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Criteria for a lean organisation: development of a lean assessment tool
Fatma Pakdil
a
*and Karen Moustafa Leonard
b
a
Industrial Engineering, Baskent University, Ankara, Turkey;
b
Management, 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 various
aspects of lean production in the literature, there is no comprehensive measure for overall lean implementation in
business firms. An appropriate measurement tool is needed to assess the effectiveness and efficiency of the lean
implementation throughout the entire organisation. Based on lean research, a comprehensive tool called the leanness
assessment 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 quantitative
performance 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; performance
analysis; quality management; Toyota production system
Introduction
Increased competition and customer expectations require organisations to gain powerful competitive advantages in the
globalised 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 Rajgopal
2007; Hino 2006;Li2013; 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, and
Steele 2004) and service organisations (cf. Laureani, Antony, and Douglas 2010; Liker and Morgan 2006; Nicholas
2012). 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 and
ever growing variety of products.
Lean implementation comprises organisation-wide lean practices (Mann 2005; Wilson 2010). To be successful, lean
implementation 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 many
empirical studies (cf. Doolen and Hacker 2005; Panizzolo 1998; Shah and Ward 2007) and review papers (cf. Behrouzi
and Wong 2011; Bhasin 2008,2011) of lean assessment, but most do not concentrate on overall lean implementation
within a qualitative and quantitative perspective. We examine these issues in the light of the following question: in
assessing the success of lean implementation, which key dimensions are needed? To answer the question, the key
dimensions 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) is
developed to use both quantitative (i.e. directly measurable and objective results) and qualitative (i.e. using perceptions
of individuals) measures of lean implementation progress and/or success in the entire organisation, with fuzzy logic
*Corresponding author. Email: fpakdil@baskent.edu.tr
© 2014 Taylor & Francis
International Journal of Production Research, 2014
Vol. 52, No. 15, 4587–4607, 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 (Hoss
and Schwengber ten Caten 2013). The word lean was introduced by Krafcik (1988) to describe Toyota’s production
system (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 and
balanced flow in a process (Stevenson 2007). The lean production concept identifies extremely efficient and effective
production systems that consume fewer resources, creating higher quality and lower cost as outcomes. Using both
practical 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 these
practices 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 optimum
quality (Cuatrecasas Arbós 2002). Eliminating waste lowers variable production costs associated with labour, materials
and energy, thus raising the unit profitability of products. Lean also attacks waste associated with the fixed costs of
facilities, 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 four
groups of (1) philosophy –long-term, (2) process –promote flow, (3) people and partners–respect and development
and (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 that
has continuous flow and balanced workload
2. Create a continuous process flow to bring problems to the
surface
3. Use pull systems to avoid overproduction
4. Level out the workload (heijunka)
5. Build a culture of stopping to fix problems, to get quality right
the first time
6. Standardized tasks are the foundation for continuous
improvement and employee empowerment
7. Use visual control so no problems are hidden
8. Use only reliable, thoroughly tested technology that serves your
people and processes
People –Respect and development 9. Growing leaders who thoroughly understand the work, living
the philosophy, and teaching it to others
10. Developing exceptional people and teams who follow your
company’s philosophy
11. Respecting your extended network of partners and suppliers by
challenging them and helping them improve
Problem solving –Continuous improvement: organise their
continuous improvement activities
12. Go and see for yourself to thoroughly understand the situation
(genchi genbutsu)
13. Make decisions slowly by consensus, thoroughly considering
all options, implement decisions rapidly
14. Become a learning organization through relentless reflection
(hansei) and continuous improvement (kaizen)
4588 F. Pakdil and K.M. Leonard
Leanness creates a tremendous sustainable competitive advantage (Womack, Jones, and Roos 1990) and lean
implementation 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 have
failed. 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 systems
must be measured and monitored continuously through various performance measures. With a broader continuous
improvement 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 concepts
within firms.
