Engineer-to-Order (ETO) companies often grow around ad-hoc know-how, and when they scale, usually they must standardize and choose a BOM setup, yet literature offers options but little guidance on how to decide. We propose a Focus Identification Model, a lightweight, tool-agnostic method that profiles context drivers, asks weighted decision questions, and links answers to a go-to setup with explicit governance. Calibrated on two industry cases, it yields a driver heatmap, decision matrix, and governance card to establish a common language and identify fit-for-purpose BOMs with less friction.

Custom manufacturers of engineered products face growing challenges in managing complex and variant Bills of Materials (BOMs). This paper proposes a visualization-driven framework for structuring and analyzing overcomplete (150%) BOMs in Engineer-to-Order environments. The framework integrates configurator rule logic, generic BOM structures, and metadata to enable explicit traceability and diagnostic analysis of variant-specific BOMs. A proof-of-concept prototype evaluated in a European fibre-laser manufacturer demonstrates support for variant validation, error detection, and alignment.