Assessment model of lean effect (AMLE)

Author:

Elrhanimi Samah,EL Abbadi Laila

Abstract

PurposeThe purpose of this paper is to present the “Assessment Model of Lean Effect” (AMLE), a theoretical model that measures Lean manufacturing implementation effect over the global performance of a company.Design/methodology/approachAMLE model is divided in two criteria types: the “Facilitators criteria” and the “Results criteria”. “Results criteria” are inspired from the European Foundation for Quality Management (EFQM), Global Reporting Initiative (GRI) and ISO 26000. The “Facilitators criteria” are based on the main philosophy of the Lean manufacturing, which is the total elimination of all types of waste. The development of the scoring scale was based on the results, approach, deployment, assessment and review (RADAR) philosophy and the experience of nine consultants from the automotive field; the choice of the consultants was based on three conditions. Furthermore, each consultant has his\her own weight according to its expertise. Lastly, the AMLE was validated via a case study set in an automotive industry company called FEBA. The validation process is divided in two different steps: the first step is related to Facilitators assessment and scoring; via the evaluation of the different projects implemented by FEBA to eliminate the different types of waste. The second step concerns Results assessment and scoring, via the evaluation of the performance measurements used by FEBA to assess the effect of the Facilitators' implementation.FindingsThe developed model (AMLE) enabled the Lean manufacturing effect assessment on the global performance of a firm from the automotive field. The case study results reveal that the aforementioned firm does not give priority to social measurements. Consequently, the performance of the firm was negatively impacted.Research limitations/implicationsThe criteria of AMLE are inspired from the definition of the Lean manufacturing given by Taiichi Ohno, from ISO 26000 and from GRI; meaning that these criteria could be adjusted if other references existed or developed. In addition, the scoring rules are established according to the experience of a limited number of consultants from the automotive field. The scoring rules establishment would lead to meaningful outcomes, if the number of participants was increased. During the assessment of the global performance, the perception of the auditor plays an important role in terms of scoring because the scoring rules allow the possibility to the auditor to give from the minimum to the maximum of the score, according to his perception and experience. For the case study, the validation of the developed model requires starting with the “Facilitators” implementation process and then measure the generated global performance. However, due to time constraints and limited opportunities for new projects, the validation was based only on existing projects managed by the firm. To address the study limitations, it is envisaged to detail and explain the scoring rules while extending the number of consultants. Furthermore, the assessment of Lean manufacturing global performance through the AMLE model may be subjective and requires a mathematical modeling. In fact, the Lean manufacturing performance assessment via the developed model could have a degree of subjectivity; that is why the design of a mathematical model seems required.Practical implicationsThe research findings may direct practitioners and decision makers to the importance of assessing the global effect of the Lean manufacturing on the overall performance of the firm. The AMLE model is a tool allowing the assessment of Lean manufacturing effect over economic, environmental and social performances.Originality/valueThe developed model is the first one assessing the global performance generated by the elimination of waste via the application of the Lean manufacturing.

Publisher

Emerald

Subject

Strategy and Management,General Business, Management and Accounting,Business and International Management,General Decision Sciences

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