A roadmap for a leanness company to emerge as a true lean organization

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A roadmap for a leanness company to emerge as a true lean organization
Article  in  Concurrent Engineering Research and Applications · December 2019
DOI: 10.1177/1063293X19888259
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Concurrent Engineering: Research and Applications 28(1) 1
Concurrent Engineering, 28(1), 3–19 https://doi.org/10.1177/1063293X19888259
A roadmap for a leanness company to emerge as a true lean organization
Leandro Silvério, Luís Gonzaga Trabasso and Marcus Vinicius Pereira Pessôa
Department of Materials, Manufacturing and Automation, Aeronautics Institute of Technology, S. J. Campos/SP, Brazil
E-mail: leandro.silverio.pereira@gmail.com, gonzaga@ita.br, mvpessoa@gmail.com
Abstract
The problem this work aims to solve is the improvement of the leanness level of a company
jeopardized by the lack of lean engagement. The objectives of the research are to present a
method based on a lean self-assessment approach, consisted of a qualitative self-assessment
method based on lean elements that drives an index definition associated with a roadmap. The
method consists in providing a roadmap for the assessed enterprise composed by the company’s
lean index, recommendations and countermeasures deriving from Delphi and Kendall
Coefficient of Concordance (W) application among lean experts, leading the assessed enterprise
to achieve results in terms of lean engagement, autonomy, and decision support criteria for
future resource allocation. The results demonstrated that method can highlight gaps where
additional improvements and investments would be necessary in the assessed enterprise.
Finally, the study concludes that the lean performance identification associated to a lean
roadmap in a company can be a highly effective tool to improve lean adoption in a leanness
organization.
Keywords: lean manufacturing, leanness company, lean product development process, lean
wheel system, lean assessment tools, lean self-assessment, lean conceptual model, lean
roadmap, Kendall Coefficient of Concordance (W), Delphi
1 Introduction
Ever since lean manufacturing first appeared in the
literature, authors have tried to describe it theoretically
(Hines et al., 2006, 2004; Lewis, 2000; Possamai and
Ceryno, 2008; Shah and Ward, 2007). However, their
descriptions have been ambiguous and unclear (Boaden,
1997). Authors have declared at least 25 lean manufacturing
tools. In common to all of them are waste elimination and
the focus on available resource optimization, to which
engineering techniques (Karam et al., 2018) and statistics
fundamentals (Kiran, 2017) are applied. In the definition
adopted by this study, lean practices are a set of methods,
procedures, techniques, and tools aimed to continuously
create customer value and reduce product lead time (Shah
and Ward, 2007). According to Morgan and Liker, a lean
company (LC) aims for lean practices along the whole lean
development process (LDP), not only the manufacturing
shop phases (Morgan and Liker, 2006; Pessôa and Seering,
2014). The non-engagement of lean aspects along the
development phases is the definition of a leanness company
(Bauch, 2004). In an ideal product development process
(PDP), the process itself should work as a single-piece
manufacturing flow. That way, it is possible to reduce errors
in investigation loops interactions (Bonnal et al., 2006).
A lean management research and deployment trajectory is a
singular process in each organization (Lewis, 2000).
Researchers have already demonstrated that implementing
lean practices can help large manufacturing enterprises to
increase their operational performance (Krafcik, 1988; Ōno,
1988; Womack et al., 1991). Other researchers have also
addressed the lean roadmap issue by focusing on the core
critical success factors for lean performance examination in
the PDP (Aikhuele and Turan, 2018; Leite et al., 2016) and
explored the roadmap, metrics and management for
concurrent engineering (CE) in the product development
environment (Prasad, 1997a, 1997d; Prasad et al., 1998).
Therefore, the objective of this research is to combine the
lean assessment to a roadmap, based on a lean index (LI)
self-assessment method focused on identifying the main
positive and negative factors for a leanness enterprise. The
self-assessment method was selected for this study in order
to insure the engagement in decision-making processes for
the lean way, where some examples and case applications
are available from recent literature (Dwarakanath and
Wallace, 1995; Hauser et al., 2006; McNally and Schmidt,
2011). On the LDP, McCarthy et al. (2006) have identified
three levels of decision-making: strategic, review, and in-
stage. The in-stage is where agents deal with multiple
decisions involving producing and processing a rich

Silvério et al. 2
diversity of criteria that are the basis of PDP creative
activities and ideas. This is the stage on which this study
intends to focus.
The first step when creating a great product is to understand
what exactly makes a product great (Prasad, 1996b). In other
words, the goal of PDP is to create such manufacturable
physical product through a set of connected life-cycle
processes (Prasad, 2016a). Also in PDP, decision-making
grows out of a process over time (Christiaans and Almendra,
2010), and the engagement in decision-making process is
closely related to on-going assessments and roadmaps.
Specifically in LDP, the more extensive presence of top
management support is critical for continued company-wide
implementation of lean practices and decision-making. To
develop a coherent management philosophy seems a
daunting task, given the wide range of possibilities and
practices that must be addressed (Prasad, 1997b). Thus, the
concept of decision making focusing on the system level is
adopted by this method and supports the engagement in
decision-making processes, specifically in PDP.
