Clarifying Core Dimensions in Digital Maturity Models: An Integrative Approach

Digital Transformation (DT) initiatives frequently face high failure rates, and while Digital Maturity Models (DMMs) offer potential solutions, they have notable shortcomings. Specifically, there is significant disparity in the dimensions considered relevant, a lack of clarity in their definitions, and uncertainty regarding their components. This study aims to provide a clearer understanding of DMMs by proposing integrative definitions of the most frequently used dimensions. Using a Systematic Mapping approach, including automatic search and snowballing techniques, we analyzed 76 DMMs to answer two Research Questions: (RQ1) What are the most frequent dimensions in DMMs? and (RQ2) How are these dimensions described, including their components? We reconcile varying interpretations of the ten most frequent dimensions – Organization, Strategy, Technology, Culture, Process, Operations, People, Management, Customer, and Data – and propose integrative definitions for each. Compared to previous analyses, this study provides a broader and more recent perspective on Digital Maturity Models.

💡 Research Summary

This paper addresses the persistent problem of high failure rates in Digital Transformation (DT) initiatives by scrutinizing the tools most commonly used to assess progress—Digital Maturity Models (DMMs). While DMMs promise a structured way to gauge an organization’s digital readiness, the literature reveals three critical shortcomings: (1) a lack of consensus on which dimensions are essential, (2) vague or inconsistent definitions of those dimensions, and (3) insufficiently articulated components within each dimension. These issues hinder both practitioners, who struggle to select and apply appropriate models, and scholars, who find it difficult to conduct comparative research.

To remedy this, the authors conducted a systematic mapping study covering the period 2010‑2023. They combined automated keyword‑based searches with snowballing (forward and backward citation tracking) to retrieve an initial set of 312 records. After title, abstract, and full‑text screening, 76 distinct DMMs were retained for analysis—making this the most extensive and up‑to‑date collection to date.

Two research questions guided the investigation:

• RQ1: Which dimensions appear most frequently across DMMs?
• RQ2: How are these dimensions described, and what are their constituent components?

The analysis identified ten dimensions that dominate the landscape: Organization, Strategy, Technology, Culture, Process, Operations, People, Management, Customer, and Data. These ten were present in the majority of the 76 models, indicating a cross‑industry, cross‑size, and cross‑regional robustness.

For RQ2, the authors performed a meta‑analysis of the textual descriptions of each dimension across the sampled models. They propose an integrative conceptualization that treats each dimension as a vector (direction) and its components as projections (specific attributes). This metaphor supports a unified, mathematically coherent view of DMM constructs. The resulting integrated definitions are:

1. Organization – structural and governance arrangements that enable digital initiatives, including hierarchy, roles, and cross‑functional coordination.
2. Strategy – the articulation of digital vision, objectives, road‑maps, investment priorities, and alignment with overall business strategy.
3. Technology – the portfolio of digital technologies (cloud, AI, IoT, platforms) and the organization’s capability to acquire, integrate, and maintain them.
4. Culture – shared digital mindset, leadership support, openness to change, learning orientation, and innovation practices.
5. Process – redesign, automation, and standardization of business processes to exploit digital capabilities.
6. Operations – day‑to‑day execution of digitally enabled activities, focusing on efficiency, agility, and resilience.
7. People – digital skills, talent acquisition, training, multidisciplinary team formation, and empowerment of staff.
8. Management – governance mechanisms, project management, performance measurement, risk management, and continuous improvement structures.
9. Customer – digital touchpoints, experience design, personalization, and the use of customer data to drive value.
10. Data – data collection, storage, integration, analytics, governance, security, and data‑driven decision‑making.

Each dimension is further broken down into 3‑7 concrete components (e.g., the Data dimension includes data quality, integration, analytics capability, security/privacy, and governance). These components are directly usable for questionnaire design, assessment item generation, and benchmarking.

The paper situates its contribution relative to five prior systematic reviews of DMMs. Earlier works mainly cataloged the number of models, sectoral focus, or methodological quality, but none offered a comprehensive, cross‑model synthesis of dimension definitions and components. By employing a rigorous search strategy, minimizing selection bias, and focusing on the semantic core of DMMs, this study delivers a standardized lexical and conceptual framework.

Practical implications are significant: organizations can now select a DMM by matching its dimensions against the ten‑dimensional template, ensuring coverage of all critical digital capabilities. Moreover, the component lists enable self‑assessment without external consultants, facilitating internal diagnostics and continuous improvement. For researchers, the unified definitions provide a common language for future empirical studies, enabling more reliable measurement, cross‑study comparisons, and meta‑analyses.

In conclusion, the authors deliver an integrative set of definitions and component inventories for the ten most prevalent DMM dimensions. This work bridges the gap between the fragmented landscape of existing models and the need for a coherent, comparable, and actionable maturity assessment framework, ultimately supporting higher success rates in digital transformation initiatives.