<p>Digital transformation of manufacturing enterprises demands a fundamental shift in leadership, requiring leaders to leverage digital technologies to drive organizational innovation. Leadership is a critical driver of digital transformation, and analyzing leadership competency is central to enhancing capabilities. Nonetheless, little research has explored this area through the lens of decision-making methodology. Hence, this study presents a hybrid decision-making framework designed to analyze the leadership competencies of manufacturing enterprises undergoing digital transformation. This framework is based on the Spherical Z-number (SZN) preference ranking organization method for enrichment evaluation (PROMETHEE) II methodology, which includes three phases. First, the group decision matrix is generated based on the SZN Relative Closeness Coefficient approach with the ordered weighted average operator. It describes more information than previous fuzzy sets through three evaluation branches and considers the reliability of experts. Second, the SZN LOPCOW (logarithmic percentage change-driven objective weighting) method for calculating criteria weights handles the structural inconsistencies of the criteria. Third, the SZN PROMETHEE II methodology is presented to obtain the complete priority of alternatives through pairwise comparisons and predefined preference functions. It also evaluates the deviation of any pair of alternatives using a simplified computational procedure. Moreover, an experimental case study of an automobile manufacturing enterprise in China is presented to verify the practicality of the proposed methodology. According to the results, “Emotional balance (<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\zeta _{16} )\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>ζ</mi> <mn>16</mn> </msub> <mrow> <mo stretchy="false">)</mo> </mrow> </mrow> </math></EquationSource> </InlineEquation>” in the dimension of “Digital ethical awareness” is the main leadership competency with the largest value, followed by the leadership competency “Digital empathy ability (<InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\zeta _{13} ).\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msub> <mi>ζ</mi> <mn>13</mn> </msub> <mrow> <mo stretchy="false">)</mo> <mo>.</mo> </mrow> </mrow> </math></EquationSource> </InlineEquation>” Within the analysis of leadership competency, the candidate <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\chi _{5}\)</EquationSource> <EquationSource Format="MATHML"><math> <msub> <mi>χ</mi> <mn>5</mn> </msub> </math></EquationSource> </InlineEquation> has the highest priority compared to others. Finally, the sensitivity and comparative analyses demonstrate the robustness and validity of the presented SZN PROMETHEE II methodology.</p>