Many studies have found that Lean practices provide better performance in a stable business environment. However, there is limited information on how Lean practices influence performance gains (defined in this paper as improvement and sustenance of performance) in an uncertain (complex and dynamic) environment. This study aims to investigate how the implementation of Lean helps to sustain performance in such context.
The study draws on an in-depth investigation of two capital goods manufacturing engineer-to-order (ETO) cases, in which performance sustenance is discussed in relation to the extent, locus and extensiveness of implemented Lean practice bundles.
Findings indicate that a higher extent of Lean practices’ implementation, covering both shop floor and transactional processes, increases the possibility of performance sustenance in ETO. Furthermore, a coherent approach in the pre-, during- and post-implementation phases of the Lean change process is required to foster performance sustenance. Lean practices in ETO are modified to suit context change from repetitive manufacturing.
This study proposes performance sustenance as a performance measure in a highly uncertain context, such as ETO, as a single reference cannot effectively measure performance improvements over diverse orders. From this perspective, appropriate Lean implementation contributes towards building capabilities for flexibly and proactively managing uncertain circumstances.
Even companies operating in highly uncertain (complex and dynamic) contexts may benefit from significant performance gains, thanks to the Lean implementation. This can be achieved by a balanced implementation of practices at shop floor and transactional processes, and their mindful customisations.
The study compares Lean implementation in ETO with that of high-volume–low-variety systems established in the literature. It qualitatively discusses how Lean implementation as an overarching effort both in shop floor and transactional processes leads to better sustenance of achieved performance improvements in shop floor under high uncertainty.
