Digital Transformation in Enterprise Asset Management: A Change Readiness Assessment of SAP ECC to S/4HANA Migration Using the Integrated ADKAR-CSF Framework
Abstract
Enterprise Resource Planning (ERP) migrations are a critical dimension of digital transformation, yet organizational readiness remains insufficiently understood in asset-intensive industries. This study investigates key change management factors influencing the SAP ECC (SAP ERP Central Component)-to-S/4HANA (SAP Suite for HANA) migration within the Operations Maintenance division of an Indonesian mining company managing over 20,000 equipment assets. Using a qualitative single-case study approach, semi-structured interviews were conducted with 14 maintenance personnel at the tactical and operational levels and senior leadership at the strategic level. The analysis integrates the ADKAR (Awareness, Desire, Knowledge, Ability, Reinforcement) model of individual readiness with seven organizational Critical Success Factors (CSFs) to provide a holistic diagnostic framework. Results indicate an overall readiness score of 4.10 out of 5 (high category); Knowledge (3.88) and Ability (3.90) are the weakest dimensions once field supervisors are included, while Reinforcement (3.98) exhibits the widest variance (1.00–5.00). Seven individual barrier points are identified, the most extreme scoring 1.00 on Reinforcement despite exceeding 4.30 on other dimensions. CSF analysis revealed five barrier factors: incomplete training coverage, absence of post-training coaching, uneven management communication, lack of performance measurement systems, and a fragmented reward scheme. The integrated ADKAR-CSF mapping demonstrates that organizational factors causally influence each individual readiness dimension, and a three-phase Change Management Roadmap (Pre-Go-Live, Stabilization, Optimization) is proposed with targeted interventions. This study contributes to the literature by demonstrating that, in mining contexts with mixed permanent and contractor workforces, Reinforcement mechanisms require more adaptive and inclusive designs than conventional frameworks suggest.