod, fuzzy membership functions are computed using Equation (1) and the organisation in example has 82.86 out of100 leanness points at the final stage on the basis of Equation (2), where m is the number of dimensions, nj is thenumber of performance indicators in each dimension j, j ¼ 1; 2; . . .;m; l~AðxÞij is the fuzzy membership value of the ithperformance indicator of the jth dimension, i ¼ 1; 2; . . .; nj; j ¼ 1; 2; . . .;m.

Pmj¼1

Pnji¼1 l~AðxÞij

ni

m� 100 (2)

Bayou and De Korvin (2008) stated that lean scores may be categorised as lean, leaner and leanest on the basis ofthe scores generated by the fuzzy measurement method. Fuzzy membership functions are converged to 100 to present abetter lean performance, i.e., the closer to 100, the better the fuzzy membership value and the better the performance oflean implementation for that dimension. As shown in the example, the organisation achieves the best performance onquality, delivery and customer dimensions, since they generated a converged fuzzy membership value closer to 100, asseen in Table 5. The results also indicate that time effectiveness and cost dimensions need to be improved to achievetotal lean implementation, since they generated a converged fuzzy membership value less than 50. Through the fuzzy-based measurement method, organisations may assess their lean implementation efforts and diagnose their improvementneeds in lean implementation. The same fuzzy logic method applies in analysis of the qualitative data.

Analysis using radar charts

Using charts, figures and tables in lean implementation efforts provides rapid and visual information about the currentperformance level for various indicators (Mann 2005). Radar charts have been frequently using for graphing multivariatedata in both academia and industry. By using radar charts, managers can more easily view their own leanness effortsand companies can be compared using similar charts, even across industries. ‘The radar chart presentation is a more effi-cient way to display a wide variety of data in a single picture’ (Saary 2008, 313). In the quantitative part, each of theeight main performance dimensions in LAT is represented on a different radius of a radar plot. Each radius index startswith zero (0) in the centre and ends with 100 points. The converged fuzzy membership values for each main dimensionare identified on the radius of the radar chart. The converged fuzzy membership values closest to the periphery representthe best main performance dimension in LAT’s quantitative assessment, while the values closest to the centre correspondto the dimensions of poor performance. An example of the use of a radar chart in LAT is shown in Figure 2. The sameprocedure is performed for the qualitative data, which has been rated on a 5-point Likert scale.


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Table 5. Empirical data and results.

LAT dimensions and performance indicators Results

Dimensions Performance indicators Actual performance level (xi) Point a Point b l~AðxÞ

Time effectiveness x1 (T1) 2 min. 0 min. 1.5 min. 0x2 (T2) 15% 0 20% 0.75x2 (T3) 5 days 0 day 6 days 0.16x3 (T4) 48 min. 24 min. 480 min. 0.84x5 (T5)x6 (T6) 50% 0 80% 0.625x7 (T7) 10% 0 5% 0x8 (T8) 25% 0 20% 0

LAT score 33.92Quality x1 (Q1) 8000 0 1,000,000 0.99

x (Q2) 3.1% 2% 100% 0.99x3 (Q3) 20,000 0 1,000,000 0.98x4 (Q4) 0.1063% 0 100% 0.99x5 (Q5) 90% 91% 100% 1x6 (Q6) 0.70% 0 100% 0.99x7 (Q7) 1.12% 0.91% 100% 0.99x8 (Q8) 5% 0 100% 0.95x9 (Q9)x10 (Q10)x11 (Q11) 2.5% 0 100% 0.975

LAT score 98.31Process x1 (P1) 70% 85% 0% 0.82

x2 (P2) 0 0 100 1x3 (P3) 70% 100% 0% 0.70x4 (P4) 90 90 0 1

LAT score 88.00Cost x1 (C1)

x2 (C2) 28 0 100 0.72x3 (C3) 1.5 1 100 0.99x4 (C4) 12 10 100 0.97x5 (C5) 79 0 100 0.21x6 (C6)x7 (C7) 6 0 100 0.94x8 (C8) 5 0 100 0.95x9 (C9) 8% 10% 0% 0.80