Some studies in the literature (cf. Bayou and De Korvin 2008; Goodson 2002; Singh, Garg, and Sharma 2010) focus
on measuring the leanness of management systems and emphasise the need for a unifying measure of the effects of
these practices. Bhasin (2008, 674) states that ‘companies need to understand how key performance measures can guide
and 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 in
mind, 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. They
also 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; Womack
and 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 an
outcome 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 general
critique of the literature, each existing lean assessment method focuses on a different side of lean operations, not the
complete picture. While some of the tools or methods focus only on perceptions of the employees, using a qualitative
approach (Bhasin 2011; Connor 2001; Doolen and Hacker 2005; Feld 2000; Fullerton and Wempe 2009; Goodson
2002; 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 and
Wong 2011; Wan and Chen 2008). None of the existing studies utilise qualitative and quantitative approaches
simultaneously.
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 different
assessment 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 fuzzy
logic, integrating eight main performance dimensions. In the light of Table 2, main dimensions and sub-performance
indicators 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 performance
dimensions to assess lean implementation, such as Behrouzi and Wong (2011), Camacho-Miñano, Moyano-Fuentes, and
Sacristán-Díaz (2013), Wan and Chen (2008), and Bayou and De Korvin (2008). Behrouzi and Wong (2011) employed
waste elimination as quality, cost and time, and analysed delivery performance in JIT systems, assessing leanness levels
International Journal of Production Research 4589
Table 2. Quantitative and qualitative lean assessment studies.
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
Behrouzi and Wong (2011)
X
X
X
X
Shileds (2006)
X
Maskell (2000)
X
Fullerton and Wempe (2009)
X
X
X
X
Wan and Chen (2008)
X
X
X
Allen, Robinson, and Stewart (2001)
X
X
X
X
Bayou and De Corvin (2008)
X
X
X
Searcy (2009)
X
X
X
X
X
Bhasin (2011)
X
X
X
X
X
X
X
Karlsson and Åhlström (1996)
X
X
X
X
X
X
X
X
X
X
X
Goodson (2002)
X
X
X
X
X
X
X
Panizzolo (1998)
X
X
X
X
X
Doolen and Hacker (2005)
X
X
X
X
X
X
X
X
Shah and Ward (2007)
X
X
X
X
Shah and Ward (2003)
X
X
X
X
X
X
X
James-Moore and Gibbons (1997)
X
Taj (2005)
X
X
X
Pettersen (2009)
X
X
X
X
X
X
X
X
X
X
X
LAT
X
X
X
X
X
X
X
X
X
X
X
X
X
(Continued)
4590 F. Pakdil and K.M. Leonard
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
James-Moore
and Gibbons (1997)
X
X
X
X
Singh et al. (2010)
X
X
X
X
X
Goodson (2002)
X
X
X
X
X
X
Panizzolo (1998)
X
X
X
X
X
X
Doolen and Hacker
(2005)
X
X
X
X
X
X
Shah an d Ward
(2003)
X
X
Shah an d Ward
(2007)
X
X
X
X
X
X
Bhasin (2011)
X
X
X
Pettersen (2009)
X
X
X
X
Taj (2005)
X
X
X
X
X
LAT
X
X
X
X
X
X
X
X
X
X
X
X
Table 2. (Continued )
International Journal of Production Research 4591
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/c
y
cle 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
Scra
p
rate
Total scra
p
s $/total sales
Total scra
p
s
$
/total
p
roducts
$
Failure rate at final inspection (First time through)
# of
p
oka-
y
oke devices
/
total defectives
,
scra
p
s
,
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
Q
9
Q8
Q
10
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
Avera
g
e cost
p
er unit
Total
p
revention costs/total costs
Total prevention costs/total sales
Pr
o
fi
ta
f
te
r in
te
r
est a
n
dta
x
/tota
l
sa
l
es
C1
C2
C3
C4
C5
C6
C7
C8
C9
DIMENSIONS INDICATORS
(Continued)(Continued)
4592 F. Pakdil and K.M. Leonard
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
j
ob classifications/total em
p
lo
y
ees
The # of hierarchical levels
Total indirect em
p
lo
y
ees/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 employee
H
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 inventor
y
/current assets
Finished goods inventory/total inventor
y
Finished goods inventory/current assets
I1
I4
I3
I2
I6
I8
I5
I7
Table 3. (Continued )
International Journal of Production Research 4593
with ratios, instead of raw data, using fuzzy logic. Bayou and De Korvin (2008) considered lean as a matter of degree
and 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, and
Sharma (2010) developed a leanness measurement methodology on a fuzzy logic base. The key dimensions in their
study were supplier issues, investment priorities, lean practices, waste and customer issues. Although their study has a
quantitative base, it allows for subjectivity, since the current performance level for key indicators were ranked by
respondents. Wan and Chen (2008) proposed an integrated quantitative measure of overall leanness using time, cost and
product value. In their study, organisations weight performance indicators so that they align with the organisation’s
strategic focus and goals.
