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

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 Delphi

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 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.

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.

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.

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.

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.

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.

Figure 1.

Lean wheel system elements (Pessôa and Trabasso, 2017).

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.

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.

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.

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.

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.

Table 4.

Theoretical true lean organization lean 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.

The referential LR is defined in order to establish a baseline for the LI calculation based on the TTLOR. Equation (1) describes the TTLOR.

TTLOR = \sum (ref . LR for each lean element)

(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).

ELR = 5 \times (\frac{\sum (element rate)}{TTLOR})

(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).

LI = \frac{\sum (ELR)}{total amount of lean elements}

(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.

Table 5.

Lean index level ranges.

LILR definition	LILR rate criteria
Excellent	Lean Index ⩾ 0.90 × TTLOR
Very Good	0.75 × TTLOR ≤ Lean Index ⩾ 0.89 × TTLOR
Good	0.60 × TTLOR ≤ Lean Index ⩾ 0.74 × TTLOR
Regular	0.45 × TTLOR ≤ Lean Index ⩾ 0.59 × TTLOR
Poor	0.30 × TTLOR ≤ Lean Index ⩾ 0.44 × TTLOR
Unqualified	Lean Index ≤ 0.29 × TTLOR

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	Excellent	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 diagnosis; LILR: lean index level range; NOK: not OK.

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.” 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).

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 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.

W = \frac{12 \sum D^{2}}{m^{2} (N) (N^{2} - 1)}

(4)

As a level of significance for equation (4), the proposed method adopted a 95% confidence interval, as indicated in equation (5).

\begin{matrix} α = 0.05 (95 %) \\ df = m = 8 (lean experts) \end{matrix}

(5)

\begin{matrix} N = 10 (lean roadmap initiatives) \\ W_{0.05} = 0.571 \end{matrix}

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.

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 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
Lean element	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.

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.

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.

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

TTLOR: theoretical true lean organization rate; ELR: element lean rate; LI: lean index; LILR: lean index level range; LELD: lean engagement level diagnosis.

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.

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: 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.

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.

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.

Footnotes

Appendix 1 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

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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