2 Background
Today manufacturing sectors are much more fiercely
competitive and global than before (Prasad, 2001a). Thus, to
design and execute an enterprise transformation, it is crucial
to have assessments that measure multiple performance
dimensions during the process’s execution in order to
understand its current state and chart out the transformation
plan that will lead the company into a different future state
(Kueng, 2000). Such assessments can help in identifying
performance gaps, prioritize focus and play a role in helping
to generate a future state vision for the enterprise. As the
transformation plan is implemented, ongoing assessments
can also offer feedbacks and measure progress. This
feedbacks can be used to revise the transformation plan and
patch over time.
The management organizational capability for an enterprise
operation (internal or external) is becoming very crucial for
achieving not only time-to-market, but also improved
productivity, and better efficiency (Prasad, 1996a). Various
methods and tools for an enterprise’s operational
performance are comprised under lean strategy’s umbrella
(Bhasin, 2012). The earliest model found in the literature
was presented by Karlsson and Åhlström (1996), who
developed a model capable of determining the progress of a
lean manufacturing firm in the effort to adopt lean
fundamentals from the book “The Machine that Changed the
World,” by Womack et al. (1991). According to Schalock et
al. (2014) one of the major strengths of an evidence-based
assessment instrument is that it is an organizational
assessment tool that represents a new approach to
organizational evaluation based on self-assessment.
In recent years, product development (PD) has been an
essential element of competitive engineering (Duhovnik et
al., 2001). Since PD is a nonlinear (Kline, 1985;
Nightingale, 2000) and dynamic system process (Huang and
Gu, 2006), it is hard to determine what value is added—
especially in LDP, where design changes constantly happen
in the first phases of a PD. In the PDP context, this also
involves design, production planning, and manufacturing
(Amitrano et al., 2015), typically leading to lots of change
and rework (Mihm et al., 2002), while seeking for a high
leanness level and there are more opportunities for
competitive advantages in PDP than in any other department
or area of industrial companies (Mendes and de Toledo,
2015; Morgan, 2002; Toledo et al., 2008). A leanness level
is defined by Vinodh and Chintha (2011) as a performance
measure of lean operation. Comm and Mathaisel (2005)
described leanness as a relative measure of whether a
company is lean or not. The number of studies in the
literature on leanness assessment is low compared to those
on lean implementation areas (Narayanamurthy and
Gurumurthy, 2016). This study’s contributions compared to
previous and very recent papers are described in Table 1 in a
chronological sequence. From the assessed studies, over 90
papers, articles, journals, and full thesis from the last
23 years were screened and refined in order to compose a
systematic literature review.
Although the first leanness research was published in 1996
by Karlsson and Åhlström (1996), the next leanness study
appeared in the literature only 4 years later in 2000, and was
by Detty and Yingling (2000). As per Table 1, there is a
majority of proposed frameworks addressing a leanness
indicator thought the usage of a qualitative/quantitative
assessment. However, there is also a lack of a self-
assessment method for the leanness level definition,
associated with a roadmap to provide insights for the
decision makers. This is one of the gaps this research aims
to fit.
3 Methodology: a roadmap for a leanness
company to emerge as a true lean
organization
The method presented by this study is divided into two
topics: the LI equations and the lean roadmap definition.
The LI is the rate responsible for indicating the current
leanness level of the enterprise and based on its adequacy to
the ranges established by the method, a specific set of
recommendations are deployed according to the criteria
detailed in the following subsections.
3.1 Lean Index
The performance of an organization is largely governed by
the system in which it is contained. Thus, a LI overall is an
important rate for any company emerging as a lean
organization (Prasad, 2001b). The lean elements considered
in this study are the ones adopted by the lean wheel system
(LWS) model. The LWS intends to be a pictorial model that
shows the elements that support lean product development
and their relationship as illustrated in Figure 1.
In the LWS metaphor, the lean elements are rooted as the
hub elements interfacing one with each other (Pessôa and
Trabasso, 2017). The LWS elements considered in this
method are defined in Table 2 and the “core lean elements”
composed by: value, waste, and continuous improvement
had their definitions criteria adopted from the literature.

Silvério et al. 3
Table 1. Present contribution compared to previous and very recent papers.
# Question
A Is the model approach a qualitative or quantitative assessment?
B Does the model have defined indicators?
C Does the model provide the enterprise’s leanness level?
D Does the model provide a lean roadmap after the assessment is performed?
