Performance Evaluation of Baosight Software's Digital-Intelligent Transformation based on E-BSC

Jie Huang; Yijun Chen; Jinghan Wang

doi:10.6981/FEM.202608_7(8).0003

Authors

Jie Huang Sichuan University of Science & Engineering, Zigong 643000, China
Yijun Chen Leshan Normal University, Leshan 614000, China
Jinghan Wang Sichuan University of Science & Engineering, Zigong 643000, China

DOI:

https://doi.org/10.6981/FEM.202608_7(8).0003

Keywords:

Baosight Software; Digital-Intelligent Transformation; E-BSC; CRITIC Method; Performance Evaluation.

Abstract

Using Baosight Software as a single case, this study examines how the performance of digital-intelligent transformation can be assessed in an industrial software enterprise. The traditional Balanced Scorecard (BSC) is kept as the basic framework, but it is not fully sufficient for this case, because platform construction, software product restructuring, AI applications, and technological output are central parts of the transformation. A digital-intelligent capability dimension is therefore added, forming a five-dimensional Enhanced Balanced Scorecard (E-BSC). Based on public materials, indicators for 2020-2025 are collected; the CRITIC method is used to determine objective weights; and composite and dimensional scores are calculated through weighted scoring. The results are not a simple story of steady improvement. After Baosight Software released its Digital-Intelligent Transformation Plan (2022-2024), the composite score increased during 2022-2024 and reached its highest value in 2024. It then dropped noticeably in 2025. The decline was mainly associated with adjustment in the downstream steel industry, higher customer concentration, project recognition timing, and weaker profitability. Dimensional scores offer a clearer reading of this change. The financial, customer, and internal process dimensions weakened in 2025, while learning and growth and digital-intelligent capability stayed at high levels. In other words, the company was still accumulating technology, talent, and platform capability, but these inputs had not yet been fully converted into financial results. For industrial software enterprises, transformation performance should be interpreted together with financial outcomes, technological accumulation, customer structure, and external industry conditions.

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