Competency Modeling and Skills-Based Organizations

Introduction and context

Job analysis traditionally begins with the job as the unit of analysis: duties are identified, tasks are documented, and the knowledge, skills, abilities, and other characteristics (KSAOs) required for effective performance are specified. Competency modeling extends this logic by examining the capabilities that explain effective performance across jobs, job families, levels, or strategic domains. Skills-based organizing goes further: it treats skills and demonstrated capabilities—not only positions, credentials, or reporting lines—as important units for allocating work, developing talent, and designing careers.

These approaches are increasingly important because organizations operate in conditions of technological change, project-based work, shifting customer expectations, and occupational ambiguity. A job description may remain stable while the capabilities needed to perform it change substantially. Competency models can provide a common language for selection, development, performance management, succession, and workforce planning. However, poorly designed models can become abstract lists of desirable traits, reproduce managerial bias, or create excessive administrative burden. Their value therefore depends on methodological rigor, strategic alignment, validation, and responsible implementation.

This chapter distinguishes competencies from skills and KSAOs, explains behavioral, functional, and leadership competency models, develops proficiency structures and skills adjacencies, and evaluates validity and strategic relevance.

Learning objectives

By the end of this chapter, readers should be able to:

1. Distinguish competencies, skills, KSAOs, tasks, outputs, and qualifications.
2. Design behavioral, functional, and leadership competency models.
3. Construct defensible proficiency levels and observable behavioral indicators.
4. Map skills adjacencies to support mobility and workforce planning.
5. Evaluate competency-model validity, reliability, fairness, usability, and strategic relevance.
6. Recommend governance practices for skills-based talent systems, including responsible uses of AI.

1. Fundamental concepts

1.1 Tasks, duties, outputs, and capabilities

A task is a discrete unit of work, such as reconciling an account or configuring a software module. A duty is a broader cluster of related tasks. An output is the result produced, such as an accurate financial report, safe patient care, or a functioning product feature. A capability is an enduring capacity to produce valued results under specified conditions.

Traditional job analysis asks, “What does the jobholder do?” Competency modeling also asks, “What patterns of behavior, judgment, knowledge, and application enable success across situations?” The distinction is consequential. Tasks can become obsolete, whereas a capability such as data interpretation, stakeholder influence, or risk judgment may remain useful across changing tasks.

1.2 Competencies

A competency is a measurable cluster of related knowledge, skills, abilities, motives, and behaviors that contributes to effective performance in a work context. Competencies are generally broader than individual skills and are expressed through behavior and results. For example, “customer orientation” may include listening, diagnosing needs, adapting communication, and following through; it is not simply a single technical skill.

Competencies should be defined behaviorally. “Strategic thinker” is too vague to assess consistently. A stronger definition might be: “Connects operational decisions to long-term organizational priorities, evaluates trade-offs, and communicates implications to relevant stakeholders.” The latter can be observed, rated, developed, and validated.

1.3 Skills and KSAOs

A skill is an acquired capacity to perform an activity, usually with some degree of proficiency. Examples include SQL querying, interviewing, negotiation, spreadsheet modeling, and equipment calibration. Skills can be technical, interpersonal, cognitive, digital, or physical.

KSAOs are:

• Knowledge: information or principles required to perform work.
• Skills: learned proficiencies in performing activities.
• Abilities: relatively enduring capacities to perform tasks, such as verbal reasoning or spatial perception.
• Other characteristics: relevant attributes not captured above, such as work values, personality-related tendencies, licenses, or availability requirements.

The categories overlap conceptually. A competency may incorporate several KSAOs and skills, while a skill may be one component of a competency. A license, for example, may be a qualification or other characteristic; operating the licensed equipment is a skill; and safe operational judgment may be a competency.

1.4 Competency models and skills taxonomies

A competency model organizes competencies, definitions, and proficiency indicators for a population such as all employees, a function, or a leadership level. A skills taxonomy classifies skills and their relationships. A taxonomy may be hierarchical—for example, “data analysis” may contain “data cleaning,” “statistical interpretation,” and “data visualization”—without specifying the behaviors or results that define effective performance.

A competency model is interpretive and contextual; a taxonomy is classificatory. Mature systems often use both: a taxonomy supplies common skill labels, while competency profiles explain how skills combine with judgment, collaboration, and organizational purpose.