Author A B C D Author A B C D
Karlsson and Åhlström (1996) L Y N N Wong and Lai (2011) T Y Y N
Detty and Yingling (2000) LT Y Y Y Kuhlang et al. (2011) T Y Y Y
Sánchez and Pérez (2001) LT Y Y N Eroglu and Hofer (2011) LT Y Y N
Soriano‐Meier and Forrester (2002) T N Y N Chauhan and Singh (2012) L Y Y N
Nightingale and Mize (2002) LT Y Y Y Vinodh and Vimal (2012) L Y Y Y
Goodson (2002) LT Y Y N Nasab et al. (2012) L N Y N
Kumar and Thomas (2002) LT Y Y N Azevedo et al. (2012) L Y Y N
Hon (2003) LT Y Y N Anvari et al. (2012) T Y Y Y
Shah and Ward (2003) LT Y N N Bhasin (2012) L Y Y N
Leung and Lee (2004) L Y Y N Amin and Karim (2013) T Y N Y
Hobbs (2004) LT Y N Y Karim and Arif‐Uz‐Zaman (2013) T Y Y Y
Kojima and Kaplinsky (2004) LT Y Y N Gupta et al. (2013) T Y Y Y
Doolen and Hacker (2005) LT Y Y N Alemi and Akram (2013) T Y Y N
Little and McKinna (2005) LT Y Y Y Behrouzi and Wong (2013) T Y Y Y
Taj (2005) LT Y Y N Mostafa et al. (2013) LT Y Y N
Wan and Chen (2006) T Y Y N Wahab et al. (2013) L Y Y N
Ray et al. (2006) T Y Y N Lemieux et al. (2013) LT Y Y Y
Wan (2006) LT Y Y N Al‐Najem et al. (2013) LT Y Y Y
Bonavia and Marin (2006) LT Y Y N Al-Ashaab et al. (2013) LT Y N Y
Srinivasaraghavan and Allada (2006) T Y Y Y Lucato et al. (2014) LT Y Y N
Wan et al. (2007) T Y Y Y Elnadi and Shehab (2014) LT Y Y N
Shah and Ward (2007) LT Y Y N Pakdil and Leonard (2014) LT Y Y Y
Matsui (2007) LT Y N N Nesensohn et al. (2014) L Y Y N
Sanati and Seyedhoseini (2008) T Y Y N Ramirez and Lorena (2014) LT Y Y Y
Dal Pont et al. (2008) LT Y N Y Hosseini and Ebrahimi (2015) L Y Y Y
Barad and Dror (2008) L Y N Y Mostafa et al. (2015) LT Y N Y
Bayou and de Korvin (2008) LT Y Y N Soltan and Mostafa (2015) LT Y Y N
Bhasin (2008) L Y Y Y Donovan (2015) LT Y Y N
Saurin and Ferreira (2008) L Y Y N Urban (2015) T Y Y N
McLeod (2009) LT Y N N Mahfouz and Arisha (2015) LT Y Y Y
Gurumurthy and Kodali (2009) LT Y Y Y Vidyadhar et al. (2016) LT Y Y Y
Wu and Wee (2009) L Y N N Omogbai and Salonitis (2016) LT Y Y Y
Marvel and Standridge (2009) LT Y Y Y Maasouman and Demirli (2016) LT Y Y Y
Puvanasvaran et al. (2009) L Y Y N Carvalhosa et al. (2016) LT Y Y N
Rahman et al. (2010) LT Y N N Leite et al. (2016) LT Y N Y
Jeyaraman and Teo (2010) L Y Y Y Hjalmarsson and Olsson (2017) LT Y Y Y
Singh et al. (2010) LT NA Y N Abreu and Calado (2017) LT Y Y Y
Zanjirchi et al. (2010) LT NA Y N Rajpurohit et al. (2017) LT Y Y Y
Sun (2010) LT NA Y N Galankashi and Helmi (2017) LT Y Y N
Nordin et al. (2010) L Y Y N Gonçalves and Salonitis (2017) LT Y N N
Anvari et al. (2010) L Y N Y Sangwa and Sangwan (2018) LT Y Y N
Asadi and Panahi (2011) T Y Y N Albzeirat et al. (2018) LT Y Y N
Aurelio et al. (2011) LT Y Y Y Bento and Tontini (2018) LT Y Y N
Anvari et al. (2011) LT Y N Y Rakhmanhuda and Karningsih (2018) LT Y Y Y
Bhasin (2011) LT Y Y N Belhadi et al. (2018) LT Y Y N
Seyedhosseini et al. (2011) L Y Y N Pakdil et al. (2018) L Y Y Y
Vinodh and Chintha (2011) LT Y Y Y Aikhuele and Turan (2018) LT Y Y N
Vinodh and Balaji (2011) LT Y Y Y
Present work L Y Y Y
Behrouzi and Wong (2011) T Y Y Y
Y: yes; N: no; NA: not applicable; L: qualitative; T: quantitative; LT: qualitative and quantitative.

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Figure 1. Lean wheel system elements (Pessôa and
Trabasso, 2017).
The LI has five possible progressive maturity levels in its
composition. The levels range from least capable (Level 0)
to a true lean organization (Level 5). Table 3 defines the
meaning of each level. These levels are intended to depict a
progression in the lean capability of the enterprise, relatively
to the particular lean aspect being assessed.
For the LI construction, each lean element defined in Table
2 receives a theoretical value rate 5 in a 0–5 scale in order to
set the referential lean rate (LR). This referential value is
called the theoretical true lean organization rate (TTLOR)
and will be used as an input for the method deployment. The
referential LR is considered to be a theoretical value because
fulfilling all lean aspects is rather difficult, if not impossible.
The referential LR is indicated in Table 4.
The referential LR is defined in order to establish a baseline
for the LI calculation based on the TTLOR. Equation (1)
describes the TTLOR.
(1)
The TTLOR is a theoretical value that indicates a true lean
organization company where all definition criteria aspects
are in line with the PDP. Each lean element considered in
Table 4 has its own (and real) element lean rate (ELR) when
the assessment is performed for each lean aspect considered
in Table 2, by the enterprise intended to emerge as a true
lean organization. The ELR is defined in equation (2).
