Digital Lean Disturbance Management

Doctoral thesis, 2024

Humans strive for learning from their mistakes to improve themselves. This thesis aims to answer if and how organizations can learn from their mistakes to improve themselves. The organization in focus in this thesis was a Swedish integrated product development company within dental implants business. The mistakes were referred as disturbances (i.e., conditions that deviate from desirable or normal). The ideology that guided the improvement was lean philosophy (e.g., simplicity, visualization, continuous improvement, eliminating waste). The learning happened through doing statistical analyses on the disturbance database that was created by registering disturbances. The technology that was used to enable the aforementioned solution was digitalization, which was not possible previously. The disturbances could not be stored long-term (i.e., disturbance information became waste in lean terms). The reasons were that lean typically employs physical tools (e.g., whiteboard) and digitalization is typically discouraged because of the risk of damaging the simplicity and causing distraction.

As a result of this thesis, digital disturbance management system was deployed to the case company. Employees captured disturbances over three years. Statistical analyses were carried out over the disturbance database. The results of the analyses were useful to the company; they guided the company while making strategic decisions. This case of successfully digitalizing lean in industrial settings showed that knowledge waste in physical lean disturbance management can be reduced by combining digitalization and lean.