In another primarily quantitative study, Karlsson and Åhlström (1996) proposed a model that contains nine main
dimensions using lean production principles. The authors found that the dimensions determining lean system
performance 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 an
organisation’s lean efforts, with an assessment of quality, capacity, productivity, inventory and costs (Searcy 2009). In
an empirical study, Fullerton and Wempe (2009) examined how non-financial manufacturing performance measures
impact the lean manufacturing/financial performance relationship. They used profitas a financial performance dimension,
while employing set-up time, production quality, lot size, employee involvement and cellular manufacturing applications
as dimensions of lean manufacturing.
Even though each study has a unique assessment structure, there are weaknesses because particular performance
dimensions are employed for specific parts of the organisation, resulting in a limited perspective. While some important
performance indicators are taken into consideration in detail, none of the existing studies present a comprehensive model
including 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 lean
implementation. 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 performance
dimension that is related to waste through over processing. Even though the dimension of cost is not directly associated
with any specific type of waste in lean, cost is totally related to lean implementation. TPS is a production system whose
goal is cost reductions, and the primary means to reduce cost is the absolute elimination of waste (Ohno 1988). The
dimension of human resource with twelve performance indicators in LAT is linked with over motion or underutilised
people (Agus and Hajinoor 2012). The delivery dimension in LAT refers to over handling. This dimension, along with
five 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 lean
assessment, considering that meeting customers’needs and expectations is the main objective in lean (Shah and Ward
2003; Singh, Garg, and Sharma 2010). The inventory dimension in LAT is associated with excess inventory and over
production, since getting rid of excessive inventory and production is a vital aim in lean implementation (James-Moore
and Gibbons 1997).
Each dimension including detailed performance indicators is discussed in the following sections, along with the
manner in which they fit into the LAT. Table 3also presents performance indicators used in each main dimension in
detail.
Time effectiveness
Time effectiveness is related to the whole organisation in different levels or segments. There are many different ways to
evaluate time-related variables or indicators in lean implementations. Previous studies utilising time effectiveness
indicators 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),
4594 F. Pakdil and K.M. Leonard
calculated using the sum of the processing and inventory times (McDonald, Van Aken, and Rentes 2002). Cumulative
lead time can be defined as the total elapsed time a company requires to fill a new order, from date of entry to delivery
to the customer site (Shileds 2006, 78). Having a short lead time not only improves quality responsiveness and cash
flow, but also increases the possibility of getting future customers. Cycle time is the amount of time required for a unit
to be processed at any given operation in the overall process (Swink et al. 2011). Therefore, a low cycle time indicates
a 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 Roos
1990), because there is less process downtime between product changeovers (Taggart 2009; Shingo 1981). According to
Shingo (1981), the waste caused by overproduction can be reduced in manufacturing primarily through set-up reduction
techniques, 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). Takt
time 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 (Yavuz
and Tufekci 2006). As defined by Monden (1998), while takt time refers to a planned standard operation time per
customer 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 production
lines. However, this machine down time may occur in support functions as well, such as accounting, human resource
and marketing, and can include computer break downs and failures in Internet access. Also, the time spent on unplanned
or 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 time
to total production time, (T3) average lead time per unit, (T4) cycle time, (T5) takt time, (T6) the ratio of takt time to
cycle time, (T7) the ratio of total down time to total machine time and (T8) the ratio of time spent on unplanned or
emergency 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, at
least in theory. However, eliminating quality control entirely is not possible because both chance and assignable causes
occur (Montgomery 2005). Previous studies utilising quality-related indicators are listed in Table 2. Quality can be
judged 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 or
service that needs additional effort to meet quality specifications to total output. Scrap rate is the ratio of the products or
services 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 lean
production 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
Quantitative
Time effectiveness Waiting time
Quality Correction of defects
Process Over processing
Cost
Human resources Over motion
Delivery Over handling
Customer
Inventory Excess inventory and over production
Qualitative
Quality Correction of defects
Customer
Process Over processing
Human resources Over motion
Delivery Over handling
International Journal of Production Research 4595
(Krafcik 1988). The ultimate quality is zero defects (Crosby 1979; Karlsson and Åhlström 1996), that is, preventing
defects or scraps instead of reworking them.