(2)
As mentioned before, the ELR is a realistic rate that comes
directly from the self-assessment performed by the
enterprise during the method’s deployment. As far as each
lean element considered in Table 2 has a different definition
criteria aspects amount, the relativeness between them are
achieved through equation (2), which standardizes the
“weights” considered for all the elements through a “5×”
multiplication factor, and also by the TTLOR considered in
the mathematics as shown in equation (2).
Within the TTLOR and the ELR, it is possible to get the LI
by calculating the average between the sum of all ELR and
the total amount of lean elements considered by the method,
as indicated in equation (3).
(3)
The LI is based on a comparison between the company’s
current state and a future target condition that best describes
a true lean organization company (theoretical value),
emerging from a scenario where all lean elements are in line
with the lean product development process. Based on the LI,
the lean index level range (LILR) and the lean engagement
level diagnosis (LELD) are established in order to deploy
the full engagement diagnosis and associated lean roadmap
for the assessed enterprise. For an LI where the result is
close to the target condition, for example, the LILR value
shall be up to 90% from the reference value in a 0–5 scale.
However, an LI with values between 44% and 30% of the
reference value on a 0–5 scale indicates poor lean
engagement. An LI below 29% from the reference value on
a 0–5 scale indicates that the assessed enterprise is
unqualified for the evaluated lean element. The definitions
and rate criteria for the LILR are presented in Table 5 and,
the LELD, definitions and rate criteria are presented in
Table 6.
Engagement OK means the LILR is between excellent and
very good. A company with such a high level is in line with
the lean concept and techniques. The lean enterprise shall
continue seeking continuous improvements and waste
reduction by the application of Kaizen, PDCA (plan, do,
control, and act), and SDCA (standardize, do, check, and
act). A new evaluation shall be performed every 6 months in
order to guarantee current LELD.
Engagement to Improve means the LILR is between good
and regular. A company at such an intermediate level is line
to succeed with the lean concept and techniques but also has
opportunities to overcome it. The lean company shall
continue seeking continuous improvements and waste
reduction according to the lean roadmap defined for each
assessed element. A new evaluation shall be performed
every 3 months in order to confirm the current LELD and to
check for progress to the next level at the assessment
reapplication.
Engagement NOK means that the LILR is between poor and
unqualified. A company with such a low level is in the
beginning of the lean transformation patch. The enterprise
shall continue seeking continuous improvements and waste
reduction according to the lean roadmap defined for each
assessed element. A new evaluation shall be performed on a
monthly basis in order to be ready for the next assessment
reapplication.
Each lean element and related definition criteria has a
selected amount of countermeasures (CMs) associated with
it. The CMs composes the lean roadmap and are applicable
only for those cases where the assessed enterprise is
diagnosed within the LELD “Engagement to Improve” or
“Engagement NOK.”

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Table 2. Lean wheel system elements definition (Pessôa and Trabasso, 2017).
Element Definition (lean aspects)
Culture
• Support excellence and relentless improvement.
• Adapt technology to fit your people and process.
• Align your organization through simple visual communication.
Knowledge
management
• Standardized “performance trade-off” data are collected for each alternative.
• Use powerful tools for standardization and organizational learning.
• Engineers are required to be knowledgeable about all solutions.
• Detailed engineering checklists and design standards are used to assure focus on product performance.
• Fully integrate suppliers into the product development system.
• Build in learning and continuous improvement.
Organizational
structure
• Managers are technically competent in engineering: “your boss can always do your job better than you.”
• The manager’s primary role is to teach by assigning questions (mentoring).
• Authority and rewarding in the system derives from technical knowledge and competence.
• Develop a value-centered system to integrate development from start to finish.
• Organize to balance functional expertise and cross-functional Integration.
Process
• No elaborate sub-schedules; Chief Engineer sets “key integration events.”
• Work is pulled to these events.
• Milestones are never missed.
• Multiple alternatives are developed for each subsystem.
• Combinations that meet performance trade-offs “survive.”
• Establish customer-defined value to separate value-added from waste.
• Create leveled product development process flow.
• Utilize rigorous standardization to reduce variation, and create flexibility and predictable outcomes.
Tools and
technology
• The lean tools and technology are those you use in the lean way, not the “lean labeled tools.”
• The tools and techniques do not make you lean – the way you use the tools is what makes them lean.
Value
• Specify value: value as defined by the final client, is the basis of LT and guide all processes in the
company. Without identifying the value, one cannot discern value added activities from waste.
• Identify the value stream: the value stream is a theoretical and ideal sequence of exclusively value-added
tasks where a value-added activity transforms the deliverables of the project in such a way that the
customer recognizes the transformation and is willing to pay for it.
• Guarantee the flow: all the value-added activities should be conducted without interruption.
• Pull the value: no activity in the value stream should be produced without being requested by the next
activity in the flow.
• Seek perfection: relentless continuous improvement is the motor that sustains and evolves the lean
philosophy.
Waste
• Overproduction: producing process outputs at a higher rate or earlier than the next process can use them
is overproduction; its subtypes are unnecessary and unsynchronized processes.
• Waiting: this refers to the part of the processing time when the creation of value remains static, hence
the value stream is considered “non-flowing” due to the lack of inputs, resources, or controls.
• Transportation: this includes the loading, transporting, and unloading of outputs/inputs (information or
material) and resources from place to place without adding value during the process.
• Over processing: completing unnecessary work during a process.
