System-Based Methodology for Accurate Problem Definition

The implementation of Lean philosophy is a practice that has become more intense in recent decades. Through this practice, it is envisioned to solve problems, reduce waste, and, in general, optimize process or system operations. Despite its widespread use, Lean implementation often falls short of expected outcomes. The lack of clarity in the problem definition step significantly contributes to these shortcomings. This challenge is not unique to Lean; it also impacts the Six Sigma methodology, a globally used data-driven approach for process improvement through defect reduction. This paper proposes an alternate innovative methodology for accurately defining problems, aiming to enhance the input integrity of critical problem-solving processes. It introduces the Sawhney Model as an effective system-based approach to improve the formulation of problem definitions for Lean and Six Sigma implementations. The model relies on the steps' modularity and the process's reliability. Concepts of process variation, disruption, and flow are integrated to identify uncertainty levels inherent in processes and systems. The proposed method is applied to define a problem in a manufacturing system through a case study. The Sawhney model, traditional Lean, and the Six Sigma methodology provide valuable insights. Based on this, a comparison between the solutions yielded by the Sawhney model, traditional Lean, and the Six Sigma methodology will be provided.