Lean Leaders may face a tremendous amount of resistance when implementing and sustaining Lean in their organizations. The complexity associated with the dynamic of organizational processes in the 21st century: mobility of the work force, ever-changing product portfolios, and their related value stream adjustments are some of the reasons for this. Taking an organizational network view, this paper provides leaders with both a definition of Resilience, as well as coherent criteria to quantify the Lean Structural Network Resilience (LSNR) to the lean transformation that is associated with the mentioned changes in the organization. By implementing LSNR as a metric to measure resistance to change to Lean, Leaders can make informed Value Stream related business decisions in order to support sustainable growth.

Lean structural network resilience / Villalba-Diez, J.; De Sanctis, I.; Ordieres-Meré, J.; Ciarapica, F. E.. - ELETTRONICO. - 689, 2018:(2018), pp. 609-619. (Intervento presentato al convegno 6th International Conference on Complex Networks and Their Applications, Complex Networks 2017 tenutosi a Lyon; France nel 29 November 2017 -1 December 2017) [10.1007/978-3-319-72150-7_49].

Lean structural network resilience

De Sanctis I.;Ciarapica F. E.
2018-01-01

Abstract

Lean Leaders may face a tremendous amount of resistance when implementing and sustaining Lean in their organizations. The complexity associated with the dynamic of organizational processes in the 21st century: mobility of the work force, ever-changing product portfolios, and their related value stream adjustments are some of the reasons for this. Taking an organizational network view, this paper provides leaders with both a definition of Resilience, as well as coherent criteria to quantify the Lean Structural Network Resilience (LSNR) to the lean transformation that is associated with the mentioned changes in the organization. By implementing LSNR as a metric to measure resistance to change to Lean, Leaders can make informed Value Stream related business decisions in order to support sustainable growth.
2018
Studies in Computational Intelligence
978-331972149-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/256302
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