• Inventory: raw, in-process, or finished buildup of information, knowledge, or material, such as
prototypes that are not being used.
• Motion: this refers to any unnecessary movement of people or activity during non-transformation task
execution in a process.
• Defects: defects are the creation of defective outputs as a result of the development process.
• Correcting: this is the result of redoing or scrapping due to feedback. Correcting subtypes is
repairing/reworking, scrapping, and inspecting to find problems.
• Wishful thinking: making decisions (mental activity) without the needed inputs (data) or operating
according to incorrect controls.
• Happenings: all reactions to unexpected happenings in the environment.
Continuous
improvement
• Make observations and propose a solution.
• Design and perform an experiment to test the solution.
• Analyze your data to determine whether to accept or reject the solution.
• Propose and test a new solution.
LT: lean thinking.

Silvério et al. 6
Table 3. Progressive maturity LI levels.
LI level Definition
0
The company does not apply lean practices in
the PDP for the evaluated aspect.
1
The company is aware of the lean practices
applicable to the evaluated aspect but does not
have any formal method established for their
implementation.
2
The company is aware of the lean practices
applicable to the evaluated aspect but uses an
informal approach for their application (tryout).
3
The company has started implementing the lean
practices applicable to the evaluated aspect by
following a formal approach. There is a
systematic methodology under development,
facilitated by metrics and visibilities.
4
The company has implemented the lean
practices applicable to the evaluated aspect by
following a formal approach. There is ongoing
refinement and continuously improvement
processes across the extended enterprise
(internal and external, including supply chain).
Improvements gains are well structured and
sustained by metrics and visibilities.
5
The company is on the lean way for the
evaluated aspect and has implemented lean
practices at a high level in all associated PDP
stages by following a formal approach. The
aspect itself is fully deployed across the
extended enterprise (internal and external,
including supply chain) and is recognized as a
best practitioner by the teams and leadership.
LI: lean index; PDP: product development process.
Table 4. Theoretical true lean organization rates.
Lean element
TTLOR
(referential LR)
Culture 5
Knowledge management 5
Organizational structure 5
Process 5
Tools and technology 5
Value 5
Waste 5
Continuous improvement 5
LR: lean rate; TTLOR: theoretical true lean organization
rate.
Table 5. Lean index level ranges.
LILR
definition
LILR rate criteria
Excellent Lean Index ≥ 0.90xTTLOR
Very Good 0.75xTTLOR ≤ Lean Index ≥ 0.89xTTLOR
Good 0.60xTTLOR ≤ Lean Index ≥ 0.74xTTLOR
Regular 0.45xTTLOR ≤ Lean Index ≥ 0.59xTTLOR
Poor 0.30xTTLOR ≤ Lean Index ≥ 0.44xTTLOR
Unqualified Lean Index ≤ 0.29xTTLOR
LILR: lean index level range; TTLOR: theoretical true lean
organization rate.
Table 6. Lean engagement level diagnosis definition.
LELD
definition
LILR rate criteria
Engagement
OK
Excellence Lean Index ≥ 4.5
Very Good 3.7 ≤ Lean Index ≥ 4.4
Engagement
to Improve
Good 3 ≤ Lean Index ≥ 3.6
Regular 2.2 ≤ Lean Index ≥ 2.9
Engagement
NOK
Poor 1.5 ≤ Lean Index ≥ 2.1
Unqualified Lean Index ≤ 1.4
LELD: lean engagement level disgnosis; LILR: lean index
level range; NOK: not OK.
For those cases, the proposed roadmap can lead the
enterprise on acting on the identified weakest lean elements.
Figure 2 illustrates an interaction cycle, where the more
countermeasures are applied after each assessment cycle, the
more a company can emergence as a true lean organization.
The objective of the interaction cycles is to demonstrate the
importance of continually seeking improvement and process
optimization after the roadmap and associated lean
initiatives take place.
Figure 2. Interaction cycle (constructed by authors).
3.2 Lean Roadmap
A roadmap is a traffic-flow example that indicates several
possible routes from a chosen starting point to a desired
destination (Prasad, 2016b). The lean roadmap proposed by
this study was established by the Delphi research

Silvério et al. 7
methodology, that has been previously presented as a survey
(Bandyopadhyay, 2005), a study (Keebler and Plank, 2009;
Stevenson and Spring, 2007), a technique (Akkermans et al.,
1999; Babbar et al., 2008; Lummus, 2007; Manuj et al.,
2009), and a method (Hameri and Hintsa, 2009; Reyes and
Giachetti, 2010). Initially, a group of 15 professionals was
invited to make up the lean experts board. However, seven
of them could not attend, resulting in a total of eight lean
experts for the Delphi application. Interviews were launched
in order to compose the roadmap for each lean element
considered on this research (see Appendix 1). The Delphi
application was performed by January 2018, and comprised
two rounds, as per the following approach. In the first round,
the respondents were asked to give their perceptions for
each lean element regarding a roadmap to be followed by a
leanness enterprise to emerge as a true lean organization. In
the second round, panel members exchanged their
assumptions in relation to those given by the group as a
whole, and they came up with an average definition after the
group’s reflection on the shared response group dynamics
performed among the participants. The second round
questionnaire (see Appendix 1) comprised same questions as
the first round, plus the average answers gathered from first
loop. Once more, it was launched among the lean experts,
now considering the “group’s response” as per the first
round conclusion. The results were considered to be the
consensus of the lean specialists group regarding a lean
roadmap for the elements considered by this study to be
implemented in a leanness enterprise emerging as a true lean
organization.