2. Why organizations use competency models

Competency models can support several connected decisions:

• Selection: identifying job-relevant predictors and structured assessment criteria.
• Onboarding: clarifying expected behaviors and early learning priorities.
• Performance management: translating organizational values into observable conduct and results.
• Learning and development: diagnosing gaps and recommending practice or learning experiences.
• Career mobility: making adjacent opportunities visible.
• Succession: assessing readiness for broader responsibility.
• Workforce planning: comparing current capability supply with future demand.
• Job design: distributing work among people, technology, teams, and external partners.

Their strategic contribution is strongest when the model reflects the organization’s competitive logic. A low-cost manufacturer may emphasize process discipline, quality control, and continuous improvement; a professional-services firm may emphasize client diagnosis, expertise integration, and relationship management. A generic model can provide consistency, but it should not replace analysis of distinctive work and strategy.

3. Types of competency models

3.1 Behavioral or core competency models

Behavioral competencies describe how people perform, interact, and exercise judgment. They are often shared across many roles. Examples include:

• ethical judgment;
• collaboration;
• communication;
• learning agility;
• customer orientation;
• accountability; and
• inclusive practice.

A behavioral competency should avoid moral labels or personality stereotypes. “Professionalism” becomes more defensible when defined through punctual communication, preparation, respectful conduct, confidentiality, and reliable follow-through, with the relevant behaviors adjusted to context.

3.2 Functional or technical competency models

Functional competencies describe capabilities specific to a discipline or job family. Examples include demand forecasting in supply chain, clinical assessment in health care, employment-law interpretation in HR, and requirements engineering in software development.

Functional models should identify the level of complexity, autonomy, tools, standards, and consequences associated with performance. “Uses statistical software” is weaker than “selects an appropriate model, checks assumptions, interprets uncertainty, and communicates limitations to decision-makers.”

3.3 Leadership competency models

Leadership models describe capabilities associated with formal or informal influence. Common domains include:

• setting direction and translating strategy;
• making decisions under uncertainty;
• developing people;
• allocating resources;
• leading change;
• building trust and psychological safety; and
• governing risk and ethics.

Leadership competencies should not be treated as universal substitutes for technical expertise. Effective leadership is contingent: the behaviors needed in a crisis, a research laboratory, and a highly regulated operation may differ. Models should therefore distinguish foundational leadership expectations from context-specific requirements.

3.4 Individual, team, and organizational competencies

An individual competency concerns a person’s capability. A team competency concerns coordinated patterns of behavior, such as shared mental models or effective handoffs. An organizational competency refers to a system-level capacity, such as rapid product commercialization or reliable regulatory compliance. Confusing these levels creates unfair accountability: an employee cannot compensate indefinitely for inadequate systems, staffing, information, or authority.

4. Designing a competency model

A defensible model is developed through a sequence of evidence-based decisions rather than through copying a popular framework.

Step 1: Clarify purpose and scope

Specify whether the model will support selection, development, job architecture, mobility, succession, or several purposes. Define the population, time horizon, jurisdictions, and decisions affected. A model designed for employee development may be broader than one used for legally consequential selection decisions.

Step 2: Analyze work and strategic context

Review job documents, performance data, customer requirements, risk events, strategic plans, technology road maps, and regulatory obligations. Use interviews, observation, focus groups, critical incidents, surveys, and work samples as appropriate. Subject-matter experts should describe effective and ineffective performance, not merely list fashionable attributes.

A critical-incident approach asks participants to describe a situation in which performance was notably effective or ineffective, the actions taken, and the consequences. Analysts then identify recurring behavioral patterns and contextual conditions.

Step 3: Generate and consolidate competencies

Code the evidence into provisional competency constructs. Remove duplicates, distinguish means from ends, and separate requirements from preferences. For example, “excellent communication,” “clear communication,” and “strong presentation” may represent different skills or one broader communication competency depending on the evidence.

Step 4: Write operational definitions

Each competency should include:

1. a concise title;
2. a definition;
3. observable behavioral indicators;
4. examples of outputs or evidence;
5. contextual boundaries; and
6. relationships to related skills or competencies.

Avoid compound constructs that cannot be assessed consistently. “Innovation, teamwork, and customer focus” should normally be separated unless evidence shows they function as one coherent construct.

