As the professional landscape evolves, competency-based modeling is transforming how credentials are defined and how individuals gain and demonstrate expertise. Individuals working across almost every industry need flexible, relevant, and credible pathways to build their knowledge and validate their skills. Micro-credentials and stackable certifications are rising to meet this demand. And at the heart of these innovations lies a powerful framework – the competency model.
This blog explores how competency models provide the structure and insight needed to support these flexible approaches to credentialing, with both strategic and psychometric integrity. It is based on a conversation I had recently with Manny Straehle, President and Founder of AERE, for the Tried and Tested Podcast.
What are competency models?
Competency models define the knowledge, skills, abilities, and other characteristics (KSAOs) required to perform effectively in a job role or profession. These models often include both cognitive and non-cognitive competencies, such as leadership, communication, and critical thinking, in addition to job-specific technical skills.
While job task analyses (JTAs) are commonly used in credentialing to define tasks and test content, competency models take a broader and more dynamic view. They consider performance across the career continuum, from novice to expert. This enables organizations to measure outcomes and provides a foundation that goes beyond testing to support workforce development, training, and career pathing.
Micro-credentials and stackable certifications defined
Micro-credentials are short, focused credentials designed to attest to proficiency in a specific skill or competency. They are flexible, modular, and can be earned in a relatively short time.
Stackable certifications allow learners to build progressive qualifications by combining individual credentials over time. These can lead to full professional certifications or specialized endorsements, offering a personalized and scalable learning path.
Both approaches appeal to modern professionals seeking just-in-time learning and organizations seeking adaptable and portable talent development frameworks.
Download our guide to find out more about micro-credentialing.
How competency models support the evolution of credentialing
Competency models provide the connective tissue that enables credentialing approaches, like micro-credentials and stackable certifications, to function effectively.
- Designing with intent
Competency models support the identification of KSAOs to define job roles, levels, and key competencies that can then be used in developing micro-credentials. This enables organizations to develop focused, relevant learning experiences and assessments that align with industry needs. - Supporting progression
One application of competency models includes the mapping of competencies across levels of expertise – beginner, intermediate, and expert – which allows for the recognition of these levels over time. A foundational credential might validate basic knowledge, while advanced micro-credentials could assess application, judgment, or leadership within the same domain. - Ensuring alignment
Competency models align the goals of credentialing with broader organizational and societal outcomes. For example, a credential may be designed to improve efficiency, patient outcomes, or customer satisfaction. The competency model helps tie those outcomes directly to defined behaviors and skills.
Competency based modelling in practice
Competency based modeling relies on validated frameworks that ensure learners demonstrate not just knowledge, but real-world application and readiness. When credentials are built on robust competency models, they reflect the actual capabilities required to succeed on the job.
Psychometric considerations
As programs consider the use of competency models, they need to continue to keep in mind psychometric principles. Competency-based assessments must still be:
- Valid – measuring the intended competencies accurately.
- Reliable – producing consistent results over time.
- Fair – free from bias and accessible to all qualified candidates.
Depending on the performance level being assessed, different methods may be appropriate. Multiple-choice items may effectively measure knowledge and comprehension at foundational levels. At higher levels, simulations, performance assessments, portfolios, or situational judgment tests may be more appropriate.
Competency models also guide test blueprints and standard-setting processes, ensuring that what is measured aligns with what matters.
Technology, personalization, and scale
Modern platforms and AI-powered tools have accelerated the development, delivery, and impact of micro-credentials. Competency models play a key role in this innovation:
- Personalized learning: By identifying what a learner knows and what they need to know next, competency models support adaptive learning paths.
- Assessment innovation: AI can simulate real-world decision-making scenarios, provide tailored feedback, and deliver scalable, formative assessments grounded in competency models.
- Digital badging and credentialing: Competency models provide the metadata and structure behind digital badges, making achievements verifiable and meaningful to employers.
Towards modular, global, and outcome-based credentials
For organizations working across borders, competency models provide a consistent foundation while allowing for regional flexibility. They also support modular credential design, making it easier to:
- Develop micro-credentials that serve as on-ramps to full certifications.
- Tailor credentials to specialties or subfields.
- Connect credentials to tangible outcomes, such as improved performance, increased revenue, or patient/client satisfaction.
When combined with analytics and performance data, competency models become tools not only for assessment but also for continuous improvement and strategic planning.
Looking ahead
Several trends make competency modeling increasingly vital to the future of certification:
- Emphasis on outcomes: Credentials are being evaluated based on real-world impact. Competency models help make the case.
- Career-based credentialing: Professionals want clear, navigable pathways. Competency models map these journeys.
- Lifelong learning and AI integration: As assessment and learning converge, competency frameworks support continuous, real-time development.
Structure and strategic clarity
Competency models provide the structure and strategic clarity needed to design effective micro-credentials and stackable certifications. They align stakeholder needs, support rigorous assessment, and ensure that credentialing programs remain relevant, dynamic, and impactful.
To hear a deeper conversation about how competency modeling is shaping the future of testing and certification, listen to my recent conversation with Manny Straehle on the Tried and Tested podcast:
Beyond job task analysis: How competency modeling is transforming credentialing.