Digital transformation (DT) is a strategic imperative, yet organizations lack systematic methods to assess digital maturity across operating model components. This study demonstrates the practical applicability of a six-dimensional maturity assessment framework in a manufacturing context, providing proof-of-concept for its utility in measuring DT progress across an operating model.
A 41-item, six-dimensional model was applied at a mid-sized German mechanical engineering firm (290 employees; €100M revenue). An Excel-based self-assessment tool with seven calculation formulas measured current and target maturity, gaps, importance, and prioritization; data were collected via structured self-assessment by the general manager, validated through a semi-structured interview, and visualized with radar charts.
Overall current maturity was 3.6 against a 4.6 target. These case-specific results are proof-of-concept outputs, not statistically validated benchmarks. Technology and Tools (3.4) and Data (3.2) showed the lowest maturity; Technology and Tools had the largest gap (1.2) – driven by tool fragmentation from unregulated M&A leaving 36 standalone systems – and the highest priority score (3.9).
Structured assessment heightens awareness of DT complexity, supports importance- and gap-based prioritization, and enables evidence-based resource allocation. Practitioners should address single-respondent subjectivity through multi-stakeholder involvement and budget for continuous investment to sustain maturity.
Although the integration of operating model and maturity theory draws on established streams, the study’s originality lies in operationalizing that integration into a deployable 41-item instrument with seven formulas and an importance-weighted prioritization mechanism. This first documented field application offers a replicable, transparently documented methodology and contributes three theoretical propositions on DT maturity dynamics.