To obtain a measure of consistency among the eight lean
expert’s responses, Kendall Coefficient of Concordance (W)
was also applied. Kendall Coefficient of Concordance (W)
is a statistical test of agreement among two or more judges,
or of the consistency of two or more sets of rankings in a
contest (Israel, 2009). This coefficient varies between “0,”
indicating no agreement between judges, and “+1,”
indicating a complete agreement among the judges on the
ranking of various attributes. In equation (4), Kendall
coefficient of concordance (W) is demonstrated.
(4)
As a level of significance for equation (4), the proposed
method adopted a 95% confidence interval, as indicated in
equation (5).
%)
(5)
According to equations (4) and (5) application, when
Kendall coefficient of concordance (W) is from 0.571 to 1,
it means that the lean experts selected for this study
consolidation set an agreement or concordance trend for the
lean element roadmap under evaluation. The same way, as
far as Kendall coefficient of concordance (W) is below
0.571–0, then there is no overall agreement or concordance
trend for the lean element roadmap under evaluation; as a
result the identified ranges for the coefficient of
concordance (W) were used for the roadmap definition.
Appendix 1 presented the same roadmap action plan
(AP)/CMs for all the lean elements considered by the
method; and only the ones assigned within Kendall
coefficient of concordance (W) attending the first criteria
(from 0.571 to 1) were considered for each lean element
roadmap definition. Table 7 presents the roadmap resulting
from the Delphi and Kendall coefficient of concordance (W)
application.
4 Results and Analysis
Recently, products like aircraft and helicopters are
becoming more and more complex than before (Prasad,
2001c) and the manufacturing industry each time moves
toward to products customization (CJ Anumba et al., 2000).
The complexity and variety of new product introduction
(NPI) have grown from a very “simple” to a “complex”
scenario. At the same time, the time-to-market dimension
has shrunk (Prasad, 1994a, 1997c). As part of this context,
the case study for the method application is an aeronautical
company responsible for supplying interiors and hydraulic
components for the Brazilian aircraft manufacturing
industry. It was founded on 4 July 1990 in Rio de Janeiro
and had around 100 employees by the time method was
deployed. The facility also contained manufacturing,
laboratory, and engineering departments engaged in the
development and production of its products.
4.1 Results
The method’s deployment results prior to the
countermeasures application in the assessed enterprise are
summarized in Table 8. In the same way, the method's
deployment results after the countermeasures application in
the assessed enterprise are summarized in Table 9.
As far as the lean index for the case study enterprise scored
2.5 on a 0–5 scale prior to the countermeasures application,
and the LILR was categorized as “Regular,” the LELD was
classified as “Engagement to Improve” according to Table 6
criteria. The “Engagement to Improve” classification
conducted the enterprise to apply the lean roadmap deployed
by the method, taking countermeasures for the assessed lean
elements classified as “Engagement to Improve” or
“Engagement NOK” as per Table 6 criteria and definitions.
Three months after the method’s application and the
roadmap recommended by this study being applied, the case
study enterprise was reassessed, and the results are
summarized in Table 9.
4.2 Analysis
As demonstrated by Table 9, after the roadmap’s application
for the case study enterprise, there was a slight improvement
in the overall LILR and several associated lean elements.
The elements “sponsored” by leadership such as:

Silvério et al. 8
Table 7. Lean roadmap.
# Action plan/countermeasures
A
Cultivate the company’s LT through a formal lean program and obtain leadership commitment to it.
Implement an approval workflow considering engineers as stakeholders and encourage continuous
improvement commitment in all employees’ levels.
B
For unexpected business and market happenings, run VSMA and 5-Whys investigations. The usage of the
seven steps waste reduction/elimination technique and the engineering participation in CoPs for lessons
learned and discussions is also recommended.
C
Analyze enterprise’s processes in order to deploy a VSMA for the most critical one. Run a daily wrap-up
meeting including suppliers (if necessary) and perform a PDCA focusing on the information flow.
Releasing an MPP integrating all development phases (PDR and CDR) is also recommended.
D
Obeya creation is recommended, indicating the “was/is” scenario for each PDP emerged from lean tools.
Provide a company’s core values and fundamentals through a simple and visual communication positioned
in strategic places in the facility. Deploying a 5S technique and running a VSMA is also recommended.
E
Select a Chief Engineer for the company and run a PDCA and KPI for the most critical process. Run an
SBCE and synchronize organizational understanding: (1) details of how the work gets done; (2) each
participant’s responsibilities; (3) key inputs, outputs, and interdependencies for each activity; and (4)
sequences of activities. To release an MPP integrating all development phases (PDR and CDR), is also
recommended.
F
Optimize knowledge barriers by the mentoring process through an engineering apprenticeship environment
creation, through which highly technical tacit skills are handed down from one generation to the next.
Create a formal knowledge management portal and a dedicated room for engineering prototyping.
Encourage leadership to participate in the engineering CoPs and to exercise the genchi genbutsu by the “go
and see” approach. Review the VSMA and run a PDCA and a KPI for the most critical process is also
recommended.