Numerous poka-yoke devices are implemented in the production and service delivery systems and are essential to
lean 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 of
maximising machine use, Toyota seeks to maximise the appropriate use of people (Dennis 2002), so that fewer
employees 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 autonomous
defect control and (Q11) the ratio of number of people dedicated to quality control to total employees were used as
quality-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 and
flexibility in production at many industrial enterprises, through process-based management and highly flexible
implementation of these processes (Cuatrecasas Arbós 2002). As shown in Table 2,process has been employed as a
unique performance dimension in lean assessment in previous studies.
One of the techniques used in lean process management is total productive maintenance (TPM), and the main
performance 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 indicator
in lean assessment.
Capacity utilisation is a crucial indicator in lean (Bhasin 2008; Searcy 2009), even in service industries (Zarbo
2011). According to Hines, Holweg, and Rich (2004, 1006), if ‘the focus within lean thinking is to create capacity by
removing waste’then it can also be achieved with the application of improvements in OEE. Lean systems minimise
floor space to maximise production and profit per square foot (Kwak and Anbari 2006). Kokuryo (1996) stated that a
lean 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 total
area, (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 with
reduced costs, continuously improving quality and enhanced customer satisfaction. Deming (1986) developed the chain
reaction model to explain relationships among productivity, quality and cost. Therefore, cost reduction, which gives a
significant competitive advantage to the organisation, is a dimension in lean assessment. Previous studies employing a
cost indicator are listed in Table 2.
Deming (1986), Juran (1951,1989), and Juran and Gryna (1988) advised organisations to systematically measure the
cost of good and poor quality to assess quality systems. Berry and Parasuraman (1992) found that most companies spend
10–30% of sales revenue on quality costs. Superville, Jones, and Boyd (2003) stated that corporations like Xerox, General
Electric 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 total
sales should be a component in lean assessment. Due to their importance in financial evaluations and audits, the ratio of
profit (after interest and tax) to annual total sales (Bhasin 2008), the inventory cost ratio (Behrouzi and Wong 2011), the
ratio of total cost to total sales and average cost per unit should be monitored in assessing lean implementation. The
ratio of total cost to total sales demonstrates how much of the total sales are dedicated to total costs. Average cost per
unit is an indication of the firm’s competitiveness; the lower the average cost per unit, the higher the competitive
advantage.
These studies demonstrate that cost-related performance indicators implemented in LAT are relevant to a thorough
analysis of lean. In LAT the indicators are: (C1) the ratio of annual transportation cost to total sales, (C2) the ratio of
4596 F. Pakdil and K.M. Leonard
inventory cost to total sales, (C3) the ratio of total warranty costs to total sales, (C4) the ratio of total cost of poor
quality to total costs, (C5) the ratio of total costs to total sales, (C6) average cost per unit, (C7) the ratio of total
prevention costs to total costs, (C8) the ratio of total prevention costs to total sales and (C9) the ratio of profit after
interest and tax to total sales.
Human resources
Research clearly shows that, without strategic human resource management, overall lean practices will not work (see for
example Agrawal and Graves 1999; Bamber and Dale 1999; Longoni et al. 2013; Rothstein 2004; Wood 2005; Yauch
and 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;Way2002). One
of the most comprehensive studies on the human factor in lean implementation is a multi-analysis which examined
research on 308 firms over 22 years (Birdi et al. 2008). They found that empowerment, training and teamwork directly
lead 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 employees
themselves 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; Wright
and McMahan 1992).