Step 5: Establish proficiency levels

Levels should represent increasing complexity, autonomy, scope, and consistency—not merely years of service or inflated adjectives. A five-level structure is common:

The labels must be adapted to the work. A level-5 laboratory scientist is not necessarily a manager, and an expert practitioner may have deep influence without formal authority.

Step 6: Validate and govern

Test whether the model is understandable, relevant, observable, and appropriately differentiated. Establish ownership, review cycles, version control, appeal mechanisms, and rules for data use. Models should be reviewed when strategy, technology, regulation, or work design changes—not only on a fixed calendar.

5. Proficiency mapping and skills adjacencies

5.1 Proficiency is multidimensional

Proficiency can include accuracy, speed, complexity, autonomy, breadth, judgment, impact, and ability to teach or improve practice. A person may be highly proficient in a routine skill but inexperienced in ambiguous application. Therefore, proficiency claims should be tied to evidence such as work samples, portfolios, supervisor observation, certifications, simulations, or validated assessments.

A useful profile records both the required level and the demonstrated level. The difference is a development or staffing signal, not automatically a performance failure. It may reflect a temporary assignment, a new technology, or an unrealistic requirement.

5.2 Skills adjacencies

A skills adjacency is a plausible transition from one skill or skill cluster to another, based on shared knowledge, tools, processes, or cognitive demands. Adjacency analysis supports internal mobility and reskilling. For example, a payroll analyst may have adjacencies to HR analytics because both involve data quality, regulatory interpretation, confidentiality, and reporting; additional training in statistical methods and visualization may be required.

Adjacency is not equivalence. Similar labels can conceal different levels of complexity or risk. A transition should consider:

• shared foundational knowledge;
• transferable methods and tools;
• domain-specific knowledge still missing;
• proficiency distance;
• learning resources and time;
• regulatory or safety constraints; and
• evidence required before independent practice.

A practical adjacency map can classify transitions as near, moderate, or distant, but the classification should be based on evidence rather than intuition. Graph-based systems may represent skills as nodes and meaningful relationships as edges; the edge should have a documented rationale, such as shared tasks or expert judgment.

5.3 Skills-based organization

A skills-based organization allocates work, learning, and opportunity with greater attention to demonstrated capabilities than to rigid job titles. It may use project marketplaces, talent profiles, internal gigs, modular jobs, skill-based pay elements, or dynamic workforce planning. It does not eliminate jobs, professions, hierarchy, or employment law. Rather, it supplements them with a more granular view of what work requires and what people can do.

Successful implementation requires reliable skill data, manager capability, transparent opportunity rules, and attention to job quality. If employees must constantly maintain profiles or compete for short-term assignments without stability, the system can increase insecurity rather than mobility.

6. Validity and strategic relevance

6.1 Content validity

Content validity concerns whether the model adequately represents important aspects of the work. Evidence includes systematic job analysis, diverse subject-matter experts, critical incidents, and coverage of both routine and exceptional demands. A model that lists only visible technical tasks may omit judgment, coordination, or ethical obligations.

6.2 Construct validity

Construct validity asks whether the competency means what it claims to mean and differs from related constructs. Evidence may include expert judgment, factor analysis of ratings, correlations with related measures, and tests of discriminant validity. Statistical evidence is informative but not sufficient: a clean factor structure does not prove that the competency is strategically important.

6.3 Criterion-related validity

Criterion-related validity concerns the relationship between competency assessments and relevant outcomes, such as quality, safety, customer outcomes, innovation, retention, or promotion. Outcomes must be reliable and substantively relevant. A competency should not be retained merely because it predicts a narrow metric that encourages undesirable behavior.

If a competency score is used to predict an outcome, a simple linear model might be expressed as:

Here, Ŷ is the predicted outcome, X is the competency measure, a is the intercept, and b is the estimated change in the outcome associated with a one-unit change in X. This model assumes that the relationship is adequately represented as linear, observations are appropriately independent for the intended inference, measurement is sufficiently reliable, and relevant variables are not systematically omitted. It is a predictive tool, not proof that the competency causes the outcome.

For multiple competencies, a regression model may be written as:

where X₁ through Xₖ are competency measures and b₁ through bₖ are partial associations, interpreted cautiously when competencies overlap. Multicollinearity, common-rater bias, restricted range, and changing performance criteria can distort conclusions.

6.4 Incremental validity

A new competency measure has incremental validity when it improves prediction or decision quality beyond existing information, such as experience, structured interview scores, or work samples. Organizations should ask whether the added complexity and cost are justified by improved decisions.

