New
(2025) AI Processed Human Approved
How do organizational capabilities mature? maturity level characteristics for organizational capabilities
This study introduces a generic, theoretically grounded Maturity Level Characterization Model (MLCM) to help organizations assess and improve their organizational capabilities. Grounded in the Dreyfus model of skill acquisition and institutional theory, the framework outlines six distinct maturity stages ranging from unaware to expert. The model was evaluated using Design Science Research methodology and validated by industry practitioners within the domain of advanced data analytics.
Problem
While maturity models are widely used across various domains, most existing frameworks focus on process-oriented incremental improvements rather than deeper organizational capability development. There is a significant theoretical gap in defining how capabilities—comprising broader competencies, knowledge, and behaviors—evolve over time. Consequently, adapting process-based maturity levels to capabilities often leads to misalignment with actual capability progression.
Outcome
- Developed the Maturity Level Characterization Model (MLCM) defining six distinct capability maturity stages from unaware to expert.
- Adapted the Dreyfus model of skill acquisition and institutional theory to establish a solid theoretical foundation for capability maturity.
- Provided an instantiation template that allows researchers and practitioners to systematically generate domain-specific capability maturity levels.
- Validated the model through practitioner evaluations in advanced data analytics, confirming its high validity, relevance, completeness, clarity, and usefulness.
- Adapted the Dreyfus model of skill acquisition and institutional theory to establish a solid theoretical foundation for capability maturity.
- Provided an instantiation template that allows researchers and practitioners to systematically generate domain-specific capability maturity levels.
- Validated the model through practitioner evaluations in advanced data analytics, confirming its high validity, relevance, completeness, clarity, and usefulness.
What it means for you
- CIO / IT Executive: On Monday morning, identify ONE core IT capability (e.g., cybersecurity incident response, cloud adoption) that is critical to your organization's strategy and initiate a discussion with your direct reports to informally benchmark its current maturity using the six MLCM stages (unaware to expert).
- IT Manager: On Monday morning, choose ONE specific IT process or technology area under your direct management (e.g., database administration, help desk ticketing system) and map its current operational state to the relevant MLCM stage, focusing on observable behaviors and knowledge rather than just process documentation.
- Business Strategist: On Monday morning, select ONE strategic business objective that relies heavily on organizational capabilities (e.g., faster product innovation, improved customer segmentation) and begin brainstorming how the MLCM's distinct maturity stages could be used to assess progress towards achieving that objective.
- Researcher: On Monday morning, take the provided MLCM instantiation template and begin populating it for a specific organizational capability relevant to your current research focus, defining clear, observable characteristics for each of the six maturity stages.
- Policymaker: On Monday morning, identify ONE area of public service or government function where improved organizational capability is a known challenge (e.g., disaster response coordination, digital service delivery) and start considering how a capability maturity framework like MLCM could inform policy development and measurement.
Transcript
Host: Welcome to A.I.S. Insights — powered by Living Knowledge. I'm your host, Anna Ivy Summers. Today, we're diving into a landmark study titled "How do organizational capabilities mature? maturity level characteristics for organizational capabilities." Joining me is our lead analyst, Alex Ian Sutherland. Alex, it's great to have you here.
Expert: Thanks, Anna. It's great to be here with you.
Host: Alex, most business leaders are very familiar with maturity models. We see them used everywhere, from software engineering to project management and digital transformation. But this study points out a pretty fundamental flaw in how many of these traditional models are designed. What is the main problem it addresses?
Expert: You're spot on, Anna. For decades, companies have relied on maturity models to evaluate their progress. But here's the catch: most existing frameworks were originally built specifically for processes, focusing on procedural steps and standardized operations. However, an organizational capability—like advanced data analytics or artificial intelligence—is much deeper than just a step-by-step process. A capability encompasses collective knowledge, dynamic behaviors, key roles, technology resources, and business goals. When organizations try to measure capability growth using rigid, process-oriented frameworks, it creates a major disconnect. Companies end up measuring whether people are following procedural rules, rather than whether the enterprise actually has the deep competency to adapt and deliver real business outcomes.
Host: That makes a lot of sense. A process is a series of steps, but a capability is the overall ability to achieve a goal. So how did the researchers behind this study tackle that gap?
Expert: They looked at how human beings acquire complex skills and adapted that concept to the organizational level. Specifically, they drew from the well-known Dreyfus model of skill acquisition—which explains how individuals progress from novice to expert—and combined it with institutional theory, which explains how individual know-how becomes embedded into an organization's memory and routines. Using a Design Science methodology, they built a generic framework called the Maturity Level Characterization Model, or MLCM. They defined six distinct stages of maturity: starting at level zero with Unaware, and then moving through Novice, Advanced Beginner, Competent, Proficient, and finally Expert.
Host: I love that concept—viewing organizational growth through the lens of skill acquisition and mastery rather than just mechanical compliance. How does the MLCM actually structure an organizational capability across those levels?
