Lean in knowledge work: Designing a framework to enable structured waste reduction

Abstract

Knowledge Work (KW) lacks a structured approach to identifying and reducing Waste, as Lean methodologies have traditionally been applied in manufacturing and service sectors. Existing studies on Lean in KW rely on context-specific adaptations, limiting their generalizability. This research aims to develop a holistic and universally applicable Waste framework for KW, incorporating a Variation-based perspective to address root causes of inefficiencies. Following the Design Science Research (DSR) methodology, this study integrates Lean Lenses and Principles, Knowledge Management (KM), and Organizational Learning (OL), as well as Problem-Solving to define three major Waste categories: Team Dysfunctions, Poor Knowledge Management Practices, and Poor Work Methodologies. The framework was operationalized into an assessment tool, supported by defined Dimensions, Indicators, and a qualitative workshop format.The artifact was evaluated through structured workshops with team leaders, facilitated in a one-on-one setting using the collaboration tool MIRO. Results confirm that the framework effectively identifies the intended Wastes. Participants found the format clear, relevant, and useful, with Likert Scale ratings averaging 4.33 across all evaluated aspects. Not only team specifics and characteristics were detected, but also structural issues could be identified. Thereby, the results highlight issues on department, business unit, as well as on site level, bringing deep insights to the overall organization and related improvement possibilities.This research contributes to Lean Thinking in KW by introducing a generalizable Waste framework and Lean KW Practices, thereby, offering a structured assessment method for continuous improvement. Future work should further formalize Lean KW Principles and Practices, expand the Work Methodology dimension, and refine more independent assessment metrics.