6.5 Reliability and measurement quality

A model may be conceptually sound but poorly measured. Reliability concerns consistency: would appropriately trained raters reach similar conclusions, and would the measure be reasonably stable when the underlying capability has not changed? Reliability does not guarantee validity. A consistently applied irrelevant criterion is still irrelevant.

Use behavioral anchors, rater training, multiple sources, work samples, and calibration. Avoid treating a single manager rating as a precise measurement of a complex competency.

6.6 Fairness and adverse impact

Competency systems can reproduce bias through culturally narrow behavioral norms, unequal access to developmental assignments, opaque algorithms, or subjective ratings. Organizations should examine subgroup differences, accessibility, language demands, accommodation needs, and whether competencies are genuinely job-related. Legal requirements vary by jurisdiction, but defensible practice generally includes documented job relevance, consistent administration, recordkeeping, and review of disparate effects.

6.7 Strategic validity

Strategic relevance is the degree to which a competency supports capabilities that matter to the organization’s mission and competitive position. A model should connect three levels:

1. Strategy: what the organization must accomplish.
2. Capabilities: what the organization must be able to do.
3. Individual and team competencies: what people must demonstrate to enact those capabilities.

This chain should be tested rather than assumed. If “innovation” is a strategic priority but employees are punished for well-designed experiments that fail, the model and reward system are misaligned.

7. Technology and artificial intelligence

Digital platforms can combine skill taxonomies, learning records, project histories, credentials, and employee-declared interests. Natural-language processing can extract skill terms from documents, while recommendation engines can suggest learning or internal opportunities. These tools can reduce search costs, but they do not eliminate the need for human judgment.

Key risks include inaccurate inference, outdated skill records, proxy discrimination, surveillance, confidentiality breaches, automation bias, and opacity. An AI system may infer a skill from a job title or course completion without evidence of competent application. Good governance requires:

• data minimization and purpose limitation;
• employee notice and meaningful explanation;
• validation of recommendations and assessments;
• human review of consequential decisions;
• monitoring for subgroup disparities;
• correction and appeal mechanisms; and
• clear separation between developmental analytics and disciplinary surveillance.

AI-generated competency descriptions should be treated as drafts. Subject-matter experts must verify work relevance, behavioral clarity, accessibility, and legal defensibility.

8. Illustrative case: Northstar Health Systems

The following is a fictional illustrative case.

Background

Northstar Health Systems operates hospitals, outpatient clinics, and a centralized digital-care unit. It experienced rising demand for virtual care, inconsistent patient handoffs, and difficulty moving administrative employees into emerging analytics roles. Its existing job descriptions were highly specialized and had not been systematically revised for six years.

Problem

Senior leaders proposed a skills-based marketplace and a new competency model. The initial proposal listed 42 competencies, including “digital fluency,” “innovation,” “resilience,” and “patient centricity,” but definitions were vague. Employees feared that opaque skill ratings would affect promotion and job security. Clinical leaders also warned that a generic model might overlook safety and professional licensing requirements.

Analysis

A cross-functional team conducted document review, interviews, observation, critical-incident workshops, and a survey of 1,100 employees. It found that successful virtual-care coordinators combined scheduling knowledge, privacy practices, empathetic communication, escalation judgment, and digital troubleshooting. The team also found that “resilience” was being used to place responsibility for understaffing on employees; it was removed as a standalone competency and replaced with observable practices involving prioritization, help-seeking, and safe escalation.

The team distinguished three layers:

• core behaviors: ethical practice, inclusive communication, collaboration, and accountability;
• functional capabilities: clinical documentation, workforce analytics, privacy compliance, and workflow improvement; and
• leadership capabilities: systems thinking, change leadership, coaching, and risk governance.

Each capability received four proficiency levels, with examples of evidence. Licenses and legally required qualifications were kept separate from developmental skills. Adjacency workshops identified near transitions, such as scheduling analysts to workforce-analytics assistants, but required supervised practice before independent reporting.

Approach and solution

Northstar piloted the model in the digital-care unit. Employees could review their profiles, contest inferred skills, and choose developmental pathways. Managers used structured evidence guides rather than unanchored ratings. The marketplace recommended short projects, but clinical work remained governed by credentialing and scope-of-practice rules.

