Performance measurement and lean maturity: congruence for improvement

Zanon, Lucas Gabriel; Ulhoa, Túlio Fígaro; Espôsto, Kleber Francisco

doi:10.1080/09537287.2020.1762136

Cited by 24 publications

(23 citation statements)

References 53 publications

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“…Regardless of the wide adoption of LM, a generalizable implementation approach has not been yet established (Marodin and Saurin, 2013;Tortorella et al, 2015a;Zanon et al, 2020). Thus, Table 1 lists LM practices most frequently studied in the specialized literature.…”

Section: Lm Practices and Leadershipmentioning

confidence: 99%

Analysing the influence of organisational culture and leadership styles on the implementation of lean manufacturing

Tortorella

Fettermann

Fogliatto

et al. 2020

Production Planning & Control

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This paper aims at identifying the combination of organizational culture profiles and leadership styles that best support companies implementing lean manufacturing practices. For that, 225 leaders from manufacturing companies at various stages of lean implementation were surveyed.The analytical approach clustered respondents and their respective firms according to prevailing organizational culture, leadership style and level of implementation of lean practices, testing for frequency differences among clusters. This study states that organizational culture profiles are related to leadership styles and lean manufacturing implementation level, suggesting different-from-expected effects of this relationship on lean manufacturing implementation. The study bridges a gap in the literature by exploring how the association between organizational culture and leadership styles occurs in companies that are adopting lean practices.

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Section: Lm Practices and Leadershipmentioning

confidence: 99%

Analysing the influence of organisational culture and leadership styles on the implementation of lean manufacturing

Tortorella

Fettermann

Fogliatto

et al. 2020

Production Planning & Control

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“…Just-in-time Pull system/Kanban system (Furlan, Vinelli & Dal Pont, 2011;Shah & Ward, 2003;Zanon, Ulhoa & Esposto, 2020;Zirar, Trusson & Choudhary, 2020) Small lot production (Furlan et al, 2011;Hoque, Hasle & Maalouf, 2020;Iqbal, Jajja, Bhutta & Qureshi, 2020;Santos & Tontini, 2018;Shah & Ward, 2003;Zanon et al, 2020) Cellular layout (Shah & Ward, 2003;Zirar et al, 2020) Quick changeover (Afonso et al, 2022;Furlan et al, 2011;Hoque et al, 2020;Iqbal et al, 2020;Santos & Tontini, 2018;Shah & Ward, 2003) Heijunka (Dave & Sohani, 2019;Santos & Tontini, 2018) JIT supplier (Bose, 2020;Hoque et al, 2020;Nawanir et al, 2016;Sisson & Elshennawy, 2015) Value Stream Mapping (Dave & Sohani, 2019;Mabunda, 2019) Total Quality Management Poka-yoke (Furlan et al, 2011;Shah & Ward, 2003;Zanon et al, 2020) Standardized work (Furlan et al, 2011;Shah & Ward, 2003) Quality at source (Sancha, Wiengarten, Longoni & Pagell, 2020;Zanon et al, 2020) Statistical process control (Sancha et al, 2020;Zanon et al, 2020;Zirar et al, 2020) Visual management (Bose, 2020;Iqbal et al, 202...…”

Section: Lm Practices Items Literaturementioning

confidence: 99%

“…Previous research has found that LMAT improves performance (Galeazzo, 2019;Santos & Tontini, 2018;Zanon et al, 2020). Manufacturers with a low degree of LMAT do not regularly employ lean tools and lack the habits to sustain a lean journey (Santos & Tontini, 2018).…”

Section: Lean Manufacturing Maturitymentioning

confidence: 99%

Save it for a rainy day! Lean strategies for cost saving: The role of Lean maturity

Aripin

Nawanir

Hussain

2023

JIEM

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Purpose: This study investigates the effect of lean implementation on production cost reduction and the moderating role of lean manufacturing maturity.Design/methodology/approach: This study employed a cross-sectional survey, of which the samples were drawn using a cluster sampling procedure from 151 middle and top-level management of medium and large manufacturing companies gathered from the Federation of Manufacturers Malaysia (FMM). Data were analyzed using the PLS-SEM approach through SmartPLS4 software.Findings: The result revealed that lean implementation does not leverage production cost reduction as the lean journey requires long-term orientation, which finally leads to valid cost reduction. The moderating role of lean manufacturing maturity was significant and positive in the relationship between lean manufacturing implementation and production cost reduction.Research limitations/implications: Future research should include longitudinal settings as this study is cross-sectional, and future research might put the present model to the test in multiple industries and regions, including a cross-country comparison to improve the generalizability of the findings. Additionally, further studies could extend this study using a mixed-method approach.Practical implications: By offering a holistic perspective, this study expands the existing literature, contributes to knowledge of integrated lean implementation and supports the management in planning their path towards cost-cutting performance.Originality/value: This study answers the inconclusive finding between lean implementation and operational performance in terms of production cost reduction. The study contributes to the body of knowledge and, most importantly, to the practitioners in planning their lean journey.

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“…In order to operationalize measurement, performance indicators are stablished to quantify the efficiency or effectiveness of actions and processes, being verifiable variables that measure and represent the current progress of the organization (Zanon et al 2020b). Hence, the four decision-makers identified the company performance indicators to be inserted in the model, as Table 2 shows.…”

Section: Pilot Application In a Start-upmentioning

confidence: 99%

Combining grey clustering and fuzzy grey cognitive maps: an approach to group decision-making on cause-and-effect relationships

Zanon

Carpinetti

2021

Soft Comput

Self Cite

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Fuzzy grey cognitive maps (FGCMs) have been widely adopted to support cause-and-effect decision-making under uncertainty. However, capturing the information for the initial state vector and the relationship matrix from various specialists can be cumbersome, which may affect the convergence of FGCMs or cause them to reach a chaotic state. To address this issue, this paper presents a novel group decision approach based on the combination of grey clustering (GC) and fuzzy grey cognitive maps for assessing causal relationships in uncertain environments. The main contribution consists in applying GC as a mean to obtain the initial state vector from the relationship matrix data. This halves the required inputs to the users, reducing uncertainty in the computational model. Also, the proposition brings a method for aggregating the linguistic judgements of multiple decision-makers when assessing causal relationships. The proposition also differs from others in the literature by providing results with lower imprecision levels, named greyness, and lower number of required iterations for the FGCM-based system to converge. A real application was conducted in a technology start-up to test the approach to practical implications. Results allowed the identification of important elements regarding the company's profile and performance, aiding prioritization and enabling the development of action plans. This paper also includes a comparison of other representative models with the proposed approach, which led to more accurate results. Hence, this study addresses the need for new alternatives to improve the reliability and convergence of FGCM-based systems. Finally, suggestions for future applications are proposed.

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Performance measurement and lean maturity: congruence for improvement

Cited by 24 publications

References 53 publications

Analysing the influence of organisational culture and leadership styles on the implementation of lean manufacturing

Analysing the influence of organisational culture and leadership styles on the implementation of lean manufacturing

Save it for a rainy day! Lean strategies for cost saving: The role of Lean maturity

Combining grey clustering and fuzzy grey cognitive maps: an approach to group decision-making on cause-and-effect relationships

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