Expert: The study identifies seven core elements for any organizational capability: context, goal, resources, knowledge, processes, actors, and performance indicators. The MLCM maps out how these seven elements evolve together across the maturity stages. For example, at the Novice level, an organization might sporadically apply generic best practices without clear leadership or dedicated resources. But as it matures to the Competent level, specific actors take ownership, clear goals are established, and best practices are tailored into defined processes. By the time an organization reaches the Expert level, it operates with intuitive flexibility, continuously updating its knowledge base and adapting its processes to changing environments.
Host: And they didn't just leave this as an abstract theory, right?
Expert: Not at all. The authors created an "instantiation template"—a practical template that allows teams to plug in domain-specific details—and demonstrated it by building a complete maturity model for Advanced Data Analytics. They then rigorously evaluated the model with 18 industry experts and practitioners, who confirmed its high validity, relevance, completeness, clarity, and usefulness.
Host: That brings us to the big takeaway for our business audience: why does this framework matter for leaders navigating transformation today?
Expert: It matters because building complex, tech-enabled capabilities—like artificial intelligence or enterprise analytics—isn't just a matter of buying tools or writing standard operating procedures. Leaders need a realistic roadmap that reflects how organizations actually build institutional muscle memory over time. The MLCM gives executives a theoretically sound, highly practical tool to assess where their capabilities actually stand today and chart a structured path forward. It prevents companies from overestimating their readiness just because a process is documented, ensuring that talent, governance, culture, and technology advance in harmony.
Host: It sounds like a crucial shift from rigid checklists to genuine organizational mastery. Alex, thank you for breaking down this insightful study for us today.
Expert: It was my absolute pleasure, Anna.
Host: And thank you to our listeners for tuning into A.I.S. Insights — powered by Living Knowledge. Until next time, keep learning and driving innovation.
Expert: Thanks, Anna. It's great to be here with you.
Host: Alex, most business leaders are very familiar with maturity models. We see them used everywhere, from software engineering to project management and digital transformation. But this study points out a pretty fundamental flaw in how many of these traditional models are designed. What is the main problem it addresses?
Expert: You're spot on, Anna. For decades, companies have relied on maturity models to evaluate their progress. But here's the catch: most existing frameworks were originally built specifically for processes, focusing on procedural steps and standardized operations. However, an organizational capability—like advanced data analytics or artificial intelligence—is much deeper than just a step-by-step process. A capability encompasses collective knowledge, dynamic behaviors, key roles, technology resources, and business goals. When organizations try to measure capability growth using rigid, process-oriented frameworks, it creates a major disconnect. Companies end up measuring whether people are following procedural rules, rather than whether the enterprise actually has the deep competency to adapt and deliver real business outcomes.
Host: That makes a lot of sense. A process is a series of steps, but a capability is the overall ability to achieve a goal. So how did the researchers behind this study tackle that gap?
Expert: They looked at how human beings acquire complex skills and adapted that concept to the organizational level. Specifically, they drew from the well-known Dreyfus model of skill acquisition—which explains how individuals progress from novice to expert—and combined it with institutional theory, which explains how individual know-how becomes embedded into an organization's memory and routines. Using a Design Science methodology, they built a generic framework called the Maturity Level Characterization Model, or MLCM. They defined six distinct stages of maturity: starting at level zero with Unaware, and then moving through Novice, Advanced Beginner, Competent, Proficient, and finally Expert.
Host: I love that concept—viewing organizational growth through the lens of skill acquisition and mastery rather than just mechanical compliance. How does the MLCM actually structure an organizational capability across those levels?
Expert: The study identifies seven core elements for any organizational capability: context, goal, resources, knowledge, processes, actors, and performance indicators. The MLCM maps out how these seven elements evolve together across the maturity stages. For example, at the Novice level, an organization might sporadically apply generic best practices without clear leadership or dedicated resources. But as it matures to the Competent level, specific actors take ownership, clear goals are established, and best practices are tailored into defined processes. By the time an organization reaches the Expert level, it operates with intuitive flexibility, continuously updating its knowledge base and adapting its processes to changing environments.
Host: And they didn't just leave this as an abstract theory, right?
Expert: Not at all. The authors created an "instantiation template"—a practical template that allows teams to plug in domain-specific details—and demonstrated it by building a complete maturity model for Advanced Data Analytics. They then rigorously evaluated the model with 18 industry experts and practitioners, who confirmed its high validity, relevance, completeness, clarity, and usefulness.
Host: That brings us to the big takeaway for our business audience: why does this framework matter for leaders navigating transformation today?
Expert: It matters because building complex, tech-enabled capabilities—like artificial intelligence or enterprise analytics—isn't just a matter of buying tools or writing standard operating procedures. Leaders need a realistic roadmap that reflects how organizations actually build institutional muscle memory over time. The MLCM gives executives a theoretically sound, highly practical tool to assess where their capabilities actually stand today and chart a structured path forward. It prevents companies from overestimating their readiness just because a process is documented, ensuring that talent, governance, culture, and technology advance in harmony.
Host: It sounds like a crucial shift from rigid checklists to genuine organizational mastery. Alex, thank you for breaking down this insightful study for us today.
Expert: It was my absolute pleasure, Anna.
Host: And thank you to our listeners for tuning into A.I.S. Insights — powered by Living Knowledge. Until next time, keep learning and driving innovation.