Empowerment and employee development are key to the high-performance work practices that are necessary for
lean implementation (Huselid 1995; Lawler 1986). Empowerment outcomes include more productive and more flexible
employees (Hackman and Oldham 1976); proactivity and self-initiating attitudes among individuals and teams (Frese
et al. 1996; Parker, Williams, and Turner 2006); reductions in control costs (Batt 2001; Parker and Wall 1998); and
development 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 many
researchers (Table 2). Cross-functional teams reduce supervision costs, allow interdependent tasks to be completed and
require 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 turnover
rate, (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 job
classifications to total employees, (H8) the number of hierarchical levels, (H9) the ratio of total indirect employees to
total 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 with
internal delivery activities, such as transporting parts, raw materials and semi-finished materials, from one station to
another. Transportation of any parts or finished product in the organisation or among various organisations and factories
in different locations does not add any value (Karlsson and Åhlström 1996), but instead increases operation costs and
lead time. Behrouzi and Wong (2011) investigated the ratio of annual transportation costs to total annual sales, finding
that 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 in
studies (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 to
inventory-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) the
ratio of total transportation distance of materials to total sales, (D3) the average total number of days from orders
received to their delivery, (D4) the ratio of order processing time to total orders and (D5) the ratio of total number of
orders delivered late to total deliveries per year were considered essential to lean implementation and thus incorporated
into the LAT.
International Journal of Production Research 4597
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, customer
satisfaction 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 management
process (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 data
in 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 by
the customer to total sales.
Inventory
The largest source of waste is inventory (Karlsson and Åhlström 1996), as parts and finished products in warehouses do
not 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 fewer
suppliers lowers supply chain management costs. Inventory in a system can be reduced by either eliminating excess
capacity or lowering throughput time, but the latter is preferred, but it requires reliable suppliers and a process reducing
lead 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 and
Chen 2008). Karlsson and Åhlström (1996) used JIT as a major measurement factor in their assessment of lean: each
process 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 in
process 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 is
included 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) the
ratio of raw material and work in process inventory to current assets and (I7–I8) the ratio of finished goods inventory
to 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 lean
implementation efforts should be conducted on the production floor by looking and asking. Many LATs reported in the
literature utilised qualitative methods as well as quantitative ones (Bhasin 2011; Connor 2001; Doolen and Hacker
2005; Feld 2000; Fullerton and Wempe 2009; Goodson 2002; James-Moore and Gibbons 1997; Panizzolo 1998;Shah
and 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 main
leanness components, rated by respondents on a five-point Likert scale. Using a survey format, James-Moore and
Gibbons (1997) tested key constructs such as flexibility, waste elimination, optimisation, process control and people
utilisation through close-ended questions ending with ‘yes’or ‘no’. Panizzolo (1998) developed a qualitative model
including face-to-face structured interviews with high-level managers from 27 sample organisations and perceptional
questions were ranked on a five point-Likert scale. Shah and Ward (2007) conducted a survey among various
manufacturing firms incorporating three main indicators (suppliers, customers and internal processes).
4598 F. Pakdil and K.M. Leonard
Others used the qualitative lean enterprise self-assessment tool (LESAT) and lean processing programme to assess
company-wide lean implementation (Wan and Chen 2008). However, solely qualitative methods generally evolve with
the respondents’perceptions and responses and contain subjectivity and bias, due to individual judgments (Wan and
Chen 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 performance
dimensions, which are categorised as: quality, process, customer, human resources and delivery. The qualitative section
of LAT contains five performance dimensions measured by 51 items, as shown in Appendix A. Items are measured on
five-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 a
variety of tasks, such as problem formulation, diagnosing the root causes and development of solutions (Mast 2011).
The flow chart in Figure 1integrates 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 picture
because organisations decide implement parts of the system rather than the entire system. In addition, lean performance
is often not evaluated using a comprehensive measurement system or tool, possibly because managers believe that the
analysis 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 implementation
efforts 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 Pakdil
2008). 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.
International Journal of Production Research 4599
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 formulate
a fuzzy-logic model, the basic definitions are given below.
Definition 1. A fuzzy set ~
Ain a universe of discourse Xis characterised by a membership function l~
AðxÞwhich
associates with each element xin X, a real number in the interval [0, 1]. The function value l~
AðxÞterms the grade of
membership of x in ~
A(Zadeh 1965).
