Date of Award
2024
Degree Type
Open Access Dissertation
Degree Name
Information Systems and Technology, PhD
Program
Center for Information Systems and Technology
Advisor/Supervisor/Committee Chair
Yan Li
Dissertation or Thesis Committee Member
Samir Chatterjee
Dissertation or Thesis Committee Member
Shan Pan
Dissertation or Thesis Committee Member
Ace Vo
Terms of Use & License Information
Rights Information
© 2024 Robert K Marohn
Keywords
Action Design Research, Big Data, Business Intelligence, Capability Maturity Model, Data Analytics, Small and Medium Enterprises
Subject Categories
Business Administration, Management, and Operations
Abstract
This dissertation details the development and application of a prescriptive Data Analytics Capability Maturity Model (DACMM), specifically designed for Small and Medium Enterprises (SMEs). Despite their need for effective data analytics for growth and competitiveness, SMEs often face challenges such as limited resources and lack of technical expertise. Traditional Capability Maturity Models (CMMs), mainly tailored for larger organizations, often fall short in addressing the specific needs and constraints of SMEs. To bridge this gap, the DACMM provides a comprehensive guide to help SMEs advance their analytics capabilities from nascent stages to more sophisticated, data-driven operations, tailored to their unique operational contexts.
Methodologically, this research adopts Action Design Research (ADR), a collaborative approach where researchers and practitioners work together to address real-world problems through the creation and application of design science artifacts. Employing teleological organizational change theory as a kernel theory, the DACMM was developed over five Build, Intervention, and Evaluation cycles with two SMEs. This iterative process allowed the DACMM to be informed and enriched by both the practical knowledge gained through organizational interactions and its strong theoretical underpinnings.
The DACMM stands out for its prescriptive nature, offering SMEs clear, actionable steps to enhance their data analytics maturity across various levels. The model encompasses five key dimensions: organizational, analytics operations, infrastructure, data management, and data governance. It delves deeper into subdimensions and elements, tailoring them specifically for SMEs and incorporating detailed best practices into the prescriptive process. Notably, the DACMM introduces a new scoring method for self-assessment by SMEs, a resource-based self-ranking tool for roadmap creation, and a systematic approach to tracking progress. Collectively, these components of DACMM provide a practical, structured pathway for SMEs to improve their data analytics maturity in line with their strategic and operational goals.
This research makes several significant contributions. It introduces the first fully prescriptive CMM tailored to data analytics for SMEs, offering a practical tool for these enterprises to enhance their data analytics capabilities. It also expands the theoretical understanding of CMM development, particularly in the application of teleological organizational change theory. Furthermore, the use of ADR in this research enriches the design process knowledge, demonstrating the effective application of principles such as reciprocal shaping, mutually influential roles, and concurrent evaluation in creating a responsive artifact that meets the needs of the involved organization.
ISBN
9798383227602
Recommended Citation
Marohn, Robert Karl. (2024). DACMM - A Data Analytics Capability Maturity Model for Small and Medium Enterprises. CGU Theses & Dissertations, 817. https://scholarship.claremont.edu/cgu_etd/817.