The organization evaluated the pilot using employee understanding, internal movement, time to fill projects, manager agreement, learning completion, and fairness indicators. It did not treat marketplace activity as a direct proxy for performance because access to projects differed by shift, location, and manager.

Outcome

After two review cycles, employees reported clearer expectations and greater visibility of developmental opportunities. Internal movement into entry-level analytics assignments increased, but Northstar found that employees with irregular schedules had less access to project work. The organization responded by creating paid learning time and rotating project access. It also removed two competencies that did not improve decision quality and revised the model to distinguish demonstrated skill from inferred potential.

Learning points

The case illustrates that competency modeling is not merely a documentation exercise. It requires strategic analysis, employee participation, evidence standards, protection of professional boundaries, and continuous evaluation. Skills-based systems work best when they expand opportunity without weakening job quality, due process, or safety.

9. Implementation challenges and best practices

Common challenges include competency proliferation, vague language, managerial inconsistency, excessive dependence on self-report, outdated taxonomies, weak links to actual work, and confusing potential with demonstrated capability. Another danger is “competency inflation,” in which every role is expected to show advanced strategic leadership regardless of scope.

Best practices include:

1. Start with decisions and work evidence, not a preferred software platform.
2. Keep the model parsimonious; include only competencies that inform real decisions.
3. Use observable behaviors and outputs, while recognizing contextual variation.
4. Separate minimum qualifications, skills, competencies, and aspirations.
5. Define proficiency through complexity, autonomy, judgment, and impact.
6. Involve jobholders, supervisors, customers, professional bodies, and underrepresented groups.
7. Validate measures for relevance, reliability, fairness, and incremental value.
8. Provide multiple ways to demonstrate capability, including work samples and portfolios.
9. Audit access to development, projects, mentoring, and promotion.
10. Review models after strategic, technological, regulatory, or work-design changes.
11. Govern data transparently and give employees correction and appeal rights.
12. Treat the model as a living hypothesis about effective work, not an immutable truth.

Chapter Summary

Competency modeling broadens job analysis from lists of tasks to integrated capabilities that explain effective performance in context. Skills are learned capacities; KSAOs classify requirements; competencies combine multiple elements into observable patterns of behavior and results. Behavioral, functional, and leadership models serve different purposes and should be designed with attention to work context, strategy, and professional boundaries.

A defensible model uses systematic evidence, clear definitions, behavioral indicators, and proficiency levels based on complexity, autonomy, judgment, and impact. Skills adjacencies can support internal mobility, but similarity does not imply equivalence: missing domain knowledge, risk, regulation, and supervised practice must be considered. Skills-based organizations use capability information to allocate work and development more flexibly, while retaining attention to job quality and employment obligations.

Validity includes content, construct, criterion-related, incremental, and strategic validity. Reliability, fairness, accessibility, data governance, and employee voice are equally important in consequential applications. Technology and AI can improve classification and recommendation, but inferred skills and algorithmic outputs require human validation, transparency, monitoring, and appeal. The central managerial task is to connect strategy, organizational capabilities, and evidence-based individual and team requirements without reducing people to unstable or opaque scores.

Key Terms

Competency: An integrated, measurable capability expressed through behavior and results in context.

Competency model: An organized framework of competencies, definitions, and proficiency indicators for a defined population.

Skill: An acquired capacity to perform an activity with some degree of proficiency.

KSAOs: Knowledge, skills, abilities, and other characteristics relevant to work performance.

Knowledge: Information, principles, or procedures required for performance.

Ability: A relatively enduring capacity to perform activities or solve problems.

Other characteristics: Relevant attributes beyond knowledge, skills, and abilities, including licenses or work values.

Task: A discrete unit of work.

Duty: A broader cluster of related tasks.

Behavioral competency: A capability concerning how work is performed and how people interact.

Functional competency: A technical or professional capability specific to a job family or discipline.

Leadership competency: A capability involving direction, influence, people development, change, or governance.

Proficiency level: A defined degree of capability based on factors such as complexity, autonomy, and impact.

Skills taxonomy: A classification system that organizes skills and their relationships.

Skills adjacency: A plausible transition between related skills or skill clusters.

Content validity: The extent to which a model adequately represents important work requirements.

Construct validity: Evidence that a competency represents the intended concept and differs from related concepts.

Criterion-related validity: Evidence that competency measures relate to relevant performance outcomes.

Incremental validity: The additional decision value contributed by a measure beyond existing information.