Definition 2. Let ~
Abe a fuzzy set and l~
AðxÞbe the membership function for x2~
A,ifl~
AðxÞis defined as given in
Equation (1) (Aydin and Pakdil 2008). In this function, ‘a’and ‘b’represent the best and worst lean performance of
each indicator, respectively (Behrouzi and Wong 2011).
l~
AðxÞ¼
1ifxia
0;if xib
1ðxiaÞ
ðbaÞ;if a\xi\b
8
<
:
(1)
After performance indicators are measured using LAT in an organisation, the fuzzy membership values are calculated
for each indicator. As a final step of the lean measurement, the final lean score is calculated as the mean of all
membership 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 LAT
quantitative assessment. Measurement using fuzzy membership functions and LAT scores are performed successfully as
given 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, they
can measure and calculate fuzzy membership functions and LAT score as they could do. According to this measurement
method, fuzzy membership functions are computed using Equation (1) and the organisation in example has 82.86 out of
100 leanness points at the final stage on the basis of Equation (2), where mis the number of dimensions, n
j
is the
number of performance indicators in each dimension j,j¼1;2;...;m;l~
AðxÞij is the fuzzy membership value of the ith
performance indicator of the jth dimension, i¼1;2;...;nj;j¼1;2;...;m.
Pm
j¼1Pnj
i¼1l~
AðxÞij
ni
m100 (2)
Bayou and De Korvin (2008) stated that lean scores may be categorised as lean,leaner and leanest on the basis of
the scores generated by the fuzzy measurement method. Fuzzy membership functions are converged to 100 to present a
better lean performance, i.e., the closer to 100, the better the fuzzy membership value and the better the performance of
lean implementation for that dimension. As shown in the example, the organisation achieves the best performance on
quality, delivery and customer dimensions, since they generated a converged fuzzy membership value closer to 100, as
seen in Table 5. The results also indicate that time effectiveness and cost dimensions need to be improved to achieve
total 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 improvement
needs 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 current
performance level for various indicators (Mann 2005). Radar charts have been frequently using for graphing multivariate
data in both academia and industry. By using radar charts, managers can more easily view their own leanness efforts
and 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 the
eight main performance dimensions in LAT is represented on a different radius of a radar plot. Each radius index starts
with zero (0) in the centre and ends with 100 points. The converged fuzzy membership values for each main dimension
are identified on the radius of the radar chart. The converged fuzzy membership values closest to the periphery represent
the best main performance dimension in LAT’s quantitative assessment, while the values closest to the centre correspond
to the dimensions of poor performance. An example of the use of a radar chart in LAT is shown in Figure 2. The same
procedure is performed for the qualitative data, which has been rated on a 5-point Likert scale.
4600 F. Pakdil and K.M. Leonard
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 x
1
(T1) 2 min. 0 min. 1.5 min. 0
x
2
(T2) 15% 0 20% 0.75
x
2
(T3) 5 days 0 day 6 days 0.16
x
3
(T4) 48 min. 24 min. 480 min. 0.84
x
5
(T5)
x
6
(T6) 50% 0 80% 0.625
x
7
(T7) 10% 0 5% 0
x
8
(T8) 25% 0 20% 0
LAT score 33.92
Quality x
1
(Q1) 8000 0 1,000,000 0.99
x(Q2) 3.1% 2% 100% 0.99
x
3
(Q3) 20,000 0 1,000,000 0.98
x
4
(Q4) 0.1063% 0 100% 0.99
x
5
(Q5) 90% 91% 100% 1
x
6
(Q6) 0.70% 0 100% 0.99
x
7
(Q7) 1.12% 0.91% 100% 0.99
x
8
(Q8) 5% 0 100% 0.95
x
9
(Q9)
x
10
(Q10)
x
11
(Q11) 2.5% 0 100% 0.975
LAT score 98.31
Process x
1
(P1) 70% 85% 0% 0.82
x
2
(P2) 0 0 100 1
x
3
(P3) 70% 100% 0% 0.70
x
4
(P4) 90 90 0 1
LAT score 88.00
Cost x
1
(C1)
x
2
(C2) 28 0 100 0.72
x
3
(C3) 1.5 1 100 0.99
x
4
(C4) 12 10 100 0.97
x
5
(C5) 79 0 100 0.21
x
6
(C6)
x
7
(C7) 6 0 100 0.94
x
8
(C8) 5 0 100 0.95
x
9
(C9) 8% 10% 0% 0.80
LAT score 79.71
Inventory x
1
(I1) 0.14 0.11 1 0.96
x
2
