A Сomparative Analysis of Digital Transformation Management Frameworks and a Context-Fit Selection Matrix

Abstract

Digital transformation is increasingly understood as enterprise-wide change in value creation, operating arrangements, and organisational capabilities, not simply technology adoption. However, many initiatives underperform because implementation becomes fragmented across strategy, governance, the operating model, and capability development. This paper synthesises recent peer-reviewed digital transformation literature and compares six widely used frameworks: Gartner, McKinsey 7S, BCG, Deloitte, MIT Sloan, and Cognizant. Using a common analytical template (causal logic, prerequisites, strengths, limitations), the study shows that frameworks mainly differ in the primary constraint they prioritise – alignment, measurable value, sequencing and maturity, enterprise orchestration, capability leadership co-evolution, or legacy/platform renewal. These results are translated into a constraint-driven selection matrix that links observable organisational signals to a suitable primary framework and indicates complementary lenses to reduce predictable blind spots. The paper contributes a practical decision aid and a basis for future empirical validation of context-fit framework choice.