Strategic validity: The degree to which competencies support capabilities important to organizational strategy.

Review Questions

Short Answer Questions

1. How does a competency differ from an individual skill?
2. What are the four elements represented by the acronym KSAO?
3. Why should proficiency levels include complexity and autonomy rather than years of experience alone?
4. What is a skills adjacency?
5. Name two risks associated with using AI in competency systems.

Long Answer Questions

1. Explain how behavioral, functional, and leadership competency models differ, and describe when each is most useful.
2. Describe a rigorous process for designing and validating a competency model.
3. Discuss the relationship between competency models, skills taxonomies, and skills-based organizations.
4. Explain content, construct, criterion-related, incremental, and strategic validity.
5. Evaluate the ethical and governance requirements for using employee skill data in talent decisions.

Analytical / Application Questions

1. A bank wants to move experienced customer-service representatives into fraud-analytics roles. Design an adjacency analysis that identifies transferable skills, missing capabilities, evidence requirements, and risks.
2. An organization rates every manager on “strategic leadership,” but ratings show little agreement between raters and no relationship with relevant outcomes. Diagnose possible measurement problems and recommend a validation plan.
3. Design a four-level competency for inclusive communication, including a definition, behavioral indicators, evidence sources, and safeguards against culturally biased interpretation.

Multiple Choice Questions with Answers

Question 1

Which statement best distinguishes a competency from a skill?

A. A competency is always a formal qualification, whereas a skill is informal.

B. A competency integrates related knowledge, skills, and behaviors in a work context.

C. A competency is a single learned activity, whereas a skill combines several jobs.

D. A competency can be assessed only through personality testing.

Correct Answer: B. A competency integrates related knowledge, skills, and behaviors in a work context.

Question 2

Which item is an example of a functional competency?

A. Ethical judgment

B. Inclusive communication

C. Requirements engineering

D. Accountability

Correct Answer: C. Requirements engineering

Question 3

What is the strongest basis for defining proficiency levels?

A. Employee age and organizational tenure

B. Job title alone

C. Increasing complexity, autonomy, judgment, and impact

D. The number of courses completed

Correct Answer: C. Increasing complexity, autonomy, judgment, and impact

Question 4

What does content validity examine?

A. Whether a model adequately represents important aspects of the work

B. Whether a measure predicts employee turnover only

C. Whether raters use exactly the same personal standards

D. Whether an algorithm processes data quickly

Correct Answer: A. Whether a model adequately represents important aspects of the work

Question 5

Which statement about skills adjacencies is correct?

A. Adjacent skills are identical and require no additional learning.

B. Adjacency indicates a plausible transition, but missing knowledge and risk must be assessed.

C. Adjacency can be determined solely from job titles.

D. Adjacent skills are relevant only to external recruitment.

Correct Answer: B. Adjacency indicates a plausible transition, but missing knowledge and risk must be assessed.

Question 6

In the model Ŷ = a + bX, what does b represent?

A. The predicted outcome

B. The intercept

C. The estimated change in the outcome associated with a one-unit change in X

D. The measurement error

Correct Answer: C. The estimated change in the outcome associated with a one-unit change in X

Question 7

Which practice most improves consistency in competency ratings?

A. Using broad labels without examples

B. Allowing each manager to define excellence independently

C. Using behavioral anchors and rater calibration

D. Replacing evidence with employee self-confidence

Correct Answer: C. Using behavioral anchors and rater calibration

Question 8

Why should licenses and legally required qualifications often be recorded separately from developmental skills?

A. Qualifications are never relevant to job performance.

B. They have different legal and eligibility implications from skills that can be developed.

C. Skills cannot be measured objectively.

D. Licenses are always less important than competencies.

Correct Answer: B. They have different legal and eligibility implications from skills that can be developed.

Question 9

Which is a major risk of inferring skills from job titles using AI?

A. The system may confuse title-based similarity with demonstrated capability.

B. The system necessarily improves fairness.

C. The system eliminates the need for employee review.

D. The system can assess only physical skills.

Correct Answer: A. The system may confuse title-based similarity with demonstrated capability.

Question 10

What is strategic validity concerned with?

A. Whether a competency supports capabilities important to organizational strategy

B. Whether every employee has the same personality

C. Whether a job description contains enough tasks

D. Whether a learning platform has many courses

Correct Answer: A. Whether a competency supports capabilities important to organizational strategy