LAT score 79.71Inventory x1 (I1) 0.14 0.11 1 0.96

x2 (I2) 6% 9% 0% 0.67x3 (I3) 28 0 100 0.72x4 (I4) 0.32 0.35 1 0.91x5 (I5) 0.09 0.06 1 0.96x6 (I6) 0.30 0.19 1 0.86x7 (I7) 0.96 0.95 1 0.93x8 (I8) 0.029 0.018 1 0.98

LAT score 87.37Human Resources x1 (H1) 1% 1% 100% 1

x2 (H2) 1.7% 1.5% 100% 0.99x3 (H3) 4.9% 5% 100% 1x4 (H4) 5.94% 7% 0 0.85x5 (H5) 0.76% 1% 0 0.76x6 (H6) 67% 100% 0 0.67x7 (H7)x8 (H8) 6 6 20 1x9 (H9)x10 (H10) 64% 100% 0 0.64x11 (H11) 23% 35% 0 0.65x12 (H12) 32,497 37,379 0 0.87

(Continued)


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Conclusion

Multiple assessment tools have been designed to measure different and often individual aspects of lean implementation.While some existing studies measure leanness level through perceptual evaluations, other studies utilise a quantitativeassessment approach. Using only one qualitative or quantitative approach in lean assessment efforts may create a biasboth in practice and theory. While quantitative assessment leads the organisations to an acceptable leanness level, stake-holders’ perceptions about leanness level may result in an opposite result. To decrease this possibility, organisationsshould utilise both perceptional and measurement approaches simultaneously to assess their lean implementation efforts.Therefore, the LAT employs an evaluation approach that includes both quantitative and qualitative bases, constructed onfuzzy logic.

The LAT measures quantitative aspects of leanness through eight performance dimensions: time effectiveness,quality, process, cost, human resources, delivery, customer and inventory along with detailed sub-performance indicators.These performance dimensions are related to seven types of waste considered in lean production. In the qualitativesection, the LAT demonstrates a perceptional view within five performance dimensions: quality, process, customer,human resources and delivery, using 51 items. As a calculation method, the fuzzy membership function highlights bothimprovement successes and needs in lean implementation, and use of fuzzy logic and radar charts allows an immediate,

020406080

100

Time effectiveness

Quality

Process

Cost

Human resources

Delivery

Customer

Inventory

Series1

Figure 2. A hypothetical example of radar chart in LAT.

Table 5. (Continued).LAT dimensions and performance indicators Firm 1 results

Dimensions Performance indicators Actual performance level (xi) Point a Point b l~AðxÞ

LAT score 84.30Delivery x1 (D1) 0.00004% 0 1% 0.99

x2 (D2)x3 (D3) 25 20 100 0.94x4 (D4) 5% 5% 100% 1x5 (D5) 0 0 1 1

LAT score 98.25Customer x1 (C1) 93% 100% 0 0.93

x2 (C2) 27% 35% 0 0.77x3 (C3) 1.5% 0 100% 0.98x4 (C4) 98% 100% 0 0.98x5 (C5) 0.000046% 0.000031% 1 0.99

LAT score 93

Total LAT score 82.86


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comprehensive view of the strong areas and those needing improvement. LAT allows organisations to use the fuzzymembership function based on data that they choose to collect. It does not require organisations to collect data for allperformance indicators given in LAT.

The LAT has theoretical and practical implications for business organisations implementing lean principles. Intheoretical terms, the LAT can support the various theories that have been developed about the intertwining of thevarious aspects of both goods and service operations and the rest of the firm (core vs. support functions). In practice,the LAT can help organizations assess lean implementation in a systematic way and eventually develop stronger leansystems. This creates a tremendous competitive advantage (Womack, Jones, and Roos 1990). In this sense, the LAT hasa potential for organisations aiming at high-performance level in lean implementation to assess and diagnose improve-ment needs and successes in lean efforts.