G
Implement the practice of a daily hansei and optimize an unsynchronized process by running a VSMA.
Register the process flow and engineering checklist in the know-how database, sharing lessons learned in
the engineering CoPs. To run a flow deﬁnition sub-matrix, VFD and deploy the SBCE process for the most
critical process is also recommended.
H
Deploy a pull event plan associated with a physical progress evidence chart available in the obeya. Make
sure the “key integration events” set by the Chief Engineer in the MPP are engaged by all development
teams.
I
Use DFX and/or DTX as a guideline to identify the most profitable tool to be applied in each development
phase, and run PDCA and KPI for the most critical process.
J
For in-process inventory, in-product inventory, and in-company inventory, establish a monitoring/data
collection indicator to be checked in a monthly basis. For physical defects, repairing/reworking, and
scrapping, find out the defect RC by evaluating the VSMA. For information wrongly perceived as complete,
make sure data provided are available in a timely manner and formally approved by the engineering teams
before it gets submitted to next development process. The usage of the seven steps waste
reduction/elimination technique and the 5-Whys investigation process is also recommended.
Lean element
Lean roadmap
A B C D E F G H I J
Culture X X X X
Knowledge management X X X X X
Organizational structure X X X
Process X X X X X
Tools and technology X X X
Value X X X X
Waste X X X X X
Continuous improvement X X X
VSMA: value stream mapping analysis; CoP: community of practice; PDR: preliminary design review; CDR: critical design
review; SBCE: set-based concurrent engineering; KPI: keep performance indicator; MPP: master phase plan; VFD: value
function deployment; DFX: design for X; DTX: design to excellence; RC: root cause.

Silvério et al. 9
culture, organizational structure, value, and continuous
improvement had a bigger impact on the reassessment,
demonstrating that lean initiatives are closely related to all
enterprises’ levels of engagement to succeed on the
transformation patch.
Table 8. Lean engagement assessment summary prior to
roadmap.
Assessment summary results Score
TTLOR 5
ELR for culture 2.3
ELR for knowledge management 2.6
ELR for organization structure 2.4
ELR for process 1.7
ELR for tools and technology 3.5
ELR for value 2.4
ELR for waste 3.4
ELR for continuous improvement 2.0
LI 2.5
LILR Regular
LELD Engagement to improve
TTLOR: theoretical true lean organization rate; ELR:
element lean rate; LI: lean index; LILR: lean index level
range; LELD: lean engagement level diagnosis.
Table 9. Lean engagement assessment summary after
roadmap.
Assessment summary results Score
TTLOR 5
ELR for culture 4.3
ELR for knowledge management 3.0
ELR for organization structure 4.4
ELR for process 2.0
ELR for tools and technology 3.5
ELR for value 4.0
ELR for waste 3.4
ELR for continuous improvement 4.0
LI 3.5
LILR Good
LELD Engagement to improve
The LILR was upgraded from ``Regular'' to “Good” but the
LELD was still classified as “Engagement to Improve.” That
way, a roadmap was also deployed by the method after the
reassessment, providing recommendations and
countermeasures only for the lean elements with low ELR as
per Table 5 and 6 criteria.
5 Conclusion
The proposed method can be used as guidance for the
managers to introduce recommended changes on their lean
implementation journey. The lean implementation patch is
not a destination but a journey, and a high lean index value
is not directly linked to the number of lean methods and
tools adopted by the company, but it is closely related to a
maturity level constructed on a daily basis and supported by
the performance indicators. The manufacturing sustained
growth and earnings are based on creating high value
products in very dynamic global markets (Prasad, 1994b).
That way, the comprehensive implementation of lean
practices is necessary and, in order to be effective, all lean
initiatives should be “sponsored” by leadership (Badri et al.,
1995; Danese et al., 2017; García et al., 2013; Hu et al.,
2015; Netland, 2016; Shah and Ward, 2007). Finally, since a
lean organization is in new technological advances constant
touch and frequently employs technologies to improve an
existing product (Prasad, 1995), it cannot be sustained using
conventional techniques alone. The application of
complementary methodologies and methods such as the lean
integrated and connected (LIC), knowledge capture and
reuse (KCR), library of knowledge frameworks (Nada et al.,
1998; Prasad, 2017), life-cycle measures and metrics for
concurrent product and process design (Prasad, 2000) and a
performance assessment based on reliability/decision-based
integrated product development (DIPD) frameworks
(Prasad, 1999, 2002) are also recommended.
Appendix 1: Interview protocol for Delphi
application - first and second rounds
Framework below is intended to support a research
regarding the lean roadmap definition for a leanness
enterprise to emerge as a true lean organization. To do this,
it is important to get the lean experts’ data and perception
related to the adequate lean roadmap to be implemented by a
leanness company for the elements considered below. Please
answer the questionnaire according to your perception in a
two-round session. First session each lean expert will
respond the questionnaire according to its own perception,
without having access to the “group’s response.” Second-
round session will consider the same questionnaire, this time
taking in consideration the “group’s response” to be shared
among the lean experts’ as per first round’s results.
Engineering Department: ___________________________
Years of experience in lean manufacturing: _____________
Questionnaire protocol: For the following lean
countermeasures please rank your perception about their
importance related to “Culture,”“Knowledge
Management,”“Organizational Structure,”“Process,”“Tools
and Technology,”“Value,”“Waste” and “Continuous
Improvement” in a leanness enterprise emerging as a true
lean organization, by considering one (1) for the most
important and ten (10) for the less important initiative.