(I2) 6% 9% 0% 0.67
x
3
(I3) 28 0 100 0.72
x
4
(I4) 0.32 0.35 1 0.91
x
5
(I5) 0.09 0.06 1 0.96
x
6
(I6) 0.30 0.19 1 0.86
x
7
(I7) 0.96 0.95 1 0.93
x
8
(I8) 0.029 0.018 1 0.98
LAT score 87.37
Human Resources x
1
(H1) 1% 1% 100% 1
x
2
(H2) 1.7% 1.5% 100% 0.99
x
3
(H3) 4.9% 5% 100% 1
x
4
(H4) 5.94% 7% 0 0.85
x
5
(H5) 0.76% 1% 0 0.76
x
6
(H6) 67% 100% 0 0.67
x
7
(H7)
x
8
(H8) 6 6 20 1
x
9
(H9)
x
10
(H10) 64% 100% 0 0.64
x
11
(H11) 23% 35% 0 0.65
x
12
(H12) 32,497 37,379 0 0.87
(Continued)
International Journal of Production Research 4601
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 quantitative
assessment approach. Using only one qualitative or quantitative approach in lean assessment efforts may create a bias
both 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, organisations
should 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 on
fuzzy 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 qualitative
section, 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 both
improvement successes and needs in lean implementation, and use of fuzzy logic and radar charts allows an immediate,
0
20
40
60
80
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 84.30
Delivery x
1
(D1) 0.00004% 0 1% 0.99
x
2
(D2)
x
3
(D3) 25 20 100 0.94
x
4
(D4) 5% 5% 100% 1
x
5
(D5) 0 0 1 1
LAT score 98.25
Customer x
1
(C1) 93% 100% 0 0.93
x
2
(C2) 27% 35% 0 0.77
x
3
(C3) 1.5% 0 100% 0.98
x
4
(C4) 98% 100% 0 0.98
x
5
(C5) 0.000046% 0.000031% 1 0.99
LAT score 93
Total LAT score 82.86
4602 F. Pakdil and K.M. Leonard
comprehensive view of the strong areas and those needing improvement. LAT allows organisations to use the fuzzy
membership function based on data that they choose to collect. It does not require organisations to collect data for all
performance indicators given in LAT.
The LAT has theoretical and practical implications for business organisations implementing lean principles. In
theoretical terms, the LAT can support the various theories that have been developed about the intertwining of the
various 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 lean
systems. This creates a tremendous competitive advantage (Womack, Jones, and Roos 1990). In this sense, the LAT has
a 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 in
LAT presents the data in a comprehensive manner that can be understood by management in its entirety. Therefore, this
perceived limitation has a capacity to create an important advantage for practitioners. As another limitation, fuzzy
membership function may be seen unfeasible and impractical for practitioners and another calculation algorithm may be
utilised within LAT. We believe, however, that presenting the data in this manner gives managers the benefitofthe
holistic view of the organisation needed at the top level of the firm. Third, whether the organisation operates in a
manufacturing or services industry may make some differences in applying the LAT, considering that some performance
indicators 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 particular
industries, the others might be more important in other industries. Fifth, the LAT may not cover all important
performance indicators and dimensions that have a potential to assess leanness level in business organisations, but we
believe it captures the most critical.
There is potential for the use of LAT above and beyond lean implementation into sustaining the process of lean
production and management in goods and services industries. Future research and development of the tool would be a
worthwhile use of time and effort, because lean efforts can lead to substantial gains in competitive advantage and
productivity. This area, while well researched, lacks comprehensive coverage of the entire lean implementation
processes. 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 Research
Program.
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Appendix A. LAT’s qualitative items
Quality
(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.
4606 F. Pakdil and K.M. Leonard
(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.
International Journal of Production Research 4607
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