Limitations of the LAT include the comprehensive nature of the tool. First, data collection process for each perfor-mance indicator may seem to be a deterrent for organisations to use it. However, the fuzzy membership function inLAT presents the data in a comprehensive manner that can be understood by management in its entirety. Therefore, thisperceived limitation has a capacity to create an important advantage for practitioners. As another limitation, fuzzymembership function may be seen unfeasible and impractical for practitioners and another calculation algorithm may beutilised within LAT. We believe, however, that presenting the data in this manner gives managers the benefit of theholistic view of the organisation needed at the top level of the firm. Third, whether the organisation operates in amanufacturing or services industry may make some differences in applying the LAT, considering that some performanceindicators include a manufacturing bias in LAT. Fourth, the organisations may prefer to give a weight to each perfor-mance dimension or indicator. While some performance indicators may have a lower importance weight in particularindustries, the others might be more important in other industries. Fifth, the LAT may not cover all importantperformance indicators and dimensions that have a potential to assess leanness level in business organisations, but webelieve it captures the most critical.

There is potential for the use of LAT above and beyond lean implementation into sustaining the process of leanproduction and management in goods and services industries. Future research and development of the tool would be aworthwhile use of time and effort, because lean efforts can lead to substantial gains in competitive advantage andproductivity. This area, while well researched, lacks comprehensive coverage of the entire lean implementationprocesses. Our paper begins to fill this gap in the literature.

Funding

This study was supported by TUBITAK (The Scientific and Technological Research Council of Turkey) 2219 Post-Doctoral ResearchProgram.

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Appendix A. LAT’s qualitative itemsQuality

(1) Employees identify defective parts and stop the line.(2) Employees identify defective parts, but do not stop the line.(3) Defective parts are sent back to the employees responsible for the defect to adjust it.(4) Processes are controlled through measuring inside the process.(5) Measuring is done after each process.(6) Measuring is done only after product is complete.


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(7) Process-focused management is employed in throughout the firm.(8) Information continuously is displayed in dedicated spaces.(9) Oral and written information are provided regularly.(10) Written information is provided regularly.(11) There is a total commitment to waste culture.

Customer(12) Our customers are directly involved in current and future product offerings.(13) We have frequent follow-up with our customers for quality/service feedback.

Process(14) We use kanban, squares, or containers of signals for production control.(15) Equipment is grouped to produce a continuous flow of products.(16) We post equipment maintenance records on shop floor for active sharing with employees.(17) We conduct product capability studies before product launch.(18) We use SPC techniques to reduce process variance.(19) TPM is applied throughout the firm.(20) 5S is integrated into the management system.(21) Value stream mapping is employed in throughout the firm.(22) Root-cause problem solving is integrated into the management system.(23) Our production system works on cellular manufacturing system.(24) We implement experimental design or Taguchi methods into our continuous improvement studies.(25) Standard operating procedures are developed, published and readily available in all areas.(26) Non-manufacturing operations are standardized.(27) Single Minute Exchange of Die programs are in use.(28) Single piece flow programs or practices are in use.

Human resources(29) Employees drive suggestion programs.(30) Employees lead product/process improvement efforts.(31) Employees undergo cross functional trainings.(32) Team leadership rotates among team members.(33) Continuous improvement and compensation link is evident.(34) Operators and supervisors are cross functionally trained and flexible to rotate into different jobs.(35) Team leaders spend their time either training employees, monitoring the process, or improving it.(36) Leaders are responsible for how the value-added work gets done.

Delivery(37) Production is pulled by the shipment of finished goods.(38) Production at the stations is pulled by the current demand of the next station.(39) We consider quality as our number one criterion in selecting suppliers.(40) We strive to establish long-term relationship with our suppliers.(41) We regularly solve problems jointly with our suppliers.(42) We have helped our suppliers to improve their product quality.(43) We have continuous improvement programs that include our key suppliers.(44) We include our key suppliers in our planning and goal-setting activities.(45) Suppliers are perceived as a partner of the firm.(46) Suppliers are directly involved in the new product development process.(47) We have a formal supplier certification program.(48) Our key suppliers deliver to plant on JIT basis.(49) We give our suppliers feedback on quality and delivery performance.(50) We and our trading partners exchange information that helps establishment of business planning.(51) We are first in the market in introducing new products.


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Criteria for a Lean Organization - Development of LAT

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