Silvério et al. 10
(A/J) Cultivate the company’s LT through a formal lean
program and obtain leadership commitment to it. Implement
an approval workflow considering engineers as stakeholders
and encourage continuous improvement commitment in all
employees’ levels.
Culture: ( ); Knowledge Management: ( ); Organizational
Structure: ( ); Process: ( ); Tools and Technology: ( );
Value: ( ); Waste: ( ); and Continuous Improvement ( ).
(B/J) For unexpected business and market happenings, run
VSMA and 5-Whys investigations. The usage of the seven
steps waste reduction/elimination technique and the
engineering participation in CoPs for lessons learned and
discussions is also recommended.
(C/J) Analyze enterprise’s processes in order to deploy a
VSMA for the most critical one. Run a daily wrap-up
meeting including suppliers (if necessary) and perform a
PDCA focusing on the information flow. Releasing an MPP
integrating all development phases (PDR and CDR) is also
recommended.
(D/J) Obeya creation is recommended, indicating the
“was/is” scenario for each PDP emerged from lean tools.
Provide a company’s core values and fundamentals through
a simple and visual communication positioned in strategic
places in the facility. Deploying a 5S technique and running
a VSMA is also recommended.
(E/J) Select a chief engineer for the company and run a
PDCA and KPI for the most critical process. Run an SBCE
and synchronize organizational understanding: (1) details of
how the work gets done; (2) each participant’s
responsibilities; (3) key inputs, outputs, and
interdependencies for each activity; and (4) sequences of
activities. To release an MPP integrating all development
phases (PDR and CDR), is also recommended.
(F/J) Optimize knowledge barriers by the mentoring process
through an engineering apprenticeship environment
creation, through which highly technical tacit skills are
handed down from one generation to the next. Create a
formal knowledge management portal and a dedicated room
for engineering prototyping. Encourage leadership to
participate in the engineering CoPs and to exercise the
genchi genbutsu by the “go and see” approach. Reviewing
VSMA and running a PDCA and KPI for the most critical
process is also recommended.
(G/J) Implement the practice of a daily hansei and optimize
an unsynchronized process by running a VSMA. Register
the process flow and engineering checklist in the know-how
database, sharing lessons learned in the engineering CoPs.
To run a flow definition sub-matrix, VFD and deploy the
SBCE process for the most critical process is also
recommended.
(H/J) Deploy a pull event plan associated with a physical
progress evidence chart available in the obeya. Make sure
the “key integration events” set by the Chief Engineer in the
MPP are engaged by all development teams.
(I/J) Use DFX and/or DTX as a guideline to identify the
most profitable tool to be applied in each development
phase, and run PDCA and KPI for the most critical process.
(J/J) For in-process inventory, in-product inventory, and in-
company inventory, establish a monitoring/data collection
indicator to be checked in a monthly basis. For physical
defects, repairing/reworking, and scrapping, find out the
defect RC by evaluating the VSMA. For information
wrongly perceived as complete, make sure data provided are
available in a timely manner and formally approved by the
engineering teams before it gets submitted to next
development process. The usage of the seven steps waste
reduction/elimination technique and the 5-Whys
investigation process is also recommended.

Silvério et al. 11
Declaration of conflicting interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
ORCID iD
Leandro Silvério: orcid.org/0000-0002-0334-877X
Luís Gonzaga Trabasso: orcid.org/0000-0003-3858-3670
Marcus V. Pereira Pessôa: orcid.org/0000-0002-1096-8344
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Author biographies
Leandro Silvério has a Master degree in Mechanical and Aeronautical Engineering obtained from
Aeronautics Institute of Technology (ITA) in 2013. Currently he is a PhD candidate in the department of
Materials, Manufacturing and Automation at the same institute. His main research interests are Lean
Manufacturing, Lean Product Development Process and Lean Assessment Tools.
Luís Gonzaga Trabasso, Ph.D., is a graduate mechanical engineer from Universidade Estadual Paulista
Júlio de Mesquita Filho, Brazil (1982) and has master of science in engineering and aerospace
technology from Instituto Nacional de Pesquisas Espaciais, Brazil (1985) and Ph.D. in mechanical
engineering Loughborough University, England (1991) and pos-doctorate in Human Centered Systems
at Linköping University, Sweden (2017). He has held various positions as a professor at the Instituto
Tecnológico de Aeronáutica, Brazil (ITA) since he entered in 1984. He is one of the founders of the
Competence Center of Manufacturing at ITA (CCM/ITA), a laboratory that hosts strategic projects with
industrial partners. Currently, he is the Chief Researcher at Senai Innovation Institute - Joinville - SC as
well as a full professor - collaborator - at ITA, focusing his research on integrated product development
(IPD), Lean IPD, industrial automation, and robotics.
Marcus Vinicius Pereira Pessôa, PhD PMP, is an assistant professor at the Design, Production and
Management Department in the University of Twente, the Nederlands. He is a retired officer from the
Brazilian Air Force, where he worked in several air defense, and air traffic management systems
development projects. His main research focus is in the improvement of the Product Design and
Development process, particularly by considering the interconnection between the disciplines of
Systems Engineering and Project Management.
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